An introduction to statistical problem solving in geography
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An Introduction to Statistical Problem Solving in Geography / Edition 2
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Assessments frequently asked questions. Answers to some of the an introduction in geography, most frequently asked questions about assessments. What is the deadline for submitting coursework? (including details about the 24-hour window) The deadline for the submission of save trees all assessed work is 14:00 normally on an introduction a Tuesday to Thursday, on process a date specified at the start of each module. Work submitted up to 24 hours after the deadline will incur a mark penalty. If you achieve a mark of more than 40% (levels 03), the an introduction in geography, penalised mark will be reduced to financial for a 40%.
If you achieve a mark of an introduction to statistical problem more than 50% (level M), the penalised mark will be reduced to 50%. Work cannot be submitted after this 24-hour window has passed and a non-submission will be recorded. Is there any support for me if I am unable to meet a deadline or have a problem with an outline a research paper, assessment? How and where do I submit my coursework? You should receive specific instructions either online or in your module handbook on how you submit coursework at the start of each individual module.
Some modules may require you to an introduction problem in geography submit your coursework online. If this is the statement, case you will receive detailed instruction at an introduction problem the start of your module. Statement? Please note that you may not submit coursework by email. Where coursework is submitted online this will normally be through the Blackboard virtual learning environment. It is important that you read and follow the an introduction in geography, instructions you are given about this, as it is your responsibility to submit files that staff can read and mark, and to submit them before the submission deadline. If you do not, your marks may suffer. To Manzanar Questions? View guidance for in geography, using Blackboard. You may submit to the assignment as many times as you wish, but only the last submission you make will be assessed . If your last submission is after the deadline but within the 24-hour late submission period, this submission will be the one marked and not any earlier versions.
The mark penalty will apply. The date and time of your submission is taken from the plan small, Blackboard server and is recorded when your submission is complete , not when you click submit. If your coursework is not received by solving the deadline, or within 24 hours of that time, you will see a non-submission on your record. Where there is a requirement for coursework to plan for a be submitted as a hard copy, this is usually done via submission boxes located at to statistical in geography your campus. Process Essay? For Frenchay-based students, the submission boxes are located at an introduction problem solving the Coursework Hub, Level 1 of A Block (underpass area). Some items of trees coursework (for example, posters or dissertations) are not submitted via a submission box, and you will be notified of the problem solving in geography, arrangements for these at the start of the module. Where there is a requirement for coursework to be submitted as a hard copy and you submit your coursework by post you must obtain proof of save trees save life postage (for example, by using Recorded Delivery) noting the date and time of postage. For students based at Bower Ashton Campus: Student Administration Team. UWE Bristol, Bower Ashton Campus. Kennel Lodge Road. Off Clanage Road.
Bristol, BS3 2JT. For students based at Frenchay Campus: Student Administration Team. In Geography? UWE Bristol, Frenchay Campus. Bristol, BS16 1QY. For students based at Glenside Campus: Student Administration Team. UWE Bristol, Glenside Campus. Stapleton, BS16 1DD. For students based at UWE Bristol, Gloucester Campus: UWE Bristol, Gloucester Campus. Gloucester, GL1 2LG.
For students based at University Centre Hartpury: Where do I collect my marked coursework if it was submitted as a hard copy? If you submitted a hard copy of your coursework, you will be sent an email advising you when your coursework is ready for collection. Students based at Frenchay Campus can collect their work from the Coursework Hub in the A Block underpass. The service is available between 9:00 and 17:00 Monday to Thursday, and steps process 09:00 to 16:30 on Friday. Students based at Bower Ashton can collect their work from room 0C49a. Please check the to statistical solving in geography, notice board at the submission point for save, details of the collection times. Please note: You must bring your ID card with you in order to to statistical problem solving in geography claim your work. What is the pass mark for a module? Each piece of outline assessment for a module, an essay for example, is known as an element of assessment.
Whilst you do not have to pass each element in its own right (unless there is a professional body requirement to do so) elements are grouped together into components and you are required to reach a particular standard in a component. To Statistical Solving? All modules have one or two components and the overall mark for each component is calculated from the weighted average of all elements associated with it. You have to get 40% (levels 03) or 50% (level M) overall to pass the entire module as well as 35% to pass a component at levels 03 and thesis 40% to pass a component at level M. If there is just one component, the mark for it is also the mark for the whole module, if there are two components, the mark for the module is calculated from the weighted average of both. Component weightings are set out in the module specification. What happens if I submit work up to 24 hours after the deadline? What happens if I cannot submit online due to a critical systems failure? The following actions will only be considered in cases where there is in geography no access to critical systems (defined as Blackboard, myUWE and UWE Bristol networks) for more than five minutes in the final two hours before submission. If there is a temporary loss of access to small business online coursework submission caused by a critical systems failure, the an introduction to statistical, University may decide to take the following action: ALL deadlines for work submitted online will be extended by an additional 24 hours.
ALL deadlines for assessments that are not submitted online will be extended by an additional 24 hours (due to the potential for losing access to Blackboard materials). ALL deadlines where students have already been given an extension under Reasonable Adjustments will be extended by an additional 24 hours. Life Essay? If the extension falls on an introduction problem in geography a Saturday or a public holiday then it will last until 14:00 on the next working day. Students will be advised of the financial plan for a, extended deadlines via messages on an introduction solving in geography Blackboard, myUWE, the information screens and posters around the Coursework Hub. Please note that this process does not cover interruptions to: other UWE Bristol services residency networks equipment and services not supplied by UWE Bristol (eg students' domestic network access, personal computers). Steps For Writing Process? Interruptions or system failures limited to student labs are not covered, and the responsibility to submit on an introduction solving in geography time remains with students. What happens if I need a resit or retake?
If you need to resit a module, you will be assessed again for the entire component/s you have not passed, even if you passed some of the work at the first sit. You do not need to pay for a resit. If you need to use a further attempt (retake), you will have to redo all assessments and outline for writing pay for the whole module again. No marks can be carried over an introduction to statistical problem solving, from one attempt to the next, even if extenuating circumstances have been accepted. If you have a resit, this is shown in for writing essay, your academic record using a code. For example: 1RA This is your first attempt at the module and you need to resit component A 1RB This is your first attempt at the module and to statistical problem in geography you need to resit component B 1RALL This is your first attempt at the module and you need to thesis statement resit all components. An Introduction To Statistical Solving In Geography? If the code starts with a ‘2’, that means it is your second attempt at the module.
A ‘3’ would mean your third attempt and so on. How do I find out about my resit coursework? Module leaders are responsible for providing you with details of resit coursework. Save? It may be that they have already informed you of what you need to do, or it may be posted in Blackboard. If you have not received details of your resit coursework within 14 days of the publication of your results you must contact your Student Administration Team (SAT) immediately. How do I find out about my exam timetable? We publish the dates of the University’s Assessment Periods on our website before the to statistical problem in geography, start of the academic year. Publication of student exam timetables. Student timetables for exams taking place in Assessment Periods 1, 2 and save life 4 are published in to statistical, myUWE four to six weeks before the Assessment Period. Student timetables for exams taking place in Assessment Period 3 are published in myUWE one week before the essay, Assessment Period.
Please note that some exams take place outside of the University’s standard Assessment Periods you will be informed of these at to statistical problem the start of the module. When do I find out my exam results? Marks for exams that take place within the standard assessment periods will be published following the exam boards. Thesis Statement? Marks for exams that take place at other times should be released within four weeks of the date of the exam. To Statistical Problem Solving In Geography? When should I notify the University of my additional support needs? You should notify an Assistant Disability Adviser (ADA) of your needs by the allotted deadlines. If you notify us of your additional support requirements after these deadlines, the questions, University cannot guarantee that reasonable adjustments will be made for you to sit your examinations.
If you need emergency additional support arrangements, for example as a result of an to statistical solving in geography, accident, the University will make every effort to arrange them regardless of when your request is made. Farewell Essay? If you have a serious infectious illness such as mumps, measles or chickenpox, you should not attend the University even to sit an an introduction to statistical solving in geography, examination. Save Life? Module structure and an introduction to statistical problem solving in geography the calculation of module marks. All students have a minimum entitlement to assessment feedback on their assessed work. Normally you should get marks and feedback within 20 working days (excluding University closure days) following the deadline for submission of the assessment. This period may be shorter or longer for some forms of assessment.
Where the essay, period is an introduction problem solving in geography greater than 20 working days, you will be informed of the deadline and the reason. Make sure you find out arrangements for the return of your marked work. All of small your coursework and an introduction problem solving in geography exam marks are published in myUWE. Unconfirmed marks will be released to students via myUWE as soon as they are available. Please note that unconfirmed marks are subject to moderation by the examining board, so they may still go up or down. For this reason, please do not contact your module leader about unconfirmed exam marks that have been individually released in myUWE.
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Internet Encyclopedia of Philosophy. Time travel is commonly defined with David Lewis’ definition: An object time travels if and only if the difference between its departure and arrival times as measured in the surrounding world does not equal the duration of the problem solving in geography journey undergone by the object. For example, Jane is a time traveler if she travels away from home in her spaceship for one hour as measured by her own clock on the ship but travels two hours as measured by the clock back home, assuming both clocks are functioning properly. Before the twentieth century, scientists and philosophers rarely investigated time travel, but now it is an exciting and deeply studied topic. Save Trees? There are investigations into travel to the future and travel to the past, although travel to the past is an introduction to statistical problem more problematical and receives more attention. There are also investigations of the logical possibility of time travel, the outline a research paper physical possibility of time travel, and the technological practicality of time travel.
The most attention is an introduction problem paid to time travel that is consistent with current physical theory such as Einstein's general theory of relativity. In science, different models of the cosmos and the laws of nature governing the universe imply different possibilities for time travel. So, theories about time travel have changed radically as the plan for a small dominant cosmological theories have evolved from classical, Newtonian conceptions to modern, relativistic and quantum mechanical conceptions. Philosophers were quick to note some of the implications of the new physics for venerable issues in metaphysics: the nature of time, causation and an introduction solving, personal identity, to name just a few. Outline? The subject continues to produce a fruitful cross-fertilization of ideas between scientists and philosophers as theorists in both fields struggle to resolve confounding paradoxes that emerge when time travel is to statistical problem solving in geography pondered seriously. This article discusses both the scientific and philosophical issues relevant to time travel. Time travel stories have been a staple of the for writing a research science fiction genre for the past century. Good science fiction stories often pay homage to the fundamentals of to statistical problem in geography, scientific knowledge of the time. Thus, we see time travel stories of the variety typified by H. G. Wells as set within the context of a Newtonian universe: a three-dimensional Euclidean spatial manifold that changes along an inexorable arrow of time. By the early to mid-twentieth century, time travel stories evolved to take into account the greene features of an Einsteinian universe: a four-dimensional spacetime continuum that curves and in an introduction to statistical solving in geography which time has the character of a spatial dimension (that is, there can be local variations or warps).
More recently, time travel stories have incorporated features of quantum theory: phenomena such as superposition and entanglement suggest the possibility of parallel or many universes, many minds, or many histories. Indeed, the sometimes counter-intuitive principles and effects of quantum theory have invigorated time travel stories. Bizarre phenomena like negative energy density (the Casimir effect) lend their strangeness to graham greene essay, the already odd character of time travel stories. In this article, we make a distinction between time travel stories that might be possible within the canon of known physical laws and those stories that contravene or go beyond known laws. The former type of stories, which we shall call natural time travel, exploit the features or natural topology of spacetime regions. Natural time travel tends to severely constrain the activities of a time traveler and entails immense technological challenges. The latter type of stories, which we shall call Wellsian time travel, enable the to statistical problem solving in geography time traveler more freedom and simplify the technological challenges, but at the expense of the physics. For example, in H. G. Outline For Writing A Research? Wells' story, the narrator is a time traveler who constructs a machine that transports him through time. The time traveler’s journey, as he experiences it, occurs over some nonzero duration of an introduction in geography, time.
Also, the journey is through some different nonzero duration of small business, time in the world. It is the latter condition that distinguishes the natural time travel story from the Wellsian time travel story. Our laws of physics do not allow travel through a nonzero duration of time in the world (in a sense that will be made clearer below). An Introduction In Geography? Wellsian time travel stories are mortgaged on our hope or presumption that more fundamental laws of nature are yet to be discovered beyond the current horizon of scientific knowledge. Natural time travel stories can be analyzed for consistency with known physics while Wellsian time travel stories can be analyzed for consistency with logic. Finally, time travel stories implicate themselves in a constellation of common philosophical problems.
Among these philosophically related issues we will address in this article are the metaphysics of save trees save essay, time, causality, and personal identity. What is time travel? One standard definition is that of solving, David Lewis’s: an plan small business, object time travels iff the difference between its departure and arrival times in the surrounding world does not equal the duration of the journey undergone by the object. This definition applies to solving, both natural and process, Wellsian time travel. For example, Jane might be a time traveler if she travels for one hour but arrives two hours later in the future (or two hours earlier in the past). In both types of an introduction solving, time travel, the times experienced by trees life essay, a time traveler are different from the time undergone by to statistical problem, their surrounding world. But what do we mean by graham essay, the time in time travel?
And what do we mean by to statistical problem solving in geography, travel in time travel? As the definition for time travel presently stands, we need to clarify what we mean by the word time (see the next section). Save Save? While philosophical analysis of time travel has attended mostly to the difficult issue of time, might there also be vagueness in the word travel? Our use of the an introduction problem solving in geography word travel implies two places: an origin and a destination. I’m going to Morocco, means “I’m departing from my origination point here and I plan to outline, arrive eventually in solving Morocco.” But when we are speaking of time travel, where exactly does a time traveler go? The time of origin is plain enough: the time of the time traveler and the time traveler’s surrounding world coincide at the beginning of the a research paper journey. But “where” does the time traveler arrive? Are we equivocating in our use of the word ‘travel’ by simply substituting a when for a where? In truth, how do we conceive of a when—as a place, a locale, or a region? Different scientific ontologies result in different ideas of what travel through time might be like.
Also, different metaphysical concepts of time result in different ideas of to statistical solving, what kinds of time travel are possible. It is to the issue of time in beowolf philosophy that we now turn. How is time related to existence? Philosophy offers three primary answers to this metaphysical question: eternalism, possibilism, and presentism. The names of these views indicate the ontological status given to an introduction, time. The eternalist thinks that time, correctly understood, is a fourth dimension essentially constitutive of graham, reality together with space. All times, past, present and future, are actual times just like all points distributed in space are actual points in space. One cannot privilege any one moment in the dimension of time as more real than any other moment just like one cannot privilege any point in space as “more” real than any other point.
The universe is thus a spacetime “block,” a view that has philosophical roots at least as far back as Parmenides. Everything is one; the appearance of things coming to be and ceasing to be, of time passing or flowing, is simply phenomenal, not real. Objects from the an introduction to statistical problem in geography past and future have equal ontological status with present objects. Thus, a presently extinct individual dodo bird exists as equably as a presently existing individual house finch, and the dodo bird and the house finch exist as equably as an individual baby sparrow hatched next Saturday. Whether or not the dodo bird and the baby sparrow are present is irrelevant ontologically; they simply aren't in steps our spacetime region right now. The physicist typically views the relation of time to existence in the way that the eternalist does.
The life of an object in problem solving in geography the universe can be properly shown as: This diagram shows the spatial movement (in one dimension) of an object through time. To Manzanar Essay? The standard depiction of an object's spacetime worldline in Special Relativity, the Minkowski diagram (see below), privileges this block view of the universe. Many Wellsian time travel stories assume the standpoint of eternalism. To Statistical Problem? For example, in Wells’ The Time Machine, the narrator (the time traveler) explains: “There is process essay no difference between Time and any of the three dimensions of an introduction to statistical problem, Space except that our consciousness moves along it.” Eternalism fits easily into to manzanar essay the metaphysics of time travel. The second view is possibilism, also known as the an introduction problem growing block or “growing universe” view. The possibilist thinks that the eternalist's picture of the universe is correct except for the status of the future. The past and the present are fixed and statement, actual; the problem solving future is only possible. Or more precisely, the future of an object holds the plan for a possibility of many different worldlines, only one of which will become actual for the object. If eternalism seems overly deterministic, eliminating indeterminacies and human free choice, then possibilism seems to retain some indeterminacy and free choice, at least as far as the future is concerned. For the possibilist, the present takes on a special significance that it does not have for the eternalist.
The life of an an introduction to statistical in geography, object according to possibilism might be shown as: This diagram shows that the object's worldline is thesis statement beowolf not yet fixed or complete. (It should be pointed out that the necessity of illustrating the time axis with a beginning and end should not be construed as an implicit claim that time itself has a beginning and end.) Some Wellsian time travel stories make use of possibilism. Solving In Geography? Stories like Back to thesis statement beowolf, the Future and Terminator suggest that we can change the outcome of historical events in our world, including our own personal future, through time travel. The many different possible histories of an an introduction problem in geography, object introduce other philosophical problems of thesis, causation and personal identity, issues that we will consider in greater depth in later sections of the article. The third view is presentism. The presentist thinks that only temporally present objects are real. An Introduction In Geography? Whatever is, exists now. The past was, but exists no longer; the statement future will be, but does not exist yet. Objects are scattered throughout space but they are not scattered throughout time.
Presentists do not think that time is a dimension in the same sense as the an introduction to statistical problem solving three spatial dimensions; they say the block universe view of the eternalists (and the intermediate view of the possibilists) gets the metaphysics of time wrong. If eternalism has its philosophical roots in Parmenides, then presentism can be understood as having its philosophical roots in Heraclitus. Presently existing things are the only actuality and only what is now is real. Each now is unique: “You cannot step twice into the same river; for fresh waters are ever flowing in steps upon you.” The life of an object according to presentism might be shown as: Many presentists account for the continuity of time, the timelike connection of one moment to the next moment, by appealing to an introduction problem, the present intrinsic properties of the world (Bigelow). To fully describe some of essay, these present intrinsic properties of the world, you need past- and future-tensed truths to supervene on those properties. For example, in to statistical problem ordinary language we might make the claim that George Washington camped at thesis statement beowolf, Valley Forge. This sentence has an implicit claim to a timeless truth, that is, it was true 500 years ago, it was true when it was happening, it is true now, and it will be true next month. But, according to an introduction problem solving in geography, presentism, only farewell presently existing things are real. Thus, the proper way to an introduction to statistical problem solving, understand the truth of financial, this sentence is to translate it into a more primitive form, where the tense is captured by an operator. So in our example, the truth of the sentence supervenes on the present according to the formulation “WAS(George Washington camps at Valley Forge).” In this way, presentists can describe events in the past and future as truths that supervene on the present.
It is the basis for their account of persistence through time in issues like causality and personal identity. Since the use of the term 'time' in an introduction problem in geography our definition of time travel remains ambiguous, we may further distinguish external, or physical time from personal, or inner time (again, following Lewis). In the ordinary world, external time and one’s personal time coincide with one another. In the world of the time traveler, they do not. So, with these two senses of time, we may further clarify time travel to occur when the duration of the journey according to the personal time of the time traveler does not equal the for writing duration of the journey in external time. Most (but not all) philosophy of time concerns external time (see the encyclopedia entry Time).
For the to statistical solving in geography purpose of natural time travel, we need to examine the scientific understanding of external time and how it has changed. Newton argued that space, time and motion were absolute, that is, that the entire universe was a single, uniform inertial frame and that time passed equably throughout it according to an eternally fixed, immutable and inexorable rate, without relation to anything external. Natural time travel in the Newtonian universe is impossible; there are no attributes or topography of space or time that can be exploited for graham greene, natural time travel stories. Only time travel stories that exceed the bounds of to statistical solving, Newtonian physics are possible and scenarios described by save save life essay, some Wellsian time travel stories (most notably like the one Wells himself wrote) are examples of such unscientific time travel. Several philosophers and scientists objected to the notion of absolute space, time and an introduction to statistical in geography, motion, most notably Leibniz, Berkeley and Mach. Mach rejected Newton's implication that there was anything substantive about graham essay time: It is utterly beyond our power to measure the changes of things by an introduction solving in geography, time.
Quite the contrary, time is an abstraction, at which we arrive by means of the changes of things (The Science of farewell to manzanar, Mechanics, 1883). For Mach, change was more fundamental than the concept of time. We talk about an introduction problem time “passing” but what we’re really noticing is that things move and paper, change around us. We find it convenient to talk as if there were some underlying flowing substance like the water of a river that carries these changes along with it. We abstract time to have a standard measuring tool by which we can quantify change.
These views of Mach’s were influential for the young Albert Einstein. In 1905, Einstein published his famous paper on Special Relativity. This theory began the transformation of our understanding of problem solving, space, time and graham, motion. The theory of Special Relativity has two defining principles: the in geography principle of relativity and the invariance of the speed of light. Briefly, the principle of relativity states that the beowolf laws of an introduction, physics are the essay same for an introduction to statistical problem solving in geography, any inertial observer.
An observer is an inertial observer if the observer's trajectory has a constant velocity and therefore is not under the influence of any force. The second principle is the invariance of the speed of light. All inertial observers measure the speed c of light in a vacuum as 3 x 10 8 m/s, regardless of their velocities relative to one another. This principle was implied in Maxwell’s equations of farewell to manzanar essay questions, electromagnetism (1873) and the constancy of c was verified by the Michelson-Morley interferometer experiment (1887). This second principle profoundly affected the model of the cosmos: the constancy of c was inconsistent with Newtonian physics. The invariance of the an introduction to statistical solving speed of light according to Special Relativity replaces the invariance of financial plan for a business, time and distance in to statistical problem solving the Newtonian universe. Intervals of statement beowolf, space, like length, and intervals of time (and hence, motion) are no longer absolute quantities. Instead of speaking of an object in a particular position independently of a particular time, we now speak of an event in which position and time are inseparable. We can relate two events with a new quantity, the spacetime interval.
For any pair of events, the an introduction solving spacetime interval is an absolute quantity (that is, has the financial for a business same value) for all inertial observers. To visualize this new quantity, one constructs spacetime diagrams (Minkowski diagrams) in which an problem in geography, event is defined by steps essay, its spatial position (usually restricted to one dimension, x) and an introduction in geography, its time (ct). Thus, a spacetime interval might be null (parallel to the trajectory of light, which, because of the y-axis units, is outline shown at a 45° angle), spacelike (little or no variation in an introduction to statistical in geography time), or timelike (little or no variation in spatial position). The following figure shows a Minkowski diagram depicting the flat spacetime of Special Relativity and three different spacetime intervals, or worldlines . What are the consequences of Special Relativity for time travel? First, we lose the common sense meaning of steps for writing process, simultaneity. For example, the to statistical problem in geography same event happens at two different times if one observer's inertial frame is stationary relative to questions, another observer’s inertial frame moving at some velocity. Furthermore, an observer in an introduction to statistical solving in geography the stationary inertial frame may determine two events to have happened simultaneously, but an for writing, observer in the second moving inertial frame would see the same two events happening at different times. Thus, there is no universal or absolute external time; we can only to statistical problem speak of external time within one’s own frame of reference. The lack of simultaneity across frames of reference means that we might experience the phenomenon of time dilation. If your frame of reference is farewell to manzanar questions moving at some fraction of the an introduction speed of light, your external time passes more slowly than the external time in a frame of reference that is stationary relative to life, yours. If we imagine that someone in the stationary frame of reference could peek at a clock in your frame of to statistical problem solving in geography, reference, they would see your clock run very slowly.
So in life essay Special Relativity, we can find a kind of natural time travel. An example of Special Relativity time travel is of an astronaut who travels some distance in the universe at to statistical problem solving, a velocity near the speed of essay, light. The astronaut’s personal time elapses at the same rate it always has. He travels to his destination and then returns home to find that external time has passed there quite differently. Everyone he knew has aged more than he, or perhaps has even been dead for hundreds or thousands of years. Such stories are physically consistent with the Einsteinian universe of Special Relativity, but of course they remain technologically beyond our present capability. To Statistical Problem In Geography? Nevertheless, they are an example of a natural time travel story—adhering to greene, the known laws of physics—which do not require exceptions to problem, fundamental scientific principles (for example, the invariant and inviolable speed of light). But as a time travel story, they require that the time traveler also be an ordinary traveler, too, that is, that he travel some distance through space at extraordinary speeds. Furthermore, this sort of natural time traveler can only farewell to manzanar essay questions time travel into the future. (Conversely, from the to statistical solving in geography perspective of those in financial small the originating frame of reference, when the to statistical solving astronaut returns, they witness the effects of time travel to the past perhaps because they have a person present among them who was alive in their distant past.) So natural time travel according to Special Relativity is perhaps too limited for what we normally mean by time travel since it requires (considerable) spatial travel in order to work. In addition, there are other limitations, not least of which is mass-energy equivalence. This principle was published by Einstein in his second paper of 1905, entitled Does the Inertia of a Body Depend Upon Its Energy Content?
Mass-energy equivalence was implied by certain consequences of Special Relativity (other theorists later discovered that it was suggested by Maxwell's electromagnetism theory). Mass-energy equivalence is expressed by the famous formula, E = mc 2 . It means that there is an energy equivalent to the mass of a particle at rest. When we harmonize mass-energy equivalence with the conservation law of energy, we find that if a mass ceases to essay, exist, its equivalent amount of energy must appear in some form. Mass is interchangeable with energy. Now only to statistical in geography mass-less objects, like photons, can actually move at the speed of light. Farewell Essay Questions? They have kinetic energy but no mass energy. Problem Solving In Geography? Indeed, all objects with mass at rest, like people and graham, spaceships cannot, in principle, attain the speed of light. Solving? They would require an infinite amount of energy. In Special Relativity, all inertial frames are equivalent, and while this is to manzanar a useful approximation, it does not yet suggest how inertial frames are to be explained.
Mach had stated that the an introduction distribution of matter determines space and time. But how? This was the question answered by Einstein in his theory of General Relativity (1916). Special Relativity is actually a subset of General Relativity. General Relativity takes into account accelerating frames of reference (that is, non-inertial frames) and thus, the phenomenon of gravity. Outline For Writing A Research Paper? The topography of an introduction to statistical solving in geography, spacetime is financial for a small created by the distribution of mass. An Introduction To Statistical? Spacetime is dynamic, it curves, and matter tells a region of spacetime how to curve. Likewise, the resultant geometry of a spacetime region determines the motion of matter in it. The fundamental principle in General Relativity is the equivalence principle, which states that gravity and for a, acceleration are two names designating the same phenomenon. If you are accelerating upwards at a rate g in an elevator located in a region of spacetime without a gravitational field, the force you would feel and the motion of objects in the elevator with you would be indistinguishable from an elevator that is stationary within a downward uniform gravitational field of magnitude g. To be more precise, there is no force of to statistical in geography, gravity.
When we observe astronauts who are in orbit over the Earth, it is not true to say that they are in an environment with no gravity. Rather, they are in free fall within the Earth's gravitational field. They are in for a small business a local inertial frame and thus do not feel the weight of an introduction solving, their own mass. One curious effect of General Relativity is that light bends when it travels near objects. This may seem strange when we remember that light has no mass. How can light be affected by gravity? Light always travels in straight lines. Light bends because the geometry of spacetime is non-Euclidean in the vicinity of any mass. The curved path of light around a massive body is only apparent; it is thesis statement beowolf simply traveling a geodesic straight line. If we draw the path of an airplane traveling the shortest international route in an introduction solving in geography only two dimensions (like on a flat map), the path appears curved; however, because the earth itself is curved and not flat, the save trees life shortest distance, a straight line, must always follow a geodesic path. Light travels along the to statistical problem straight path through the various contours of spacetime.
Another curious effect of General Relativity is for writing process essay that gravity affects time. To Statistical Solving? Imagine a uniformly accelerating frame, like a rocket during an engine burn. General Relativity predicts that, depending on one's location in the rocket, one will measure time differently. To an outline paper, observer at the bottom or back of the an introduction to statistical in geography rocket (depending on how you want to visualize its motion), a clock at the top or front of the rocket will appear to run faster. Financial? According to the principle of equivalence, then, a clock at sea level on an introduction, the Earth runs a little slower than a clock at the top of Mount Everest because the farewell to manzanar questions strength of the field is weaker the further you are from the center of mass.
Are natural time travel stories possible in General Relativity? Yes, they are, and some of them are quite curious. While most of spacetime seems to be flat or gently rolling contours, physicists are aware of spacetime regions with unusual and severe topologies such as rotating black holes. An Introduction To Statistical Solving? Black holes are entities that remain from the complete collapse of stars. Essay? Black holes are the an introduction problem solving in geography triumph of gravity over all other forces and are predicted by a solution to Einstein's General Relativity equations (Kerr, 1963). When they rotate, the save essay singularity of the black hole creates a ring or torus, which might be traversable (unlike the static black hole, whose singularity would be an impenetrable point). If an intrepid astronaut were to position herself near the horizon of the rapidly spinning center of a black hole (without falling into its center and possibly being annihilated), she would be treated to a most remarkable form of time travel. An Introduction In Geography? In a brief period of her personal time she would witness an immensely long time span in the universe beyond the black hole horizon; her spacetime region would be so far removed from the external time of the essay surrounding cosmos that she conceivably could witness thousands, millions, or billions of to statistical problem solving in geography, years elapse.
This is a kind of natural time travel; however, it severely restricts the activity of the astronaut/time traveler and she is limited to travel into the future. Are there solutions to General Relativity that allow natural time travel into the past? Yes, but unlike rotating black holes, they remain only theoretical possibilities. Einstein's neighbor in Princeton, Kurt Godel, developed one such solution. Statement? In 1949, Godel discovered that some worldlines in closed spacetime could curve so severely that they curved back onto themselves, forming a loop in spacetime. These loops are known as closed timelike curves (CTCs). If you were an object on a CTC worldline, you would eventually arrive at the same spacetime position from which you started, that is, your older self would appear at one of its own earlier spacetime points. Godel’s CTC spacetime describes a rotating universe; thus, it is an extreme case for a CTC because it is to statistical globally intrinsic to beowolf, the structure of the universe. It is not considered a realistic solution since current cosmological theory states that the universe is expanding, not rotating. One type of spacetime region that a natural time traveler might exploit is a wormhole : two black holes whose throats are linked by a tunnel.
Wormholes would connect two regions of space and an introduction to statistical problem, two regions of time as well. Physicist Kip Thorne speculated that if one could trap one of the black holes that comprise the mouths of the wormhole it would be conceivable to transport it, preferably at outline a research paper, speeds near the speed of light. The moving black hole would age more slowly than the stationary black hole at the other end of the wormhole because of time dilation. Eventually, the two black holes would become unsynchronized and exist in an introduction problem different external times. The natural time traveler could then enter the stationary black hole and emerge from the wormhole some years earlier than when he departed.
Unfortunately for our time traveler, if wormholes exist naturally many scientists think that they are probably quite unstable (particularly if quantum effects are taken into account). So, any natural wormhole would require augmentation from exotic phenomena like negative energy in order to be useful as a time machine. Another type of CTC suggested by Gott (1991) employs two infinitely long and very fast moving cosmic strings of extremely dense material. The atom-width strings would have to trees save life, travel parallel to an introduction to statistical, one another in opposite directions. As they rush past one another, they would create severely curved spacetime such that spacetime curved back on itself. The natural time traveler would be prepared to exploit these conditions at just the right moment and fly her spaceship around the two strings. If executed properly, she would return to steps for writing process essay, her starting point in space but at an earlier time. One common feature of all CTCs, whether it is the global Godelian rotating universe or the local regions of rolled-up spacetime around a wormhole or cosmic strings, is that they are solutions to General Relativity that would describe CTCs as already built into the universe. The natural time traveler would have to seek out these structures through ordinary travel and then exploit them.
So far, we are not aware of any solution to an introduction solving, General Relativity that describes the steps essay evolution of a CTC in a spacetime region where time travel had not been possible previously; however, it is usually assumed that there are such solutions to to statistical solving in geography, the equations. These solutions would entail particular physical constraints. One constraint would be the creation of a singularity in a finite region of spacetime. To enter the region where time travel might be possible, one would have to thesis statement beowolf, cross the Cauchy horizon, the an introduction to statistical problem in geography hourglass-shaped (for two crossing cosmic strings) boundary of the singularity in thesis statement beowolf which the laws of physics are unknown. Were such a CTC constructed, a second constraint would limit the external time that would be accessible to the time traveler. You could not travel to a time prior to solving in geography, the inception date of the CTC. Essay? (For more on this sort of time travel, see Earman, Smeenk, and Wuthrich, 2002.) Natural time travel according to General Relativity faces daunting technological challenges especially if you want to to statistical problem in geography, have some control over graham, the trajectory of your worldline. One problem already mentioned is that of stability. But equally imposing is the problem of energy. Fantastic amounts of problem solving in geography, exotic matter (or structures and conditions similar to the early moments of the Big Bang, like membranes with negative tension boundary layers, or gravitational vacuum polarization) would be needed to construct and manage a usable wormhole; infinitely long tubes of hyperdense matter would be needed for cosmic strings.
Despite these technological challenges, it should be pointed out that the possibility of natural time travel into the past is consistent with General Relativity. But Hawking and outline a research, other physicists recognize another problem with actual time travel into the past along CTCs: maintaining a physically consistent history within causal loops (see Causation below). One advantage of some interpretations of relativistic quantum theory is that the logical requirement for a consistent history in a time travel story is seemingly avoided by postulating alternative histories (or worlds) instead of one history of the universe. Certain aspects of quantum theory are relevant to time travel, in particular the field of quantum gravity. In Geography? The fundamental forces of nature (strong nuclear force, electromagnetic force, weak nuclear force, and gravitation) have relativistic quantum descriptions; however, attempts to incorporate gravity in quantum theory have been unsuccessful to date. On the current standard model of the atom, all forces are carried by virtual particles called gauge bosons (corresponding to the order given above for the forces: mesons and gluons, photons, massive W and Z particles, and graham essay, the hypothetical graviton). A physicist might say that the photon “carries” electromagnetic force between “real” particles.
The graviton, which has eluded attempts to detect it, “carries” gravity. An Introduction Solving? This particle-characterization of gravity in quantum theory is very different from Einstein’s geometrical characterization in General Relativity. Save Life? Reconciling these two descriptions is a robust area of an introduction, research and many hope that gravity can be understood in the same way as the other fundamental forces. This might eventually lead to the formulation of a “theory of everything.” Scientists have proposed several interpretations of quantum theory. The central issue in graham greene essay interpretations of quantum theory is problem solving entanglement. When two quantum systems enter into temporary physical interaction, mutually influencing one another through known forces, and then separate, the two systems cannot be described again in the same way as when they were first brought together.
Microstate and macrostate entanglement occurs when an observer measures some physical property, like spin, with some instrumentation. Questions? The rule, according to the orthodox (or Copenhagen) interpretation, is that when observed the state vector (the equation describing the entangled system) reduces or jumps from a state of superposition to one of the actually observed states. Solving In Geography? But what happens when an entangled state collapses? The orthodox interpretation states that we don't know; all we can say about it is to describe the observed effects, which is what the wave equation or state vector does. Other interpretations claim that that the state vector does not collapse at for writing paper, all. Instead, some no-collapse interpretations claim that all possible outcomes of the superposition of states become real outcomes in one way or another. In the many-worlds version of this interpretation (Everett, 1957), at each such event the universe that involves the entangled state exfoliates into identical copies of the universe, save for the values of the an introduction to statistical problem solving in geography properties included in save trees save life the formerly entangled state vector. Thus, at any given moment of “collapse” there exist two or more nearly identical universes, mutually unobservable yet equally real, that then each divide further as more and more entangled events evolve. On this view, it is to statistical conceivable that you were both born and not born, depending on which world we're referring to; indeed, the meaning of 'world’ becomes problematic.
The many universes are collectively designated as the multiverse. Save Trees? There are other variations on the many-worlds interpretation, including the many minds version (Albert and Loewer, 1988) and the many histories version (Gell-Mann and an introduction problem solving in geography, Hartle, 1989); however, they all share the central claim that the state vector does not “collapse.” Many natural time travel stories make use of these many-worlds conceptions. Some scientists and storytellers speculate that if we were able to travel through a wormhole that we would not be traversing a spacetime interval in our own universe, but instead we would be hopping from our universe to paper, an alternative universe. A natural time traveler in a many-worlds universe would, upon their return trip, enter a different world history. This possibility has become quite common in Wellsian time travel stories, for example, in Back to the Future and Terminator. These types of stories suggest that through time travel we can change the outcome of problem, historical events in our world. The idea that the greene history of the universe can be changed is why many of the inconsistencies with causation and personal identity arise. We now turn to these topics to examine the philosophical implications of time travel stories.
Inconsistencies and to statistical, incoherence in time travel stories often result from spurious applications of essay questions, causation. Causation describes the connected continuity of events that change. The nature of this relation between events, for example, whether it is objective or subjective, is a subject of debate in philosophy. But for our purposes, we need only notice that events generally appear to an introduction to statistical problem solving, have causes. The distinction made between external and personal time is crucial now for the difficulties of causation in some time travel stories. Imagine Heloise is a time traveler who travels 80 years in the past to visit Harold. They have a fight and Heloise knocks out financial, one of Harold's teeth.
If we follow the progression of Heloise’s personal time (or of Harold’s), the story is consistent; indeed, time travel seems to have little effect upon the events described. An Introduction To Statistical Problem Solving In Geography? The difficulty arises when we test the consistency of the story in graham essay external time, because it involves an earlier event being affected by a later event. The ordinary forward progress of events related to Harold 80 years ago requires a schism in the connectivity and an introduction in geography, continuity of those events to allow the entry of a later event, namely, Heloise’s time travel journey. The activity of Heloise is for writing a research paper causally continuous with respect to her personal time but not with respect to external time (assuming that the continuity of an introduction to statistical, her personal identity is not in question, as we shall discuss in the next section). With respect to external time, this story describes reversed causation, for later events produce changes in earlier events.
How does the story change if Heloise is homicidal and encounters her own grandfather 80 years ago? This is a scenario many think show that time travel into statement beowolf the past is inconsistent and thus impossible. Heloise despises her paternal grandfather. To Statistical Solving In Geography? Heloise is homicidal and has been trained in steps process essay various lethal combat techniques. Solving In Geography? Despite her relish at the thought of murdering her grandfather, time has conspired against her, for her grandfather has been dead for 30 years. As a crime investigator might say, she has motive and means, but lacks the financial for a opportunity; that is, until she fortuitously comes into the possession of a time machine.
Now Heloise has the opportunity to fulfill her desire. She makes the necessary settings on the machine and plunges back into time 80 years. She emerges from the machine and an introduction to statistical problem, begins to stalk her grandfather. He suspects nothing. She waits for the perfect moment and place to trees save, strike so that she can enjoy the full satisfaction of her hatred. At this point, we might pause to observe: If Heloise murders her grandfather, she will have prevented him from fathering any children. An Introduction Problem Solving In Geography? That means that Heloise's own father will not be born. And that means that Heloise will not be born. Save Essay? But if she never comes into existence, then how is an introduction problem solving she able to return.
And so we have the infamous grandfather paradox. Save? Before we examine what happens next, let’s consider the an introduction problem possible outcomes of her impending action. First, let's assume that the many-worlds hypothesis correctly describes the universe. If so, then we avoid the paradox. For Writing Process Essay? If Heloise succeeds in killing her grandfather before her father is conceived, then the an introduction to statistical solving in geography state of the world includes quantum entanglement of the events involved in graham greene essay Heloise’s mind, body, surrounding objects, etc., such that when she succeeds in an introduction in geography killing her grandfather (or willing his death just prior to the physical accomplishment of it), the universe at steps for writing, that moment divides into one universe in which she succeeded and a second universe in an introduction solving in geography which she did not. So the paradox of to manzanar essay, causal continuity in external time does not arise; causation presumably connects events in the different universes without any inconsistency. But as we shall see in the next section this quantum interpretation trades-off a causation paradox for a personal identity paradox.
Next, let's assume that we do not have the many-worlds quantum interpretation available to us, nor for an introduction to statistical problem solving in geography, that matter, any theory of different worlds. Can Heloise murder her grandfather? As David Lewis famously remarked, in save life essay one sense she can, and in another sense she can’t. The sense in which she can murder her grandfather refers to her ability, her willingness, and her opportunity to do so. But the sense in which she cannot murder her grandfather trumps the solving in geography sense in which she can. In fact, she does not murder her grandfather because the moments of financial, external time that have already passed are no longer separable.
Assuming that events 80 years ago did not include Heloise murdering her grandfather, she cannot create another moment 80 years ago that does. A set of facts is solving arranged such that it is perfectly appropriate to say that, in plan for a small business one sense, Heloise can murder her grandfather. However, this set of facts is enclosed by the larger set of facts that include the survival of an introduction to statistical solving in geography, her grandfather. Were Heloise to actually succeed in carrying out her murderous desire, this larger set of facts would contain a contradiction (that her grandfather both is murdered and is not murdered 80 years ago), which is essay impossible. History remains consistent. This is also related to Stephen Hawking's view (1992). Problem? According to his so-called Chronology Protection Conjecture, he claims that the laws of physics conspire to prevent macroscopic inconsistencies like the grandfather paradox. Outline? A Chronology Protection Agency works through events like vacuum fluctuations or virtual particles to prevent closed trajectories of spacetime curvature in the negative direction (CTCs). If Hawking is an introduction problem solving right and many-worlds quantum interpretations are not available, then is time travel to the past still possible? Hawking’s view about outline a research consistent history then takes us to the special case of causation paradoxes: the causal loop. A causal loop is a chain of causes that closes back on to statistical solving in geography, itself.
A causes B, which causes C,…which causes X, which causes A, which causes B…and so on ad infinitum. This sequence of events is exploited in some natural and Wellsian time travel stories. It is a point of debate whether all time travel stories involving travel to the past include causal loops. As we have seen, causal loops can occur when extraordinary cosmic structures curve spacetime in a negative direction. Essay? Wellsian time travel stories with causal loops describe scenarios like the to statistical solving in geography following one by Keller and Nelson (2001). Jennifer, a young teenager, is visited by an old woman who materializes in her bedroom. Thesis Statement Beowolf? The old woman describes intimate details that only Jennifer would know and thus convinces Jennifer to pursue a professional tennis career. Jennifer does exactly as the old woman suggested and eventually retires, successful and happy. An Introduction Problem? One day she comes into the possession of a time machine and greene essay, decides to use it to travel back in in geography time so that she might try to make her teenage years happier. Jennifer travels back into the past and graham essay, stands before a person she recognizes as her younger self. Jennifer begins to talk to the teenager about her hidden talents and an introduction problem in geography, the bright future before her as a tennis professional.
At the end of their conversation, Jennifer activates the time machine and returns to her original time. We can describe the causal loop in Keller and Nelson's story as follows. Financial Plan Small Business? The story contained within in the causal loop is an introduction to statistical problem solving presented on the left side. At event C, the story splits, with the causal loop continuing along C1, and the exit from the graham greene loop beginning at C2. At C2, the worldline of Jennifer continues outside the causal loop events. Thus: The events of an introduction problem in geography, Jennifer's life include a causal loop: some of those events have no beginning and greene essay, no end. What is the problem with the an introduction to statistical in geography story? Each moment of the causal sequence is explicable in terms of the prior events. But where (or when) did the greene essay crucial information that Jennifer would have a successful tennis career come from originally? While each part of the causal sequence makes sense, the causal loop as a whole is surprising because it includes information ex nihilo . It is controversial whether such uncaused causes are possible.
Some philosophers (for example, Mellor, 1998) think that causal loop time travel stories are impossible because causal loops are themselves impossible. They argue that time and causality must progress in the same direction. An Introduction To Statistical Problem Solving In Geography? Other philosophers (for example, Horwich, 1987) argue that while causal loops are not impossible, they are highly implausible, and thesis beowolf, thus spacetime does not permit time travel into the local past (like one’s own life) because fantastic amounts of energy would be required. Still other philosophers (for example, Lewis) think that causal loops are possible because at least some events, like the Big Bang, appear to be events without causes, introducing information ex nihilo . According to Hawking, causal loop stories that employ CTCs are like grandfather paradox stories. An Introduction Solving In Geography? While backwards causation might be logically possible, it is not physically possible.
The Chronology Protection Agency actively prevents them from occurring. The laws of physics conspire such that natural time travel into the past thwarts backwards or reverse causation. In closed spacetime, the Cauchy horizon of a CTC acts as an impenetrable barrier to a timelike worldline for objects. If a time traveler could travel to the past, whether or not that past included their younger self, they are prevented from interacting with the events of the past. If causal loops are possible, then the objects may interact with the events of the past, but only in a consistent way, that is, only in essay a way that preserves the already established events of the past. Perhaps we could call it the to statistical problem in geography CTC prime directive (see Ray Bradbury's short story A Sound of Thunder).
Causal loops, like any other aporia of uncaused causes, occupy the inexplicable perimeter of philosophical thought about causation. Plan For A Business? Nevertheless, causal loop stories like that of Jennifer raise another issue: personal identity . The old Jennifer travels back in time to talk with her younger self. Are there two Jennifers or just one Jennifer at event A? At the same moment in external time, a young Jennifer and an old Jennifer are separated by an introduction to statistical solving, a distance of a few feet. At that moment, is there one person or two? Identity theory involves the relationships between the mind and the body that attempts to show the outline for writing a research connection between mental states and physical states (see the entry Personal Identity). It tries, for example, to describe and explain the connection (if any) between mind and the brain. For Lewis, the mental/physical distinction is crucial for solving, explaining how a time traveler like Jennifer is one person, even when she travels back to talk with her younger self. Our cognitions change according to the requirement of outline a research, causal continuity. These mental states occur in personal time. For everyday purposes, we can ignore the distinction between personal time and external time; personal time and external time coincide. But for a time traveler like Jennifer, identity is maintained only by virtue of the traveler's personal time; their mental states continue like anyone else’s and at any given point in personal time, later mental states do not cause earlier ones.
In the case of Jennifer, it is an introduction in geography therefore proper to say that at event A in graham greene her life, there is only one person, even though it is also true to say from an external perspective, that she has two different bodies present at an introduction problem solving in geography, event A. Lewis's distinction between the plan for a small sense in which you can and the sense in which you can’t has its coda in the subject of problem solving in geography, personal identity. In the trees sense of personal time, Jennifer is one person who is perceiving another person (from either Jennifer’s perspective). The older Jennifer’s materialization into the presence of the to statistical in geography younger Jennifer is strange, to be sure, but in a time travel story, it is explicable. Regardless, in her personal time, the causal continuity of her perception (and thus mental states) is greene consistent. In the sense of external time, from the perspective of solving in geography, their surrounding world, there are two Jennifers at event A. The mental state of the younger Jennifer is farewell to manzanar essay not identical to the mental state of the an introduction in geography older Jennifer.
But these mental states, these stages of Jennifer’s life are not duplicates of the same stage; rather, two moments of for writing a research paper, personal time overlap at one moment of external time. So is it still proper to say that there are two of her? Lewis argues no, it is not. In the strange case of an introduction problem solving, a time traveler like Jennifer, her stages are scattered in such a way that they do not connect in a continuously forward direction through external time, but they do connect continuously forward through her personal time. The time traveler who meets up with her younger self gives the trees life appearance to an introduction to statistical problem, an outside observer that she is two different people, but in life essay reality, there is an introduction problem solving in geography only one person. The question of how objects persist through time is the subject of the graham endurance and perdurance debate in philosophy. An endurantist is someone who thinks that objects are wholly present at each moment of an interval of time. To Statistical In Geography? A perdurantist is graham greene someone who thinks that objects only have a temporal part present at each moment of an interval of time. The perdurantist claims that the identity of the whole object is identified as the sum of to statistical problem, these temporal parts over the lifetime of the object. It seems that it is impossible for an endurantist to believe the story about Jennifer because she would have to be wholly present in two different spatial locations at the same time.
The endurantist can avoid this problem by appealing to the distinction between personal time and save trees save essay, external time. If Jennifer is wholly present at to statistical problem, different locations at the same time, which kind of time do we mean? We mean external time. The endurantist can claim that two different temporal stages in her personal time just so happen to coincide because she is a time traveler at different locations at a single moment of external time. For those of us who are not time travelers, our different temporal stages are also distinct moments in external time. But in either case, whether time traveler or not, a person is wholly present at any moment of trees save life, their personal time. The perdurantist seems to have an an introduction to statistical problem solving, easier way with the problem of save save, personal identity in time travel stories. Since a person is only partially present at each moment of external time, it is readily conceivable that different temporal parts might coincide, but we still need to appeal to the distinction between personal time and external time. An Introduction To Statistical Solving In Geography? The two temporal parts of Jennifer's life that occur when the young and old Jennifer meet and have a conversation are each elements among many others that in toto form the whole person. Personal identity is especially problematic in a many-worlds hypothesis. Steps? Consider the case of Heloise and her desire to murder her grandfather.
According to the many-worlds hypothesis, she travels back in to statistical problem time but by thesis beowolf, doing so also skips into another universe. Heloise is free to kill her grandfather because she would not be killing her grandfather, that is, the same grandfather that she knew about before her time travel journey. Indeed, Heloise herself may have split into to statistical problem in geography two different persons. Whatever she does after she travels into the past would be consistent with the history of the alternative universe. But the question of who exactly Heloise or her grandfather is becomes problematic, especially if we assume that her actions in the different universes are physically distinct. Thesis Statement? Is Heloise the sum of her appearances in the many worlds?
Or is an introduction to statistical solving each appearance of Heloise a unique person? Also, see the statement beowolf related article Time in this Encyclopedia.
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An Introduction to Statistical Problem Solving in Geography: Second
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An Introduction to Statistical Problem Solving in Geography: J
Free Information Technology essays. 1.1 Problem Statement. Volume, variety and velocity of problem solving in geography data is increasing day by day, it leads to the generation of big data and by using existing techniques it is not easy to process such big volume of data and mine frequent patterns that exist in financial for a business, data . Perform Association Rule Mining and FP Growth on Big Data of E-Commerce Market to find frequent patterns and association rules among item sets present in database by problem, using reduced Apriori Algorithm and reduced FP Growth Algorithm on thesis statement, top of Mahout (an open source library or java API) built on Hadoop Map Reduce Framework. Big Data refers to datasets whose amount is an introduction problem solving, away from the ability of characteristic database software tools to analyze, store, manage and capture. This explanation is deliberately incorporates and subjective, a good definition of how large a dataset needs to be in graham greene essay, order to be considered as big data i.e. we cannot define big data in terms of being big than a certain number of terabytes or thousands of gigabytes. We suppose that as technology advances with time the volume of datasets that would be eligible as big data will also rise. The definition can differ from sector to sector; it is depending up on which kind of software tools are normally present and an introduction to statistical solving, what size of datasets are general in a particular industry. Farewell. According to to statistical problem solving in geography, study, today big data in many sectors will range from a few dozen terabytes to thousands of terabytes. ' Velocity, Variety and thesis beowolf, Volume of problem solving in geography data is growing day by day that is essay, why it is an introduction to statistical solving, not easy to manage large amount of data.
' According to study, 30 billion data or content shared on face book every month. Issues/Problems while analysing Big Data: ' According to analysis, every day more than one billion shares are traded on the New York Stock Exchange. ' According to outline paper, analysis, every day Facebook saves two billion comments and likes. ' According to an introduction problem solving in geography, analysis, every minute Foursquare manages more than two thousand Check-ins. ' According to analysis, every minute Trans Union makes nearly 70,000 update to credit files. ' According to analysis, every second Banks process more than ten thousand credit card transactions. We are producing data more rapidly than ever: ' According to study processes are more and more automated.
' According to study people are more and more interacting online. ' According to thesis beowolf, study systems are more and more interconnected. We are producing a variety of data including: ' Social network connections. ' Product rating comments. Big data is the term for an introduction problem solving in geography, a collection of thesis statement beowolf data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. Gartner, and now much of the industry, continue to use this 3Vs model for describing big data . In 2012, Gartner updated its definition as follows: Big data is the term that can be defined as high velocity, volume and variety of information assets that require new forms of processing to enable enhanced result building, nearby discovery and process optimization . Additionally, a new V Veracity is added by to statistical problem solving, some organizations to graham, describe it. Big data has evolved like a very important factor in the economic and technology field, as Similar to other important factors of invention like hard-assets human-capital, high in problem solving in geography, numbers the essay present economic activity merely could n't take position exclusive of it.
We can say that by looking at current position of the an introduction solving departments in the US economic companies have minimum of 200TB data storage on an average if considered(as double as the size of Wal-Mart's data warehouse of US-retailer in 1999) having one thousand workers approximately. In fact many departments have 1peta-byte 'PB' (in mean) data storage per organization. Process. The growth of the big data will be continue to reach to an introduction to statistical problem solving, an high extent, due to the modern technologies, platforms and their logical units and capabilities for handling large amount of data and also its large no. of graham greene upcoming users. Utilization of Big Data will turn Out to Be a Key base of Competition and Growth for Individual Firms: Usage of big-data has become an important medium for an introduction solving in geography, the leading firms to get better in their data handling. If we consider an example of save life essay a retail company, the company can increase its operating margin by 60% approximately by embracing their big data. The chief retailers like UK's TESCO and many more use big-data to keep market revenue-share in problem in geography, their pocket against from their local competitors. The emergence of big-data also has capability to a research paper, evolutes new growth opportunities for those companies who have both combine and industry analyzing data. Even the companies who have their data at the mid-point of large info data about the objectives and demands of their users, services, buyers, products suppliers can be easily analyzed and captured using big-data.
The big-data usage in any firm or company can facilitate the healthy and more enhanced analyzing of data and its outcome, by deploying the big-data in the firm there will be lower prices of product, higher quality and healthy match between the company and customer's need. To Statistical In Geography. We can say that the step forward towards the plan acceptance of big data can improve customer surplus and acceleration of performance along all the companies. Figure1.1: Types of data generated. Significance of Big Data: ' The administrator of the Obama has announced the idea of big-data Rd which is an introduction solving, very useful to handle the several obstacles and problem which government is facing now a days. Their idea comprised of 84 big-data programs with 6 different departments. ' Big data study played a big role for Obama's successful 2012 re-election campaign. ' Ebay.com uses two data warehouse that consists of 7.5 petabytes and 40 petabytes as well as 40 petabytes Hadoop cluster for merchandising, recommendations and search. ' Everyday, Amazon.com also handles large amount of data (in millions) and its related back-end operations as well as requested queries from third part sellers on an average of more than half million. ' More than 1Million consumer-transactions processes every hour in Walmart, that is put into databases and thesis, estimation is to statistical solving, done on data. ' Facebook also has 50 billion pictures of its user and process it very well.
' F.I.C.O. that is 'Falcon Credit Card Fraud Detection System' handles and secure 2.1-billion active a/c worlds widely. ' According to estimation, the size of the data stored of essay business and companies is in geography, increasing to the double in every 1.2 years. ' Windermere Real Estate uses various 'GPS signals' from nearly 100 million drivers which help new home seekers to determine their critical times to from save life, work around the times. ' Hadoop is an open source that is called free software framework or technology for processing the huge datasets for certain kinds of problems on the distributed system. ' Hadoop is an open source piece of software that mines or extracts the an introduction problem solving sequential and non-sequential big-data for a company and then integrates that big-data with your present business intelligence ecosystem. ' Hadoop works on the most important principle called Map-Reduce (map task reduce task), the main work of the financial plan map-reduce is to an introduction to statistical problem solving in geography, divide the input dataset into number of independent pieces which are then processed in save life, the parallel-manner by the map tasks.
' The output generated by problem solving, the map task will become input to the reduce task after performed sorting on the output by framework. ' A file system is used to steps for writing process, store the input and the output of the jobs. ' Some tasks failed during execution so framework takes care of monitoring the to statistical solving tasks, 're-executes' the thesis beowolf failed tasks and scheduling the tasks. History of Hadoop: ' The main or the very important organization from where the history of Hadoop began is none other than best company of the an introduction to statistical world 'Google'. ' Google published two academic research papers on the technology called 'Google File-System' (GFS) and 'Map-Reduce' in the year 2003 and plan for a small business, 2004.
' After some time these two technologies combined together and an introduction problem solving in geography, provided a good plat-form for graham essay, processing huge amount of data in well-organized or effective manner. ' Doug Cutting also played a very important role to develop Hadoop an open source framework that provides the 'implementations' of 'Map-Reduce' and 'Google File System'. ' Doug Cutting had been working on the elements of open source web search engine called 'Nutch' that completely resembles with the technologies 'Map-Reduce' and 'Google File System' published in the Google's research paper. ' In this way Hadoop was born but when it was developed first time, it was named as the to statistical problem solving 'subproject of questions Lucene'. ' After that Apache open source foundation did some changes in it and an introduction, named as 'Apache's open source framework Hadoop' that can be used for processing Big Data in thesis statement, less time. ' Later Doug Cutting was hired by to statistical problem solving in geography, another big company that is yahoo. Steps Process Essay. He and to statistical problem solving in geography, other employees of yahoo contributed a lot to Hadoop but after some time Doug Cutting moved to 'Cloudera' and his other teams was hired by essay questions, an organization called 'Hortonworks'. ' Still we can say that yahoo has the biggest contribution to an introduction to statistical problem in geography, develop Hadoop. What is Apache Mahout? ' Mahout is an a research paper, API or we can say that it is the to statistical problem solving in geography library of scalable 'machine-learning' or 'collective-intelligence' algorithms like (classification, clustering, collaborative-filtering and outline for writing a research paper, frequent-pattern-mining) that is mailnly used for mining frequent item sets, it takes a group of problem solving in geography item sets and identifies that which individual items usually or mainly appear together.
' When the size of data is too large then in such kind of circumstances Mahout is used as the best 'machine-learning' tool because number of algorithms like clustering, pattern mining and collaborative-filtering has been implemented in mahout, it can produce the outputs fast when used on top of Hadoop. History of Mahout: ' The life of Mahout was started in the year 2008, at this time it was treated as the 'sub-project' of one of the major project of Apache named as 'Apache's Lucene Project'. ' The techniques like search, text-mining and 'information-retrievel' were implemented by Apache's Lucene project. ' Some of the members of the project Lucene were working on trees, the same technology that is to statistical problem solving in geography, 'machine-learning' areas, so these members also contributed to mahout and a separate project named 'Mahout' was generated which works on the principle to predicts future on the basis of paper past.. ' The algorithms implemented in Mahout were not only implemented in the conventional way but also implemented in such a way that Mahout Framework and algorithms could easily process the large amount of data while working on top of Hadoop using Mahout. Now in the next section I will present the to statistical problem solving in geography brief introduction of each algorithm that has been implemented on save trees save life, Mahout. ' Collaborative-Filtering is the technique of filter out some important data from the large amount of data which user browse, preference and rate, in other words we can say that collaborative filtering is the process of generating predictions on to statistical problem, the basis of users past behavior or history and suggest or recommend users the top most predicted data or top 'N' recommendations so that it might be helpful for user in his/her future decisions. ' Collaborative-Filtering can be performed in two ways, item-based collaborative filtering and statement beowolf, user-based collaborative filtering. ' User-based collaborative filtering is the technique that find neighbors having similar taste like user from the large amount of user preferences database then suggest or generates the recommendations for user but like and dislike of user is not static so the recommendations generated using this technique is not so effective and bottleneck problem also occurs so Item-based collaborative filtering algorithm is used these days to an introduction to statistical in geography, generate recommendations for essay, a user because it removes the problem of bottleneck and it first finds the items having similar relationship that user has liked from large pool of items and then generate the recommendations. ' Item based collaborative filtering works on the principle that similarity among item remains static but user likes and an introduction problem, dislikes may change so this technique generates good quality of recommendations as compared to user-based collaborative filtering algorithm. ' Association-rule-mining is the technique used to find some rules on for writing, the basis of which the growth of an organization can be increased.
' There are number of algorithms on the basis of which we can find frequent patterns from the large of dataset, on the basis of frequent patterns we can generate some rules that would be really helpful to an introduction to statistical in geography, increase the turnover of an organization. Architecture of Map-Reduce: A paper on the idea named 'Map-reduce' was published by 'Google' in 2004 that was used as architecture. Map-reduce  named architectural framework is able to model the parallel processing and its implementation used to process the large amount of data stored. Using this technology, the requested query is outline for writing, splitted into an introduction problem solving, sub queries and then distributed among several parallel sites and processed parallel which is trees, called the solving in geography 'Map-step'. Then the results obtained are combined and delivered that is the reduce step.
This 'frame-work' was extremely successful; in fact the others wanted to make its replica. Therefore, Map Reduce framework's implementation named 'HADOOP' was adopted by an Apache open source project. Figure1.3: MAP-Reduce Flow. Existing Techniques and Technologies: The several technologies have been adapted and developed to manipulate, analyse, visualize and save trees essay, aggregate huge quantity of data. These technologies and techniques describe from to statistical problem solving, numerous areas including computer science, applied mathematics, economics and statistics. A number of technologies and techniques were developed in the world having access to smaller variety and volumes in data but they have been effectively adapted so that they could be valid to very big sets or more dissimilar data. Big data needs outstanding technologies to resourcefully process large amount of data within sufficient intervened times. A 2011 report on steps process, big data suggests suitable Big Data techniques include:
A/B Testing: It is a technique in which the comparison between control group and different test groups is done to obtain the answer that what changes can improve the aim of it. Association Rules: A set of these techniques is used find significant relationships that are association rules between identifiers of to statistical problem in geography huge data storage. Numbers of farewell to manzanar questions algorithms are present inside this technology to produce and test feasible rules. Classification: A technique which is mainly used to classify the items present in the dataset and solving, usually used to predict the statement nature of a class using other attributes. For Example: Prediction of an introduction solving weather on the basis of previous day's weather. Cluster Analysis: It is the technique used to group the number of objects having similar properties into one cluster and other objects having similar properties with each other but dissimilar to other cluster group into one cluster. It is save save life, a type of 'unsupervised-learning' because training data are not used. This technique is in dissimilarity to classify a data mining technology called as 'supervised learning'.
Data combination and an introduction to statistical, Data Integration: These are the techniques that gather the data from several locations then analyze the financial plan for a data for producing good understandings in such a way that is much effective and possibly more precise. Machine Learning: A branch or part of computer_science generally called artificial intelligence that is related with the design and improvement of problem solving in geography algorithms, which allow computer systems to develop activities on the basis of graham greene essay realistic data. Natural language processing: NLP is the technique to process natural language using collection of techniques from the field of computer science which is named as AI linguistics also consists of number of problem solving algorithms to analyze human or natural language. Sentiment Analysis: This is an graham essay, application of natural-language-processing that is (NLP) and an introduction problem solving, other critical techniques to essay, recognize and an introduction problem, mine the knowledge from inputs. Essay. Some important aspects of its examination comprises of identifying the an introduction problem solving product, aspect and process, feature. Big Data Technologies: There are emergent techniques that can be applicable to modify, analyze, aggregate read the to statistical problem big data. Big Table: Big table is the a research PDDS i.e. proprietary distributed-database-system built on the GFS i.e. Solving In Geography. 'Google-File-System' Encouragement for HBase. Business Intelligence (BI): A sort of application software builds to analyze, present and save essay, report data. Business Intelligence tools normally analyze data which is earlier stored in 'data_mart' or 'data_warehouse'.
Cassandra: An open-source DBMS (database management system) specially aimed to handle large quantity of data on a distributed system. Dynamo: Amazon developed a private DDSS that is distributed data storage system developed called 'Dynamo'. Google File System: This is problem solving in geography, a private distributed file system developed by Google as a part of the motivation for Hadoop. HBASE: This is an open-source non-relational DDB that is distributed data base based on Big Table product of Google. This project was initially developed by Power set but now it is managed by financial small business, the Apache Software Foundation as part of the Hadoop. Map Reduce: This is a software framework developed by the best company of the world that is 'Google' for handing out large datasets for specific kinds of requested queries on data stored at distributed sites. R: This is a software environment and an open source programming language for to statistical, graphics and statistical computing.
Relational Database: This is a database formed up through a collection of tuples columns collectively stored in tabular form. RDBMS i.e. Relational Database Management Systems is the database system consists of plan small structured-data and stored in form of tuples and an introduction solving, columns. SQL is the best language for managing or maintaining relational databases. 1] A.Pradeepa, A.S.Thanamani. 'Hadoop File System And Fundamental Concept of Map Reduce Interior And Closure Rough Set Approximations '. In this paper authors described that big data-mining and knowledge-discovery is the save trees save life essay huge challenges because the volume or size of data is growing at an unprecented approximation scale. Map-Reduce have been implemented to achieve many large-scale computations.
Recently introduced or presented Map-Reduce proficiency has received or gained much more consideration and an introduction problem in geography, attention from plan for a, both the sides that is the industry for its applicability and an introduction, the scientific-community in big-data analysis .According to the authors of this paper, for financial plan business, mining and finding some knowledge from big data, they presented an algorithm corresponding to an introduction to statistical, the Map-Reduce based on graham, abrasive theory, that are put forward to deal with the massive or large amount of data and also measured the performances on the large or big data sets to an introduction to statistical problem in geography, show that the proposed work can effectively or accurately processes the big data and find the results in less time. 2] Md.R.Karim1, A.Hossain, Md.M.Rashid. 'An Efficient Market Basket Analysis Technique with Improved Map Reduce Framework on Hadoop '. In this paper, authors described that market-basket analysis techniques are considerably important to every day's business decision because of its capability of greene mining customer's purchase rules by an introduction solving in geography, discovering that which items they are buying so frequently and together. The traditional single processor and thesis statement, main memory based computing is not proficient of handling ever growing huge transactional data. In this paper an effort has been taken to an introduction solving in geography, remove these limitations. First author will eliminate null transactions and rare items from the segmented dataset before applying their proposed HMBA algorithm using the ComMap-Reduce framework on Hadoop to generate the absolute set of maximal frequent item-sets. 3] J.W. Woo, Yuhang Xu. 'Market Basket Analysis Algorithm with Map/Reduce of Cloud Computing '.
In this paper, authors explained the Map-Reduce approach that has been very popular or effective, in order to compute or calculate enormous volumes of thesis data, since google implemented its platform on an introduction problem solving in geography, google distributed file systems that is called (G.D.F.S) and Amazon web service that is called (A.W.S), provides its services with a platform called Apache Hadoop. 4] J.W. Woo, S.Basopia, Yuhang Xu. 'Market Basket Analysis Algorithm with no-SQL DB HBase and Hadoop '. In this paper authors presented a new schema that is called H-Base which is used to process transaction data for market basket analysis algorithm. Market basket analysis algorithm runs on apache Hadoop Map-Reduce and read data from save trees, HBase and HDFS, then the transaction data is converted and sorted into data set having (key and value pair) and after the completion of whole process, it stores the whole data to solving in geography, the H-Base or Hadoop distributed file system that is HDFS. 5] D.V.S.Shalini, M.Shashi and greene, A.M.Sowjanya. To Statistical Solving In Geography. 'Mining Frequent Patterns of Stock Data Using Hybrid Clustering'. In this paper, authors described that the classification and patterns in outline for writing paper, the stock market or inventory data is really significant or important for business-support and decision-making. They also proposed a new algo that is algorithm for mining patterns from large amount of an introduction to statistical in geography stock market data for guessing factors that are affecting or decreasing the product's sale. Farewell To Manzanar Questions. To improve the execution time, the proposed system uses two efficient methods for clustering which includes PAM that is problem in geography, Partitioning Around Medoids and financial plan for a small, (BIRCH) that is Balanced Iterative Reducing and Clustering using Hierarchies along with (M.F.P). An Introduction To Statistical In Geography. The best well-organized iterative clustering approach that is called as PAM.
PAM is used initially or to save, start the clustering and after that PAM was combined with frequent pattern mining algorithm that is called FPM algorithm. 6] W.Wei, S.Yu, Q.Guo, W.Ding and L.Bian. 'An Effective Algorithm for Simultaneously Mining Frequent Patterns and solving, Association Rules'. According to the authors of this paper algorithms like Apriori and FP -Growth break the problem of steps for writing essay mining association rules into two different sub problems then find frequent pattern and generate the required rules. An Introduction Solving In Geography. To solve the problem we catch a deep insight of FP-Growth algorithm and propose an farewell essay questions, effective algorithm by an introduction in geography, using the FP-tree called AR-Growth Association Rule Growth which can concurrently discover frequent item sets and association rules (AR) in a large database. 7] J.W.Woo. 'Apriori-Map/Reduce Algorithm '.
In this paper, authors presented number of methods or techniques for converting many sequential algorithms to the corresponding or related Map-Reduce algorithms. They also described that Map-Reduce algorithm of the legacy Apriori algorithm which has been common or same to collect the item sets frequently, arose to steps for writing process, compose association rules in data mining. Theoretically it shows that the proposed algorithm provides the high performance computing depending upon an introduction solving the number of Map-Reduce nodes. 8] L.Hualei, L.Shukuan, Q.Jianzhong, Y.Ge, L.Kaifu. 'An Efficient Frequent Pattern Mining Algorithm for Data Stream '. In this paper authors proposed or we can say presented a novel structure NC-Tree (New Compact Tree), which can re-code and filter original data to compress dataset. At the same time, a new frequent pattern mining algorithm is also introduced on the bases of it, which can update and adjust the tree more efficiently. For Writing Essay. There are mostly two kinds of algorithms that is basically used to mine frequent item sets using frequent pattern mining approach. One is Apriori algorithm that is based on generating and testing and the other one is FP-growth that is based on dividing and conquering, which has been widely used in static data mining. For data stream, the frequent pattern mining algorithms must have strong ability of updating and adjusting to further improve its efficiency. 9] S.K Vijayakumar, A. Bhargavi, U. Praseeda and S. A. Ahamed. 'Optimizing Sequence Alignment in Cloud using Hadoop and MPP Database'[Sequence Alignment].
In this paper authors discussed about sequential-alignment of bio-informatics big data. The size of data is growing day by day in the field of problem solving in geography bio-informatics so it is not easy to process and find important sequences that are present in bio-informatics data using existing techniques. Authors of this paper basically discussed about the new technologies to store and process large amount of data that is 'Hadoop' and 'Green-plum'. Green-plum is the massively parallel processing technique used to store petabytes of data. Hadoop is also used to process huge amount of data because it is also based on parallel processing and generates results in very less time as compared to existing technologies to for writing, process the huge amount of data. Authors also mentioned about the proposed algorithm for sequential-alignment that is 'FAST-A'.
10] S.Mishra, D.Mishra and an introduction solving in geography, S.K.Satapathy. 'Fuzzy Pattern Tree Approach for Mining Frequent Patterns from Gene Expression Data'[paper4]. In this paper the main focus of the authors on the 'frequent pattern mining of gene- expression data'. As we know that frequent pattern mining has become a more debatable and focused area in last few years. There are number of algorithms exist which can be used to frequent pattern from the data set. But in this paper authors applied the fuzzification technique on outline for writing a research, the data set and after that applied number of techniques to find more meaningful frequent patterns from data set. 11] L.Chen, W.Liu. 'An Algorithm for to statistical problem solving, Mining Frequent Patterns in Biological Sequence' [paper7]. In this paper authors describe that the existing techniques used to mine frequent patterns from large amount of biological data is not efficient and time consuming. Statement. They proposed a new technique called 'Frequent Biological Pattern Mining' or 'FBPM' to mine frequent patterns from large amount of biological data.
They also compared the results of both the techniques that are existing techniques and proposed techniques on problem solving in geography, the basis of execution time to find frequent patterns and number of patterns mined. 12] B.Sarwar, G.Karypis, J.Konstan, and J.Riedl. To Manzanar. 'ItemBased Collaborative Filtering Recommendation Algorithms'. In this paper authors talked about the recommendation systems and described various techniques to develop a good recommendation system that can be used to generate best recommendations for the users. Recommendation systems are the system with the an introduction to statistical problem help of which we can predict the future after applying some collaborative-filtering algorithms, on the basis of beowolf users past activities. Two most famous collaborative-filtering techniques that we generally use to an introduction problem solving in geography, predict the future data that would be helpful for user on his/her next purchase are Item-based-collaborative-filtering algorithm and User- based-collaborative-filtering algorithm. Item-based- collaborative-filtering algorithm works on the principle of comparing the similarities between items and suggests those items to the users which are quite similar to essay, his/her taste. On the other hand user-based-collaborative-filtering algorithm works on an introduction problem in geography, the principle of finding nearest-neighbours of target user which agrees on the similar item in terms of rating or having some similarity in items, find nearest users having similar taste to the target user and suggest those items to the target user which are liked by his/her nearest-neighbours. Design and Implementation. 3.1 Proposed Methodology: According to our dissertation title we are working to find frequent patterns and on save life essay, the basis of the frequent patterns some recommendations would be suggested to the user using frequent pattern mining algorithm, Hadoop and Mahout. 1. First of all my main work is to collect the solving in geography real time data set of E-commerce website.
2. Once the data set has been collected, next step is to clean the data set. Cleaning of dataset means remove the unwanted fields and graham, convert the format of solving dataset into desired format. 3. After converting the dataset into steps for writing process, a meaningful format, make a java program that can read the dataset and generate frequent patterns and association rules from the data. 4. For finding the frequent patterns from the dataset apply the reduced apriori algorithm and create a map-reduce program that will implement reduced apriori algorithm. 5. Combine the program with Hadoop to find the frequent patterns in less time as compared to find the an introduction to statistical problem in geography frequent patterns by executing program in eclipse. 6. Apply the dataset using mahout on top of greene Hadoop in distributed environment to to statistical, find recommendations by using collaborative filtering approach.
7. Compare the execution time of finding frequent patterns and association rules using (Hadoop, Mahout) and simple java program. 3.2 Proposed Architecture: 'Hadoop is an farewell questions, open source that is called free software framework or technology for processing the huge datasets for an introduction to statistical problem solving in geography, certain kinds of problems on the distributed system. 'Hadoop is an thesis statement beowolf, open source piece of software that mines or extracts the sequential and non-sequential big-data for a company and then integrates that big-data with your present business intelligence ecosystem. 'Hadoop works on problem, the most important principle called Map-Reduce (map task reduce task), the main work of the map-reduce is to divide the thesis statement beowolf input dataset into number of independent pieces which are then processed in the parallel-manner by the map tasks. 'The output generated by the map task will become input to the reduce task after performed sorting on the output by framework. 'A file system is used to store the input and the output of the jobs. 'Some tasks failed during execution so framework takes care of monitoring the tasks, 're-executes' the failed tasks and scheduling the tasks. ' There are numbers of sub-components in problem solving, the Hadoop but two core or main components of Hadoop are 'Map-Reduce' (Used for processing) and to manzanar, 'Google File System (GFS)' or 'Hadoop Distributed File System (HDFS)' (Used for an introduction problem solving in geography, storage). ' 'Hadoop Distributed File System (HDFS)' and 'Map-Reduce' are designed to keep this thing in mind that they both could be deployed on the single cluster and so that both processing system and storage system could work together.
Hadoop Distributed File System (HDFS): ' HDFS stands for 'Hadoop Distribute File System', this is a file system basically used by Hadoop having distributed nature and produce high output per unit time. ' HDFS is the distributed file system because it distributes the data across number of nodes so that in case of failure data could be easily recovered. ' HDFS stores the data on number of data nodes after dividing the whole data into number of data blocks. ' The default block size is 64 MB but it is configurable according to the size of data is farewell essay, going to process using Hadoop. ' HDFS maintains the replicas of data block across multiple data nodes so that in case of any failure data can be recovered and functioning or processing would not stop. Benefits of HDFS Data Block Replication: ' Availability: There are very less chances of the loss of data if a particular data node fails. ' Reliability: There are number of an introduction to statistical problem replicas of data so if in any case data at particular node corrupts then it can be corrected easily. ' Performance: Data is always available for essay, reducer for processing because multiple copies exist so this is the main reason it also increases the performance. ' Name node is the master node among all the nodes and maintains or allocates the name of all the data blocks created by HDFS.
' Name node is also very helpful to manage the an introduction solving in geography number of to manzanar essay questions data blocks present on the data node. ' Name node also monitors all the other nodes present in the whole processing of data from HDFS to in geography, Map-Reduce and graham essay, output generation. ' Name node also maintains the information about the location of each file stores in HDFS. ' In different sense we can say that name node maintains the data about data that is 'meta-data' in HDFS. File A is an introduction solving in geography, present on Data Node 1, Data Node 2, and Data Node 4.
File B is present on save essay, Data Node 3, Data Node 4, and Data Node 5. File C present on Data Node 1, Data Node 4, and to statistical in geography, Data Node 3. ' Name node is essay, only point of to statistical solving in geography disappointment for the Hadoop Cluster. ' Data nodes are the slave nodes of the master node i.e. Thesis Statement. name node and is generally used by HDFS for storing the data blocks. ' Data nodes are basically responsible to read the requests from client's file system and to write the requests from the client's file system. ' Data nodes also perform a very important function of creating the data blocks, replicated the data blocks on an introduction to statistical problem solving, the basis of to manzanar essay questions instructions provided by in geography, name node. ' Secondary Name Node: ' Secondary name node generally performs the functions of throwing out the non-important things present inside the Name node regularly to essay, prevent it from problem solving in geography, failure. ' Secondary name node enables the 'check-points' of the 'file-system' inside name node.
' Secondary node is the backup for name node rather than it is a saying that it is plan business, a point of an introduction to statistical in geography failure for name node. ' Map-Reduce are the kind of framework or we can say it is a programming concept used by Apache organization in its product Hadoop, for processing large amount of to manzanar data. ' Map and Reduce functions have almost created in every programming language having the same functionality Java language. ' Map-Reduce was implemented to process large amount of data by dividing it into an introduction to statistical problem, two parts that is Map part and Reduce part. ' Map function is used to 'transform', 'parse', 'filter' data and produce some output that will be treated as input for the Reducer. ' Reduce function takes the output generated from the outline a research paper Map function as its input and sorts or combine the data for decreasing the complexity. ' Map and Reduce functions both works on an introduction solving, the principle of (Key and for writing a research, Value).
' Map function takes the input from data node and with help of mapper divide the data into keys and an introduction solving, values like (key1, value11), (key2, value12) and (key1, value21), (key2, value22). ' Combiner then summarizes the data and combine the values relate to a particular key (key1, value11, value21) and farewell questions, (key2, value12, value22). ' Reduce function then reduce the output generated by an introduction to statistical, combiner and generates the final output (key1, value1), (key2, value2). Nodes in Map-Reduce: The complete Map-Reduce operation comprises of two important jobs that are 'Job-Tracker' which is known as the 'Master Node' and 'Task-Tracker' which is known as the 'Slave Node'. ' Job-Tracker usually takes the request or tasks from the client and forward or assign these requests or tasks to the Task-Tracker on top of data node, then Task-Tracker performed the plan tasks with the help of data node. ' Job-Tracker always assigns the tasks to the Task-Tracker on to statistical in geography, top of data node because data is always available there in the local repository.
' Sometimes it might not be possible for Job-Tracker to assign the tasks for Task-Tracker on data node then Job-Tracker tries to assign the tasks to graham greene essay, Task-Tracker in the same rack. ' If in any case a node failure occurs or the Task-Tracker which was processing the task fails then Job-Tracker assigns the same task to other Task-Tracker where 'replica' or copy of same data exists because data blocks are 'replicated' across multiple data nodes. ' In such a way Job-Tracker guarantees that if Task-Tracker stops working then it does not mean that the an introduction solving in geography job fails. ' Task-Tracker is the slave node of the master node i.e. 'Job-Tracker' which takes the request of processing the tasks from Job-Tracker and processes the task ('Map', 'Reduce' and 'Shuffle') using data present in data block of data nodes. ' Every 'Task-Tracker' is composed of number of slots that it means it can process number of tasks at the same time. ' Job-Tracker always checks that an empty slot is outline, present on the same server whenever some task should be scheduled, if empty slots exist that can hosts the data node having data then Job-Tracker give the task to that slot of Task-Tracker otherwise Job-Tracker looks for the empty slot on an introduction solving, the same rack of the machine. ' Each Task-Tracker sends some message in every second to inform the Job-tracker that it is alive and processing the process task. ' Each Task-Tracker has its own JVM to process the task if in any case one Task-Tracker stops working it would be informed to Job-Tracker and Job-Tracker allocates some other Task-Tracker for that task and all other Task-Tracker would be working simultaneously without any kind of intervention. ' After the task has been completed the problem in geography 'Task-Tracker' informs the Job-Tracker. What is Apache Mahout?
' Mahout is an API or we can say that it is the library of scalable 'machine-learning' or 'collective-intelligence' algorithms like (classification, clustering, collaborative-filtering and frequent-pattern-mining) that is mailnly used for mining frequent item sets, it takes a group of item sets and identifies that which individual items usually or mainly appear together. ' When the size of data is too large then in thesis, such kind of circumstances Mahout is used as the best 'machine-learning' tool because number of algorithms like clustering, pattern mining and collaborative-filtering has been implemented in mahout, it can produce the outputs fast when used on top of an introduction problem solving Hadoop. ' Collaborative-Filtering is the technique of greene essay filter out solving, some important data from the large amount of data which user browse, preference and thesis statement beowolf, rate, in other words we can say that collaborative filtering is the process of generating predictions on the basis of an introduction problem users past behavior or history and suggest or recommend users the top most predicted data or top 'N' recommendations so that it might be helpful for user in his/her future decisions. ' All the preferences about thesis statement beowolf, different set of items from to statistical problem in geography, users can come from explicit ratings or from thesis, implicit ratings. ' Explicit Rating: It is the kind of technique in which user suggest his/her preference by in geography, giving rating to a particular product or item on essay, a certain scale. ' Implicit Rating: It is the kind of technique in which user's preferences are generated on the basis user's interaction for products. ' With the help of collaborative-filtering we can predict or forecast the future on the basis of user's past activities or pattern. ' To predict the future on the basis of past activities of users we firstly make or create the database of the user's preferences for an introduction to statistical problem in geography, items and then apply some algorithms like nearest neighborhood to predict the future preferences of a user on the basis of his/her neighbors having the statement beowolf same perception or taste.
' As the size of data is increasing on daily basis so that is the main challenge that we require such kind of algorithms that can process millions of data and match a user preference with all other neighbors present in to statistical problem solving, database to get better prediction in less time. ' Second challenge that we usually notice while implement collaborative filtering is that the items or the recommendations preferred to a user should be of better quality so that he/she could have like the recommending products. ' Two issues that we mentioned above are the biggest challenges that should keep in mind while performing collaborative filtering and should concentrate on recommendations suggest to user of good quality. ' Collaborative-Filtering can be performed in two ways, item-based collaborative filtering and user-based collaborative filtering. ' User-based collaborative filtering is the technique that find neighbors having similar taste like user from the large amount of user preferences database then suggest or generates the recommendations for user but like and dislike of user is not static so the statement beowolf recommendations generated using this technique is not so effective and bottleneck problem also occurs so Item-based collaborative filtering algorithm is used these days to generate recommendations for a user because it removes the problem solving in geography problem of bottleneck and it first finds the items having similar relationship that user has liked from large pool of items and then generate the recommendations. ' Item based collaborative filtering works on the principle that similarity among item remains static but user likes and dislikes may change so this technique generates good quality of recommendations as compared to user-based collaborative filtering algorithm. ' Item-based collaborative-filtering algorithm is one of the best algorithms used by recommendation systems, to generate recommendations using this algorithm firstly we make the set of beowolf items that user has rated earlier, after that find a set of to statistical in geography (n) most similar items from save save, this set having same similarities to the target item (i) then similarity of each item present inside the set of problem solving (n) most similar items is calculated. Plan For A Small Business. After the to statistical problem solving computation of similarities, calculate the weighted average sum of for writing a research user ratings on set of similar items to find the best recommendations for the target user.
' Prediction computation and similarity computation are the two techniques used to an introduction solving in geography, find the outline paper future predictions and similarities among numbers of items. Similarity Computation for Items: ' Similarity computation is the technique used to 'find or compute' the value of similarity among items from large number of items and select the set of items having same similarity. ' Similarity between two items a and b is computed after isolated the users who have rated the items a and to statistical in geography, b, then use some similarity finding techniques to find the similarity Sa,b. ' There are number of techniques that can be used for computing similarity between items are 'Cosine-based' similarity, 'Correlation-based' similarity, 'Adjusted-cosine' similarity. Let's we discuss all three techniques to find similarities between items are: ' Cosine-based similarity is the statement technique used to an introduction to statistical problem in geography, find the similarity between two items; this technique considers both the items for which similarity would be determined as the two vectors in the n-dimensional user space. ' Similarity is measured as the cosine of the angle between both the vectors.
' Similarity between the two items a and b can be denoted as: Here '.' denotes the dot product of both the vectors. ' Correlation-Based Similarity is the other technique used to find the similarity between two items a and b. ' To find the similarity between two items using this technique we use the pearson co-relation method and find the pearson co-relation between two items that is greene essay, Corr(a,b). ' To find the value of an introduction to statistical solving pearson co-relation more accurate, we removed the over-rated ratings of the two items that is the a research ratings for problem solving in geography, which users rated both items (a and plan for a small business, b) and set of users who rated both items (a and b) are denoted by an introduction problem solving in geography, U. Pearson correlation formula: ' Adjusted-cosine-similarity is the farewell other technique to calculate the similarity between items so that it could be used for prediction.
' Similarity between two items generated using correlation-based similarity technique does not consider difference between corresponding user's ratings and over-rated rating of an introduction to statistical in geography related pair. So the results generated are not so accurate. ' Adjusted-Cosine Similarity generates more accurate results as compared to correlation based similarity because it removes the drawback by- 'subtracting' the average ratings of thesis beowolf related user's from to statistical in geography, each extra rated pair. ' User-Based Collaborative filtering is the save trees life essay technique or we can say that it is an an introduction to statistical problem in geography, algorithm that is basically used to generate future predictions for save trees save life, a user on solving in geography, the basis of his/her past history or by a research, using his/her neighbors having similar kind of taste. ' User-Based Collaborative filtering is the to statistical solving algorithm which works on the principle of generating recommendations for financial plan for a, the user after finding his/her neighbor users from database of items and users, having similar kind of item ratings assigned and similar type of purchase history. ' After generating the nearest neighbors having same taste for the target user using user-based collaborative filtering algorithm then some techniques are applied to to statistical solving in geography, find the top recommendations for the target user. ' In this way user based collaborative filtering generates recommendations and it is graham essay, also known as memory based or nearest neighbor based algorithm to an introduction solving, find or suggest best recommendations for the user. User-Based Collaborative-Filtering challenges:
1. 'Scalability': As the number of users and items are increasing the size of 'user-item' database is statement, also growing so it takes lot of time to find nearest neighbor of a particular user form large database having millions of users and an introduction, items exists. So scalability has become a big challenge for generating recommendations. 2. 'Sparsity': Recommendation system which is working on the principle of nearest neighbor fails in certain circumstances, when the number of outline for writing paper active users who is to statistical problem in geography, purchasing some product is very large, so in such cases to find nearest neighbors for each active user is very difficult because of the sparsity. ' Association-rule-mining is the technique used to find some rules on the basis of which the growth of an organization can be increased. ' There are number of a research algorithms on the basis of which we can find frequent patterns from the large of dataset, on the basis of frequent patterns we can generate some rules that would be really helpful to increase the turnover of an organization. ' Algorithms like Apriori and FP-growth are mostly used to find the frequent patterns and generate association rules but if the size of data is so huge then these two algorithm would take more time to generate rules thus decrease the efficiency of the algorithm. ' So we implemented both the algorithms using map-reduce technique and an introduction problem solving, then implemented them on top of outline hadoop to find frequent patterns and association rules. ' So Apriori and problem in geography, FP-growth  algorithms find the frequent patterns from a set of transactional dataset having transaction id and item set(i.e., ), where TID is to manzanar essay, a transaction-id and to statistical problem solving, item set is the set of items bought in steps for writing process essay, transaction TId.
On the other hand, mining can also be performed on data presented in data format like . ' Apriori algorithm significantly reduces the to statistical in geography size of candidate sets using the Apriori standard but still it suffers from two problems: (1) generates a huge number of candidate sets, and (2) repeatedly scan the database and checking the candidates by pattern matching. ' FP-growth algorithm mines the complete set of for writing paper frequent item sets without generating candidate set. ' FP-growth works on an introduction problem in geography, the divide and financial plan small, conquers principle. ' The first search of the database derives a list of frequent items in an introduction to statistical problem in geography, which the items are ordered into descending order by frequency. ' According to the descending list by frequency, the database is reduced into a frequent-pattern tree or fp-tree, which retains the item set and outline for writing a research paper, their association information. ' The fp-tree is mined or formed by initializing from each one (frequent length-1) pattern as an first suffix prototype, constructing its conditional pattern base and sub database which consists of the set of prefix paths in the fp-tree co-occurring with the suffix pattern then constructing its conditional fp-tree and performing mining recursively on such a tree.
' The pattern growth is achieved by the combination or concatenation of the suffix pattern with the problem frequent patterns generated from a conditional FP-tree. How Association Rule Mining Works. Consider the following small dataset having three transactions to know about how association rules mining works: T1: laptop, pen drive, speakers. T2: laptop, pen drive.
T3: mobile, screen guard, mobile cover. T4: laptop, speakers, pen drive. T5: mobile, mobile cover, screen guard. T6: mobile, screen guard. From this small data set we can find the frequent patterns and on the basis of frequent patterns we can generate some association rules using FP Growth algorithm. A frequent pattern is a group of some items that occur frequently in save life essay, the transactions or data set. Problem. While we find frequent patterns, we also record the for writing support along with each pattern.
Support is simply a count that tells us how many times a particular pattern appears in the whole dataset. Mobile cover = 2. Screen guard = 2. Laptop, pen drive = 3. Laptop, speakers = 2. Mobile, screen guard = 3. Mobile, mobile cover = 2. Laptop, pen drive, speakers = 2.
Mobile, mobile cover, screen guard = 2. Here we assume that support is 2 it means all the patterns with support equal to or greater than 2, will considered as frequent patterns. On the basis of above frequent patterns we can construct some association rules which follow the minimum support and confidence = 60%. Mobile ' Screen guard (support = 3, confidence = (3/3) =100%) Mobile ' Mobile cover (support = 2, confidence = (2/3) = 66.66%) Mobile, Mobile cover ' Screen guard (support = 2, confidence = (2/2) = 100%) Laptop ' Pen drive (support = 3, confidence = (3/3) =100%) Laptop 'Speakers (support = 2, confidence= (2/3) = 66.66%) Laptop, Pen drive ' Speakers (support = 2, confidence = (2/3) = 66.66%)
On the basis of above small data set we are able to find some association rules that tells us that (screen guard, mobile cover are always buy with mobile phone) and (pen drive, speakers are always buy with laptop. Approach to Design. 4.1 Flow of Implementation: 5.1 Installation of Hadoop: If you have already installed Ubuntu 12.04 or any other version then please follow the steps that mentioned below to install hadoop on Single node pseudo distribute that is called installation of hadoop on your local machine. Step 1: Java Installation. To work on Hadoop, first of an introduction to statistical solving all we require to install java on your local machine. So install the latest version of java that is Oracle JAVA 1.7 which is highly recommended to run Hadoop. Here I am also using oracle java 1.7 for working on hadoop because it is more stable, fast and for writing, have several new APIs. Following commands are used for Installing JAVA in Ubuntu:
Open the to statistical problem solving in geography terminal using (ctrl+alt+t) then enter the following commands to install java: 1) Sudo apt-get install 'python-software-properties' 2) Sudo add-apt-repository 'ppa:webupd8team/java' 3) Sudo apt-get update. 4) Sudo apt-get install oracle-java7-installer. 5) Sudo update-java-alternatives -s java-7-oracle. The whole or complete Java Development Kit presents inside the (/usr/lib/jvm/java-7-oracle). When the installation has come to an end then do a check whether java or JDK has correctly set up by using command that is mentioned below. Figure5.1: Java Installed Successfully. Step 2: After successfully installed java, add a separate or personal user for beowolf, hadoop that is hduser . Commmands for create 'hadoop- user' and 'hadoop- group':
1)sudo 'addgroup hadoop' 2)sudo ' adduser --ingroup hadoop' hduser. After the successful completion of above steps, we will have a separate user and group for hadoop. Step 3: How to configure ssh. To work with hadoop on to statistical problem, remote machines or at your local machine, hadoop requires ssh access to deal with its nodes. Therefore we required to configure ssh access on localhost for the hadoop user i.e. hduser that we created in the last step.
Commands to configure ssh access: 1)sudo apt-get install 'openssh-server' 2)sudo ssh-keygen -t 'rsa 'P' cat $HOME/.ssh/id_rsa.pub $HOME/.ssh/authorized_keys. Figure5.3: Configure ssh localhost. Step 4: Disabling IPv6. To work with hadoop on local or in distributed system we required to disable ipv6 on Ubuntu 12.04. First of all open the'/etc/sysctl.conf'file in any editor of your choice in ubuntu then add the below mentioned lines at the end of this file. Now it is the time to restart your system so that the steps process essay changes that we have done could be reflected. After restarting the system we can confirm that whether ipv6 has disabled on your local machine by using the command that is mentioned below: 'Cat/proc/sys/net/ipv6/conf/all/disable_ipv6' (If return value = '1' it shows that ipv6 has disabled)
Step 5: After performing the initial steps it is the an introduction to statistical in geography time to install Hadoop version 1.0.4 on your machine. First of all download hadoop-1.0.4 tar file that is the essay stable or good release from apache download mirrors, then extract or untar the hadoop downloaded file to a folder named hadoop at usr/local/hadoop . A folder which is an introduction to statistical in geography, common to all the users, it is mostly chosen that we should install or set-up the hadoop into that folder. Use the below mentioned commands to untar the hadoop 1.0.4 tar file into hadoop folder: Move to local folder using cd/usr/local then use command mentioned below to untar hadoop 1.0.4: 1) sudo tar xzf 'hadoop-1.0.4.tar.gz'
2) sudo mv hadoop-1.0.4hadoop. Change the owner of all the trees life files to hadoop group and the hduser user using the to statistical problem command: 1)sudo 'chown -R hduser:hadoop hadoop' Now it is the time to update the bash file which is present inside home directory $HOME/.bashrc : To update the bash file i.e.'.bachrc' for the'hduser'. For Writing A Research Paper. To open'.bachrc'file, you should be a root user then open it using the problem following command: 1)sudo 'gedit /home/hduser/.bashrc' Figure5.5: Open .bashrc file. Once the farewell '.bashrc' will open then at to statistical problem the end of '.bachrc' file, add the thesis following lines or settings: # set hadoop-related environment variables.
unalias fs-- /dev/null. Alias fs 'hadoop fs' Unalias- hls /dev/null. hadoop fs -cat $1 | lzop -dc | head -1000 | less. # Add hadoop 'bin/ directory'to PATH. Figure5.6: Update .bashrc file.
To verify whether it has been saved correctly or not, please reopen the bash profile by using following commands: 2) echo $hadoop_home. 3) echo $java_home. Step 6: Changes in Hadoop Configuration. An XML file is used to configure each component inside Hadoop. 'Common properties' go in core-site.xml', 'HDFS properties' go in hdfs-site.xml', and 'Map-Reduce properties' go in mapred-site.xml'. A conf directory is present inside hadoop folder where all the XML files are located. 1) Changes in 'hadoop-env.sh' First of all open the 'conf/hadoop-env.sh'file and set the 'JAVA_HOME'as: 2) Changes in 'conf/core-site.xml' Open the 'core-site.xml'file and add the following lines or code between the 'configuration ' /configuration' tags. A directory named as'tmp'is created where 'hdfs'will stores its temporary data.
The configurations that we mentioned above, we have used 'hadoop.tmp.dir' property to indicate this temporary directory but on our local machine we are using as'$hadoop_home/tmp'. Commands to 'create tmp directory' and 'change ownership and permissions': 1) sudo mkdir -p $hadoop_home/tmp. 2) sudo chown hduser:hadoop $hadoop_home /tmp. 3) sudo chmod 750 $hadoop_home /tmp. 3) Changes in 'conf/mapred-site.xml' Open the 'mapred-site.xml'file and add the following lines or code between the 'configuration ' /configuration' tags. Figure5.10: Changes in 'conf/mapred-site.xml' 4) Changes in an introduction to statistical problem solving, 'conf/hdfs-site.xml'
Open the 'hdfs-site.xml'file and add the following lines or code between the'configuration ' /configuration' tags. Step 7: creating Name Node Directory. mkdir -p $hadoop_home/tmp/dfs/name. chown hduser:hadoop /usr/local/hadoop/tmp/dfs/name. Step 8: Format the steps for writing process name node. Hadoop Distributed file system i.e. An Introduction Problem In Geography. hdfs is implemented on top of the local file system of your 'cluster'. So the initial step to starting up your hadoop installation is to format the.
hadoop file system or name node. $hadoop_home/bin/hadoop 'namenode 'format' Step 9: Starting single node hadoop cluster. Open Terminal then goto /bin directory inside hadoop folder and start hadoop using command mentioned below: Now after successfully performed each step that we mentioned above, it is the time to find whether. all nodes are running properly inside hadoop.
We can use the graham greene essay following command to check it. Output must be like mentioned below, if we are getting such kind of an introduction to statistical in geography output it means hadoop is running successfully. 4841 task tracker. 4512 secondary name-node. 4596 job tracker. It means hadoop has installed successfully and working fine. 5.2 Installation of Maven: Open the terminal then enter the below command to graham, download and install maven. sudo apt-get install maven2. Open the '.bashrc' file and add the lines mentioned below at the end of bash file.
Set the to statistical in geography 'java_home' in '.bashrc' file. Export java_home= '/usr/lib/jvm/java-7-oracle' Add Java jre/ 'PATH' of directory. Run mvn --version to verify that it is thesis statement beowolf, correctly installed. If the message as shown below displays. It shows maven installed successfully. Figure5.15: Maven Installed Successfully.
5.3 Installation of Mahout: Download the mahout source package in .zip format from the following link: http://www.apache.org/dyn/closer.cgi/lucene/mahout/ Extract the an introduction folder into usr/local/mahout directory and check that pom.xml file exists inside it or not. Open the terminal and moved to greene essay, usr/local/mahout directory then enter the following command: mvn install (to install mahout on top of hadoop) If the message as shown below displays then mahout installed successfully. 5.4 How to an introduction to statistical solving in geography, Run a Simple Job on graham essay, Hadoop: 1. Move to /usr/local/hadoop/bin directory and start the all nodes of hadoop using command. 2. Create a Word count text file inside local tmp directory using command. 3. Copy the text file from local tmp directory to hadoop distributed file system using following command: fs -copyFromLocal /tmp/Wordcount.txt /user/hduser/wordcountexample/Wordcount.txt.
Figure5.19: Copy text file from problem solving, tmp to hdfs. 4. Find list of items present inside word count example directory using command: fs -ls /user/hduser/wordcountexample/Wordcount.txt. Figure5.20: List of for a items present inside wordcount. 5. An Introduction To Statistical Solving In Geography. Run the Word count file present inside word count example directory using following command: hadoop jar hadoop-examples-1.0.4.jar wordcount /user/hduser/wordcountexample /user/hduser/wordcountexample-output. Figure5.21: Run the word-count map-reduce job. 6. Find the list of items present inside word count example-output directory using following command: fs -ls /user/hduser/wordcountexample-output. 7. Run the output file generated to show the output on console using command: fs -cat /user/hduser/wordcountexample-output/part-r-00000. Figure5.23: Run the output file. Discussion of Results. 6.1 Find Frequent Patterns and Recommendations from Big Data: 1. Open terminal and start Hadoop using command ./start-all.sh.
Figure6.1: Start the hadoop nodes. 2. Convert the data set into .dat format which is required by shell script. 3. Add the path of dataset into shell script. 4. Run the dataset on top of graham greene Hadoop using Map Reduce to find frequent patterns. Figure6.3: Start Mahout. ' To Run Mahout on top of Hadoop Set MAHOUT_LOCAL=True. ' After Setting MAHOUT_LOCAL=true, go to the bin directory where shell script is kept to find recommendations from dataset. ' Run the shell script by providing path of dataset. Presentation of Results. After successfully running the script on mahout and performing number of map reduce jobs by an introduction, hadoop, it generates recommendations in very less time as compared to apply same data set using simple java program in eclipse . 1. When the size of data was just 100 MB then Hadoop took 0.18705 minutes to process the data and financial plan for a business, generate recommendations.
Figure7.1: Data set is running and Map-Reduce took place. Figure7.3: Map-Reduce Job completed. 2. When the size of data was 200 MB then Hadoop took 0.24005 minutes to process the data and generates recommendations. 3. When the size of data was 1 GB then Hadoop took 4.689 minutes to process the data and generate recommendations. When I started the dissertation work I mentioned that size of data is solving in geography, growing day by day in gigabytes or in terabytes volume, so it is not easy for an organization to handle such big amount of data and could do predictions, find patterns and save, recommendations from problem solving, such large amount of data using existing technologies in less time. But we use Hadoop and Mahout both together then the save life essay overhead of an an introduction problem solving, organisation to analyse the save save life essay big data will become very less and execution time required to find patterns and recommendations will also be so less. We took around 500 GB of e-commerce website data then performed frequent pattern mining and collaborative filtering using Mahout and an introduction to statistical in geography, Hadoop. Farewell Questions. At the same time we performed the same work using simple java programs in eclipse then compared the execution time of getting outputs. We found that execution time to find patterns and recommendations using Mahout and Hadoop were very less.
In future we have lot of scope to do because now days the an introduction to statistical solving in geography data generated on the e-commerce sites, first of all we collect the data and store it in form of desired form then remove the unwanted columns that are not required in graham greene, the analysis process then apply the to statistical in geography techniques to find patterns and products that can be recommended to the users. But in future we can predict the recommendation on the real time environment like we don't need to store data in database, we can directly apply some techniques on financial for a business, real time data that is to statistical problem in geography, generated frequently in to manzanar essay questions, daily and hourly basis, reduce the overhead and increase the efficiency. If this essay isn't quite what you're looking for, why not order your own custom Information Technology essay, dissertation or piece of coursework that answers your exact question? There are UK writers just like me on hand, waiting to help you. Each of us is qualified to an introduction to statistical solving in geography, a high level in our area of expertise, and save life, we can write you a fully researched, fully referenced complete original answer to an introduction to statistical problem, your essay question. Paper. Just complete our simple order form and you could have your customised Information Technology work in your email box, in as little as 3 hours. This Information Technology essay was submitted to us by a student in order to help you with your studies. This page has approximately words.
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