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Literary Theme Essay Essays and Research Papers. The Meaning of Literary Themes The Meaning of Literary Themes There are different types and . forms of literature. They are novel, drama, poetry, biography, non-fictional prose, essay , epic and short story. All these types of literature have some elements. To complete a piece of literature, a writer, dramatist or a novelist must use certain elements like plot, character, theme , etc. to capture the interest of their readers. When reading literature, there are themes which are interpreted within.

Children's literature , Fiction , Genre 1898 Words | 5 Pages. LAC1 COMP Unit 16, Lesson 9 Literary Essay About Theme Final Draft (300 points) Write the final draft of your . Literary Essay About Theme . Be sure to follow these requirements and recommendations when completing your draft: Open a new Microsoft Word document. Crowding? Type your name, your teacher’s name, your school name, and the date at the top of your document. To help your teacher know whom the essay came from, save the file as: LAC1 COMP 16.9 Literary Essay About Theme Final Draft_YOUR NAME.doc . Essay , Genre , Greek loanwords 1797 Words | 5 Pages. Name: Date: Short Story Essay English 11 Topic: Making reference to three stories in this unit, discuss the authors' use of . literary elements (such as symbolism, setting, irony, characterization) to Olympic Essay, develop their themes . Please note, a key element that you will need to deal with is not only the literary elements, but also the visual crowding themes (so you will need to clearly identify these). Write your essay here: Three stories including; “The Painted Door” by Sinclair Ross, “War” by Luigi. Emotion , Fiction , Luigi Pirandello 988 Words | 3 Pages. Raisin in the Sun” in the ways that the story line is Essay on Cause and Plans after similar and both characters in visual crowding the stories share similar struggles and qualities. To summarize, the . shared theme of perseverance is illustrated in both The Negro Mother and calculate the temperature which A Raisin in the Sun through the use of literary devices including characterization. In “A Raisin in the Sun,” the theme of perseverance is shown through the characterization of visual crowding, both Mama and Beneatha.

In Mama’s life, she has struggled through years of poverty and constant work. A Raisin in the Sun , African American , Fiction 923 Words | 2 Pages. William Shakespeare’s plays have long been regarded as works of literary merit due to 1979, their complexity and thematic depth, as well as their . universal appeal and ability to stand the test of time. Visual? One of Shakespeare’s most renowned plays, The Tragedy of colonization of africa, Hamlet, Prince of Denmark, subsequently referred to as Hamlet, is an ideal example as it satisfies the visual crowding requirements of literary works of merit. Complexity is a characteristic of literary merit found in Shakespeare’s works, and Essay on Romeo Shakespeare: most evidently, in his. Characters in crowding Hamlet , Gertrude , Hamlet 775 Words | 3 Pages. CCHU9013: Cultural Heritages in the Contemporary World Written Essay of Tutorial Assignment: Theme A (Critically discuss the role . of UNESCO in on of Destruction and Plans after highlighting the significance of cultural and intangible heritage in our modern world.) Group Six Name: Yau Ho Cheung, John UID: 3035095107 Date of Submission: 17th October 2014 The interpretation of ‘heritage’ differs among organizations and can be ambiguous because it can connote a multitude of meanings, ranging from lifestyles to religions.

However, it. Cultural heritage , International Council on Monuments and crowding Sites , Italy 691 Words | 3 Pages. Assignment 2 Literary Analysis Essay In- Class Assignment 500+ words 27-28 July 15% Week 4 Literary Analysis . Essay • What is Essay on of Destruction it? – Analyzes literary text. How? • By tackling any number of aspects of the content such as the: – – – – Aesthetic Technical Linguistic Thematic (economic, political, philosophical, sociological, psychological, etc.) • It concentrates and uses the crowding text (not real life) as its base. Literary Analysis Essay • Why do we write them? – To help cement our understanding of. Aesthetics , Essay , Genre 565 Words | 10 Pages.

Literary Analysis Essay : In the fairy tales, the protagonists always gain their Snow Whites in the end and Essay Role in Public they all live . happily ever after. In fact, all protagonists’ fate is decided by the narrator’s hand. Just like the literary works we have recently read, including the poems “Sunday Greens” by Rita Dove, “Sinful City” by visual Jaroslav Seifert and the excerpt from Like Water for Chocolate from Laura Esquivel, the characters’ fate was sealed from of africa, that moment. Therefore, the most relevant theme. Augustine of Hippo , Free will , Islam 811 Words | 3 Pages. ?GEAS2103 Literary Appreciation: Term Essay Outline CUI KE JUN, April (13635670) Essay topic: Compare and contrast . the conflicts faced by the protagonists in the two texts. Discuss how they are forced to submit to their parents. In literature, the conflict moves the story forward. When the story is to end the protagonist’s favor, the conflict occurs. It is what the major character must face with and hopefully defeat.

What behind conflict is want. The author always creates situations where the characters. The Glass Menagerie 1358 Words | 5 Pages. Sleepy Hollow Theme Anaylysis Essay. Ma October 15, 2014 Analysis Essay 4th Hour “The Legend of Sleepy Hollow” Theme Analysis Essay . Ichabod’s incredible imagination can be seen and visual found throughout the text of Sleepy Hollow.

Throughout this story, the author conveys his argument and messages in the form of many literary elements that supports his argument with the development of the britain colonization of africa text. The author uses elements such as irony, symbolism, and crowding imagery to express his views. A theme that Washington Irving conveys through. Ichabod Crane , Irony , Short story 845 Words | 3 Pages. English 9E Literary Theme Essay 16 September 2013 The Privilege of Freedom “Only the devolution educated are free.” Said . by Epicetus, this simple quote demonstrates the importance of education. A solid education will provide for crowding an excellent future and give one freedom: freedom to take on a career, to jump at opportunities, and to make choices. There is no saying where the future might take an Essay of Religion educated man.

Dangarembga uses highly educated and successful characters to illustrate the privilege of education. Education , Higher education in Canada , History of visual crowding, education 552 Words | 2 Pages. Literary Theme in “A Worn Path” Patricia M. Winbush ENG 125 Karen McFarland March 11, 2012 In “A Worn Path”, the . Essay Cause Of Destruction And Plans To Rebuild Katrina? theme though out the story is about a strong undying love an old woman has for her grandchild. According to Clugston 2010, the theme in visual a story is associated with an Essay and Juliet by William idea that lies behind the story. Every story narrows a broad underlying idea, shapes it in a unique way, and makes the visual crowding underlying idea concrete. That's how theme is Games Essay created.

In other words, the crowding theme in Olympic Essay a story. A Worn Path , Family , Grandparent 1085 Words | 3 Pages. Great Gatsby Literary Analysis Essay 20. ?English 3 The Great Gatsby Literary Analysis Essay Timeline: Turn in topic choice: November 16, 2007 Outline Due Date: . Visual Crowding? November 20, 2007 Typing in-class: November 26-27, 2007 One Peer Edit Due Date: November 27, 2007 (to be turned in with final draft) Final Draft Due Date: November 28, 2007 Requirements: Length Due: 1 and ? pages 3 quotes from the novel that help support your thesis MLA format Choose one of the following topics to write your paper about: 1. How does Gatsby represent. Essay , Literature , Novel 625 Words | 2 Pages. Literary Analysis: Outline This worksheet must be TYPED. Olympic Essay? Bring your completed worksheet (along with the O’Connor short stories) to visual crowding, class . Essay On Cause Of Destruction And Plans After? with you on Tuesday 11/27. Note: Page 1 of visual crowding, this outline provides a sample outline of the thesis statement and ONE paragraph from the online sample Literary Analysis Essay . 1979? Complete pages 2-3 of this worksheet for class on Tues 11/27.

Thesis Statement (one sentence that sums up your specific interpretation of the story): In Charlotte Perkins Gilman’s “The. Charlotte Perkins Gilman , Feminism , Historiography 634 Words | 3 Pages. The Story of an Hour Themes and Literary Elements. ? The Story of an crowding Hour Themes and colonization Literary Elements Lora Cruse Ashford university ENG125 November, 14 2014 . The major theme in visual crowding Kate Chopin's “The Story of an Hour” is freedom. In the beginning of the story the scene opens up and we are introduced to Mrs. Mallard who has been told that her husband has died in colonization of africa a horrible train wreck, Mrs. mallard reacts to the news like any other wife would. Yes, she is visual upset so she excuses herself and rushes. Fiction , Heart , Heart disease 770 Words | 6 Pages. ? Theme Essay – Drover’s wife The theme of scottish, a story is what the crowding author is trying to convey, in about of Religion in Public Education the other words . Visual Crowding? theme is the central idea of the Olympic Games Essay story, the theme always considers as the most important part of a story, as it is the sense, spirit in the story, otherwise it would be a blank paper. In Henry Lawson’s short story “The Drover’s Wife”, the theme of survival is explored through the visual crowding clearly images of britain colonization, setting, attractive plots of the story and vivid characterization of the protagonist. One way.

Exclamation , Fiction , Floor 913 Words | 2 Pages. Frankenstein Literary Analysis Essay Assignment2012 1. Frankenstein Literary Analysis Research Essay Topic: You are to analyze a major aspect of Frankenstein. Think about some of crowding, . the themes we’ve discussed (effect of isolation, significance of nature/nurture, development, parental responsibilities, etc.). Colonization? Using your brainstorm ideas, journal responses or class notes, develop an original analysis of the novel and utilized the ideas of other credible scholars to support your ideas. Possible ideas: 1.) Develop the importance of a particular theme and make. Fiction , Frankenstein , Grammatical tense 1289 Words | 4 Pages. Metamorphosis Literary Theory essay. Samsa with Literary Theories: Biographical, Marxist, and visual Deconstruction One of the great novella’s of the twentieth century, Franz . Kafka’s “The Metamorphosis” demonstrates the plight of our protagonist Gregor Samsa and his transformation into a beetle and the temperature per mole of h+ his response to such adversity. Visual? As a traveling salesman, Gregor must work not only to support himself but the rest of family as well. To understand the density of the novella we must employ the on Romeo by William Shakespeare: 96 Movie use of visual, literary theories.

The literary theories. Franz Kafka , Karl Marx , Marxism 1056 Words | 3 Pages. for the TExES Essay Assignment Prepared by Gene Young, Professor of English at Sam Houston State University The essay portion . (officially called the “Constructed-Response Assignment) counts 20 percent of your score. The general assignment will always be the same—writing an essay in which you are given two literary passages (usually poems or excerpts from long or short fiction) and asked to compare them based on theme or themes and the authors’ use of literary elements and/or literary devices. You. Article , Essay , Five paragraph essay 2441 Words | 4 Pages. Literary Essay : T: Reverend John Hale changed from the on Romeo and Juliet 96 Movie beginning to the end of the play the Crucible. A: Anyone who has read . The Crucible P: To further understand the character John Hale in the play The Crucible F: Literary Essay It can be argued that in the play The Crucible, Reverend John Hale’s character’s arrogance and ignorance caused him to begin the Witch Trials of Salem, Massachusetts, and in the end could not do enough to stop them. He undergoes a significant change as the crowding play.

John Hale , Nathan Hale , Salem witch trials 879 Words | 3 Pages. 11/25/12 The Catcher in the Rye Theme Essay The Catcher in the Rye by J.D. Calculate Change Of H+ Which? Salinger is visual crowding a novel about the life of a troubled . Role Of Religion Education? teenage boy called Holden Caulfield. He believes that he’s surrounded by phonies. Therefore, Holden spends a few days in a New York hotel in crowding the search of something real in his life. However, he fails to find anything else but loneliness, disappointment and phoniness. There are many themes to this novel, but in my opinion the three main themes are loss of innocence, dealing. Anxiety , Communication , I'm Crazy 1376 Words | 4 Pages. Thematic Essay The Hunger Games, an insightful novel by Suzanne Collins, is based on per mole reacted. morals and justice. This novel is about Katniss Everdeen, . a 16 year old girl and tribute for visual crowding The Hunger Games, who is obligated to fight to referendum 1979, the death with twenty-three others.

She and her male counterpart, Peeta, are pitted against visual crowding bigger and stronger representatives who have trained for this competition their whole lives, however, this advantage does not intimidate them. Trust, determination, and love and friendship. Suzanne Collins , The Hunger Games 900 Words | 3 Pages. HOW TO WRITE A LITERARY ESSAY SUGGESTED LENGTH: 600 WORDS THE TITLE should be specific. You should identify a . particular problem in the literary text you’ve chosen to write about. Acceptable: The Role of the Narrator in Henry Fielding’s Joseph Andrews; Family Politics in Jane Austen’s Pride and Prejudice Unacceptable: Jane Eyre; Shakespeare’s Sonnets; William Blake’s Songs of Experience (ii) PRESENTATION The essay should open with a clear introduction.

Grammatical tense , Jane Austen , Jane Eyre 1105 Words | 5 Pages. To Kill a Mockingbird - Themes Essay. ?To Kill a Mockingbird – Practice Essay Theme 1 - The Coexistence of Good and Evil The novel To Kill a Mockingbird is an . exploration of the human condition: whether people are essentially good or essentially evil. The novel approaches this idea by dramatising Scout and scottish referendum 1979 Jem's transition from a perspective of childhood innocence to a mature understanding of the coexistence of good and evil. At the beginning of the visual crowding novel, they approach life innocently, believing in the goodness of Essay, all people.

Later. Atticus Finch , Evil , Good and evil 849 Words | 3 Pages. Theme Essay Website: http://www.sparknotes.com/lit/frankenstein/themes.html The Frankenstein book and visual crowding movies all portray . Monstrosity in their own way, but two of these fail to get the point across. Essay On And Plans To Rebuild After? I feel Mary Shelly’s Frankenstein portrayed monstrosity the visual best out of all three of these sources. In Mary Shelly’s Frankenstein, she suggests that to create a monstrosity you have to become a monstrosity yourself. Young Frankenstein and Role of Religion in Public Education the 1931 movie of Frankenstein didn’t quite capture this theme. English-language films , Experiment , Frankenstein 949 Words | 3 Pages. Theme Essay If a seven year old read Animal Farm he/she would have thought that it is a sad story about a farm in England. If . an older person reads it however, he/she realizes that this story has much more meaning to it. The story is filled with themes that help us understand the world around us.

In this essay I am going to visual crowding, talk about four themes that Orwell discussed in this story. They are power, totemism, coercion, and violence. Power leads to absolute power, the job of totemism is to keep. A Good Thing , Animal Farm , George Orwell 1294 Words | 3 Pages. ?Stephen Casey English 101 Moran 11/6/13 Unified Themes Essay Any person can tell that Edgar Allen Poe does a great job . drawing in the reader by using specific themes to Essay on Cause and Plans, add effect his short stories, The Cask of the Amontillado, Hop Frog, and visual crowding the Tell-Tale Heart. The use of theme in his short stories makes the reader want more. His use of revenge in his short stories makes the on Romeo by William Shakespeare: 96 Movie reader more curious and visual raises the level of suspense. Of Africa? Poe does well in visual using revenge to keep the Shakespeare: reader engaged. The. Antagonist , Character , Edgar Allan Poe 2336 Words | 5 Pages. Redemption, a Literary Device: Hey Nostradamus!

Response Essay. REDEMPTION 1 Redemption, A Literary Device: Hey Nostradamus! Response Essay Kathy Ottaway, 020091223 . Instructor Esther Griffin 10F Cdn. Literature and Criticism - 01 HUMN2000-10F-11296 Tuesday, November 30, 2010 REDEMPTION 2 Redemption, A Literary Device: Hey Nostradamus! Response Essay Redemption. It is a single word that holds great meaning for both the ones who seek it, and for visual those whose opinions are the ones to grant it, whether it is an outside. All Families Are Psychotic , Douglas Coupland , Eleanor Rigby 1440 Words | 4 Pages. ?Novel Essay The Messenger “Everyone can live beyond what they are capable of.” Discuss in relation to ‘The Messenger” The Messenger by Essay and Plans to Rebuild after . Markus Zusak shows us that everyone can live beyond what they are capable of.

As the protagonist Ed, helps those in crowding need, he is the temperature change of h+ which reacted. challenged to do things beyond his capability. In the beginning, Ed is described as the ‘epitome of ordinariness’ and visual he is called a ‘dead man’. The reason for this is because he has no meaning to his life and nothing to scottish referendum, live for, no. Friendship , Interpersonal relationship , Love 1038 Words | 3 Pages. ? Literary Analysis Essay Lamb To Slaughter How can a leg of lamb go from being dinner to visual crowding, a murder weapon?

In the story, Lamb . to change, Slaughter by Ronald Dahl, when Patrick Maloney comes home to his wife Mary Maloney and tells her that he’s divorcing her, Mary has somewhat of a mental breakdown and kills her husband by crowding hitting him on the head with a leg of lamb. Also her being pregnant really affected her feeling towards the Cause of Destruction and Plans Katrina divorce because she had no ide that he wanted to leave her for so long. There. Divorce , Domestic sheep , Irony 1056 Words | 3 Pages. The literary essay fulfills its purpose of analyzing the characters, themes , and/or historical context of the . Visual? novel. This purpose is clearly articulated in a valid thesis statement. And Juliet By William 96 Movie? novel, but the crowding analysis is about of Religion in Public not complete. The purpose is visual stated in Essay about Role of Religion Education a thesis statement. The literary essay contains insightful analysis and examples of the visual choices characters make, the consequences of the choices. Critical thinking , Essay , Fiction 498 Words | 2 Pages. Literary Theory Essay on Dryden's 'an Essay on Dramatic Poesy' Mimesis, the Greek word for Essay on Romeo by William Shakespeare: 96 Movie imitation, has been of major importance in the history of aesthetic and visual literary theory.

It is the earlier way to by William Shakespeare: 96 Movie, . judge any work of art in relation to crowding, reality and to decide whether its representation is accurate or not. Though this mode starts from Plato, it runs through many great theorists of Renaissance up to some modern theorists as well. A literary work is taken to be a representation of reality or of any aspect of it. Plato holds a rather negative view on mimesis;. Ancient Greece , Drama , Literary criticism 1295 Words | 4 Pages. ? LOTF Literary Analysis Essay “Inside each individual there is the colonization seed of both good and evil. It’s a constant struggle as to crowding, . which one will win. And one cannot exist without the referendum 1979 other.” This quote by Eric Burdon epitomizes the main idea of Lord of the flies by William Golding, that mankind possesses the quality of dualistic natures but these sides can have a good or negative impact on society.

The book, Lord of crowding, The Flies, is about the pack of British school boys are stranded on a deserted island. Civilization , English-language films , Evil 1021 Words | 4 Pages. ? Kianna Vinson Dr. Forrest-Carter English 1305-06 25 October 2014 A Critical Analysis on Theme According to Literature: A Portable Anthology . theme is “the central idea embodied by or explored by devolution a literary work” (1360). Visual Crowding? Many times in Games life humans experience hardships that affect their journey to success. Sometimes these hardships negatively impact how one determines their ability to become successful. This often times leads to one seeking advice from their peers. While some peers may give advice. Drug addiction , English-language films , Jazz 1168 Words | 4 Pages. Interpretative Literary Critical Essay on Truman Capote’s “Miriam”: the Theme of Death in the Story.

Mrs. Visual? Miller does not like it but she finds out that there is nothing she can do about it. The end of the the temperature change per mole story is visual crowding open and there are a lot of symbols in . the Essay Role in Public Education story so the visual crowding readers can come up with many possible interpretations. This essay will focus on Essay Role Education the theme of crowding, death in this story. There are lot of symbols connected to colonization of africa, Mrs. Miller’s preparation for death and visual it allows us the interpretation of this story dealing with oncoming death and its connection with the small girl. Viewed in this way. A Story , Afterlife , Death 825 Words | 3 Pages. Literary Analysis Essay Parallel Paths by Kevin Clark We would like to calculate, believe that love brings us together, but this . is not always the visual crowding case as Kevin Clark implies in britain of africa the first two lines of “Parallel Paths” when he states “Today you’re lucky, in love with your wife for crowding the first time in weeks”. We lead very hectic lives and in the mist of all the in Public Education commotion we tend to visual crowding, forget to scottish referendum, pencil in visual time for Essay by William our loved ones, the people we are supposed to keep near and dear.

The poem “Parallel. 1990 singles , Aerosmith , Feeling 1237 Words | 4 Pages. GUIDELINES FOR LITERARY ANALYSIS Spring 2015. ?GUIDELINES FOR LITERARY ANALYSIS 1. This essay must be three to five full pages in length; in addition, it must have a . Works Cited page. Crowding? 2. The essay must be typed in Times New Roman, # 12 font, according to MLA style. 3. The essay must contain at least two secondary sources, and these sources must be articles taken from Southeastern’s college databases or from scottish 1979, legitimate, scholarly print sources. See the difference between primary, secondary, and tertiary sources here. A Thousand Years of Good Prayers , Essay , Historiography 1341 Words | 5 Pages. Literary Criticism for John Updike AP ? Literary Criticisms on visual crowding John Updike’s “AP” First and Last Name Class Section 11/21/13 . About Role Of Religion Education? http://www.notablebiographies.com/images/uewb_10_img0695.jpg Introduction: John Updike is considered to visual, be one of the greatest modern American writers. He was able to use his All-American upbringing as inspiration for Essay on Romeo and Juliet 96 Movie a lot of his writing, making it relatable to many people. Updike was born in visual Reading, Pennsylvania on referendum 1979 March 18, 1932.

He moved around in the area during his childhood, and the. Essay , Fiction , George Saunders 2050 Words | 6 Pages. ? Literary Analysis Essay La Fontaine's Fables Peter Arowolo Jean de La Fontaine was a widely read 17th century . French poet, he is best known for his fables, which have been read and greatly appreciated by generations of children and writers in many languages. Visual? He also wrote comedies and Essay verse tales derived from Boccaccio. Jean de La Fontaine was born on July 8, 1621, in crowding Chateau-Thierry, central France. He was the colonization of africa son of a government official. He studied at a Catholic Jesuit college. Aesop , Aesop's Fables , Fable 1170 Words | 5 Pages. ?Mr Van Gogh Literary Essay Will there always be a Mr Van Gogh?

Owen Marshall’s short story ‘Mr Van Gogh’ is an . explanation of crowding, society’s harsh attitudes towards individuals today. Through characterization, religious allusion and imagery Owen Marshall portrays Mr Van Gogh as someone who is overcoming society’s acts of judgement. This is reflected on the audience because Marshall makes us question our own behavior in the hope that we will change. Owen Marshal uses imagery, biblical allusion. Allusion , Audience , Fiction 924 Words | 3 Pages. Julia Jones Literary Analysis Essay Language Arts 1.14.12 Feel?ings noun [feliNGs]- 1. An emotional state or reaction; . love compassion grief. In the story The Giver, by Lois Lowry, ‘feelings’ is nothing but a word, for feelings do not exist. They were removed long ago, along with all other forms of diversity, leaving everyone numb, unable to britain colonization, experience love, depth, risks, and the unknown.

Everyone, that is, except Jonas, who learns the importance of crowding, feelings and discovers the on Cause of Destruction and Plans Katrina many imperfections. Combined oral contraceptive pill , Emotion , Family 1012 Words | 3 Pages. English 9 Pre-Diploma • In-class essay next block – Tuesday/Wednesday, February 14/15 Achilles and Hector’s Outlook on: • War • Duty • . Heroism (#3 on page 380) Three-Column Chart Topic War Duty Heroism For homework, you must find textual evidence that supports each character’s outlook on the three topics. Achilles’ Outlook Hector’s Outlook Achilles • Believes that heroism is symbolized by tangible prizes • Experiences internal conflicts about the purpose and visual validity of war. Achilles , Agamemnon , Briseis 1128 Words | 5 Pages. Essays are generally scholarly pieces of writing written from an author's personal point of britain colonization of africa, view, but the definition is crowding vague, overlapping with . Of Africa? those of an article, a pamphlet and a short story. Essays can consist of a number of elements, including: literary criticism, political manifestos, learned arguments, observations of daily life, recollections, and reflections of the visual crowding author. Almost all modern essays are written in prose, but works in verse have been dubbed essays (e.g. Alexander Pope's.

Alexander Pope , Essay , Essays 1053 Words | 4 Pages. Literary Essay : The Crucible by Arthur Miller In The Crucible by Arthur Miller, Reverend Parris is a character in the play . Essay And Juliet By William 96 Movie? that is very static. Visual Crowding? His character does not evolve in many ways during the course of the play. By the end of the play, Reverend Parris is still selfish, stubborn, and greedy. However, one of his most prominent flaws at the begging of the Essay on Cause to Rebuild Katrina play is his selfishness. Crowding? At the very beginning of the play, it is scottish devolution quite obvious that Parris is a selfish person. He only cares. Daniel Day-Lewis , Elizabeth Proctor , John Proctor 1120 Words | 3 Pages.

Jacob Lachini Ms. Batten ENG 4U1-03 Monday, October 29th, 2012. Literary Criticisms in Relation to Heart of Darkness Interpretation . is the revenge of the intellect upon art. Even more. It is the revenge of the intellect upon the world. To interpret is to impoverish, to deplete the world -- in order to set up a shadow world of ''meanings,” Susan Sontag. Crowding? It is a persons interpretation of any form of literary work that defines itself, what the calculate the temperature change per mole of h+ reacted. author intends a reader to discover may be completely.

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Fiction , Literary criticism , Literature 1134 Words | 4 Pages. ELA5-05 February 9th, 2014 The Great Gatsby Literary Essay The Great Gatsby, written by scottish devolution referendum F. Scott Fitzgerald, is a . perfect example of the ever decaying American Dream. The novel depicts how rich, or upper-class, people use materialism, money and social status to get ahead in life. The original American Dream is nothing compared to visual, what's depicted in the book. The use of Olympic Essay, lies and cheating is also very present in this story, it's practically everywhere. Lastly, materialism and money go. Arnold Rothstein , F. Scott Fitzgerald , Ginevra King 1012 Words | 3 Pages. the emotions expressed within this work, emotions of bravery, valor, and ethics still speak to visual, us centuries later. The anonymous author of the on Romeo and Juliet Shakespeare: 96 Movie poem convinces . us through the masterful use of various literary elements that emphasize its meaning and message.

Conflict, imagery and setting are three literary elements that contribute to the effectiveness of the poem. The use of visual, conflict aids us to visualize the struggles between Beowulf and his opposing forces. To begin with, we are first introduced to. Anglo-Saxons , Beowulf , Epic poetry 882 Words | 3 Pages. The Crucible Theme Essay Courage Truly courage played an important role in the Salem Witch Trials, and it may have been one . Per Mole Which? of the key reasons the gruesome Salem Witch Trials finally came to its end. The courage shown by people impacted others during this time period by forcing people to acknowledge their viewpoints, which led to the end of the trials. Courage was displayed in three ways, emotionally, physically, and spiritually. Crowding? Emotional courage means showing courage without physical means. John Proctor , Magic , Mary Warren 1092 Words | 3 Pages. ? The purpose of a literary analysis essay is to carefully examine and scottish devolution 1979 sometimes evaluate a work of literature or an aspect of . a work of literature. As with any analysis, this requires you to break the subject down into its component parts.

Examining the different elements of a piece of literature is not an crowding end in britain of africa itself but rather a process to help you better appreciate and crowding understand the Cause and Plans Katrina work of literature as a whole. Visual Crowding? For instance, an analysis of a poem might deal with the different types of. Essay , Greek loanwords , Literature 1348 Words | 4 Pages. GRADE 12 UNIVERSITY ENGLISH Unit 2: Comparative Essay Writing Summative Task Task: Select a particular idea or theme and/or . an aspect of form and style and by William Shakespeare: analyse the way it or they is/are depicted in Archibald Lampman’s poem, “In November” and one other poem. You may use: William Wordsworth’s “The World is too much With Us”, Robert Frost’s “Dust of Snow” E.J Pratt’s A November Landscape Mary Soutar-Hynes – “For Writers Whose Work I Have Loved” In completing. Doctor of Philosophy , Essay , Logic 1073 Words | 7 Pages. 1997 GATTACA THEME NOTES: quotes /scenes for visual an essay -Love/trust: Scene: nostalgic music harmony: I was conceived in the . Riviera, the Detroit variety: warm colours natural light trees and the beach Scene: stark cold procedural surgical emotionless clinical. Olympic Essay? They say a child conceived in love has a greater chance of happiness they don't say that anymore it seems your everything they say you are and more Irene says how she has a heart condition to Jerome (v) he replies if there's.

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think of any complex choices. I shared this with you because one of the themes in Lois Lowry’s science fiction novel The Giver is “Choices . cannot be made without wisdom and knowledge of the on Romeo Shakespeare: 96 Movie past”. This is displayed in visual many times in the book. Three examples are; the elders asking the Giver for advice on important tasks, Jonas’s father releasing a baby, and britain colonization of africa Jonas’s choice to leave community. The first examples of the theme take place after Jonas recently received the crowding painful memory of war. That. Cognition , Decision making software , Decision theory 917 Words | 3 Pages. Romeo and Juliet Literary Analysis Essay Writing Prompt: An important question that Shakespeare poses in of Religion in Public Education this play is who . Crowding? or what is to blame for the deaths of Romeo and Juliet? Are Romeo and scottish referendum Juliet responsible for the fates that befall them, or should others take responsibility for their deaths?

In a five paragraph essay , you must analyze what are the contributing factors that lead to the final tragedy. Visual Crowding? You may analyze the characters themselves or situations and devolution social factors that contribute. Characters in crowding Romeo and Juliet , Count Paris , Juliet Capulet 794 Words | 3 Pages. | C-100 End of Theme Essay | | DDE-ILE: C1719 February 2013 | | | | There have been a myriad of britain colonization of africa, . Visual? topics covered during the Intermediate Level Education Common Core (C100) portion that are beneficial to Field Grade officers in the Army. Britain Colonization Of Africa? These include classes ranging from symbology to organizational structure to individual development plans. After careful consideration of visual crowding, all the lessons introduced in the C100 module, the 96 Movie most important and beneficial class that officers. Communication , Field officer , Fiscal year 1180 Words | 4 Pages. probably noticed, essay writing assignments can pop up in any class. An essay is a literary composition that . Visual? expresses a certain idea, claim, or concept and backs it up with supporting statements.

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The play helps us question the justifiability and benefits of the temperature of h+ which, revenge through the crowding story’s. Characters in Hamlet , Death , Gertrude 924 Words | 3 Pages.

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' 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 analysis, every day Facebook saves two billion comments and likes. ' According to 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.

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We can say that by looking at Essay Katrina, current position of the departments in the US economic companies have minimum of crowding, 200TB data storage on an average if considered(as double as the devolution, 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. The growth of the big data will be continue to reach to visual crowding 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 on Cause of Destruction and Plans to Rebuild Katrina, upcoming users. Utilization of Big Data will turn Out to Be a Key base of Competition and Growth for crowding Individual Firms: Usage of big-data has become an important medium for the leading firms to get better in scottish devolution, their data handling. If we consider an visual crowding, example of 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 referendum 1979 keep market revenue-share in their pocket against crowding, from their local competitors. The emergence of to Rebuild, big-data also has capability to 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 crowding 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. We can say that the step forward towards the 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 very useful to handle the several obstacles and britain problem which government is facing now a days. Crowding! Their idea comprised of 84 big-data programs with 6 different departments. ' Big data study played a big role for Olympic Games Obama's successful 2012 re-election campaign. ' Ebay.com uses two data warehouse that consists of visual crowding, 7.5 petabytes and 40 petabytes as well as 40 petabytes Hadoop cluster for Essay on Cause and Plans to Rebuild after Katrina 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 estimation is done on data. ' Facebook also has 50 billion pictures of its user and process it very well.

' F.I.C.O. Visual Crowding! 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 business and companies is 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 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 Games Essay, the distributed system. ' Hadoop is an 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 the most important principle called Map-Reduce (map task reduce task), the main work of the map-reduce is to divide the 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 visual crowding the reduce task after performed sorting on the output by framework. ' A file system is used to store the on and Plans after Katrina, input and the output of the jobs. ' Some tasks failed during execution so framework takes care of monitoring the visual crowding, tasks, 're-executes' the on Romeo and Juliet by William Shakespeare:, failed tasks and scheduling the visual, tasks. History of Hadoop: ' The main or the very important organization from where the by William 96 Movie, history of Hadoop began is none other than best company of the world 'Google'. ' Google published two academic research papers on the technology called 'Google File-System' (GFS) and 'Map-Reduce' in the year 2003 and 2004.

' After some time these two technologies combined together and visual provided a good plat-form for scottish devolution 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 'subproject of Lucene'. ' After that Apache open source foundation did some changes in crowding, it and named as 'Apache's open source framework Hadoop' that can be used for processing Big Data in less time. ' Later Doug Cutting was hired by another big company that is Essay on Cause of Destruction to Rebuild, yahoo. He and other employees of crowding, yahoo contributed a lot to Hadoop but after some time Doug Cutting moved to 'Cloudera' and his other teams was hired by an organization called 'Hortonworks'. ' Still we can say that yahoo has the biggest contribution to develop Hadoop. 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 the temperature, 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 visual crowding, Hadoop. History of Mahout: ' The life of britain colonization, Mahout was started in the year 2008, at this time it was treated as the crowding, 'sub-project' of one of the major project of Apache named as 'Apache's Lucene Project'. ' The techniques like search, text-mining and Olympic Games Essay 'information-retrievel' were implemented by Apache's Lucene project. ' Some of the visual, members of the project Lucene were working on the same technology that is calculate change of h+ which, 'machine-learning' areas, so these members also contributed to visual mahout and a separate project named 'Mahout' was generated which works on calculate the temperature per mole, the principle to predicts future on the basis of past.. ' The algorithms implemented in visual crowding, 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 brief introduction of each algorithm that has been implemented on 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 britain colonization of africa, 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 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 visual, recommendations for user but like and Essay about dislike of user is not static so the crowding, 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 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 Essay Shakespeare: 96 Movie dislikes may change so this technique generates good quality of recommendations as compared to user-based collaborative filtering algorithm. ' Association-rule-mining is the crowding, technique used to find some rules on the basis of which the Essay of Destruction and Plans after Katrina, growth of an organization can be increased.

' There are number of crowding, algorithms on the basis of which we can find frequent patterns from the calculate the temperature change of h+, large of dataset, on visual, the basis of frequent patterns we can generate some rules that would be really helpful to Essay increase the turnover of an visual crowding, organization. Architecture of Map-Reduce: A paper on the idea named 'Map-reduce' was published by calculate the temperature change of h+ which reacted. 'Google' in visual crowding, 2004 that was used as architecture. Role Of Religion In Public Education! Map-reduce [9] named architectural framework is able to visual model the parallel processing and its implementation used to process the by William, large amount of data stored. Crowding! Using this technology, the requested query is splitted into sub queries and then distributed among several parallel sites and processed parallel which is called the 'Map-step'. Then the results obtained are combined and of Religion in Public delivered that is the reduce step.

This 'frame-work' was extremely successful; in fact the visual, others wanted to on Katrina 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 aggregate huge quantity of data. These technologies and techniques describe from numerous areas including computer science, applied mathematics, economics and statistics. A number of technologies and techniques were developed in visual crowding, 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 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 Essay Cause of Destruction and Plans to Rebuild after Katrina, used find significant relationships that are association rules between identifiers of huge data storage. Numbers of 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 usually used to crowding predict the the temperature per mole reacted., nature of a class using other attributes. For Example: Prediction of weather on the basis of previous day's weather. Cluster Analysis: It is the technique used to visual group the number of and Juliet 96 Movie, objects having similar properties into one cluster and other objects having similar properties with each other but dissimilar to crowding other cluster group into one cluster. It is 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 Data Integration: These are the techniques that gather the calculate the temperature, data from several locations then analyze the data for producing good understandings in such a way that is visual crowding, 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 calculate change per mole of h+, algorithms, which allow computer systems to develop activities on the basis of 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 visual crowding, number of calculate the temperature change reacted., algorithms to analyze human or natural language. Sentiment Analysis: This is an application of natural-language-processing that is (NLP) and other critical techniques to recognize and mine the crowding, knowledge from inputs. Some important aspects of its examination comprises of the temperature change per mole of h+ which reacted., identifying the product, aspect and feature. Big Data Technologies: There are emergent techniques that can be applicable to modify, analyze, aggregate read the big data. Big Table: Big table is the PDDS i.e. proprietary distributed-database-system built on the GFS i.e. 'Google-File-System' Encouragement for HBase. Business Intelligence (BI): A sort of application software builds to analyze, present and report data. Visual! 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 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 devolution, managed by 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 visual crowding, requested queries on data stored at distributed sites. R: This is a software environment and an open source programming language for 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 Role Education, structured-data and stored in form of visual, tuples and Essay and Juliet 96 Movie columns. SQL is the visual crowding, best language for managing or maintaining relational databases. 1] A.Pradeepa, A.S.Thanamani. Colonization! 'Hadoop File System And Fundamental Concept of Map Reduce Interior And Closure Rough Set Approximations [5]'. In this paper authors described that big data-mining and knowledge-discovery is the huge challenges because the volume or size of data is growing at an unprecented approximation scale. Map-Reduce have been implemented to visual achieve many large-scale computations.

Recently introduced or presented Map-Reduce proficiency has received or gained much more consideration and attention from both the sides that is the Cause and Plans after, industry for its applicability and visual the scientific-community in big-data analysis .According to the authors of this paper, for mining and finding some knowledge from big data, they presented an algorithm corresponding to the Map-Reduce based on 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 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 colonization, Hadoop [6]'. In this paper, authors described that market-basket analysis techniques are considerably important to every day's business decision because of its capability of visual, mining customer's purchase rules by discovering that which items they are buying so frequently and together. The traditional single processor and main memory based computing is not proficient of handling ever growing huge transactional data. In this paper an effort has been taken to remove these limitations. First author will eliminate null transactions and rare items from the about of Religion in Public Education, segmented dataset before applying their proposed HMBA algorithm using the ComMap-Reduce framework on Hadoop to generate the absolute set of visual, maximal frequent item-sets. 3] J.W. Woo, Yuhang Xu. 'Market Basket Analysis Algorithm with Map/Reduce of Cloud Computing [7]'.

In this paper, authors explained the Role of Religion in Public Education, Map-Reduce approach that has been very popular or effective, in order to compute or calculate enormous volumes of crowding, data, since google implemented its platform on google distributed file systems that is called (G.D.F.S) and britain of africa 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 [8]'. In this paper authors presented a new schema that is visual, 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 Essay of Destruction and Plans read data from visual crowding, HBase and calculate 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 the H-Base or Hadoop distributed file system that is HDFS. 5] D.V.S.Shalini, M.Shashi and A.M.Sowjanya. 'Mining Frequent Patterns of Stock Data Using Hybrid Clustering[9]'. In this paper, authors described that the classification and patterns in 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 stock market data for guessing factors that are affecting or decreasing the product's sale. To improve the execution time, the visual, proposed system uses two efficient methods for Essay by William Shakespeare: 96 Movie clustering which includes PAM that is visual, Partitioning Around Medoids and (BIRCH) that is Balanced Iterative Reducing and Clustering using Hierarchies along with (M.F.P). The Temperature Change Per Mole Which Reacted.! The best well-organized iterative clustering approach that is called as PAM.

PAM is visual, used initially or to 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 Association Rules[10]'. According to the authors of this paper algorithms like Apriori and FP -Growth break the problem of mining association rules into two different sub problems then find frequent pattern and generate the required rules. Of H+! To solve the problem we catch a deep insight of FP-Growth algorithm and propose an effective algorithm by visual 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 [11]'.

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 britain colonization of africa, legacy Apriori algorithm which has been common or same to collect the crowding, item sets frequently, arose to compose association rules in data mining. Theoretically it shows that the proposed algorithm provides the high performance computing depending upon 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 [12]'. 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 scottish devolution compress dataset. At the same time, a new frequent pattern mining algorithm is also introduced on crowding, the bases of it, which can update and adjust the calculate the temperature change per mole, tree more efficiently. There are mostly two kinds of algorithms that is basically used to visual 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. Games! 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 crowding, the field of 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 the temperature per mole which, 'Hadoop' and visual crowding '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 change per mole, data because it is also based on parallel processing and generates results in visual crowding, very less time as compared to existing technologies to process the huge amount of data. Essay Cause After Katrina! Authors also mentioned about the crowding, proposed algorithm for sequential-alignment that is 'FAST-A'.

10] S.Mishra, D.Mishra and S.K.Satapathy. Colonization! '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 crowding, gene- expression data'. As we know that frequent pattern mining has become a more debatable and the temperature focused area in last few years. Visual Crowding! 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 the data set and after that applied number of techniques to Essay Cause of Destruction and Plans find more meaningful frequent patterns from data set. 11] L.Chen, W.Liu. 'An Algorithm for 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 visual, not efficient and devolution 1979 time consuming. Visual Crowding! They proposed a new technique called 'Frequent Biological Pattern Mining' or 'FBPM' to mine frequent patterns from large amount of of h+ reacted., biological data.

They also compared the results of both the techniques that are existing techniques and proposed techniques on the basis of execution time to find frequent patterns and number of patterns mined. 12] B.Sarwar, G.Karypis, J.Konstan, and J.Riedl. 'ItemBased Collaborative Filtering Recommendation Algorithms'. In this paper authors talked about the recommendation systems and crowding described various techniques to colonization of africa develop a good recommendation system that can be used to generate best recommendations for the users. Recommendation systems are the crowding, system with the help of which we can predict the future after applying some collaborative-filtering algorithms, on the basis of users past activities. Two most famous collaborative-filtering techniques that we generally use to 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 his/her taste. On the other hand user-based-collaborative-filtering algorithm works on the principle of finding nearest-neighbours of target user which agrees on the similar item in terms of the temperature change of h+ which reacted., 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 visual crowding Implementation. 3.1 Proposed Methodology: According to colonization of africa our dissertation title we are working to find frequent patterns and on the basis of the visual crowding, frequent patterns some recommendations would be suggested to about Education the user using frequent pattern mining algorithm, Hadoop and Mahout. 1. First of all my main work is to collect the 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 convert the format of dataset into desired format. 3. After converting the dataset into visual crowding, a meaningful format, make a java program that can read the britain colonization of africa, dataset and generate frequent patterns and crowding association rules from the data. 4. For finding the frequent patterns from the scottish 1979, 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 frequent patterns by executing program in eclipse. 6. Visual! Apply the Essay on Romeo by William, dataset using mahout on top of Hadoop in distributed environment to 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 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 sequential and non-sequential big-data for a company and crowding then integrates that big-data with your present business intelligence ecosystem. 'Hadoop works on on Cause after Katrina, the most important principle called Map-Reduce (map task reduce task), the main work of the map-reduce is to divide the crowding, input dataset into calculate per mole of h+ reacted., number of visual, 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 devolution referendum, monitoring the tasks, 're-executes' the failed tasks and scheduling the tasks. ' There are numbers of sub-components in the Hadoop but two core or main components of Hadoop are 'Map-Reduce' (Used for processing) and 'Google File System (GFS)' or 'Hadoop Distributed File System (HDFS)' (Used for visual crowding 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 on Romeo by William 96 Movie, a file system basically used by Hadoop having distributed nature and crowding 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 Essay, data blocks. ' The default block size is 64 MB but it is configurable according to visual crowding the size of data is going to process using Hadoop. ' HDFS maintains the Olympic Games, replicas of data block across multiple data nodes so that in visual, 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 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 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 number of 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 Map-Reduce and output generation. ' Name node also maintains the on Romeo and Juliet Shakespeare: 96 Movie, information about the location of each file stores in HDFS. ' In different sense we can say that name node maintains the visual, data about data that is 'meta-data' in HDFS. File A is present on Data Node 1, Data Node 2, and Data Node 4.

File B is scottish devolution referendum, present on Data Node 3, Data Node 4, and Data Node 5. File C present on visual crowding, Data Node 1, Data Node 4, and Data Node 3. ' Name node is only point of disappointment for the Hadoop Cluster. ' Data nodes are the slave nodes of the master node i.e. name node and is generally used by HDFS for storing the data blocks. ' Data nodes are basically responsible to read the Essay of Religion Education, requests from visual crowding, 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 the basis of instructions provided by name node. ' Secondary Name Node: ' Secondary name node generally performs the functions of throwing out the non-important things present inside the calculate of h+ which, Name node regularly to prevent it from failure. ' Secondary name node enables the crowding, 'check-points' of the 'file-system' inside name node.

' Secondary node is the backup for Essay Role Education name node rather than it is a saying that it is a point of failure for name node. ' Map-Reduce are the kind of framework or we can say it is a programming concept used by crowding Apache organization in its product Hadoop, for processing large amount of data. ' Map and Reduce functions have almost created in about of Religion, every programming language having the same functionality Java language. ' Map-Reduce was implemented to process large amount of data by dividing it into 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 visual the Reducer. ' Reduce function takes the output generated from the scottish devolution 1979, Map function as its input and sorts or combine the data for decreasing the complexity. ' Map and crowding Reduce functions both works on the principle of (Key and and Juliet by William Shakespeare: Value).

' Map function takes the input from data node and visual with help of mapper divide the data into keys and 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 (key2, value12, value22). ' Reduce function then reduce the output generated by combiner and Essay 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 visual crowding, data node, then Task-Tracker performed the tasks with the help of data node. ' Job-Tracker always assigns the tasks to the Task-Tracker on colonization, top of data node because data is always available there in the local repository.

' Sometimes it might not be possible for Job-Tracker to visual crowding assign the tasks for Task-Tracker on data node then Job-Tracker tries to assign the tasks to Task-Tracker in the same rack. ' If in any case a node failure occurs or the Task-Tracker which was processing the devolution referendum 1979, 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 visual, job fails. ' Task-Tracker is the calculate the temperature of h+ which reacted., slave node of the master node i.e. 'Job-Tracker' which takes the request of processing the tasks from Job-Tracker and processes the crowding, task ('Map', 'Reduce' and 'Shuffle') using data present in data block of data nodes. ' Every 'Task-Tracker' is colonization, composed of number of slots that it means it can process number of tasks at the same time. ' Job-Tracker always checks that an crowding, empty slot is 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 the same rack of the machine. ' Each Task-Tracker sends some message in calculate per mole which, every second to inform the Job-tracker that it is alive and processing the task. ' Each Task-Tracker has its own JVM to visual crowding process the task if in Olympic Games, 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 'Task-Tracker' informs the visual, Job-Tracker. What is Apache Mahout?

' Mahout is an Olympic Games Essay, API or we can say that it is the library of visual crowding, scalable 'machine-learning' or 'collective-intelligence' algorithms like (classification, clustering, collaborative-filtering and Essay 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 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 visual, mahout, it can produce the outputs fast when used on top of Hadoop. ' Collaborative-Filtering is the technique of filter out some important data from the large amount of data which user browse, preference and on Romeo by William rate, in other words we can say that collaborative filtering is the visual, process of generating predictions on 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. ' All the preferences about different set of items from users can come from explicit ratings or from implicit ratings. ' Explicit Rating: It is the kind of technique in which user suggest his/her preference by giving rating to a particular product or item on a certain scale. ' Implicit Rating: It is the kind of technique in on of Destruction Katrina, which user's preferences are generated on crowding, 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 about Education, future on crowding, the basis of on of Destruction and Plans, past activities of crowding, users we firstly make or create the database of the calculate the temperature per mole, user's preferences for items and then apply some algorithms like nearest neighborhood to predict the visual, future preferences of a user on the basis of his/her neighbors having the same perception or taste.

' As the calculate the temperature per mole reacted., size of data is increasing on daily basis so that is the main challenge that we require such kind of visual, algorithms that can process millions of data and match a user preference with all other neighbors present in 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 Essay, 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 visual, not static so the recommendations generated using this technique is Games, 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 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 visual crowding 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 items that user has rated earlier, after that find a set of (n) most similar items from britain colonization of africa, this set having same similarities to the target item (i) then similarity of each item present inside the crowding, set of (n) most similar items is calculated. After the on Romeo 96 Movie, computation of crowding, similarities, calculate the weighted average sum of user ratings on set of similar items to find the best recommendations for the target user.

' Prediction computation and similarity computation are the britain colonization of africa, two techniques used to find the future predictions and visual crowding similarities among numbers of items. Similarity Computation for Items: ' Similarity computation is the technique used to Essay on of Destruction and Plans after Katrina 'find or compute' the value of similarity among items from large number of items and visual crowding select the set of Essay by William 96 Movie, items having same similarity. ' Similarity between two items a and b is computed after isolated the visual crowding, users who have rated the items a and b, then use some similarity finding techniques to find the similarity Sa,b. ' There are number of 1979, 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 technique used to 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 visual, 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 on of Destruction and Plans to Rebuild, similarity between two items using this technique we use the crowding, pearson co-relation method and find the pearson co-relation between two items that is Corr(a,b). ' To find the value of pearson co-relation more accurate, we removed the over-rated ratings of the two items that is the ratings for calculate the temperature change of h+ which which users rated both items (a and visual b) and set of scottish 1979, users who rated both items (a and crowding b) are denoted by U. Pearson correlation formula: ' Adjusted-cosine-similarity is the 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 related pair. So the calculate reacted., 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 related user's from each extra rated pair. ' User-Based Collaborative filtering is the technique or we can say that it is an algorithm that is basically used to generate future predictions for visual a user on the basis of his/her past history or by using his/her neighbors having similar kind of taste. ' User-Based Collaborative filtering is the algorithm which works on the principle of generating recommendations for the user after finding his/her neighbor users from on Romeo and Juliet Shakespeare: 96 Movie, 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 crowding the target user using user-based collaborative filtering algorithm then some techniques are applied to about Role in Public Education find the top recommendations for the target user. ' In this way user based collaborative filtering generates recommendations and visual it is also known as memory based or nearest neighbor based algorithm to find or suggest best recommendations for devolution referendum 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 also growing so it takes lot of visual, time to find nearest neighbor of on Cause to Rebuild Katrina, a particular user form large database having millions of users and items exists. So scalability has become a big challenge for generating recommendations. 2. Visual! 'Sparsity': Recommendation system which is working on the principle of nearest neighbor fails in certain circumstances, when the number of Essay on Romeo by William Shakespeare:, active users who is purchasing some product is very large, so in such cases to find nearest neighbors for visual crowding 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 Essay Role of Religion Education, 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 visual crowding, 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 then implemented them on top of hadoop to find frequent patterns and association rules. ' So Apriori and Essay about Role Education FP-growth [10] algorithms find the frequent patterns from a set of visual, transactional dataset having transaction id and item set(i.e., ), where TID is a transaction-id and item set is the set of items bought in transaction TId.

On the other hand, mining can also be performed on data presented in data format like . ' Apriori algorithm significantly reduces the size of candidate sets using the Apriori standard but still it suffers from two problems: (1) generates a huge number of Essay Katrina, candidate sets, and (2) repeatedly scan the database and visual crowding checking the candidates by pattern matching. ' FP-growth algorithm mines the complete set of frequent item sets without generating candidate set. ' FP-growth works on Games Essay, the divide and conquers principle. ' The first search of the database derives a list of frequent items in which the items are ordered into descending order by frequency. ' According to crowding the descending list by frequency, the database is about Role of Religion in Public Education, reduced into a frequent-pattern tree or fp-tree, which retains the visual crowding, item set and their association information. ' The fp-tree is mined or formed by britain of africa 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 visual, suffix pattern then constructing its conditional fp-tree and performing mining recursively on and Juliet, such a tree.

' The pattern growth is achieved by the combination or concatenation of the suffix pattern with the frequent patterns generated from visual, 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 of Destruction and Plans to Rebuild Katrina, 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 the transactions or data set. While we find frequent patterns, we also record the 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 crowding or greater than 2, will considered as frequent patterns. On the Cause and Plans after, basis of crowding, 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 Cause of Destruction to Rebuild after, basis of crowding, 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 devolution referendum 1979, 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 crowding, Single node pseudo distribute that is called installation of hadoop on your local machine. Step 1: Java Installation. To work on Hadoop, first of on Romeo 96 Movie, all we require to install java on your local machine. So install the latest version of java that is crowding, Oracle JAVA 1.7 which is on Cause Katrina, 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 crowding have several new APIs. Following commands are used for Installing JAVA in Ubuntu:

Open the 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 on Romeo by William, (/usr/lib/jvm/java-7-oracle). When the installation has come to visual an end then do a check whether java or JDK has correctly set up by using command that is Essay on Cause and Plans to Rebuild after Katrina, mentioned below. Figure5.1: Java Installed Successfully. Step 2: After successfully installed java, add a separate or personal user for hadoop that is hduser . Commmands for visual create 'hadoop- user' and scottish devolution referendum '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 visual crowding, remote machines or at your local machine, hadoop requires ssh access to deal with its nodes. Therefore we required to Essay configure ssh access on localhost for the hadoop user i.e. Visual! hduser that we created in Olympic Games Essay, 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 visual 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 Olympic Essay, the end of this file. Now it is the time to restart your system so that the 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 time to install Hadoop version 1.0.4 on your machine. First of all download hadoop-1.0.4 tar file that is the 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 . Visual! A folder which is of africa, common to all the users, it is visual crowding, mostly chosen that we should install or set-up the hadoop into that folder. Use the colonization, below mentioned commands to untar the hadoop 1.0.4 tar file into crowding, 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 files to hadoop group and calculate change per mole which reacted. the hduser user using the 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'. Visual! To open'.bachrc'file, you should be a root user then open it using the following command: 1)sudo 'gedit /home/hduser/.bashrc' Figure5.5: Open .bashrc file. Once the '.bashrc' will open then at the end of of Destruction and Plans to Rebuild, '.bachrc' file, add the 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 visual 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 colonization, '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 crowding, '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 Games Essay, 'configuration ' /configuration' tags. Figure5.10: Changes in visual, 'conf/mapred-site.xml' 4) Changes in '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 colonization, name node. Hadoop Distributed file system i.e. Crowding! hdfs is implemented on top of the local file system of change per mole which reacted., your 'cluster'. So the initial step to starting up your hadoop installation is to visual 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 on Romeo Shakespeare: find whether. all nodes are running properly inside hadoop.

We can use the following command to check it. Output must be like mentioned below, if we are getting such kind of visual, 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 Essay Role of Religion in Public Education, terminal then enter the below command to download and install maven. sudo apt-get install maven2. Open the '.bashrc' file and visual add the lines mentioned below at the end of bash file.

Set the '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 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 Olympic, mahout source package in .zip format from the following link: http://www.apache.org/dyn/closer.cgi/lucene/mahout/ Extract the folder into usr/local/mahout directory and check that pom.xml file exists inside it or not. Open the crowding, terminal and moved to usr/local/mahout directory then enter the calculate per mole of h+ which reacted., 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 visual Run a Simple Job on Hadoop: 1. Scottish! 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 visual crowding hadoop distributed file system using following command: fs -copyFromLocal /tmp/Wordcount.txt /user/hduser/wordcountexample/Wordcount.txt.

Figure5.19: Copy text file from 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 items present inside wordcount. 5. 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 devolution 1979, list of visual, 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 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 scottish devolution 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 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 visual process the data and 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 Essay on of Destruction and Plans 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 growing day by visual crowding day in gigabytes or in terabytes volume, so it is not easy for an organization to scottish devolution handle such big amount of data and could do predictions, find patterns and recommendations from such large amount of visual, data using existing technologies in less time. But we use Hadoop and Mahout both together then the overhead of an organisation to analyse the big data will become very less and execution time required to find patterns and recommendations will also be so less. Calculate The Temperature Change Per Mole Reacted.! We took around 500 GB of e-commerce website data then performed frequent pattern mining and collaborative filtering using Mahout and visual Hadoop. At the same time we performed the same work using simple java programs in eclipse then compared the britain of africa, 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 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 visual crowding, unwanted columns that are not required in the analysis process then apply the techniques to find patterns and products that can be recommended to the users. But in future we can predict the recommendation on britain, the real time environment like we don't need to store data in database, we can directly apply some techniques on real time data that is generated frequently in visual, daily and hourly basis, reduce the overhead and increase the Essay on Romeo by William 96 Movie, 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 visual, hand, waiting to help you. Each of Olympic Games, us is qualified to a high level in our area of expertise, and we can write you a fully researched, fully referenced complete original answer to your essay question. Just complete our simple order form and you could have your customised Information Technology work in your email box, in visual, 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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dissertation l'amour Analyse des termes. a) sens général et le plus courant : attachement, désir de fusion, entre deux êtres. Visual Crowding? C'est donc quelque chose dont on Essay by William 96 Movie, attend : du plaisir, du bien, le bonheur. Domaine : affectif; sentiment, ou passion? b) sentiment : affection pour quelqu'un (amour filial; amour maternel; amour du prochain, etc) c) attachement exclusif et excessif envers quelqu'un ou quelque chose : c'est alors une passion (l'Amour-passion) Se méfier : on crowding, se méfie de quelque chose ou de quelqu'un qui ne nous fait pas confiance, parce qu'il nous a déjà trompé, ou parce qu'il est susceptible de nous tromper, malgré qu'il ait l'apparence contraire. On Cause To Rebuild Katrina? (On se méfie, dit-on souvent, des apparences). a) nécessité physique : il faut/il est nécessaire de manger si on visual, veut se maintenir en vie (on ne peut faire autrement, c'est une contrainte naturelle) b) obligation morale : il faut/on doit obéir à la loi (c'est un devoir, quelque chose qui nous oblige; que les hommes soient naturellement enclins à être méchants, ne change rien à un devoir, puisque le doit-être ne dérive pas du ce qui est). Mise en rapport des termes (problématique, présupposé, enjeu).

Faut-il donc se méfier de l'amour? Ie, d'abord, l'amour, au lieu d'être une source de bien, de bonheur, de plaisir, ne serait-il pas source de maux (malheur, souffrance autant physique que morale, et contraire à la morale)? N'est-il pas alors, dans ce cas, de l'ordre de l'erreur, de l'illusion? (puisqu'au premier abord, on on to Rebuild, croit qu'il nous rendra heureux, etc) Mais cette illusion est-elle dangeureuse? En effet, pour qu'il soit nécessaire de se méfier de l'amour, tout comme par exemple il est nécessaire de se nourrir pour se maintenir en vie, encore faut-il que l'erreur ou l'illusion qu'il provoque soit dangeureuse. Crowding? Cette interrogation nous mène donc à chercher de quel ordre peut bien être cette illusion, et de quels dangers elle est la source.

On se demandera ensuite s'il faut se méfier de l'amour au sens éthique : alors, cet amour est-il nécessairement lié au mal, et peut-être à l'extinction de la société? L'amour est-il nécessairement néfaste à l'homme, à la fois au sens physique et moral? Se méfier de l'amour, est-ce alors un devoir, une obligation morale? La réponse à ce questionnement ne suppose-t-elle pas qu' il y aurait plusieurs sortes d'amour, des amours positifs et négatifs, des usages positifs ou négatifs de l'amour? Plutôt donc que de se demander s'il faut se méfier de l'amour, il convient donc se demander : de quel amour faut-il se méfier? I- L'amour est-il une illusion?

Et si oui, est-ce une illusion vitale ou éthique? A- D'abord, on scottish devolution 1979, peut facilement montrer que l'amour est une illusion. Crowding? En effet, comme l'a montré Stendhal dans De l'Amour, l'amour nous trompe. Cf. Essay Of Religion? la cristallisation. Erreur sur la réalité : nous ne voyons plus le réel tel qu'il est; nous ne voyons pas non plus notre bienaimé tel qu'il est réellement Nous croyons aimer quelqu'un pour ce qu'il est réellement, mais en fait, nous n'aimons, à travers lui, que l'idée qu'on se fait de l'amour.

Il faut donc bien se méfier de l'amour. Visual? -Préciser que cet amour dont il s'agit ici est la passion au sens strict du terme : ie, une attirance exagérée et dominante, exclusive, pour quelqu'un (ou quelque chose, mais c'est moins pertinent). B- Mais si l'amour nous trompe, est une illusion, puisqu'il idéalise son objet, et ne le voit pas comme il est réellement, mène-t-il à la souffrance, physique, morale ? Et, peut-être, à la mort? (Ie : est-il nécessaire de s'en méfier) -Souffrance physique : pas très pertinent. -A la souffrance morale : après tout, c'est bien ce à quoi renvoie l'étymologie du terme de passion : patior : je souffre, je subis. Olympic Essay? La passion n'est-elle pas quelque chose qui devient pour moi un fardeau, dont je deviens l'esclave? Cf. Visual Crowding? deuxième phase de la cristallisation : l'amour tourmente. -A la mort : cf. Colonization? Tristan et Iseult.

L'amoureux fou va s'isoler de la société, du réel, pour vivre son amour librement. Visual? Ce qui peut évidemment mener à la folie et à la mort (sous-entendu : l'homme est bien un être inter-subjectif, qui n'est rien sans la société) C- Obligation morale ? L'amour s'oppose à la vérité, puisqu'il déguise son objet. On Romeo By William Shakespeare:? Ce que nous aimons dans l'amour ce n'est pas ce que nous croyons. Crowding? Mais est-ce néfaste pour la morale? Si nous devons nous méfier de l'amour, est-ce parce qu'il contredit la morale? Parce qu'il est source de mal et non de bien, et ce, essentiellement? D'abord, que suppose la morale? On peut répondre que la condition qui fait de nous des êtres moraux, c'est que l'on soit libre.

En effet, nul ne peut nous accuser de notre forfait, si nous ne sommes pas considérés comme libres. Colonization? Nous sommes certes coupables d'avoir commis un crime, nous en sommes bien la cause, l'origine, mais nous n'en sommes peut-être pas responsables. Visual? S'il est admis par des spécialistes que je n'étais pas en possession de toute ma raison, alors, on scottish, dira que je ne porte pas la responsabilité de ce crime, puisque je n'ai pas consciemment accompli cet acte. Visual? En général, on calculate of h+ which reacted., dit que ce qui m'a fait accomplir cet acte, c'est l'alcool, ou la folie, ou un choc émotionnel intense qui remonte à ma petite enfance (l'inconscient), et évidemment, la passion, l'amour passionnel. L'amour fait donc partie de ce qui me pousse à faire des choses sans que j'en sois vraiment conscient, ou sans que je puisse rien y faire. Visual Crowding? L'amour, c'est une force aveugle qui, comme l'inconscient, agit sur moi à mon insu, et m'aliène à moi-même. Britain Colonization Of Africa? Je ne m'appartiens plus, je ne suis plus moi. Crowding? C'est que je suis complètement obsédé par cet amour, plus rien ne compte pour moi, si ce n'est cet amour. On Romeo And Juliet By William 96 Movie? Dès lors, si un obstacle surgit sur la voie qui me mène vers la réalisation de cet amour, tous les moyens seront jugés bons pour anéantir cet obstacle. Visual? Celui qui est victime d'un amour fou se moque de la morale, il emploiera un moyen moralement condamnable s'il lui paraît nécessaire à la réalisation de sa passion.

Exemple : tuer sa femme et son amant s'ils commettent un adultère ou même si je crois seulement qu'ils le font. De plus, l'amour est souvent égoïste et malveillant. Olympic Games Essay? Cf. Crowding? opposition entre un amour concupiscent et un amour bienveillant : l'amour bienveillant mène à vouloir et à faire le bien des autres; l'amour concupiscent au contraire n'est que désir de l'autre, ie, désir de possession. Essay Of Religion In Public Education? Ce qui m'intéresse en l'autre duquel j'attends du bien, c'est juste mon propre plaisir, la satisfaction de mon désir. Visual Crowding? Cet amour là ne renvoie donc qu'à moi-même. Britain Of Africa? Ainsi l'amour concupiscent envers quelqu'un est un amour qui nie autrui, qui ne le respecte pas.

Pour reprendre la formule de Kant, cet amour traite autrui seulement comme un moyen, mais pas en même temps comme une fin en soi. Il faut donc se méfier de l'amour, au sens éthique cette fois. Visual Crowding? L'amour passionnel est dangeureux car il mène irrésistiblement à l'accomplissement d'actes moralement condamnables. C'est bien ce que montre Kant dans L'anthropologie au point de vue pragmatique. Essay On Romeo And Juliet By William 96 Movie? L'amour étant une passion, il empêche toute réflexion, tout usage normal de la raison. Crowding? Celui qui est amoureux fou n'est plus en mesure d'écouter sa raison. Essay? Dès lors, comment pourrait-il être moral, mener à accomplir une action morale? En effet, qu'est-ce qu'une action morale selon Kant? C'est une action qui est accomplie seulement par pur respect de la loi morale.

Elle a pour origine la raison, mais la raison en son sens pratique. Visual Crowding? Il faut savoir se placer du point de vue de tout homme pour savoir si mon acte est moral. Role In Public? Ie, savoir faire usage de la raison, raisonner. Crowding? Exemple : pour savoir s'il est bien ou mal de tuer mon prochain, il faut que je puisse me demander si cet acte est contradictoire ou non (application d'une règle logique), et ce qui se passerait si tout le monde en faisait autant. Shakespeare: 96 Movie? Si j'aboutis à une contradiction, alors, mon acte est immoral.

Voyons si l'amoureux fou peut accomplir cela et donc agir conformément à la morale. Visual Crowding? Peut-il se demander si son acte est contradictoire, et si par exemple il mène à l'extinction de l'humanité? Non, car il ne peut écouter sa raison, il est sous l'emprise de la passion.Peut-il agir et même agit-il en faisant comme si tout le monde pouvait en faire autant? Non, car il ne se soucie nullement du reste des hommes. Essay And Juliet 96 Movie? Ce qui l'intéresse, c'est lui, ce sont ses petits intérêts égoïstes.

Ne pensant qu'à la satisfaction de son intérêt propre, à satisfaire son amour, l'amoureux fou ne peut qu'ignorer l'aspect universel de la morale. Conséquence : c'est un devoir de se méfier de l'amour, car si on crowding, l'universalisait, ce serait sans doute la ruine de la société. Calculate The Temperature Of H+ Which Reacted.? On a donc raison de dire qu'il faut se méfier de l'amour. II- Mais n'avons-nous pas restreint, ci-dessus, l'amour à la passion? Tout amour est-il passion, et faut-il donc se méfier de tout amour? Tout amour mène-t-il nécessairement à la mort, au malheur, et au vice, à la perte de maîtrise de soi? Après tout, la vie est-elle possible sans amour? N'est-ce pas une nécessité vitale?

Et l'amour n'est-il pas parfois source de bien? A- En effet, l'amour n'est pas seulement synonyme de passion au sens d'attachement exclusif et unique envers quelqu'un ou quelque chose . Crowding? Descartes, dans le Traité des passions, rattache ainsi l'amour au sens plus général du terme de passion. Cause And Plans? La passion, c'est le domaine de l'affectif. Visual Crowding? Est passion tout phénomène qui a pour origine le corps, mais qui est ressenti comme en l'âme même. On And Plans To Rebuild After? Le lieu originaire de la passion, c'est le corps. Crowding? Mais elle est vécue comme psychologique. Devolution Referendum? Ce qui nous intéresse pour notre analyse, c'est que tout ce qui est de l'ordre de la passion, est de l'ordre de l'affectif, c'est un sentiment. L'amour étant une passion, est donc un sentiment. Visual Crowding? Or, le sentiment, nous dit Descartes, est ce qui fait que nous avons un rapport au monde; ce qui fait, par conséquent, que nous voyons les dangers ou les bienfaits des choses de ce monde.

Sans lui, je ne serais pas averti qu'il faut s'échapper lorsque je vois un danger (peur); ou que la nourriture m'est néfaste. Cf. Devolution Referendum 1979? déf cartésienne précise de l'amour (TPA, 79): l'amour est une émotion de l'âme causée par le mouvement des esprits, qui l'incite à se joindre de volonté aux objets qui lui paraissent lui être convenables ; (TPA, 80)en sorte qu'on imagine un tout duquel on visual crowding, pense être seulement une partie, et que la chose aimée en est une autre. Ainsi, sans l'amour, je serais incapable de savoir ce qui m'est convenable, et de m'unir à cette chose. Essay Shakespeare: 96 Movie? Donc : incapable d'être heureux, puisque ma moitié me resterait inconnue! J'ai donc besoin de l'amour car il est de l'ordre de la nécessité vitale. Visual? Il n'est pas nécessaire de se méfier de l'amour, car il n'est pas cause de souffrance ni mortel en soi. Calculate The Temperature Per Mole? Les passions, nous dit Descartes, sont toutes bonnes de leur nature. Visual Crowding? C'est leur mauvais usage seulement qui peut nous être néfaste.

Mais alors, s'il y a un mauvais usage de l'amour, on Olympic, doit quand même faire attention, et donc se méfier de l'amour! Ce dont on crowding, ne doit pas se méfier, c'est de l'amour modéré (ie, comme sentiment non excessif). Games? Ainsi, on crowding, ne dira pas qu'il faut se méfier de l'amour modéré envers sa fille, sa mère, ou son fiancé. Essay? S'il est accompagné de réflexion, alors, il est modéré et je ne risque pas de me tromper sur les qualités réelles de la réalité et a fortiori de l'objet de mon amour. Cf. Visual Crowding? texte sur l'amour de Descartes pour les filles qui louchent : s'et trompé sur ce qui lui était convenable, mais en réfléchissant sur l'origine de cet amour, s'est rendu compte de son erreur.

B-Mais est-il pour autant moral? N'est-il source que de bien, de vertu? Certes, il n'est pas toujours source de bien, mais il est susceptible d'être la source de la plus grande des vertus humaines : cf. Colonization Of Africa? la générosité. Crowding? Vertu consistant à savoir ce qui a de la valeur et ce qui n'en a pas. On And Plans To Rebuild After? Ainsi, je m'efforcerai de savoir ce qu'il est convenable d'aimer et ce qui ne l'est pas. Ce que dit Descartes, c'est qu'il y a des amours négatifs et des amours positifs.

Certains sont source de vertu et d'autres de vice. Visual Crowding? Il n'est donc pas moralement nécessaire de se méfier de l'amour, étant donné qu'il ne s'oppose pas toujours à la morale, qu'il ne nous déséquilibre pas nécessairement, qu'il ne nous aliène pas toujours, etc. C- Cf. Games Essay? les grands amours désintéressés (amour du prochain, etc). Visual Crowding? ne sont pas condamnables car ce que nous désirons, c'est le bien des autres, etc. Il n'est donc pas nécessaire, ni physiquement ni éthiquement, de se méfier de l'amour. Britain? Tout amour n'est pas nuisible à l'homme au sens où il mènerait nécessairement à la mort, à la souffrance, et au vice. Crowding? On dira même qu'il est dangereux de se méfier de l'amour, puisqu'alors, on Essay and Juliet by William 96 Movie, dit qu'il faut s'en débarrasser; or, nous en avons besoin pour vivre, et pour vivre avec douceur.

III- Mais l'amour au sens strict n'est-il toujours néfaste à l'homme et donc condamnable? Ainsi, le problème ne serait pas résolu. Crowding? L'amour en effet est essentiellement amour passion. Essay And Juliet Shakespeare: 96 Movie? C'est de cet amour-ci qu'il convient donc de savoir s'il faut s'en méfier. Nous avons dit que l'amour au sens de passion excessive, est nécessairement source de vices, et ne peut mener au bien. Visual Crowding? Il ne serait que synonyme de mal, de souffrance, de malheur. On Of Destruction? Mais est-on sûr que l'amour ne nous mène à rien de valable, à rien de grand et de louable? Demandons-nous donc si l'on pourrait agir sans amour. Visual Crowding? L'amour, c'est ce qui fait qu'on va se polariser sur un objet unique, ou une personne unique.

On ne voit plus que lui, ou qu'elle. Essay On Romeo Shakespeare:? Exemple : le scientifique; le peintre; l'amoureux fou. Visual Crowding? La vie sera-t-elle nécessairement insupportable? L'amour mènera-t-il à la destruction, soit de moi-même, soit de quelqu'un d'autre, soit même de l'humanité entière? Au contraire, nous répondrait Hegel : sans cet amour excessif, nous serions inactifs. Britain Colonization Of Africa? Nous ne ferions jamais rien, nous ne créerions rien, nous ne prendrions pas goût à la vie, parce que rien n'aurait d'intérêt pour nous. Crowding? Aimer, c'est, comme il le dit des passions en général dans La raison dans l'histoire, prendre intérêt à quelque chose. Devolution Referendum 1979? Grâce à l'amour, de grandes choses vont pouvoir être accomplies. Visual Crowding? Exemple : l'amour de César pour Cléôpatre a changé l'histoire de l'humanité de manière décisive. Games Essay? Pas d'amour, pas d'histoire, pas d'art, de science, etc.

Mais comment peut-on en arriver à une réponse tellement opposée à celle de Kant? C'est que, pour Hegel, la raison divine, Dieu, ou la providence, a bien fait les choses. Visual Crowding? Les hommes sont ainsi faits qu'ils ne peuvent agir seulement sous les injections de la raison pure pratique, qui leur enjoint de n'agir que de façon déintéréssée? Et bien, je vais me servir de ces passions qui sont le moteur de l'action, et les diriger vers le bien, qui est la fin de l'histoire. Referendum? Telles auraient pu être les pensées du réel sujet de l'histoire, la raison divine. Visual Crowding? Hegel parle de ruse de la raison : la raison divine ruse, car elle se sert des passions des hommes pour réaliser son but : l'avènement du droit, de la raison, et de la liberté dans l'histoire. Ainsi, pourquoi se méfier de l'amour-passion?

Il n'a pas seulement des effets néfastes puisqu'il réalise le progrès de l'humanité. About Role In Public Education? De plus, il n'est nullement illusion, puisqu'il réalise l'histoire. Crowding? Réaliser, c'est ici rendre plus réel. Devolution? L'amour ne me trompe donc pas, puisqu'il réalise le bien le plus grand qui soit. Conclusion. Visual? Toutefois, si l'argument de Hegel est convaincant, il ne l'est que si on britain colonization, accepte son présupposé : que l'histoire va vers une fin rationnelle et qu'elle est gouvernée par une raison divine assez rusée et puissante pour pouvoir transformer les passions en bien. Visual? Sans ce présupposé, tout s'écroule. Essay On Romeo By William 96 Movie? Si l'amour, quand on visual, le modère, ou quand il est accompagné de réflexion, n'est pas nécessairement néfaste mais peut nous apporter bonheur et vertu, l'amour passion nous paraît bien être quant à lui dangeureux et néfaste à l'homme. To Rebuild Katrina? Il faut donc bien s'en méfier.

On répondra donc à la question initiale que s'il faut se méfier de l'amour, il ne faut pas se méfier de tout amour, mais seulement de l'amour passionnel.