Higher Quality Input Phrase To Driven Reverse Dictionary

Higher Quality Input Phrase To Driven Reverse Dictionary Implementing a Higher Quality Input Phrase To Driven Reverse Dictionary E.Kamalanathan  and C.Sunitha Ram ABSTRACT Implementing a higher quality input phrase to driven reverse wordbook. In contrast to a conventional forward wordbook, that map from word to their definitions, a reverse wordbook takes a user input phrase describing the specified construct, and returns a group of candidate words that satisfy the input phrase. This work has important application not just for the final public, notably those that work closely with words, however conjointly within the general field of abstract search. The current a group of algorithms and therefore the results of a group of experiments showing the retrieval accuracy and therefore the runtime latency performance is implementation. The experimental results show that, approach will offer important enhancements in performance scale while not sacrificing the standard of the result. Experiments scrutiny the standard of approach to it of presently on the market reverse dictionaries show that the approach will offer considerably higher quality over either of the opposite presently on the market implementations. Index Terms : Dictionaries, thesauruses, search process, web-based services. . INTRODUCTION A Report work on creating a reverse dictionary, As against a regular (forward) wordbook that maps words to their definitions, a WD performs the converse mapping, i.e., given a phrase describing the required conception, it provides words whose definitions match the entered definition phrase. It’s relevant to language understanding. The approach has a number of the characteristics expected from a strong language understanding system. Firstly, learning solely depends on unannoted text information, which is abundant and contain the individual bias of an observer. Secondly, the approach is predicated on all-purpose resources (Brill’s PoS Tagger, WordNet [7]), and also the performance is studied below negative (hence additional realistic) assumptions, e.g., that the tagger is trained on a regular dataset with doubtless totally different properties from the documents to be clustered. Similarly, the approach studies the potential advantages of victimization all potential senses (and hypernyms) from WordNet, in an endeavor to defer (or avoid altogether) the necessity for Word Sense Disambiguation (WSD), and also the connected pitfalls of a WSD tool which can be biased towards a particular domain or language vogue BACKGROUND WORK Natural Language Processing: Natural Language Processing (NLP) [6] is a large field which encompasses a lot of categories that are related to this thesis. Specifically NLP is the process of computationally extracting meaningful information of natural languages. In other words: the ability for a computer to interpret the expressive power of natural language. Subcategories of NLP which are relevant for this thesis are presented below. WordNet: WordNet [7], [2]is a large lexical database containing the words of the English language. It resembles the traits of a thesaurus in that it structures words that have similar meaning together. WordNet is something more, since it also specifies different connections for each of the senses of a given word. These connections place words that are semantically related close to one another in a network. WordNet also displays some quality of a dictionary, since it describes the definition of words and their corresponding part-of-speech. Synonym relation is the main connection between words, which means that words which are conceptually equivalent, and thus interchangeable in most contexts, are grouped together. These groupings are called synsets and consist of a definition and relations to other synsets. A word can be part of more than one synset, since it can bear more than one meaning. WordNet has a total of 117 000 synsets, which are linked together. Not all synsets have a distinct path to another synset. This is the case, since the data structure in WordNet is split into four different groups; nouns, verbs, adjectives and adverbs (since they follow different rules of grammar). Thus it is not possible to compare words in different groups, unless all groups are linked together with a common entity. There are some exceptions which links synsets cross part-of-speech in WordNet, but these are rare. It is not always possible to find a relation between two words within a group, since each group are made of different ba se types. The relations that connect the synsets within the different groups vary based on the type of the synsets. Application Programming Interface Several Application Programming Interfaces (API) exists for WordNet. These allow easy access to the platform and often additional functionality. As an example of this the Java WordNet Library [8] (JWNL) can be mentioned. This allows for access to the WordNet Library files. PoS Tagging PoS tags[8] are assigned to the corpus using Brill’s PoS tagger. As PoS tagging require the words to be in their original order this is done before any other modifications on the corpora. Part-of-speech (POS) tagging is the field which is concerned with analysing a text and assigning different grammatical roles to each entity. These roles are based on the definition of the particular word and the context in which it is written. Words that are in close proximity of each other often affect and assign meaning to each other. The POS taggers job is to assign grammatical roles such as nouns, verbs, adjectives, adverbs, etc. based upon these relations. The tagging of POS is important in information retrieval in general text processing. This is the case since natural languages contain a lot of ambiguity, which can make distinguishing words/terms difficult. There are two main schools when tagging POS. These are rule-based and stochastic. Examples of the two are Brill’s tagger and Stanford POS tagger, respectively. Rule-based taggers work by applying the most used POS for a given word. Predefined/lexical rules are then applied to the structure for error analysis. Errors are corrected until a satisfying threshold is reached. Stochastic taggers use a trained corpus to determine the POS of a given word. Stopword Removal Stopwords, i.e. words thought not to convey any meaning, are removed from the text. The approach taken in this work does not compile a static list of stopwords, as usually done. Instead PoS information is browbeaten and all tokens that are not nouns, verbs or adjectives are removed. Stop words are words which occur often in text and speech. They do not tell much about the content they are wrapped in, but helps humans understand and interpret the residue of the content. These terms are so generic that they do not mean anything by themselves. In the context of text processing they are basically just empty words, which only takes up space, increases computational time and affects the similarity measure in a way which is not relevant. This can result in false positives. Table: 1 List of Stop words This class includes only one method; which runs through a list of words and removes all occurrences of words specified in a file. A text file, which specifies the stop words, is loaded into the program. This file is called â€Å"stop-words.txt† and is located at the home directory of the program. The text file can be edited such that it only contains the desired stop words. A representation of the stop words used in the text file can be found in table 1. After the list of stop words has been loaded, it is compared to the words in the given list. If a match is found the given word in the list is removed. A list, exposed from stop words, is then returned. Stemming Words with the same meaning appear in various morphological forms. To capture their similarity they are normalised into a common root-form, the stem. The morphology function provided with WordNet is used for stemming, because it only yields stems that are contained in the WordNet dictionary. This class contains five methods; one for converting a list of words into a string, two for stemming a list of words and two for handling the access to WordNet through the JWNL API[8]. The first method listToString() takes an ArrayList of strings and concatenate these into a string representation. The second method stringStemmer() takes an ArrayList of strings and iterates through each word, stemming these by calling the private method wordStemmer(). This method checks if the JWNL API has been loaded and starts stemming by looking up the lemma of a word in WordNet. Before this is done, each word starting with an uppercase letter is checked to see if it can be used as a noun. If the word can be used as a noun, it does not qualify for stemming and is returned in its original form. The lemma lookup is done by using a morphological processor, which is provided by WordNet. This morphs the word into its lemma, after which the word is checked for a match in the database of WordNet. This is done by running through all the specified POS databases defined in WordNet. If a match is found, the lemma of the word is returned, otherwise the original word is simply returned. Lastly, the methods allowing access to WordNet initializes the JWNL API and shuts it down, respectively. The initializer() method gets an instance of the dictionary files and loads the morphological processor. If this method is not called, the program is not able to access the WordNet files. The method close() closes the dictionary files and shuts down the JWNL API. This method is not used in the program, since it would not make sense to uninstall the dictionary once it has been installed. It would only increase the total execution time. It has been implemented for good measure, should it be needed. Stemming[5] is the process of reducing an inflected or derived word to its base form. In other words all morphological deviations of a word are reduced to the same form, which makes comparison easier. The stemmed word is not necessarily returned to its morphological root, but a mutual stem. The morphological deviations of a word have different suffixes, but in essence describe the same. These different variants can therefore be merged into a distinct representative form. Thus a comparison of stemmed words turns up a higher relation for equivalent words. In addition storing becomes more effective. Words like observes, observed, observation, observationally should all be reduced to a mutual stem such as observe. PROPOSED SYSTEM Reverse dictionaries approach can provide significantly higher quality. The proposed a set of methods for building and querying a reverse dictionary. Reverse dictionary system is based on the notion that a phrase that conceptually describes a word should resemble the word’s actual definition, if not matching the exact words, then at least conceptually similar. Consider, for example, the following concept phrase: â€Å"talks a lot, but without much substance.† Based on such a phrase, a reverse dictionary should return words such as â€Å"gabby,† â€Å"chatty,† and â€Å"garrulous.† Forward mapping (standard dictionary): Intuitively, a forward mapping designates all the senses for a particular word phrase. This is expressed in terms of a forward map set (FMS). The FMS of a (word) phrase W, designated by F(W) is the set of (sense) phrases {S1, S2, . . . Sn } such that for each Sj à Ã¢â‚¬Å¾ F(Wi), (Wi à ¯Ã†â€™Ã‚   Sj) à Ã¢â‚¬Å¾ D. For example, suppose that the term â€Å"jovial† is associated with various meanings, including â€Å"showing high-spirited merriment† and â€Å"pertaining† to the god Jove, or Jupiter.† Here, F (jovial) would contain both of these phrases. Reverse mapping (reverse dictionary): Reverse mapping applies to terms and is expressed as a reverse map set (RMS). The RMS of t, denoted R(t), is a set of phrases { P1, P2, Pi,†¦Ã¢â‚¬ ¦, Pm}, such that à ¯Ã¢â€š ¬Ã‚ ¢Pi à ¯Ã¢â€š ¬Ã‚  Ãƒ ¯Ã†â€™Ã… ½ R(t), t à ¯Ã†â€™Ã… ½ F(Pi). Intuitively, the reverse map set of a term t consists of all the (word) phrases in whose definition t appears. The find candidate words phase consists of two key sub steps: 1) Build the RMS. 2) Query the RMS. A. COMPONENTS The first preprocessing step is to PoS tag the corpus. The PoS tagger relies on the text structure and morphological differences to determine the appropriate part-of-speech. For this reason, if it is required, PoS tagging is the first step to be carried out. After this, stopword removal is performed, followed by stemming. This order is chosen to reduce the amount of words to be stemmed. The stemmed words are then looked up in WordNet and their corresponding synonyms and hypernyms are added to the bag-of-words. Once the document vectors are completed in this way, the frequency of each word across the corpus can be counted and every word occurring less often than the pre specified threshold is pruned. Stemming, stopword removal and pruning all aim to improve clustering quality by removing noise, i.e. meaningless data. They all lead to a reduction in the number of dimensions in the term-space. Weighting is concerned with the estimation of the importance of individual terms. All of these have been used extensively and are considered the baseline for comparison in this work. However, the two techniques under investigation both add data to the representation. a PoS tagging adds syntactic information and WordNet is used to add synonyms and hypernyms. B. BUILDING REVERSE MAPPING SETS The input phrases sentence is split into words and then removes the stop words ( a, be, person, some, someone, too, very, who, the, in, of, and, to) if any appears, and find other words, which is having same meaning from the forward dictionary data sources. Given the large size of dictionaries, creating such mappings on the fly is infeasible. Thus, Procreate these Rs for every relevant term in the dictionary. This is a one time, offline event; once these mappings exist, we can use them for ongoing lookup. Thus, the cost of creating the corpus has no effect on runtime performance. For an input dictionary D, we create R mappings for all terms appearing in the sense phrases (definitions) in D. C. RMS QUERY This module responds to user input phrases. Upon receiving such an input phrase, we query the R indexes already present in the database to find candidate words whose definitions have any similarity to the input phrase. Upon receiving an input phrase U, we process U using a stepwise refinement approach. We start off by extracting the core terms from U, and searching for the candidate words (Ws) whose definitions contain these core terms exactly. (Note that we tune these terms slightly to increase the probability of generating Ws) If this first step does not generate a sufficient number of output Ws, defined by a tuneable input parameter ÃŽ ±, which represents the minimum number of word phrases needed to halt processing and return output. D. CANDIDATE WORD RANKING In this module sorts a set of output Ws in order of decreasing similarity to U, based on the semantic similarity. To build such a ranking, we need to be able to assign a similarity measure for each (S,U) pair, where U is the user input phrase and S is a definition for some W in the candidate word set O. Wn and Palmer’s Conceptual similarity, WUP Similarity between concepts a and b in a hierarchy, Here depth(lso(a,b)) is the global depth of the lowest super ordinate of a and b and len(a,b) is the length of the path between the nodes a and b in the hierarchy SOLUTION ARCHITECTURE We now describe our implementation architecture, with particular attention to design for scalability. The Reverse Dictionary Application (RDA) is a software module that takes a user phrase (U) as input, and returns a set of conceptually related words as output. Figure 1. Architecture of reverse dictionary. The user input phrase, split the word from the input phrase, perform the stemming. Predict every relevant term in the forward dictionary data source. In the generate query. input phrase, minimum and maximum output thresholds as input, then removal of level 1 stop words ( a, be, person, some, someone, too, very, who, the, in, of, and, to) and perform stemming, generate the query.Execute the query find the set of candidate words. Finally sort the result based on the semantic similarity EXPERIMENTAL ENVIRONMENT Our experimental environment consisted of two 2.2 GHz dual-core CPU, 2 GB RAM servers running Windows XP pro and above. On one server, we installed our implementation our algorithms (written in Java). The other server housed is wordnet dictionary data. CONCLUSION We describe the many challenges inherent in building a reverse lexicon, and map drawback to the well-known abstract similarity problem. We tend to propose a collection of strategies for building and querying a reverse lexicon, and describe a collection of experiments that show the standard of our results, similarly because the runtime performance underneath load. Our experimental results show that our approach will give important enhancements in performance scale while not sacrificing answer quality. The higher quality input phrase to driven reverse dictionary. Unlike a traditional forward dictionary, which maps from words to their definitions, a reverse dictionary takes a user input phrase describing the desired concept, it reduce the well-known conceptual similarity problem. The set of methods building a reverse mapping querying a reverse dictionary and it produces the higher quality of results. This approach can provide significant improvements in performance scale without sacrificing solution quality but for larger query it is fairly slow. REFERENCES T. Dao and T. Simpson, â€Å"Measuring Similarity between Sentences,† 2009. http://opensvn.csie.org/WordNetDotNet/trunk/ Projects/ T. Hofmann, â€Å"Probabilistic Latent Semantic Indexing,† SIGIR ’99: Proc. 22nd Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval, pp. 50-57, 1999. D. Lin, â€Å"An Information-Theoretic Definition of Similarity,† Proc .Int’l Conf. Machine Learning, 1998. M. Porter, â€Å"The Porter Stemming Algorithm,†http://tartarus.org/martin/PorterStemmer/ , 2009. G. Miller, C. Fellbaum, R. Tengi, P. Wakefield, and H. Langone, â€Å"Wordnet Lexical Database,† http://wordnet.princeton.edu/wordnet/download/, 2009. P. Resnik, â€Å"Semantic Similarity in a Taxonomy: An Information-Based Measure and Its Application to Problems of Ambiguity in Natural Language,† J. Artificial Intelligence Research, vol. 11, pp. 95- 130, 1999. AUTHORS PROFILE E Kamalanathan is pursuing his Master of Engineering (part time ) from Department of Computer Science and Engineering, SCSVMV University Enathur,

Comparing Gilliams Brazil and Radfords Adaptation of 1984 :: comparison compare contrast essays

Comparing Gilliam's Brazil and. Radford's Adaptation of 1984  Ã‚     Ã‚   While researching for a book on the making of and feud over the American release of Terry Gilliam's Brazil, author Jack Mathews read virtually every review of the film printed in the United States and found that very few failed to refer to the film as "futuristic" or "Orwellian." "The comparisons are understandable, if inaccurate," says Mathews, "There isn't a futuristic element in Brazil. The story is Orwellian, in the sense that it is set in a totalitarian state where individuality is smothered by enforced conformity. But where George Orwell...was envisioning a future ruled by fascism and technology, Gilliam was satirizing the bureaucratic, largely dysfunctional industrial world that had been driving him crazy all his life"(Mathews). Terry Gilliam's Brazil, made in 1985, at first glance, seems much like Michael Radford's film version of George Orwell's 1984, made in 1984, in its setting and story. However, upon further examination of the two films, there are differences in style and tone that distance them from each other. 1984 is dark and gloomy from beginning to end while Brazil, though still dark, has a much lighter atmosphere. The love stories presented in both films are unmistakably similar and make the plots seem closer to each other, but this is the only strong link they share, for differences in tone distance the films from each other. Because of its dark humor, Brazil is a satire of the very society in which the story takes place, while 1984, though also a satire, lacks any humor whatsoever and is more of a horror story of a society that might await mankind. In the opening scene, Terry Gilliam's Brazil seems to be quite jovial. A shot in which the camera hovers through the sky, passing in and out of clouds, starts the film off while the song "Brazil," after which the movie was named, fills the soundtrack. Titles begin to appear over the soaring shot. The titles read, "Somewhere in the 20th Century," informing the audience of the time period, but confusing them as well. The world in which the movie's main character dwells is a dreary, dystopian, retro-futuristic metropolis, a far cry from anything that has been seen this century. In this world, nobody is protected from the government; individuals are executed as a result of administrative errors. The compensation for these wrongful deaths is a simple refund check.

The Heart of Darkness: the Ultimate Choice of Man

The Heart of Darkness: The Ultimate Choice of Man A single word holds the potential to have multiple connotations. Stringing these subjective words into a novel may have a catastrophic effect on the readers. However, a story’s ability to comprise of several different interpretations provides deeper insight and depth. In Joseph Conrad’s novel, The Heart of Darkness, there are various viewpoints one may take throughout the main character Marlow’s journey.But Conrad’s artful use of dualistic symbolism is arguably the most crucial because it highlights the underlying theme, which stresses the dual nature of man and his choice to control his actions. During the entirety of the book, dualism is constantly utilized to contrast separate entities, such as wilderness and civilization. Some may argue the two are merely classifications of environments but in actuality, they represent the effect that order or lack of can have on people. Civilizations consist of laws an d rules to uphold man’s morals to ensure a working and efficient society.But as mentioned in the novel, Marlow says, â€Å"And [London] also†¦has been one of the dark place of the earth†¦I was thinking of very old times, when the Romans first came here†¦Oh yes – [they] did it. Did it very well, too, no doubt and without thinking much about it either, except afterwards to brag of what he had gone through in his time, perhaps. They were men enough to face the darkness†(67-69). London, a symbol of enlightenment, is also once a â€Å"dark place of the earth† until Romans force civilization upon the land. The city is an example stressing how civilization is a learned habit and is not an innate characteristic of humanity.To maintain a stable and harmonious community, it appears necessary to establish a code of ethics to enforce stability on its people. But if defined in this sense, imperialism is clearly a hypocritical attempt to justify exploita tions of the indigenous and primitive states of man and nature alike. The Company in The Heart of Darkness insists it will colonize the people, but this reasoning is extremely ironic because the damage that the jungle has on the white man’s soul exceeds the physical pain of the black men’s toil.Near the beginning of the trip, Marlow distinguishes the feeling of the jungle and says, â€Å"In some inland post feel the savagery, the utter savagery, had close round him – all that mysterious life of the wilderness that stirs in the forest, in the jungles, in the hearts of wild men†¦ He has to live in the midst of the incomprehensible, which is also detestable. And it has a fascination, too, that goes to work upon him†(69). Even if the wilderness is constantly described as dark and savage, it holds a fascination upon civilized men.This is partly due to the incomprehensibility of the wilderness that imposes itself as an ominous, omnipotent force testing one ’s ability to hold onto sanity. Once people enter the wild, their primitive impulses are revealed since they are free to do as they desire without fear of consequence. The jungle is referred to as â€Å"the heart of darkness† not because it unleashes the evil of civilized men, but because it mirrors the darkness already apparent in every being. As Marlow progresses deeper into the jungle, he says, â€Å"The earth seemed unearthly.We are accustomed to look upon the shackled form of a conquered monster, but there – there you could look at a thing monstrous and free. It was unearthly, and the men were – No, they were not inhuman†¦but if you were man enough you would admit to yourself that there was in you just the faintest trace of a response to the terrible frankness†¦ Principles won’t do. Acquisitions, clothes, pretty rags – rages that would fly off at the first good shake. No; you want a deliberate belief†(108-109). Society may restrain savage tendencies, yet it cannot eliminate them.Primeval tendencies are always lurking, and the superficial morals of civilization are much more unstable than it seems at first glance. The acquisitions and material possessions mentioned are considered to be valuable requirements to live an accomplished and successful life. Greed fuels the expedition and it is what overcame Kurtz, who represents what man can become if left solely to his inner desires. On the other hand, Marlow is a civilized soul who is left mostly unscathed by the darkness. In the lawlessness of the wilderness, it is up to the individual to either abide to his morals or sacrifice his soul to the darkness.When men are confronted with the boundless opportunities for sin in the wilderness, they can choose to restrain their internal greed or to accede to their temptations. Conrad uses these two intangible contrasts to stress that man does indeed have a choice in his actions. Even the â€Å"savage† me n who are natives of the jungle are primary examples of restraint in the novel. During the expedition, Marlow characterizes the natives and says, â€Å"Yes; I looked at [the natives] as you would on any human being with a curiosity of their impulses, motives, capacities, weaknesses, when brought to the test of an inexorable physical necessity.Restraint! What possible restraint? â€Å"(116). Desires and impulses of humanity can often fuel their ambitions. At the same time, desires can bring ruin to a man because they may compel him to commit treacherous and evil deeds. However, they cannot be an excuse for man to brush aside his wrongdoings for they do not force him to make any actions. A person’s actions must be judged accordingly, regardless of his or her intended motives or societal status. One’s lack of restraint is exemplified when Marlow says, â€Å"[The helmsman] had no restraint, no restraint-just like Kurtz-a tree swayed by the wind†(129).Before, the h elmsman is a native of the Congo, but he becomes accustomed to the white man’s ways after accompanying the sailors on their journey. The native men of the Congo are both physically and mentally stronger because they are not enticed by material temptations. Association with proud civilized men causes the helmsman to be careless, leading to his untimely death. Instead of upholding his original ideals, the man’s absence of self-control indicates his newfound weakness.Kurtz, a man of great power and wealth, is ironically the ultimate representation of a man blinded by temptation, which deteriorates his willpower and produces a weak and unstable mentality. In his final moments, Kurtz cries out, â€Å"The horror! The horror†(154). These final words are Kurtz’s recognition of the â€Å"horrors† he has committed by allowing temptation to overtake him. In Kurtz’s situation, temptation triumphs and concludes in his death, basically suggesting that suc cumbing to one’s temptations results in the ultimate punishment.Restraint and temptation are dualities implying that everyone possesses a good and evil nature, but the choice to uncover the restraint required to preserve humanity is ultimately left to the discretion of each person. Both wilderness and civilization along with temptation and restraint comparisons symbolize the good and bad within human nature, which is exemplified the most generally by portrayal of light and dark. Conrad twists the usual denotation of light and its common interpretations because light often portrays ignorance and narrow-mindedness in the novel.The dark is ever present in the jungle; hence the title The Heart of Darkness, but it is also strongly characterized by Kurtz. One of the descriptions of Kurtz says, â€Å"The point in his being a gifted creature, and that all his gifts the one that stood out pre-eminently, that carried with it a sense of real presence, was his ability to talk, his words –the gift of expression, the bewildering, the illuminating, the most exalted and the most contemptible, the pulsating stream of light, or the deceitful flow from the heart of an impenetrable darkness†(124).During this specific moment, light is symbolized as a force used to enlighten, while darkness represents the â€Å"impenetrable† evil. Again, it is ironic that the two are juxtaposed together because Conrad clearly states the light cannot pierce the dark, yet Kurtz is evidently a man who wields the power to speak truth and wisdom. Although Kurtz is a man who embodies the darkness of the jungle, he affirms the understanding that all humans have good and evil coexisting within them. Conrad’s abandonment of the traditional connotation of light is noted when Marlow says, â€Å"I know that the sunlight can be made to lie too†¦ â€Å"(151).Surprisingly, the light which is previously portrayed as truth has evolved into the complete opposite. Since his co ntradiction blurs the line between good and evil, Marlow loses the confidence in his previous ability to judge between the two. As a result, both Marlow and the readers realize that nothing and no one can be totally good or evil, and there are no restrictions to which the concept applies to. Perhaps the most controversial statement about light and dark is when Marlow notices a work of art and says, â€Å"Then I noticed a small sketch in oils, on a panel, representing a woman, draped and blind-folded, carrying a lighted torch.The background was somber–almost black. The movement of the woman was stately, and the effect of the torchlight on the face was sinister†(94). The painting can have a multitude of meanings, ranging from the hypocrisy of imperialism, to the unwillingness of any individual to admit his or her wrongs. Many are quick to endorse the wrongs and flaws of others but refuse to defer to their own, as portrayed by the blindfold of the woman.This is the reason why a majority of people live in a false reality of a black and a white perspective on the world, in which there are only two outcomes to a situation. If everyone could concede to an understanding that all entities have a balance between one another, light and dark would be totally different concepts than what they are today. The three major dualities all contribute to highlight Conrad’s fundamental theme, which asserts that all men are composed of both good and evil and have the choice to maintain an optimal balance.Marlow and Kurtz are not as different as they once appeared in the beginning of the book. Each character struggles with the temptation of the darkness, but only Kurtz is totally consumed. The two characters embody two common choices that occur in reality; to either find a balance between good and evil or to be pushed into the extremity of one side. However, it is important to acknowledge that one entity cannot exist without the other, and in the end, only the in dividual can control his or her fate.

What Drives Someone to Complete the Devastating Acts of...

Since the darkest day, September 11, 2001, the citizens of The United States of America are on alert and are weary of acts of terrorism. One can turn on the television and can easily find an act of terrorism. Most recent acts are the Boston bombings or the bombings in Volgograd, and most recently the two bombings in Sochi. What drives someone to complete the devastating acts of terrorism? How can on predict, based off of antisocial behaviors, who is more likely to become a terrorist? Regardless of ethnicity, nationality, or racial background, experts agree terrorists share one common link: their childhood. One tends to be more susceptible to becoming a terrorist because of a traumatic event in their childhood to cause antisocial behavior.†¦show more content†¦For example Osama Bin Laden, disagreed with political views in his country and what did he do? He gained power and struck fear in people and gained their support to start the revolution for change. All terrorist start their journey to terrorism early in childhood. Most terrorists have a â€Å"criminal mentality and had previous lives as criminals† (Kershaw). Terrorists are criminals; however, their crimes are on a larger scale and tend to be recognized throughout the world. Most terrorists have an â€Å"unconscious fear of mortality, of leaving no legacy† (Kershaw). This explains that a terrorist who upgraded from a criminal does not want to die without leaving a legacy behind. Also there is a â€Å"trigger of some kind to accelerate radicalization - for example, the politically related killing of a friend or relative† (Kershaw). Typically terrorists who started out with a low level criminal mindset, begin to think about dying without a legacy, which causes the person to execute acts of terrorism. The initial trigger for the person to act out is the killing of a relative or close friend. Two of the most famous terrorists that we know today are, Osama Bin La den and Adolf Hitler. We know Bin Laden very well because he left vivid images of the twin towers being destroyed on 9/11, as well as heShow MoreRelated`` Night `` By Elie Wiesel2409 Words   |  10 Pagesinterviews prove the ghastly sights troop encountered while fighting and the hatred they proceeded to take. All of the struggles our troops endured, and they still had to come home to a mind-numbing defeat. On more modern bases, war is fought on terrorism, since the bombing of the world trade center in 2001; furthermore, our troops have been stationed in the Middle East. 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NATORead MoreProject Mgmt296381 Words   |  1186 Pages5) 5.1.2.4 Delphi method Chapter 6 10.5.3 Cost/schedule system (.1) 6.6 .2.1 Time performance 7.2.3.1 Cost baseline development 7.3.2.1 Earned value system (F.4) 7.3.2.4 E.V., performance status report 7.3.2.2 E.V., forecasts 7.3.2.3 EV., to complete index (EAC) 7.3.2.5 Schedule and cost variance Developing a Project Plan 4.2.2 Planning tools 6.2 Sequence activities [1.2] 6.5.1 Bar and milestone charts 6.5.2 Critical path method (.2) 6.5.2.6 Lead and lag activities [6.2.3] F.3 Project duration Read MoreSecurity Forces51988 Words   |  208 Pagesbecome more effective in daily operations would be TACON. The flight chief is the best example of TACON as they run the flight who is conducting the daily operations. They are told to conduct guardmount, but they are not told in what order they conduct their briefings or what type of information needs to be briefed every day. They also assign who gets posted at each location for the day. OPCON would be the post priority chart that tells the flight chief which posts are the most important and requireRead MoreAccounting Information System Chapter 1137115 Words   |  549 Pagessimultaneously. For example, more timely information is also likely to be more relevant. Verifiable information is likely to be more reliable. However, achieving one objective may require sacrificing another. For example, ensuring that information is more complete may reduce its timeliness. Similarly, increased verifiability and reliability may reduce its timeliness. The decision maker must decide which trade-offs are warranted in a given situation. 1-1 Ch. 1: Accounting Information Systems: An Overview Read More1000 Word Essay85965 Words   |  344 Pages382 387 Page 3 / 389  © Copyright 1999-2012 ArmyStudyGuide.com Version 5.3 Army Programs What does ASAP stand for? Army Substance Abuse Program (AR 600-85 Mar 2006) What is the mission of ASAP? The ASAP’s mission is to strengthen the overall fitness and effectiveness of the Army’s total workforce and to enhance the combat readiness of its Soldiers. (AR 600-85 Mar 2006 / 1-30 / PDF 19) What are the objectives of ASAP? Increase individual fitness and overall unit readiness. Provide servicesRead MoreProject Managment Case Studies214937 Words   |  860 Pageselectronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the Web at www.copyright.com. Requests to the Publisher for permission should be addressed to