Lewis Carroll And Hilary T. Smith Use Dialogue - 781 Words

One of the most direct ways for an author to reveal the thoughts and personality of a character is through their interactions with other characters, namely, their dialogue. These interactions will differ depending on the point of view of the story with each perspective offering a different insight into the disposition of the other characters. Authors such as Lewis Carroll and Hilary T. Smith use dialogue to create and enhance conflict within and surrounding their characters. In Alice’s Adventures in Wonderland, Lewis Carroll uses third-person limited to give the reader an intimate look into the thoughts, feelings, and actions of Alice by way of an anonymous narrator. With this perspective, it is possible to see the changes Alice undergoes during her adventure in Wonderland and her feelings on them. It also adds to the mystique surrounding the motives and intentions of the other characters within the story and adds to the tension created by the nonsensical application of reason. The dialogue between Alice and the other characters in the story gives the most insight into the underlying meaning of the story where Alice finds her herself in a fantastical world. Everything she knows is questioned, and the absurd and nonsensical are the norms. â€Å"Alice felt dreadfully puzzled. The Hatter’s remark seemed to have no sort of meaning in it, and yet it was certainly English. Alice had been looking over his shoulder with some curiosity. ‘What a funny watch!’ she remarked, ‘It tells the

Describe with Examples the Kinds of Influences That Affect...

Assessment Task TDA – 2.1 Child and young person development. Task 2 links to learning outcome 2, assessment criteria 2.1 and 2.2. Describe with examples the kinds of influences that affect children and young people’s development, including: - background - heath - environment While children are influenced by many things, there are no stronger influences than that of their parents. Parents are usually their children’s first playmates, and while there world expands with each passing year, parental influence is still one of the greatest factors in determining the ways in which the child will grow and develop. Background: Naturally parents want to see their children do well. Sometimes though in an effort to keep kids safe,†¦show more content†¦As children all develop at different speeds, a child that struggles at school and has not been identified as having any specific special needs, could suffer from depression thus affecting the child’s development. Other factors that can affect a child’s development can include genetic problems passed on by a parent, mental or physical disabilities, poor living conditions causing illness such as asthma, learning difficulties, autism, dyspraxia, aspergers, poor communication skills due to sensory impairment such as deafness, blindness, partially sighted. Disability brings problems to schools too causing the child to be disadvantaged. These could include lack of specialist staff or poor staff knowledge which can lead to lack of socialisation and integration into the school. Environment: Socialisation is important for children. Parents who offer their children varied opportunities in which to meet new people and experience new things give their children an invaluable gift. When they are babies, children need no more than the attentive, loving care given by their parents, but as they grow, it is beneficial for children to expand their worlds by making friends with other people and learning about different cultures. Children who gain a sense of confidence in their ability to interact with people will take them into adulthood making both their personal and professional livesShow MoreRelated2.1 Describe with Examples the Kinds of Influences That Affect Children and Young People‚Äà ´s Development Including; Background, Health and Environment803 Words   |  4 PagesA child development is influenced in many ways such as their background, health and environment. These factors will have an impact on the child’s different areas of development. Background Children come from all different family environments, cultures and circumstances. Children go through significant family changes such as a family break-up or a new step-family. These can affect a child’s emotional and intellectual development. A child may also change their behaviour, which means there abilityRead MoreChild and young person development1148 Words   |  5 PagesChild and Young Person Development Title Describe the main stages of a child and young person development from birth to 19 years old and the kind of influences that affect this process. Evidence Covered 1.1 Describe the expected pattern of children and young peoples development from birth to 19 years, to include: a) physical development b) communication and intellectual development c) social, emotional and behavioural development 1.2 Describe with examples how differentRead MoreEssay on Child and Young Person Development1179 Words   |  5 PagesAssessment Task – TDA 2.1 Child and Young Person Development Task 2 2.1. Describe with examples the kinds of influences that affect children and young people’s development, including: * Background * Health * Environment Background Children will come from a diverse range of backgrounds including family environments, cultures and circumstances. A child is at school from a very young age to late teens and during this time many families will go through significant changes,Read MoreTDA21 Child and Young Person Developmen6757 Words   |  28 PagesChild and Young Person Development 1) 1.1 Describe the expected pattern of children and young people’s development from birth to 19 years to include Physical Development Communication and Intellectual Development Social, emotional and behavioural Development Physical Development There are expected patterns of development for children from birth to 19 years old. Although all children are individuals and unique and there are factors which can have a bearing on development such as health, environmentRead MoreCache Level 3 Award, Level 3 Certificate and Level 3 Diploma in Child Care and Education15197 Words   |  61 Pagesintroduction to working with children Development from conception to age 16 years Supporting children Keeping children safe The principles underpinning the role of the practitioner working with children Promoting a healthy environment for children Play and learning in children’s education Caring for children Research into child care, education and development Care of sick children Nutrition and healthy food for children Child, family and outside world Working with children with special needs DevelopingRead MoreTda2.1 Child and Young Person Development Essay2286 Words   |  10 PagesTDA 2.1 Child and young person development TDA 2.1 Child and young person development. 1.1 Describe expected pattern of children and young people’s development from birth to 19 years. Birth to one year New-born babies can: * see faces as fuzzy shapes * grasp an object that has touched the palm of their hand * turn their head to look for a nipple or teat if their cheek is touched * suck and swallow * try to make stepping movements if they are heldRead MoreDescribe the expected pattern of children and young peoples development from birth to 19 years, to include: - physical development3356 Words   |  14 PagesSupporting evidence Attachments TDA 2.1.1 ac[1.1a] Describe the expected pattern of children and young people s development from birth to 19 years, to include: - physical development When looking at the expected pattern of children and young peoples development from birth to 19 years, it is important to remember that each child will develop and grow at different rates. Reaching milestones at a more advanced pace or a slower pace than the broad average. This expected pattern includes physicalRead MoreCashe Level 2 Essay example18123 Words   |  73 PagesCACHE Qualification Specification CACHE Level 2 Certificate for the Children and Young People’s Workforce (QCF) CACHE Level 2 Certificate for the Children and Young People’s Workforce (QCF)  © CACHE 2011 Except as allowed by law, or where specified in the text, no part of this publication may be reproduced or transmitted in any form or by any means without prior permission from the Council for Awards in Care, Health and Education. CACHE has provided this Qualification Specification in MicrosoftRead MoreLevel 3 Childcare Unit1 Essay6759 Words   |  28 PagesUnit 1. Understanding child and young person development. 1. Explain the sequence and rate of each aspect of development from birth – 19years. The word development refers not to the physical growth of children and young people, but to the skills and knowledge that they are developing. When looking at child development it is divided into the following areas – Physical Development Refers to learning how to master physical movement. Fine motor skills Read MoreSchools as Organisations Level 36524 Words   |  27 Pagesuniversity 1.2 Describe the characteristics of the different types of schools in relation to educational stage and school governance Local Authority Nurseries * Usually cater for children aged 3-5yrs, can be attached to a primary school or children’s centre. Usually open term time only. Hrs of 9 – 3.30pm. * Follows the EYFS (early year’s foundation stage). Framework to support a child’s development and learning from birth to 5ys. State funded through the LA for children 3-5yrs, 15hrs

The Constitution vs. Racial Profiling The Knock-out Round free essay sample

Explores constitutional issues in racial profiling and discrimination in the wake of 9/11. Examples of profiling are derived from general minority experiences and specifically Arab/Muslim discrimination after 9/11. This paper presents a detailed examination of racial profiling. The writer addresses four scenarios and argues for or against their legal and moral foundation based on the 14th amendment of the United States Constitution. In addition to the writers belief regarding each scenario, we are given key elements of the oppositions argument and the writers rebuttal to that opposition. From the paper: Following the attacks on America September 11, 2001, there were cries for revenge throughout the nation. Anyone who looked Muslim was endangered as Americans took their anger to the streets. Following the attack there were several instances in which pilots refused to fly planes until Muslim looking passengers were removed and angry residents threatened those who looked like one of them. We will write a custom essay sample on The Constitution vs. Racial Profiling: The Knock-out Round or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page The initial rage died down and in its place we were given many new security measures that we have been told are for the good of national security. The measures boil down to legalized racial profiling in some cases. Racial profiling is not a new event. It has been around for many years. Racial profiling goes against everything the constitution of this nation stands for; yet in light of the attacks in New York, Americans are less vocal about it then they have been in the past. Now, instead of denouncing all profiling as unconstitutional and wrong, we find ourselves looking at individual profile scenarios and holding them against the constitution to see if we can slide them through. We have entered a new world since the attacks. It is a world in which we are trying to walk a much thinner line between protecting the safety of those who live here and protecting the constitution.

Job Design free essay sample

Hackman and Oldham’s job characteristics model can be used for job design to make sure organizations goals are achieved and employees are satisfied with their jobs. They propose that a satisfied employee has better performance, internal motivation, and lower absenteeism. In order to achieve this, an employee must believe his work is meaningful, he must be responsible for the outcomes, and must see the end result. They believe that using techniques such as job enlargement, job rotation, employee empowerment, and job crafting. Job enlargement is when the tasks and responsibilities of a job are enlarged. More tasks and responsibilities means the employees will feel more meaningful about their jobs. Job rotation is when employees switch jobs from time to time to decrease boredom and repetitiveness. This can be a huge benefit to an employer because the employees will know how to do many different jobs. The employer will have flexible employees who can be utilized in many different ways. We will write a custom essay sample on Job Design or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Another technique an employer can use is employee empowerment. This is when the employee’s opinions are listened to and they have more responsibility. This allows them to take risks and try to become innovators. Employee innovation can really increase productivity because they know their jobs the best. It also means they will be responsible for the outcomes of their innovations. Another technique is job crafting were an employee tailors their job to their strengths. This will help motivate them and will make them more productive. These are ways that the job characteristics model improves job design.

Impact of the Black Death

Impact of the Black Death Introduction The Black Death was, no doubt, the greatest population disaster that has ever occurred in the history of Europe. The name is given to the bubonic plaque that occurred in the fourteenth century in Europe killing millions of people. The plaque began in the year 1348, and by the year 1359, it had killed an approximate 1.5 million people, out of an estimated total population of about 4 million people.Advertising We will write a custom essay sample on Impact of the Black Death specifically for you for only $16.05 $11/page Learn More So terrifying was the Black Death that peasants were blaming themselves for its occurrence, and thus some of them resulted to punishing themselves as a way of seeking God’s forgiveness. The bubonic plaque was caused by fleas that were hosted by rats, a common phenomenon in the cities and towns. The presence of rats in the cities and towns was due to the fact that the towns were littered, and they were poorly manage d. The worst part of it is the fact that the medieval peasants did not know that the plaque was caused by the pleas hosted by the rats. They actually believed that the plague was caused by the rats themselves. As more and more people died from the Black Death, the impacts of the plague became more profound. The plague affected the demographic composition of the society, and thus it had far-reaching effects on the social, economic, political and even cultural realms of the medieval society. To this day, the Black Death is remembered as the worst demographic disaster to be ever experienced in European history (Robin, 2011). This paper is an in-depth analysis of the impacts of the Black Death. Social impacts of the Black Death The Black Death had far reaching social impacts on the people who lived during the fourteenth century. An obvious social impact of the plague is the fact that the Black Death led to a significant reduction in the human population of the affected areas. This had e xtensive effects on all aspects of life, including the social and political structure of the affected areas. Before the plague, feudalism, the European social structure in medieval times, had created a society in which inequality was rife, with many poor peasants, and rich lords. This fuelled overpopulation, which was a catalyst for the mortality of the plaque. After the plaque, a large number of the overpopulated peasants became victims of the plaque, and thus the lords lacked labourers in their farms. This also led to a significant reduction in the population (Bryrne, 2011). The people who were spared by the plague lived full lives. They regarded themselves as the next victims of the bubonic plague. This led to immoral behaviour that saw societal codes like the sexual codes broken. People did not care about having virtues anymore because they knew that death was approaching fast. As people lost their partners to the plague, the marriage market grew, fuelling more sexual immorality (Carol, 1996).Advertising Looking for essay on history? Let's see if we can help you! Get your first paper with 15% OFF Learn More Also among the immediate social impacts is the fact that at one point, the number of people who were dying from the bubonic plague was seemingly more than the number of the living. This made it virtually impossible for the living to take care of the ailing, or even for the living to bury the deceased. This was a social crisis that has remained in the books of history as a remarkable impact of the bubonic plague. Economic impacts of the Black Death Immediately after the occurrence of the Black Death, all economic activities were paralysed. The first economic activity to suffer substantially from the plaque was trade. Although people were not aware that it was the infectiousness of the plaque that was making it to kill more people, they were afraid to travel to plagued areas for fear of coming into contact with rats, which they bel ieved was the source of the disease. This substantially affected trade ties between villages and communities in the medieval European society. After the occurrence of the Black Death, other impacts of the plague started affecting the community. The population of the European parts affected by the plaque reduced drastically, leading to a severe shortage of labour for the farms. The demand of peasant farmers increased, with the lords competing for them by relocating them from their villages to the farms of the latter. This made the peasants have a competitive economic edge, as they were able to negotiate for better salaries. As the Black Death claimed more lives, farms were left unattended because the peasants who were responsible for ploughing had fallen victims of the plague. Where the lords were lucky to have had some harvest, it was challenging to bring it home due to a serious shortage of manpower. Some harvest got destroyed in the field as there were no men to bring it home. Som e animals got lost because the people who used to look after them had also fallen victims of the plague. These problems led to a number of other impacts in the medieval society of the fourteenth century (Bridbury, 1973). As farms went unploughed and some harvest remained in the fields, people in the villages starved for food. Cities and towns also faced severe shortages of food since the farming villages around the towns did not have sufficient foodstuffs. Lords had to strategize economically in order to survive, and thus most of them resulted to keeping sheep since it was easier without the manpower. Economic activities that required the presence of large numbers of peasants like the farming of grains lost their popularity. This, in turn, led to serious shortage of basic commodities like bread. This, coupled with the fact that the production of all kinds of foodstuffs had decreases, led to inflationary prices on commodities (â€Å"The Black Death And Its Effects†, 1935). The poor were left thriving in an environment full of hardships as the prices of foods skyrocketed.Advertising We will write a custom essay sample on Impact of the Black Death specifically for you for only $16.05 $11/page Learn More Political impacts of the Black Death The Black Death had a number of political impacts. First of all, the feudal social system of the fourteen-century European population demanded that peasants could not relocate from their villages at will. For a peasant to relocate from his/her village, he/she had to seek the permission of his/her lord. After the Black Death, it became increasingly difficult for lords to get the number of peasants they required to provide them with the labour for their farms. This made lords to disregard the law, and relocate peasants to their villages so that they could work in their farms. Most of the times, the lords even declined to return the latter to their rightful villages in a bid to get maximum benefit from their labour. Another political impact of the Black Death also stems from the reduced population of the affected areas. This is because after the number of peasants reduced, and they were able to negotiate salaries and even relocate from their villages, contrary to feudal law, the government imposed stricter rules to regulate the way peasants offer their manpower to the lords. This was done by the introduction of the 1351 â€Å"statute for labourers† (Bridbury, 1973). The statute provided that payments to peasants were to be made with reference to the payments that were made in 1346. This meant that peasants would receive payments using the terms that were prevailing before the plague occurred. The statute was structures such that both the lord and the peasant could be accused of breaking the law by either the peasant receiving a higher payment, or the lord giving the same. The effect of this statute was that a good number of peasants disobeyed it, leading to, arguably i nhumane punishment. This fuelled revolt among the peasants who sought to fight for their rights in the 1381 Peasants Revolt (Bentley et al., 2008). After oppressive statutes like the statute for labourers came into force, peasants started to be resistant. They therefore organized a number of revolts in a bid to attract the attention of legislators to their plea of fairness. The most serious of these revolts was the aforementioned 1381 peasant revolt. The peasants had gathered in huge numbers and marched to London. They killed senior officials of the King and took control over the tower of London. Among their main grievances was the fact that, thirty-five years after the occurrence of the Black Death, the population had reasonably grown and the pre-existent demand for labour had substantially reduced. The lords were therefore threatening to withdraw the privileges they had given to peasants since their demand was no more. This led to the revolt as the peasants sought to fight for the ir privileges.Advertising Looking for essay on history? Let's see if we can help you! Get your first paper with 15% OFF Learn More Conclusion From the discussion above, it is evident that the Black Death had a lot of impacts on the European medieval society. It changed the demographic set-up of the community and thus it substantially affected the social activities of the peasants. This can be evidenced by the aforementioned increase in cases of sexual immorality as people had lost their partners in the plague. The Black Death also had a number of economic impacts which resulted from the drastic decrease in the population of peasants. This can be evidenced by the aforementioned change by lords from grain farming to sheep farming. Lastly, the Black Death had a number of political impacts which can be exemplified by the development of the aforementioned statute for labourers. Studies of the impacts of the bubonic plague are still ongoing. This is despite the fact that most of the impacts were realized immediately after the plague and their effects on the society analyzed. Political activists during the time, who w ere mostly lords, had observed the effects of the plague and made societal changes that were bound to benefit them. However, scientists still believe that the European society still suffers significant effects of the bubonic plague. For instance, it has been established that England, where the greatest effects of the bubonic plague were perhaps felt, has significantly lower genetic diversity than it is suspected to have had in the eleventh century. Geneticists explain this by the argument that the deaths that resulted from the Black Deaths were the cause of the low genetic variation in Europe. Reference List Bentley, Jerry H., Ziegler, Herbert F., Streets, Heather E. (2008) Traditions and Encounters: A Brief Global History, ch9,15,19, McGraw-Hill, Inc. Bridbury, A. (1973). The Black Death. The Economic History Review, 26: 577 – 592. Bryrne, J. (2011). Black Death. World Book Advanced. Web. Carol, B. (1996). Bubonic Plague in the nineteenth-century China. Robin, N. (2011). Apo calypse Then: A History of Plague. Special Report. World Book Advanced. Web. The Black Death And Its Effects. (1935). Readings in English History Drawn from the Original Sources: Intended to Illustrate a Short History of England. Boston: Ginn.

Function of the SAT - PrepScholar 2016 Students Encyclopedia

Function of the SAT - PrepScholar 2016 Students' Encyclopedia SAT / ACT Prep Online Guides and Tips Many 4-year U.S. colleges and universities require SAT or ACT scores fromtheir prospective students. Admissions officers, particularly those selecting for academic ability, consider the SAT as a measurement of academic ability and potential. The SAT is meant to be a reasoning test that evaluates students' problem-solving and analytical skills, rather than their specific content knowledge. Note: this article is a series in the PrepScholar2016 Students' Encyclopedia, a free students' and parents' SAT / ACT guide that provides encyclopedic knowledge. Read all the articles here! SAT scores are not the sole criterion for admission, nor are they the only measure of academic ability within a student's college application. Scores are considered in conjunction with high school grade point average (GPA), course selection, and other indicatorsof achievement. Many admissions officers emphasize that they take a holistic view of each applicant, considering the "whole person" as evidenced by his/her grades, extracurricular involvement, recommendations, and personal essay, among other demonstrated interests, accomplishments, and goals. While most colleges do not publicize specific SAT score minimums, many share data on the average scores of their accepted students. If this data shows a range of scores from the 25th to the 75th percentile, then the higher end of the range may be more representative of the school's SAT score expectations for the majority of regular applicants. The lower end of this kind of range may reflect the scores of special interest applicants who can gain admission with lower SAT scores, like students who are recruited for athletics. While many admissions officers claim they take a holistic approach, some will not review applications that do not contain a certain minimumSAT score. Conversely, high SAT scores are rarely a guarantee of admission, especially not at selective institutions like those in the Ivy League. Studentsthat entered Harvard's class of 2017, for example, had an average SAT score of 2237. Harvard's recruited athletes, on average, scored 173 points lower on the SAT than their non-recruited classmates. In addition to sharing data on average SAT scores of incoming students, most colleges share their policies on SAT scores. Some schools "superscore" the SAT, or take students' highest section scores across all testing dates and recombine them into a maximized composite score. Popular schools that have a policy of superscoring the SAT include Boston University, Columbia, Harvard, Johns Hopkins, MIT, Princeton, and the University of Connecticut. Other colleges look at a student's highest sitting on one date he/she took the SAT. Schools that consider students' "highest sitting" include Arizona State University, Colorado State University, Oregon State University, and University of Wisconsin. By researching their prospective colleges' stance on SAT scores, students may adjust their preparation and test-taking plans accordingly. An increasing number of colleges have adopted test flexible and test optional policies. These may allow students to send SAT Subject tests or AP tests in lieu of the general SATor to choose whether or not to send their SAT scores. NYU, for example,allows students to send three SAT Subject Tests or three AP tests in lieu of the SAT, among other options. While students may be able to decide whether their scores are an accurate representation of their academic ability when applying to test optional schools, those who omit their scores may be at an empirical disadvantage when compared with theirpeers who chose to include their scores. HampshireCollege is the only school thus far that has adopted a "test blind" policy, stating, "We will not consider SAT/ACT scores regardless of the score. Even if it's a perfect score, it will not weigh into our assessment of an applicant." While colleges take varied approaches to their consideration of SAT scores, College Board states that the SAT is meant to give national perspective to local data from schools on students' achievement and ability. As a standardized test, College Board maintains that the SAT measures academic ability independent from differences among students' educational experiences by school district, including variationsin curricula, school funding, and course rigor. Critics of the SAT drawon data that shows a correlation between higher SAT scores and higher levels of family income and parental education. Rather than testing students "on a level playing field," SAT critics claim that the SAT contributes to existing patterns of social and educational inequality. The changes made to the redesigned SAT, which will be administered starting in March of 2016, may have been partially motivated to address these criticismsand to make the SAT more accessible to students across income levels. The elimination of high level vocabulary words in favor of medium-range, multiple meaning words, for instance, may be one change aimed to make the test more fair and to improve its validity and predictive power. College Board also recently began a collaboration with Khan Academy to offer free videos, lessons, and sample questions for students to prepare for the new SAT. In addition to addressing the concerns of critics, College Board may have been motivated to update the SAT in order to remain competitive with its counterpart, the ACT. Historically, the majority of American students who lived on the East and West coasts took the SAT while students in Midwestern states took the ACT. In 20, the number of students who took the ACT nationwide surpassed the number that took the SAT for the first time. The redesigned SAT will more closely resemble the ACT in several ways, particularly in the format of its vocabulary questions and its newly optional essay. Read more from the SAT Encyclopedia! Further Reading Which Colleges Superscore the SAT? Colleges Requiring All SAT Scores Sent: Complete List How Can You Build the Most Versatile College Application?

B.F. Skinner and Operant Conditioning Research Paper

B.F. Skinner and Operant Conditioning - Research Paper Example Subjects opt for alternatives that result to low risks. Choice introduces self-control where the subject learns how to wait for better rewards instead of settling on immediate smaller rewards. A reinforcement schedule delivers reinforcement to an organism according to a predefined rule. Food is a common reinforcement used to condition hungry rats and pigeons. The schedule delivers the food for a switch closure as a result of a lever press or a peck. Similar experiments have been conducted on humans and the results are similar to those from animals. However, human beings have resulted into a wider range of adopted behavioral strategies compared to animals. A time-based schedule is the most effective where the reinforcement is delivered after a fixed or variable time period. A time marker or the reinforcement is utilized in time-based schedules. Trial-by-trial versions are also utilized during conditioning. For example, in the fixed interval schedule, an inter-trial interval precedes e ach trial and extra-empty trials where no food is given to the rats. In operant conditioning, the acquired behavior is reversible and can only be repeated when the reinforcement is available. ... This is evident in different results from subsequent results of the experimental history. This indicates that the animal has undergone some internal transformation, but the learned behavior is reversible. Several researchers have encountered problems when uncovering the reversible behavior and the nonreversible internal state of the animal. Skinner is concerned with the reversible behavior and not the internal state of the subject. This makes it difficult to draw a plausible conclusion on the cause of the reversible behavior when a second reinforcement is withdrawn after a short exposure. During conditioning, the organism is exposed to the reinforcement at timed intervals. Doubling the interval time doubles the wait time after a learning period. The organism develops an approximation to the interval to be timed. In some procedures, the organism can be exposed to a stimulus and different responses are expected after an absolute or relative duration. The subject can be exposed to two s timuli that confront it with two choices. For example, a rat can be given food after either a press on the left or right lever. After a learning period, the subject is presented with the two stimuli in lieu, which introduces the question of how it distributes the responses. The subject has to develop an intermediate duration in order to differentiate between the two stimuli. Other factors such as the degree of hunger can influence the response during a fixed interval procedure. A time discrimination procedure can mitigate this problem. The subject is exposed to food after a fixed time followed by a longer period of no food. This helps the subject learn to wait then respond until the behavior has been learnt properly. Interval timing is widely used by

Time Travel Essay Example | Topics and Well Written Essays - 2500 words

Time Travel - Essay Example And having thought what to do, we can only do it now: while the time for action is future we can only await it, and once it is past it is too late. When it comes to time travel, the perception of difference somewhat diminishes, according to various scientists theories presented in various ways we conclude that most of them agree with the notion that in order to travel back in time one has to travel faster than the speed of light. Only in such condition one can travel in time. Along with the speed of light, there are other three factors that are considered for a person in order to travel. Those factors or four elements on which time travel is based are considered at the very core of science fiction, which are: Foote has his own unique perception according to which traveling whether it be the future or the past is reasonable to justify and can be universally accepted by the judgment that a person is always involved in traveling all the time, every minute and at every second and particularly in his sleep because as we sleep our consciousness takes a several hour-long leap into the future. It is no wonder that this scenario has a respectable, if dateable, past in the literature of science and fiction. But nothing, nothing except dream and memory, stands in relation to travel to the past as sleep does to travel to the future. Travel to the past takes all customary notions of cause and effect, as Foote believes in the laws of thermodynamics. (Foote, 1991, p. 9) which suggests, "heat is a form of energy that is in motion". Let us examine this quotation what Foote has said. Heat is a form of energy and so is the man. A living energy in the form of meat and flesh. A man if moves in motion obviously generates and radiates energy and if a man travels faster than the speed of a light it is for sure that he would wake up in an environment which is quite old and ancient for him. Faster than light travel No doubt Foote has related human capabilities with those of the speed of light. Here is the theory presented by Foote based upon FTL travel first: it is true that the physicists of the tribe have devised a mathematical fiction called the tachyon, which, if it exists, must travel faster than light. Greatly simplified, the logic runs like this: in the universe we observe, we postulate the existence of tardyons, particles which must travel more slowly than light, and luminons, which always travel at precisely the speed of light. The more energy one puts behind a tardyon, the faster it travels and the heavier it gets; but as one approaches the speed of light, vast increases in energy are required to accomplish minuscule increases in speed. Only an infinite amount of energy which is not available to us in this universe will suffice to bring a tardyon to the speed of light". (Foote, 1991, p. 9) There is indeed an asymmetry in respect of past and future in the way in which we describe events when we are considering them as standing in causal relations to one another; Macbeath explains this as it reflects an objective asymmetry in nature and thinks that this asymmetry would reveal itself to us even if we were not agents but mere observers. It is indeed true, that our concept of cause is bound up with our concept of intentional action: if an

Atticus Finch Essay Example for Free

Atticus Finch Essay Atticus Finch Abraham Lincoln once said, â€Å"You cannot escape the responsibility of tomorrow by evading it today.† Atticus Finch, in many ways, lives this quote everyday by understanding what has to be done today in order to avoid future consequences of today’s mistakes. Atticus is a kind-hearted, slow-tempered, wise man, who always knows the right thing to say. In the story, one can deduce that Atticus Finch is a kind-hearted man who knows what to do in order to fix the toughest of problems. The author remarks, â€Å"There was a brown book and some yellow tablets on the solicitor’s table, Atticus’s was bare† (138). This statement explains how Atticus is always prepared to do what is right, and still be humane about what point he is trying to get across. Therefore, Atticus must also set the example for his children by showing that he has a kind heart, so maybe his two children would learn to follow; however, in the story he is faced with many obstacles on the way, reducing his time spent trying to do the right thing. Atticus definitely knows how to react under pressure. In the story the author writes, â€Å"Miss Stephanie said Atticus didn’t even bat an eye, just took out his handkerchief and wiped his face and stood there and let Mr. Ewell call him names wild horses could not bring her to repeat† (185). This is a perfect example of Atticus having a long fuse. Even though Mr. Ewell cussed him until the cows came home, Atticus took it calmly and was relieved that Mr. Ewell finally got his steam out from the case. Whenever he is in trouble, he reacts calmly because he knows in the end it will all blow over. Atticus is obviously a very wise man, who can get the job done. In the part of the story with Mrs. Dubose, Atticus states, â€Å"I wanted you to see what real courage is, instead of getting the idea that courage is a man with a gun in his hand. Its when you know youre licked before you begin, but you begin anyway and see it through no matter what† (93). Atticus uses many quotes like this in the book, all consisting of the wisest comments out of the whole story. In this quote Atticus is lecturing Jem after he is finished reading his book to Mrs. Dubose, and Jem realizes that Atticus was talking about him. He also said he would have made him do it eventually anyway, just to show him what real courage was, even if he would not have destroyed Mrs. Dubose’s flowers. The author indirectly says that Atticus knows what he is saying. As I have stated, Atticus is a kind-hearted, slow-tempered, and wise beyond his year’s sort of man. Atticus is the ideal human being in the story. He is also the stories main protagonist, showing all the characteristics of a gentleman.

American Democracy in the 21st Century: A Look into the Effects and Val

I. Introduction to Global Leadership â€Å"The one who has been entrusted with much, much more will be asked† (Luke 12:48). â€Å"It is now a clichà © that America is the world’s only superpower†¦[n]ever before, however, has America been so alone at the pinnacle of global leadership.† It is this belief, that the U.S. has assumed the role of â€Å"global leadership, which caused American foreign policy to shift from being more isolationistic in the mid 20th Century to becoming infamously characterized by imperialism. Unfortunately, the modern interpretation of American â€Å"leadership† has been â€Å"taken to an extreme, [where] global leadership implies U.S. interest in and responsibility for virtually everything, anywhere.† It is because America clings so tightly onto this role as the world’s â€Å"police† that its foreign policy has made it become involved in the affairs of other countries, even when matters of national security or others are not at stake. The price of â€Å"global leadership† costs the U.S in excess of a $600 billion â€Å"defense budget spent to support U.S. aspirations to lead the world, not to defend the United States.† As American involvement in other nations increases, so declines international support and the legitimacy of the U.S.’s policy involving itself in serious international affairs. Recently, the United States became involved in yet another conflict which has no direct affect upon its economy or security. As of March, 2011 the U.S. started yet another bombing campaign against a third Muslim nation, Libya, on the basis that its leader Prime Minister, and Colonel, Muammar el-Qaddafi was committing â€Å"human rights violations† by attacking his own citizens, who were notably attempting to oust him from his role as Libya’s president. The Unit... ... 2011. . Ryan, Julia L, and Kevin J Wu. "Profs React to U.S. Involvement in Libya." The Harvard Crimson. Harvard University, 29 Mar. 2011. Web. 3 Apr. 2011. history-military-granara-libya/>. WPO. "World Publics Reject US Role as the World Leader." World Public Opinion. N.p., 17 Apr. 2007. Web. 3 Apr. 2011. pipa/articles/views_on_countriesregions_bt/ 345.php?nid=&id=&pnt=345&lb=btvoc>. Zunes, Stephen. "History of US-Libya Relations Indicates US Must Tread Carefully as Uprising Continues." Truthout. N.p., 24 Feb. 2011. Web. 3 Apr. 2011. history-us-libya-relations-indicates-us-must-tread-carefully-uprising-continues68 033>. American Democracy in the 21st Century: A Look into the Effects and Val I. Introduction to Global Leadership â€Å"The one who has been entrusted with much, much more will be asked† (Luke 12:48). â€Å"It is now a clichà © that America is the world’s only superpower†¦[n]ever before, however, has America been so alone at the pinnacle of global leadership.† It is this belief, that the U.S. has assumed the role of â€Å"global leadership, which caused American foreign policy to shift from being more isolationistic in the mid 20th Century to becoming infamously characterized by imperialism. Unfortunately, the modern interpretation of American â€Å"leadership† has been â€Å"taken to an extreme, [where] global leadership implies U.S. interest in and responsibility for virtually everything, anywhere.† It is because America clings so tightly onto this role as the world’s â€Å"police† that its foreign policy has made it become involved in the affairs of other countries, even when matters of national security or others are not at stake. The price of â€Å"global leadership† costs the U.S in excess of a $600 billion â€Å"defense budget spent to support U.S. aspirations to lead the world, not to defend the United States.† As American involvement in other nations increases, so declines international support and the legitimacy of the U.S.’s policy involving itself in serious international affairs. Recently, the United States became involved in yet another conflict which has no direct affect upon its economy or security. As of March, 2011 the U.S. started yet another bombing campaign against a third Muslim nation, Libya, on the basis that its leader Prime Minister, and Colonel, Muammar el-Qaddafi was committing â€Å"human rights violations† by attacking his own citizens, who were notably attempting to oust him from his role as Libya’s president. The Unit... ... 2011. . Ryan, Julia L, and Kevin J Wu. "Profs React to U.S. Involvement in Libya." The Harvard Crimson. Harvard University, 29 Mar. 2011. Web. 3 Apr. 2011. history-military-granara-libya/>. WPO. "World Publics Reject US Role as the World Leader." World Public Opinion. N.p., 17 Apr. 2007. Web. 3 Apr. 2011. pipa/articles/views_on_countriesregions_bt/ 345.php?nid=&id=&pnt=345&lb=btvoc>. Zunes, Stephen. "History of US-Libya Relations Indicates US Must Tread Carefully as Uprising Continues." Truthout. N.p., 24 Feb. 2011. Web. 3 Apr. 2011. history-us-libya-relations-indicates-us-must-tread-carefully-uprising-continues68 033>.

Open Domain Event Extraction from Twitter

Open Domain Event Extraction from Twitter Alan Ritter University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Mausam University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Oren Etzioni University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Sam Clark? Decide, Inc. Seattle, WA sclark. [email  protected] com ABSTRACT Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that can extract, aggregate and categorize important events.Previous work on extracting structured representations of events has focused largely on newswire text; Twitter’s unique characteristics present new challenges and opportunities for open-domain event extraction. This paper describes TwiCal— the ? rst open-domain event-extraction and categorization system for Twitt er. We demonstrate that accurately extracting an open-domain calendar of signi? cant events from Twitter is indeed feasible. In addition, we present a novel approach for discovering important event categories and classifying extracted events based on latent variable models.By leveraging large volumes of unlabeled data, our approach achieves a 14% increase in maximum F1 over a supervised baseline. A continuously updating demonstration of our system can be viewed at http://statuscalendar. com; Our NLP tools are available at http://github. com/aritter/ twitter_nlp. Entity Steve Jobs iPhone GOP Amanda Knox Event Phrase died announcement debate verdict Date 10/6/11 10/4/11 9/7/11 10/3/11 Type Death ProductLaunch PoliticalEvent Trial Table 1: Examples of events extracted by TwiCal. vents. Yet the number of tweets posted daily has recently exceeded two-hundred million, many of which are either redundant [57], or of limited interest, leading to information overload. 1 Clearly, we can bene? t from more structured representations of events that are synthesized from individual tweets. Previous work in event extraction [21, 1, 54, 18, 43, 11, 7] has focused largely on news articles, as historically this genre of text has been the best source of information on current events. Read also Twitter Case StudyIn the meantime, social networking sites such as Facebook and Twitter have become an important complementary source of such information. While status messages contain a wealth of useful information, they are very disorganized motivating the need for automatic extraction, aggregation and categorization. Although there has been much interest in tracking trends or memes in social media [26, 29], little work has addressed the challenges arising from extracting structured representations of events from short or informal texts.Extracting useful structured representations of events from this disorganized corpus of noisy text is a challenging problem. On the other hand, individual tweets are short and self-contained and are therefore not composed of complex discourse structure as is the case for texts containing narratives. In this paper we demonstrate that open-domain event extraction from Twitter is indeed feasible, for example our highest-con? dence extracted f uture events are 90% accurate as demonstrated in  §8.Twitter has several characteristics which present unique challenges and opportunities for the task of open-domain event extraction. Challenges: Twitter users frequently mention mundane events in their daily lives (such as what they ate for lunch) which are only of interest to their immediate social network. In contrast, if an event is mentioned in newswire text, it 1 http://blog. twitter. com/2011/06/ 200-million-tweets-per-day. html Categories and Subject Descriptors I. 2. 7 [Natural Language Processing]: Language parsing and understanding; H. 2. [Database Management]: Database applications—data mining General Terms Algorithms, Experimentation 1. INTRODUCTION Social networking sites such as Facebook and Twitter present the most up-to-date information and buzz about current ? This work was conducted at the University of Washington Permission to make digital or hard copies of all or part of this work for personal or classr oom use is granted without fee provided that copies are not made or distributed for pro? t or commercial advantage and that copies bear this notice and the full citation on the ? rst page.To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speci? c permission and/or a fee. KDD’12, August 12–16, 2012, Beijing, China. Copyright 2012 ACM 978-1-4503-1462-6 /12/08 †¦ $10. 00. is safe to assume it is of general importance. Individual tweets are also very terse, often lacking su? cient context to categorize them into topics of interest (e. g. Sports, Politics, ProductRelease etc†¦ ). Further because Twitter users can talk about whatever they choose, it is unclear in advance which set of event types are appropriate.Finally, tweets are written in an informal style causing NLP tools designed for edited texts to perform extremely poorly. Opportunities: The short and self-contained nature of tweets means they have very simple d iscourse and pragmatic structure, issues which still challenge state-of-the-art NLP systems. For example in newswire, complex reasoning about relations between events (e. g. before and after ) is often required to accurately relate events to temporal expressions [32, 8]. The volume of Tweets is also much larger than the volume of news articles, so redundancy of information can be exploited more easily.To address Twitter’s noisy style, we follow recent work on NLP in noisy text [46, 31, 19], annotating a corpus of Tweets with events, which is then used as training data for sequence-labeling models to identify event mentions in millions of messages. Because of the terse, sometimes mundane, but highly redundant nature of tweets, we were motivated to focus on extracting an aggregate representation of events which provides additional context for tasks such as event categorization, and also ? lters out mundane events by exploiting redundancy of information.We propose identifying im portant events as those whose mentions are strongly associated with references to a unique date as opposed to dates which are evenly distributed across the calendar. Twitter users discuss a wide variety of topics, making it unclear in advance what set of event types are appropriate for categorization. To address the diversity of events discussed on Twitter, we introduce a novel approach to discovering important event types and categorizing aggregate events within a new domain. Supervised or semi-supervised approaches to event categorization would require ? st designing annotation guidelines (including selecting an appropriate set of types to annotate), then annotating a large corpus of events found in Twitter. This approach has several drawbacks, as it is apriori unclear what set of types should be annotated; a large amount of e? ort would be required to manually annotate a corpus of events while simultaneously re? ning annotation standards. We propose an approach to open-domain eve nt categorization based on latent variable models that uncovers an appropriate set of types which match the data.The automatically discovered types are subsequently inspected to ? lter out any which are incoherent and the rest are annotated with informative labels;2 examples of types discovered using our approach are listed in ? gure 3. The resulting set of types are then applied to categorize hundreds of millions of extracted events without the use of any manually annotated examples. By leveraging large quantities of unlabeled data, our approach results in a 14% improvement in F1 score over a supervised baseline which uses the same set of types. Stanford NER T-seg P 0. 62 0. 73 R 0. 5 0. 61 F1 0. 44 0. 67 F1 inc. 52% Table 2: By training on in-domain data, we obtain a 52% improvement in F1 score over the Stanford Named Entity Recognizer at segmenting entities in Tweets [46]. 2. SYSTEM OVERVIEW TwiCal extracts a 4-tuple representation of events which includes a named entity, event p hrase, calendar date, and event type (see Table 1). This representation was chosen to closely match the way important events are typically mentioned in Twitter. An overview of the various components of our system for extracting events from Twitter is presented in Figure 1.Given a raw stream of tweets, our system extracts named entities in association with event phrases and unambiguous dates which are involved in signi? cant events. First the tweets are POS tagged, then named entities and event phrases are extracted, temporal expressions resolved, and the extracted events are categorized into types. Finally we measure the strength of association between each named entity and date based on the number of tweets they co-occur in, in order to determine whether an event is signi? cant.NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. news articles) perform very poorly when applied to Twitter text due to its noisy and u nique style. To address these issues, we utilize a named entity tagger and part of speech tagger trained on in-domain Twitter data presented in previous work [46]. We also develop an event tagger trained on in-domain annotated data as described in  §4. 3. NAMED ENTITY SEGMENTATION NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. ews articles) perform very poorly when applied to Twitter text due to its noisy and unique style. For instance, capitalization is a key feature for named entity extraction within news, but this feature is highly unreliable in tweets; words are often capitalized simply for emphasis, and named entities are often left all lowercase. In addition, tweets contain a higher proportion of out-ofvocabulary words, due to Twitter’s 140 character limit and the creative spelling of its users. To address these issues, we utilize a named entity tagger trained on in-domain Twitter data presented in previous work [46]. Training on tweets vastly improves performance at segmenting Named Entities. For example, performance compared against the state-of-the-art news-trained Stanford Named Entity Recognizer [17] is presented in Table 2. Our system obtains a 52% increase in F1 score over the Stanford Tagger at segmenting named entities. 4. EXTRACTING EVENT MENTIONS This annotation and ? ltering takes minimal e? ort. One of the authors spent roughly 30 minutes inspecting and annotating the automatically discovered event types. 2 In order to extract event mentions from Twitter’s noisy text, we ? st annotate a corpus of tweets, which is then 3 Available at http://github. com/aritter/twitter_nlp. Temporal Resolution S M T W T F S Tweets POS Tag NER Signi? cance Ranking Calendar Entries Event Tagger Event Classi? cation Figure 1: Processing pipeline for extracting events from Twitter. New components developed as part of this work are shaded in grey. used to train sequence models to extract events. While we apply an established approach to sequence-labeling tasks in noisy text [46, 31, 19], this is the ? rst work to extract eventreferring phrases in Twitter.Event phrases can consist of many di? erent parts of speech as illustrated in the following examples: †¢ Verbs: Apple to Announce iPhone 5 on October 4th?! YES! †¢ Nouns: iPhone 5 announcement coming Oct 4th †¢ Adjectives: WOOOHOO NEW IPHONE TODAY! CAN’T WAIT! These phrases provide important context, for example extracting the entity, Steve Jobs and the event phrase died in connection with October 5th, is much more informative than simply extracting Steve Jobs. In addition, event mentions are helpful in upstream tasks such as categorizing events into types, as described in  §6.In order to build a tagger for recognizing events, we annotated 1,000 tweets (19,484 tokens) with event phrases, following annotation guidelines similar to those developed for the Event tags in Timebank [43] . We treat the problem of recognizing event triggers as a sequence labeling task, using Conditional Random Fields for learning and inference [24]. Linear Chain CRFs model dependencies between the predicted labels of adjacent words, which is bene? cial for extracting multi-word event phrases.We use contextual, dictionary, and orthographic features, and also include features based on our Twitter-tuned POS tagger [46], and dictionaries of event terms gathered from WordNet by Sauri et al. [50]. The precision and recall at segmenting event phrases are reported in Table 3. Our classi? er, TwiCal-Event, obtains an F-score of 0. 64. To demonstrate the need for in-domain training data, we compare against a baseline of training our system on the Timebank corpus. precision 0. 56 0. 48 0. 24 recall 0. 74 0. 70 0. 11 F1 0. 64 0. 57 0. 15 TwiCal-Event No POS TimebankTable 3: Precision and recall at event phrase extraction. All results are reported using 4-fold cross validation over the 1,000 manu ally annotated tweets (about 19K tokens). We compare against a system which doesn’t make use of features generated based on our Twitter trained POS Tagger, in addition to a system trained on the Timebank corpus which uses the same set of features. as input a reference date, some text, and parts of speech (from our Twitter-trained POS tagger) and marks temporal expressions with unambiguous calendar references. Although this mostly rule-based system was designed for use on newswire text, we ? d its precision on Tweets (94% estimated over as sample of 268 extractions) is su? ciently high to be useful for our purposes. TempEx’s high precision on Tweets can be explained by the fact that some temporal expressions are relatively unambiguous. Although there appears to be room for improving the recall of temporal extraction on Twitter by handling noisy temporal expressions (for example see Ritter et. al. [46] for a list of over 50 spelling variations on the word â€Å"tomorrow †), we leave adapting temporal extraction to Twitter as potential future work. . CLASSIFICATION OF EVENT TYPES To categorize the extracted events into types we propose an approach based on latent variable models which infers an appropriate set of event types to match our data, and also classi? es events into types by leveraging large amounts of unlabeled data. Supervised or semi-supervised classi? cation of event categories is problematic for a number of reasons. First, it is a priori unclear which categories are appropriate for Twitter. Secondly, a large amount of manual e? ort is required to annotate tweets with event types.Third, the set of important categories (and entities) is likely to shift over time, or within a focused user demographic. Finally many important categories are relatively infrequent, so even a large annotated dataset may contain just a few examples of these categories, making classi? cation di? cult. For these reasons we were motivated to investigate un- 5. EXTRACTING AND RESOLVING TEMPORAL EXPRESSIONS In addition to extracting events and related named entities, we also need to extract when they occur. In general there are many di? rent ways users can refer to the same calendar date, for example â€Å"next Friday†, â€Å"August 12th†, â€Å"tomorrow† or â€Å"yesterday† could all refer to the same day, depending on when the tweet was written. To resolve temporal expressions we make use of TempEx [33], which takes Sports Party TV Politics Celebrity Music Movie Food Concert Performance Fitness Interview ProductRelease Meeting Fashion Finance School AlbumRelease Religion 7. 45% 3. 66% 3. 04% 2. 92% 2. 38% 1. 96% 1. 92% 1. 87% 1. 53% 1. 42% 1. 11% 1. 01% 0. 95% 0. 88% 0. 87% 0. 85% 0. 85% 0. 78% 0. 71% Con? ct Prize Legal Death Sale VideoGameRelease Graduation Racing Fundraiser/Drive Exhibit Celebration Books Film Opening/Closing Wedding Holiday Medical Wrestling OTHER 0. 69% 0. 68% 0. 67% 0. 66% 0. 66% 0. 65 % 0. 63% 0. 61% 0. 60% 0. 60% 0. 60% 0. 58% 0. 50% 0. 49% 0. 46% 0. 45% 0. 42% 0. 41% 53. 45% Label Sports Concert Perform TV Movie Sports Politics Figure 2: Complete list of automatically discovered event types with percentage of data covered. Interpretable types representing signi? cant events cover roughly half of the data. supervised approaches that will automatically induce event types which match the data.We adopt an approach based on latent variable models inspired by recent work on modeling selectional preferences [47, 39, 22, 52, 48], and unsupervised information extraction [4, 55, 7]. Each event indicator phrase in our data, e, is modeled as a mixture of types. For example the event phrase â€Å"cheered† might appear as part of either a PoliticalEvent, or a SportsEvent. Each type corresponds to a distribution over named entities n involved in speci? c instances of the type, in addition to a distribution over dates d on which events of the type occur. Including calen dar dates in our model has the e? ct of encouraging (though not requiring) events which occur on the same date to be assigned the same type. This is helpful in guiding inference, because distinct references to the same event should also have the same type. The generative story for our data is based on LinkLDA [15], and is presented as Algorithm 1. This approach has the advantage that information about an event phrase’s type distribution is shared across it’s mentions, while ambiguity is also naturally preserved. In addition, because the approach is based on generative a probabilistic model, it is straightforward to perform many di? rent probabilistic queries about the data. This is useful for example when categorizing aggregate events. For inference we use collapsed Gibbs Sampling [20] where each hidden variable, zi , is sampled in turn, and parameters are integrated out. Example types are displayed in Figure 3. To estimate the distribution over types for a given event , a sample of the corresponding hidden variables is taken from the Gibbs markov chain after su? cient burn in. Prediction for new data is performed using a streaming approach to inference [56]. TV Product MeetingTop 5 Event Phrases tailgate – scrimmage tailgating – homecoming – regular season concert – presale – performs – concerts – tickets matinee – musical priscilla – seeing wicked new season – season ? nale – ? nished season episodes – new episode watch love – dialogue theme – inception – hall pass – movie inning – innings pitched – homered homer presidential debate osama – presidential candidate – republican debate – debate performance network news broadcast – airing – primetime drama – channel stream unveils – unveiled – announces – launches wraps o? shows trading – hall mtg – zoning – brie? g stocks – tumbled – trading report – opened higher – tumbles maths – english test exam – revise – physics in stores – album out debut album – drops on – hits stores voted o? – idol – scotty – idol season – dividendpaying sermon – preaching preached – worship preach declared war – war shelling – opened ? re wounded senate – legislation – repeal – budget – election winners – lotto results enter – winner – contest bail plea – murder trial – sentenced – plea – convicted ? lm festival – screening starring – ? lm – gosling live forever – passed away – sad news – condolences – burried add into – 50% o? up shipping – save up donate – tornado relief disaster relief – donated – raise mone y Top 5 Entities espn – ncaa – tigers – eagles – varsity taylor swift – toronto britney spears – rihanna – rock shrek – les mis – lee evans – wicked – broadway jersey shore – true blood – glee – dvr – hbo net? ix – black swan – insidious – tron – scott pilgrim mlb – red sox – yankees – twins – dl obama president obama – gop – cnn america nbc – espn – abc – fox mtv apple – google – microsoft – uk – sony town hall – city hall club – commerce – white house reuters – new york – u. . – china – euro english – maths – german – bio – twitter itunes – ep – uk – amazon – cd lady gaga – american idol – america – beyonce – glee church – jesus – pastor faith – god libya – afghanistan #syria – syria – nato senate – house – congress – obama – gop ipad – award – facebook – good luck – winners casey anthony – court – india – new delhi supreme court hollywood – nyc – la – los angeles – new york michael jackson afghanistan john lennon – young – peace groupon – early bird facebook – @etsy – etsy japan – red cross – joplin – june – africaFinance School Album TV Religion Con? ict Politics Prize Legal Movie Death Sale Drive 6. 1 Evaluation To evaluate the ability of our model to classify signi? cant events, we gathered 65 million extracted events of the form Figure 3: Example event types discovered by our model. For each type t, we list the top 5 entities which have highest probability given t, and the 5 event phrases which as sign highest probability to t. Algorithm 1 Generative story for our data involving event types as hidden variables.Bayesian Inference techniques are applied to invert the generative process and infer an appropriate set of types to describe the observed events. for each event type t = 1 . . . T do n Generate ? t according to symmetric Dirichlet distribution Dir(? n ). d Generate ? t according to symmetric Dirichlet distribution Dir(? d ). end for for each unique event phrase e = 1 . . . |E| do Generate ? e according to Dirichlet distribution Dir(? ). for each entity which co-occurs with e, i = 1 . . . Ne do n Generate ze,i from Multinomial(? e ). Generate the entity ne,i from Multinomial(? n ). e,i TwiCal-Classify Supervised Baseline Precision 0. 85 0. 61 Recall 0. 55 0. 57 F1 0. 67 0. 59 Table 4: Precision and recall of event type categorization at the point of maximum F1 score. d,i end for end for 0. 6 end for for each date which co-occurs with e, i = 1 . . . Nd do d Generate ze,i from Multinomial(? e ). Generate the date de,i from Multinomial(? zn ). Precision 0. 8 1. 0 listed in Figure 1 (not including the type). We then ran Gibbs Sampling with 100 types for 1,000 iterations of burnin, keeping the hidden variable assignments found in the last sample. One of the authors manually inspected the resulting types and assigned them labels such as Sports, Politics, MusicRelease and so on, based on their distribution over entities, and the event words which assign highest probability to that type. Out of the 100 types, we found 52 to correspond to coherent event types which referred to signi? cant events;5 the other types were either incoherent, or covered types of events which are not of general interest, for example there was a cluster of phrases such as applied, call, contact, job interview, etc†¦ hich correspond to users discussing events related to searching for a job. Such event types which do not correspond to signi? cant events of general interest were simply marked as OTHER. A complete list of labels used to annotate the automatically discovered event types along with the coverage of each type is listed in ? gure 2. Note that this assignment of labels to types only needs to be done once and produces a labeling for an arbitrarily large number of event instances. Additionally the same set of types can easily be used to lassify new event instances using streaming inference techniques [56]. One interesting direction for future work is automatic labeling and coherence evaluation of automatically discovered event types analogous to recent work on topic models [38, 25]. In order to evaluate the ability of our model to classify aggregate events, we grouped together all (entity,date) pairs which occur 20 or more times the data, then annotated the 500 with highest association (see  §7) using the event types discovered by our model. To help demonstrate the bene? s of leveraging large quantities of unlabeled data for event classi? cation, we compare against a supervised Maximum Entropy baseline which makes use of the 500 annotated events using 10-fold cross validation. For features, we treat the set of event phrases To scale up to larger datasets, we performed inference in parallel on 40 cores using an approximation to the Gibbs Sampling procedure analogous to that presented by Newmann et. al. [37]. 5 After labeling some types were combined resulting in 37 distinct labels. 4 0. 4 Supervised Baseline TwiCal? Classify 0. 0 0. 2 0. 4 Recall 0. 0. 8 Figure 4: types. Precision and recall predicting event that co-occur with each (entity, date) pair as a bag-of-words, and also include the associated entity. Because many event categories are infrequent, there are often few or no training examples for a category, leading to low performance. Figure 4 compares the performance of our unsupervised approach to the supervised baseline, via a precision-recall curve obtained by varying the threshold on the probability of the most lik ely type. In addition table 4 compares precision and recall at the point of maximum F-score.Our unsupervised approach to event categorization achieves a 14% increase in maximum F1 score over the supervised baseline. Figure 5 plots the maximum F1 score as the amount of training data used by the baseline is varied. It seems likely that with more data, performance will reach that of our approach which does not make use of any annotated events, however our approach both automatically discovers an appropriate set of event types and provides an initial classi? er with minimal e? ort, making it useful as a ? rst step in situations where annotated data is not immediately available. . RANKING EVENTS Simply using frequency to determine which events are signi? cant is insu? cient, because many tweets refer to common events in user’s daily lives. As an example, users often mention what they are eating for lunch, therefore entities such as McDonalds occur relatively frequently in associat ion with references to most calendar days. Important events can be distinguished as those which have strong association with a unique date as opposed to being spread evenly across days on the calendar. To extract signi? ant events of general interest from Twitter, we thus need some way to measure the strength of association between an entity and a date. In order to measure the association strength between an 0. 8 0. 2 Supervised Baseline TwiCal? Classify 100 200 300 400 tweets. We then added the extracted triples to the dataset used for inferring event types described in  §6, and performed 50 iterations of Gibbs sampling for predicting event types on the new data, holding the hidden variables in the original data constant. This streaming approach to inference is similar to that presented by Yao et al. 56]. We then ranked the extracted events as described in  §7, and randomly sampled 50 events from the top ranked 100, 500, and 1,000. We annotated the events with 4 separate criter ia: 1. Is there a signi? cant event involving the extracted entity which will take place on the extracted date? 2. Is the most frequently extracted event phrase informative? 3. Is the event’s type correctly classi? ed? 4. Are each of (1-3) correct? That is, does the event contain a correct entity, date, event phrase, and type? Note that if (1) is marked as incorrect for a speci? event, subsequent criteria are always marked incorrect. Max F1 0. 4 0. 6 # Training Examples Figure 5: Maximum F1 score of the supervised baseline as the amount of training data is varied. entity and a speci? c date, we utilize the G log likelihood ratio statistic. G2 has been argued to be more appropriate for text analysis tasks than ? 2 [12]. Although Fisher’s Exact test would produce more accurate p-values [34], given the amount of data with which we are working (sample size greater than 1011 ), it proves di? cult to compute Fisher’s Exact Test Statistic, which results in ? ating poin t over? ow even when using 64-bit operations. The G2 test works su? ciently well in our setting, however, as computing association between entities and dates produces less sparse contingency tables than when working with pairs of entities (or words). The G2 test is based on the likelihood ratio between a model in which the entity is conditioned on the date, and a model of independence between entities and date references. For a given entity e and date d this statistic can be computed as follows: G2 = x? {e, ¬e},y? {d, ¬d} 2 8. 2 BaselineTo demonstrate the importance of natural language processing and information extraction techniques in extracting informative events, we compare against a simple baseline which does not make use of the Ritter et. al. named entity recognizer or our event recognizer; instead, it considers all 1-4 grams in each tweet as candidate calendar entries, relying on the G2 test to ? lter out phrases which have low association with each date. 8. 3 Results The results of the evaluation are displayed in table 5. The table shows the precision of the systems at di? rent yield levels (number of aggregate events). These are obtained by varying the thresholds in the G2 statistic. Note that the baseline is only comparable to the third column, i. e. , the precision of (entity, date) pairs, since the baseline is not performing event identi? cation and classi? cation. Although in some cases ngrams do correspond to informative calendar entries, the precision of the ngram baseline is extremely low compared with our system. In many cases the ngrams don’t correspond to salient entities related to events; they often consist of single words which are di? ult to interpret, for example â€Å"Breaking† which is part of the movie â€Å"Twilight: Breaking Dawn† released on November 18. Although the word â€Å"Breaking† has a strong association with November 18, by itself it is not very informative to present to a user. 7 Our high- con? dence calendar entries are surprisingly high quality. If we limit the data to the 100 highest ranked calendar entries over a two-week date range in the future, the precision of extracted (entity, date) pairs is quite good (90%) – an 80% increase over the ngram baseline.As expected precision drops as more calendar entries are displayed, but 7 In addition, we notice that the ngram baseline tends to produce many near-duplicate calendar entries, for example: â€Å"Twilight Breaking†, â€Å"Breaking Dawn†, and â€Å"Twilight Breaking Dawn†. While each of these entries was annotated as correct, it would be problematic to show this many entries describing the same event to a user. Ox,y ? ln Ox,y Ex,y Where Oe,d is the observed fraction of tweets containing both e and d, Oe, ¬d is the observed fraction of tweets containing e, but not d, and so on.Similarly Ee,d is the expected fraction of tweets containing both e and d assuming a model of independence. 8. EXPERIMENTS To estimate the quality of the calendar entries generated using our approach we manually evaluated a sample of the top 100, 500 and 1,000 calendar entries occurring within a 2-week future window of November 3rd. 8. 1 Data For evaluation purposes, we gathered roughly the 100 million most recent tweets on November 3rd 2011 (collected using the Twitter Streaming API6 , and tracking a broad set of temporal keywords, including â€Å"today†, â€Å"tomorrow†, names of weekdays, months, etc. ).We extracted named entities in addition to event phrases, and temporal expressions from the text of each of the 100M 6 https://dev. twitter. com/docs/streaming-api Mon Nov 7 Justin meet Other Motorola Pro+ kick Product Release Nook Color 2 launch Product Release Eid-ul-Azha celebrated Performance MW3 midnight release Other Tue Nov 8 Paris love Other iPhone holding Product Release Election Day vote Political Event Blue Slide Park listening Music Release Hedley album Music Rele ase Wed Nov 9 EAS test Other The Feds cut o? Other Toca Rivera promoted Performance Alert System test Other Max Day give OtherNovember 2011 Thu Nov 10 Fri Nov 11 Robert Pattinson iPhone show debut Performance Product Release James Murdoch Remembrance Day give evidence open Other Performance RTL-TVI France post play TV Event Other Gotti Live Veterans Day work closed Other Other Bambi Awards Skyrim perform arrives Performance Product Release Sat Nov 12 Sydney perform Other Pullman Ballroom promoted Other Fox ? ght Other Plaza party Party Red Carpet invited Party Sun Nov 13 Playstation answers Product Release Samsung Galaxy Tab launch Product Release Sony answers Product Release Chibi Chibi Burger other Jiexpo Kemayoran promoted TV EventFigure 6: Example future calendar entries extracted by our system for the week of November 7th. Data was collected up to November 5th. For each day, we list the top 5 events including the entity, event phrase, and event type. While there are several err ors, the majority of calendar entries are informative, for example: the Muslim holiday eid-ul-azha, the release of several videogames: Modern Warfare 3 (MW3) and Skyrim, in addition to the release of the new playstation 3D display on Nov 13th, and the new iPhone 4S in Hong Kong on Nov 11th. # calendar entries 100 500 1,000 ngram baseline 0. 50 0. 6 0. 44 entity + date 0. 90 0. 66 0. 52 precision event phrase event 0. 86 0. 56 0. 42 type 0. 72 0. 54 0. 40 entity + date + event + type 0. 70 0. 42 0. 32 Table 5: Evaluation of precision at di? erent recall levels (generated by varying the threshold of the G2 statistic). We evaluate the top 100, 500 and 1,000 (entity, date) pairs. In addition we evaluate the precision of the most frequently extracted event phrase, and the predicted event type in association with these calendar entries. Also listed is the fraction of cases where all predictions (â€Å"entity + date + event + type†) are correct.We also compare against the precision of a simple ngram baseline which does not make use of our NLP tools. Note that the ngram baseline is only comparable to the entity+date precision (column 3) since it does not include event phrases or types. remains high enough to display to users (in a ranked list). In addition to being less likely to come from extraction errors, highly ranked entity/date pairs are more likely to relate to popular or important events, and are therefore of greater interest to users. In addition we present a sample of extracted future events on a calendar in ? ure 6 in order to give an example of how they might be presented to a user. We present the top 5 entities associated with each date, in addition to the most frequently extracted event phrase, and highest probability event type. 9. RELATED WORK While we are the ? rst to study open domain event extraction within Twitter, there are two key related strands of research: extracting speci? c types of events from Twitter, and extracting open-domain even ts from news [43]. Recently there has been much interest in information extraction and event identi? cation within Twitter. Benson et al. 5] use distant supervision to train a relation extractor which identi? es artists and venues mentioned within tweets of users who list their location as New York City. Sakaki et al. [49] train a classi? er to recognize tweets reporting earthquakes in Japan; they demonstrate their system is capable of recognizing almost all earthquakes reported by the Japan Meteorological Agency. Additionally there is recent work on detecting events or tracking topics [29] in Twitter which does not extract structured representations, but has the advantage that it is not limited to a narrow domain. Petrovi? t al. investigate a streaming approach to identic fying Tweets which are the ? rst to report a breaking news story using Locally Sensitive Hash Functions [40]. Becker et al. [3], Popescu et al. [42, 41] and Lin et al. [28] investigate discovering clusters of rela ted words or tweets which correspond to events in progress. In contrast to previous work on Twitter event identi? cation, our approach is independent of event type or domain and is thus more widely applicable. Additionally, our work focuses on extracting a calendar of events (including those occurring in the future), extract- . 4 Error Analysis We found 2 main causes for why entity/date pairs were uninformative for display on a calendar, which occur in roughly equal proportion: Segmentation Errors Some extracted â€Å"entities† or ngrams don’t correspond to named entities or are generally uninformative because they are mis-segmented. Examples include â€Å"RSVP†, â€Å"Breaking† and â€Å"Yikes†. Weak Association between Entity and Date In some cases, entities are properly segmented, but are uninformative because they are not strongly associated with a speci? c event on the associated date, or are involved in many di? rent events which happen to oc cur on that day. Examples include locations such as â€Å"New York†, and frequently mentioned entities, such as â€Å"Twitter†. ing event-referring expressions and categorizing events into types. Also relevant is work on identifying events [23, 10, 6], and extracting timelines [30] from news articles. 8 Twitter status messages present both unique challenges and opportunities when compared with news articles. Twitter’s noisy text presents serious challenges for NLP tools. On the other hand, it contains a higher proportion of references to present and future dates.Tweets do not require complex reasoning about relations between events in order to place them on a timeline as is typically necessary in long texts containing narratives [51]. Additionally, unlike News, Tweets often discus mundane events which are not of general interest, so it is crucial to exploit redundancy of information to assess whether an event is signi? cant. Previous work on open-domain informat ion extraction [2, 53, 16] has mostly focused on extracting relations (as opposed to events) from web corpora and has also extracted relations based on verbs.In contrast, this work extracts events, using tools adapted to Twitter’s noisy text, and extracts event phrases which are often adjectives or nouns, for example: Super Bowl Party on Feb 5th. Finally we note that there has recently been increasing interest in applying NLP techniques to short informal messages such as those found on Twitter. 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Impact of WTO membership on China’s Agriculture Sector Essay

Although fruitful for sectors like finance and banking, China’s WTO member has not proved to be that much lucrative for the agriculture sector of China since it provides both opportunities and threats for the country’s economy. At one hand, China’s decreasing tariffs of agricultural exports attracted global market thereby causing a considerable boom in the year 2004 in which China’s agricultural exports raised to $17. 3 billion. At the other hand, as a result of free trade China faces a major threat in terms of the competition for domestic grains like corn and soybeans with the imported grains of better quality thereby snatching the livelihood of many farmers and people related to the agriculture sector. For the very reason, China has not opened its market of agricultural products as much as it has for the manufactured goods. Another reason behind a non restricted import of agricultural goods is that such a step on China’s behalf would have led to a trade deficit. Keeping in mind China’s growing population, China’s import would have superseded its export in case of non-protectionism. Also, China faces a risk of suffering losses because such products are easily infected and such a scenario can not only leave a scar for China’s growing international repute but can also cause a major set back to the Chinese exporters. Impact of China’s membership of WTO on China’s Manufacturing Industry: The manufacturing industry of China represents one of the major successes pertaining to the membership of WTO. Because of the cheaper prices of China made goods in the international market, the demand of these products is ever increasing. In case of manufacturing of automobiles, China has been excelling since 1975 but the major boom after its membership of WTO indicating a production percentage increase of 41. 3 percent in a single year when its production number raised to 3. 25 million in the year 2002. Today, the China’s automobile industry stands among the world’s top automobile giants. In the case of China’s Telecommunication Industry with China having entered 2nd generation of mobile communications equipment, china has launched its replica mobile phone. Unusually similar in appearance to the high quality branded cell phones, china made replica mobile phones are cheaper enough to satisfy a number of customers across the globe. Impact of WTO membership on China’s International repute: Having discussed the impact of WTO membership on China’s economy, what remains worth mentioning is a series of changes for the other sectors of the country. The impact of globalization is not just confined to the financial gains but has also left a strong image of China thereby hushing away the chances of any other world war in future. For the pro-globalists, globalization has opened new horizons for China to reach out to the world. This has resulted in an ascendance of China’s products across the world. The proliferation of China made good across the world are so wide that it has left U. S. with a ‘China Street’ in the New York City and Pakistan with a ‘China Market’ in the country’s capital. Both these markets are peculiarly meant for the selling of China made goods that are much cheaper as compared to those made by other countries. It is the result of internationalization that China has permeated into every corner of the global community by attracting the customers with its cheaper prices. But the other side of the coin suggest contrary to the positive side WTO membership on China’s international repute. The exemption of trade barriers encourages the flow of infections and diseases through products from one place to another. SARS stands as one such example that had left many people at the verge of death. It was in first few months of the year 2003 that marked the outbreak of SARS. â€Å"Originating in southern China in late 2002 (or earlier by some accounts), the epidemic quickly infected more than 8,000 people in 30-plus countries, causing nearly 800 deaths within six months. By the time the disease was finally brought under control, Beijing’s initial mishandling of the crisis, as well as the SARS scourge itself, had taken a serious toll on China’s economy and its international reputation. † Impact of WTO membership on China’s Legal System: Gregory C. Chow in his article ‘The impact of joining WTO on China’s economic, legal and political institutions’ suggests that the WTO membership of China has not only resulted in economic boom but has also brought an amelioration in the legal system of the country. He lays his assumption on the fact that by WTO membership China is dealing with a number of international firms. The exposure of foreign laws would positively affect China to pave its way to legal modernization. Also, it is in the aggrandizing phase of globalization that China has enacted many commercial laws that involve the laws pertaining to bankruptcy and corporate behaviour. It is a direct result of this fact that the number of Chinese legal personnel continue to increase. With WTO membership, this move towards globalization is further facilitated thereby suggesting a further amelioration of China’s legal system. Impact of China’s membership of WTO on other nations: Of all the corollaries of China’s entrance into the World Trade Organization, the global competition supersedes providing both the optimistic and pessimistic implications for the world. At one hand the increasing competitive has triggered a wave of fear for many smaller economies by dragging them at the verge of economic fiasco. At the other hand, the same competitiveness has fostered the production of high quality products and innovative technologies employed by the competitors. China’s accession to WTO demanded a decline in China’s tariffs on goods. These tariff barriers were employed by China as a technique of economic protectionism in order to flourish the domestic industry that might have faced overwhelming competition by the entrance of foreign goods with low tariffs. Making it crystal clear, the WTO membership not only opened new opportunities for China to globalize its export but with the ascendance of export the integration also caused the increase of import by China being forced to lower the tariffs on imported goods. According to the findings of Dorothy Guerrero in ‘China, the WTO and Globalization: looking beyond growth figures’ China had to lower down its overall tariffs on agricultural goods from 54 percent in 2001 to 15. 3 percent in 2005. However the net results favoured China in a sense that even in the absence of high tariffs, some invisible barriers for the products of foreign countries were still implemented by China. These non tariff barriers indirectly dissuade the participants of international trade market from progressively entering China’s domestic market. These non tariff barriers involve issues pertaining to stringent security check, product certification, labelling standards, delay in customs clearance and import approval. The stringency of these national non tariff barriers significantly differ from the international standards and often keep varying from time to time. As a result of rejection based on these national standards, foreign manufacturers suffered a great loss especially in terms of agricultural products. This rejection has lessened their share of goods exported to China. Apparently being insulated from the economic progress and WTO membership of China, Chinese Politics also experiences changes in terms of the preference of communists or democrats. Just like WTO demands free trade and rights of all the nations, the Chinese citizens of future can be predicted to unanimously demand democracy for the rights of every citizen.