Martin Luther King Jr.

Martin Luther King Jr. Martin Luther King Jr. Martin Luther King Jr. Martin Luther King was born on January 15, 1929, in Atlanta, Georgia. When he was grown, he wrote that he came from a family â€Å"where love was central and where lovely relationships were ever present† (Colaiaco, 1984). He could never remember his parents fighting, and he was surrounded by people with deep religious beliefs and a profound sense of human dignity. His father was pastor of Ebenezer Baptist Church and his mother had been a teacher. Her father had been pastor of Ebenezer before his death. Martin had an older sister; Christine, and a younger brother, A.D. Martin grew up during the Depression, a time when many were without jobs and had to struggle to make a living. His family wasn't wealthy, but they were comfortable and had enough to eat.Discussion and BackgroundHans Luther sent his son to the University of Effort to maintain the dream of him becoming a lawyer. By 1505, Luther had completed the Bachelor s program and received his Master s degree. He was on his way to becoming the lawyer that his father had always dreamed of, until June 1505. On his way back to the University after visiting his family, Martin was caught in a thunderstorm and a flash of lightning hit him. In the open field where he laid, he promised God he would join a religious order. (Leonard, 2002) When Martin s friends heard of his promise, they were shocked. His father was angered that he had spent a large amount of money to send his son to school, and his son was not going to be able to support the family.For the rest of his brief life, he inspired people to fight for their rights using nonviolent means (Lincoln, 2001). King paid a great price for his vision. From 1956 until his death in 1968, he was arrested, stabbed, stoned, and finally assassinated. And although he loved his family, he was often away from home, traveling tirelessly, from town to town, state to state, and even to Europe, Africa, and Asia to share his dream of peace and love.ConclusionIn 1964, Martin Lu ther King, Jr., won the Nobel Peace Prize. This important award is given almost every year to the person, people, or organization most responsible for promoting peace. King, at age thirty – five, was the youngest person ever to receive the prize. In December, he set off with family and friends to Oslo, Norway, where the award ceremony look place. On his return, King was shower with honors. The city of Atlanta, where he lived, gave him a dinner. Together blacks and whites sang the civil rights movement's anthem, â€Å"We Shall Overcome† (Lincoln, 2001). Only a few years before, King had been arrested in Atlanta for trying to eat al an all-white lunch counter. ReferencesColaiaco, James A. (1984).†The American Dream Unfulfilled: Martin Luther King, Jr., and the ‘Letter from the Birmingham Jail'.† Phylon.Leonard, Cowries, W. (2002) Martin Luther Jr. Leader of the Reformation. New York: Fredrick A. Pager.Lincoln, C. Eric, (2001). Martin Luther King, Jr.: A Profile. American Century Series. New York: Hill and Wang. P 156-159

Motifs and Characterization in Macbeth Essay

The Tragedy of Macbeth, written by William Shakespeare, uses various literary elements; among the strongest are motifs and characterizations used to express and symbolize important changes and events throughout the play. Macbeth is a brave and ambitious man full of self-doubt who is driven by evil forces into bad situations. The motif of light and darkness symbolizes the conflict between good and evil. A motif is a significant word, phrase, image, description, idea, or other element repeated throughout a literary work and related to the theme. Manhood is a motif used throughout the play to symbolize the manly and weak sides of people and what qualities people expect a man to have. Blood comes to symbolize guilt and violence. The clothes as titles motif symbolizes the title a person holds in the Kingdom. Characterization is used to explain how each character changes throughout the play and the reasoning behind their actions. Shakespeare also uses characterization to develop his plot. Shakespeare shows that Lady Macbeth is a very ambitious, dominating, and controlling character throughout the play. She is the reason Macbeth decides to kill Duncan. King Duncan is loved by everyone in the Kingdom. He is characterized as praiseworthy, caring, naà ¯ve, and trusting. Banquo is characterized as brave, innocent, logical, and full of reason. He is the mastermind behind the murder of King Duncan. Shakespeare uses many motifs throughout the story but he uses a lot of imagery of darkness and light. This is one of the strongest motifs used in the play. The motif of light and darkness symbolizes the conflict between good and evil. This motif is used to foreshadow when something good or bad is going to happen. It also shows the readers which characters are good and which characters are bad. In this play, darkness stands for evil, bad deeds, and hell. It is always dark when something bad is going to happen like when Lady Macbeth decides to kill Duncan. When she makes her decision she says, â€Å"Come, thick night, / And pall thee in the dunnest smoke of hell, / That my keen knife see not the wound it makes† (Act 1. Scene 5. Lines 49-51). The darkness she calls on shows the evil or darkness in the act she plans to commit. The witches are also associated with darkness. They always meet in dark, stormy scenes and talk about wandering in foggy and filthy air. They symbolize evil. Light is associated with Heaven, God, and goodness. When Lady Macbeth calls on the murderous spirits saying, â€Å"Nor heaven peep through the blanket of the dark† (Act 1. Scene 5. Line 52), she is implying that light is the only thing that could stop her from murdering Duncan. Also, when Macbeth is fighting his ambition to kill Duncan and become King, he says, â€Å"Stars, hide your fires; / Let not light see my black and deep desires† (Act 4. Scene 4. Lines 50-51). This statement is implying that he is thinking evil thoughts and he does not want God to know his evil desires. Light and darkness are very prominent in all the characters’ actions and thoughts. Macbeth is a man that at first seems content to defend his King and country against treason and rebellion, and yet, his desire for power plays a major role in the way he commits the most heinous acts. Macbeth is characterized as brave, valiant, and loyal. The witches also awaken Macbeth’s ambition in the first act. The act gives the initial impression of Macbeth as a brave hero and then shows us how he changes. It reveals his fixation on the witches’ prophecy. Macbeth is characterized as a brave and noble warrior when King Duncan says, â€Å"For Brave Macbeth-well he deserves that name† (Act 1. Scene 2. Line 16). But, Macbeth’s reaction to the witches’ predictions emphasizes his great desire for power and prestige. Macbeth realizes that murder might be required to achieve this. He thinks about it but has no means of acting on it. He begins to be confused and he is conflicted. He is caught between his loyalty to the King and his desire for power. He yearns for a simple way out, free of guilt and consequence. He implies this when he says, â€Å"If it were done when ‘tis done, then ‘twere well/ It were done quickly† (Act 1. Scene 7. Lines 1-2). Lady Macbeth finally emerges and drives the hesitant Macbeth to act; she is the will propelling his achievements. Macbeth knows what he does is wrong, and recognizes there will be consequences. He is tempted but tries to resist it. He is not strong enough to stand up to his wife. Literary elements like motifs and characterization help develop the entire plot. By using characterization, Shakespeare is able to reveal the characters’ thoughts and feelings in order for readers to analyze the characters’ motives for their actions. Characterization gives the reader a better understanding of each character. The use of motifs in â€Å"Macbeth† help define the setting and mood of the Act, as well as the good or bad intentions of the characters. For example, darkness or night in Macbeth is associated with evil, murder, murderous intent, and mischief, and death. Light is feared by those who wish murder on the King, because they do not want their evil thoughts/deeds revealed. Characters who are innocent were always shown in bright, lighted scenes to stress their goodness. Darkness was the background for evil, as exhibited by the scenes where murder occurs, or where the mischievous, evil witches appear. Blood is a recurring symbol or motif that symbolizes death, and later, Macbeth’s guilt. These are just a few of the many motifs and symbols found in Macbeth. Motifs are used to add depth and richness to characters and settings, and bring out the major themes and ideas of the play.

Fixing Poverty in the Philippines: Mission Impossible Essay

The Philippines has the second highest poverty incidence at 40%, in Southeast Asia, following East Timor which has 55% (Aldaba, 2005). Also according to Aldaba (2005), poverty in the Philippines has always been a rare rural occurrence, in spite of the fact that the poverty in urban areas is also increasing. More than two-thirds of the poor families in the Philippines live in rural areas. The Family Income and Expenditure Survey (FIES) states, based on legitimate poverty lines, that poverty incidence in the Philippines has dropped from 49.3% in 1985 to 36.8% in 1997, a downfall of a total of 12.5 percentage points in 12 years. On the other hand, poverty incidence increased by 3.2 percent from 36.8 percent in 1997 to 40.0 in 2000 (Aldaba, 2005). According to the article written by Ted Torres (2013) in The Philippine star, the percentage of Filipinos living below the poverty line has remained almost unaltered in the past six years. The statement was based on the latest poverty data rele ased by the National Statistical Coordination Board (NSCB). For the first half of 2012, the poverty incidence recorded was 27.9 which is slightly less than the 28.8 percent recorded in the first half of 2006, and 28.6 percent in the first half of 2009 and 2011. The NSCB report on the 2012 first semester state of poverty in the Philippines presented that a family with five members can be considered extremely poor if it is earning an amount of P5, 458 a month or just enough to place some food on the table. The same family has to earn at least P7, 821 a month to satisfy other primary needs such as clothing. Discussion and knowledge about the high poverty incidence that is dominating the country is very significant. It should be shown to the Filipinos especially to the people who are considered living a first-class life. Because of too much poverty that governs the country, it can be concluded that poverty in the Philippines cannot be helped anymore. One main reason behind the high poverty incidence in the Philippines is because of the high population growth. De Dios (1993) stated that high population growth affects poor households through a smaller distribution of incomes among them. The Philippines has recorded one of the highest population g rowth rates in Southeast Asia, at 2.6 percent from 1960 to 1994; this rate is higher than Indonesia and Singapore at 2.1 percent and Thailand as 2.3 percent (De Dios, as cited in Aldaba, 2005). De Guzman (1994) notes that crude birth dates has been declining since 1975, but this downfall has been slow, at 35.3 percent in 1973 to 32.8 percent in 1983. De Guzman also noted that contraceptive prevalence is quite low (30%-40%), and an increasing apportionment of females are getting married – factors which may weaken the decline. High population growth can be pulled down by consistent use of right family planning. Different government departments are actually conducting talks, meetings, and seminars about Family Planning. These departments are inviting parents and married couples from different parts of the country to attend the seminars to hear and be open to the use of family planning. But this advocacy seems to be impossible because there are too many undisciplined Filipinos wh o cannot be controlled by the government. Those undisciplined Filipinos are not open to any advice or suggestions from the hierarchy to improve their way of living. Another huge reason for the high population growth in the Philippines is the government system. According to the former Philippines senator, Mr. Francis Pangilinan (n.d.), the government people have heard never ending complaints about how the government has become a stumbling block for progress in the Philippines. Because of corruption and inefficiency, as well as lack of vision and direction, the government has become impediment to reforms and authentic and real change when it ought to be in the forefront of making change happen. It is enough to say that the old methods of governance have not worked and the usual and old style of electing political leaders characterized by patronage and money politics has failed the disappointed the people. The old ways of selecting leaders, the old ways of electing politicians have not resulted in a better nation. The truth is the country is in a mess because of the failure of the government to lead the country (Pangilinan, n.d). But on the other hand, maybe, the â€Å"Tuwid na Daan† of the [NoyNoy] Aquino Administration can pull this country up from its flat and dull position. This advocacy, consisting of many programs that can help improve the Philippines and its people, can be the sight solution to poverty. But, according to Pangilinan (n.d), there is still a great problem that holds the government from its right leadership – the corruption. Corruption, waste and inefficiency prosper within many situations and yet the government, despite a few valorous attempts to break this cycle, has largely failed to change the character of the bureaucracy (Stiftung, 1989). Ubiquitous corruption will not end unless the Philippine government punish more and punish swiftly and that cannot be done unless the country modernize its Judiciary and supply it with the necessary resources to do so. Too many politicians denounce corruption yet apart from exposes, they have not presented definite steps to address it (Pangilinan, n.d). One way to modernize the Judiciary system is to increase conviction rates. According to Pangili nan (n.d), the conviction rate of the Ombudsman in the Sandiganbayan (anti graft court) for corruption cases is held down at an estimate of less than 20 percent. For every 10 cases filed, less than two end up in conviction; the rest of the cases are the dismissed. No wonder and doubt that most of the people have no fear of committing corrupt acts. Imagine the situation when more than 8 out of 10 corruption cases get away. This can be sharply compared to the conviction rates in Hong Kong, which is pegged at 79 percent. Meaning, nearly 8 out of 10 are convicted. When more are punished and punished promptly, respect for the rule of law will return. It is certainty of punishment that inculcate fear and respect for the laws. It is the duty of the Judiciary system to ensure that the conviction rates are upped. It is also ideal to organized an anti corruption task force, at the highest levels, to monitor big cases and to ensure that government resources are equipped to ensure convictions w ithin months from the time of its organization. The proverbial big fish must not be allowed to get away (Pangilinan, n.d). Another way to modernize the Judiciary system is to double its budget. By upping the budget of the Judiciary, to say 2 percent of the 1.17 trillion national budget, we give rise to the prompt dispensation of justice, the creation of more courts, and expanding of the compensation and benefits of judges, prosecutors and court personnel (Pangilinan, n.d). Corruption cannot be ended. It may be lessened, but not totally ceased. It is because there will forever be government people who will be blinded by the power they got from their position and the huge amount of money they handle. It is a very risky and dangerous work to do corruption acts just for the sake of getting money, but that is the nature of the government people in the Philippines. One politician cannot end his or her term without even getting a single centavo from the money of the Philippine citizens. Another reason behind the high poverty incidence in the Philippines is the lack of jobs and employment. Too many Filipino citizens are still unemployed and most of them are having a hard time finding jobs. The private sector of the government is blamed for lack of jobs in the Philippines. According to Senator Ralph Recto (Recto, as cited in Cabacungan, 2013), â€Å"the job of the private sector is to create wealth and jobs. Unfortunately, the private sector in the Philippines does not have a high degree or culture of giving and sharing.† Sen. Recto also added that, maybe, the administration is focusing too much on government, which accounts for only 17 percent of the Gross Domestic Product when it should have its eyes on the 83 percent controlled by the private sector that is creating too many poor people. Recto and Salceda (Recto & Salceda, as cited in Cabacungan, 2013) said that the social inequality or injustice was the reason for the increase of unemployment to 7.5 percent or 3.086 million in April this year from 6.9 percent or 2.803 million in the same month in 2012 despite a record 7.8 percent growth in the economy in the first quarter of 2013. The Department of Labor and Employment (DOLE) continuously creates programs to help the Filipinos find jobs. One way is the online website which encourages the unemployed people to submit resumes online. In the perspective of the employer, it is very easy to find an employee by just visiting the website made by DOLE. The employer can just type in there the position needed in the company and the search results will give the employer the list of the people who are capable of doing the said job. Regardless of the effort of the government to plant more jobs in the Philippines for the Filipinos to be successfully employed, there are still millions of Overseas Filipino Workers (OFWs) who risk their lives in other lands just to get a job and leap their family from poorness. There are mountains of reasons why great poverty is still colonizing the Philippines. Some can be helped but most of it cannot be solved anymore. No matter how the government strives to give jobs to the Filipinos, it will remain as a nonsense act if the Filipinos are not going to help themselves out of this poverty. It was stated by Mahatma Gandhi that poverty is the worst from of violence. It is really the worst and it cannot be helped anymore. Reference List Aldaba, F. (2005). The fight against poverty in SouthEast Asia NGO good practices in Cambodia, Indonesia and the Philippines. Stiftung, F. (1989). Poverty and growth in the Philippines. Metro Manila, Philippines: FRESAN Printing. Torres, T. (2013, April 24). Poverty level in Phl unchanged since ’06. The Philippine Star. Retrieved August 10, 2013 at http://www.philstar.com/headlines/2013/04/24/934243/poverty-level-phl-unchanged-06 Cabacungan, Gil. (2013, June 12). Private sector blamed for lack of jobs. Inquirer News. Retrieved August 10, 2013 from http://newsinfo.inquirer.net/425271/private-sector-blamed-for-lack-of-jobs Pangilinan, F. (n.d). 4 proposed solutions to help fix the Philippines. Senator Francis â€Å"Kiko† Pangilinan: Senator of the Republic of the Philippines. Retrieved August 10, 2013 from http://kiko.ph/index.php?option=com_content&view=article&id=505:4-proposed-solutions-to-he..

Action learning review - work design Essay Example | Topics and Well Written Essays - 2000 words

Action learning review - work design - Essay Example Considering personal objectives, work design should allow employees to find a sense of fulfillment and potential in their job. There should be particular attention given to employee perceptions regarding autonomy and the challenges of such an environmentAs a socio-technical system, work design is critical in the consideration of the human factors in the workplace. The objective is to be able to create an environment were workers can achieve job satisfaction, efficiency, effectivity and be able to have access to channels for the resolution of problems. In a company that operates on flexible hours and remotely, it is important to create work designs that can be accessed 24/7. At the same time, communication and resolution of policies and issues alike must be done in real time and promptly. At the same time, there should be consideration for security, privacy and sensitivity of programs to circumvent ant limitations that may develop from the nature or structure of the organization. It w as only recently, around in the early part of the 20th century that the value of human resources was given its much and due importance in the organization. Research had shown that employee commitment and satisfaction are highly correlated and this coincides with their intrinsic motivation to work and stick with the organization through its up and downs. Employees are willing to go beyond their call of duty if they have a high job commitment (Bartol & Martin, 1998). There is evidence that work designs are up to par: job satisfaction is high, there is low staff turnover and many employees have been with the company for more than two years which suggests employee commitment. In small organizations such as the one I am working in, the individual efforts are even higher in magnitude. The objectives for the design are to be able to endure that every employee will be given the opportunity and the capability to contribute fully to the company. This will be done by ensuring that work scenarios meet both the corporate and personal objectives, contribute to improving services and enhance effectivity and efficiency of processes and resources (Managing People & Organisations [MOP], 2007, p. 5). Corporate and Personal Objectives The company is in an industry that is competitive and technology oriented. Both of these factors emphasize the need to be responsive and sensitive to developments and trends not only in our main medium, online communications, but also to social trends and demographics. Therefore, the company must be able to have employees who will provide these competencies to develop. Considering this corporate objectives, the work design should afford employees the ability to deliver these needs to company (Niebel & Freivalds, 2002). At the same time, the design should be able to help the company ensure that employees reflect these needs in their work through their innovativeness and ability to deliver collaterals that support client requirements. Considering personal objectives, work design should allow employees to find a sense of fulfillment and potential in their job. There should be particular attention given to employee perceptions regarding autonomy and the challenges of such an environment (Mischel, 1968). The degree of autonomy viewed in a small organization like this is more than compared to a traditional and highly hierarchical management. The problem with too much autonomy could lead to the team inability to work cohesively with other members of the organization (Niebel & Freivalds 2002). Products and Services The company should consider the opinion of Rothwell and Sullivan (2005) who assert the value of non-traditional set ups. This can be particularly to our organization where employees work remotely and independently. In turn, there is an expected variance in the product and service development. Consider schedules alone: in a traditional set-up, people work on relatively the same schedules. In the company, since work is relatively more independent, this may not be a given condition. Therefore, there is less communication regarding products and services particularly on the evaluation phases. Clients will consider status, security, comfort and quality to be the essential

Islam's Cultural Unity and Political Diversity Essay - 2

Islam's Cultural Unity and Political Diversity - Essay Example All who devote their faith to Islam must, therefore, heed its teachings on injustice. Justice is a virtue that if upheld by most societies of the world, the world can be a much peaceful community. Since the time of creation, justice has been preached to the world by both religious and unreligious means. The big problem is that injustice still runs the society to date. It is not news to hear a person being prosecuted without trial today or a person mobbed to death because of an accusation of theft, burglary and so forth. Injustice has grown to a level that is almost irreversible. Beefed with the various discriminations based on race, religion and political affiliations and interests, injustice all over the world is the order of the day. Despite the good teachings of Prophet Muhammad, (peace be upon Him) and the Quran people have chosen to ignore the lessons and go on with wrongdoing. From the Quran teaching on peace, it is clear that one should not personal interests to hinder justice. Those who believe in the good teachings should stand with integrity and shun injustice with actions and not mere words. In so doing, they could help many people to get justice as so required. Prophet Muhammad also teaches us about justice. He tells us that among the six things that would guarantee us Paradise, is getting our hands off injustice. In the clip number two, Yusuf Hamza brings out how injustice is in play in the world today. In the third minute of the discussion, he narrates how the western countries and the other powerful states play the blame game of wars. He says that the powerful countries have always accused the Islamic countries to be producing weapons of mass destruction. He argues that the weapons are made by the mostly the Western nations and sell them to the Islamic countries that are then triggered against themselves to use the weapons. What the Western countries are doing is not just in the face

Identifying Characteristics of Gifted Children Essay

Identifying Characteristics of Gifted Children - Essay Example There has been a debate regarding nurturing and dealing with gifted children with normal children, and one can observe mix responses of experts and nonprofessionals. Still, experts believe that it is very imperative that parents identify particular characteristics in their gifted children, as their ignorance or avoidance may result in adverse outcomes, and in other words, it is very important that gifted children should receive proper guidance or path to utilize their skills, an absence of a platform may result in inappropriate usage. Analysis has indicated that gifted children usually have the ability to carry out any creative task like a professional artist, for instance, they can create paintings at the age of eight without any professional training. There have been few instances of gifted children reading professionally at the age of three or four. Particularly, experts believe, â€Å"Gifted children interpret life differently from others† (Distin, pp. 22-23). In this rega rd, it is essential that parents and teachers play a significant role in identifying different perceptions and skills of gifted children, and at the same time, they appreciate their different skills and perspectives (Distin, pp. 22-23). ... l that is very uncommon in gifted children, there is a possibility that the same child will be doing something exceptional at home or somewhere else, and here, one requires efforts of parents and teachers to identify their skills and extraordinary talent. In addition, a majority of studies have recognized higher retaining power of gifted children that is one of the major reasons for their exceptional achievements on academic, as well as non-academic levels. On one hand, gifted children have a higher IQ level; on the other hand, experts and psychologists have always found gifted children to be highly sensitive, and thus, parents and teachers should stay ready to expect adult behavior at one time and a little crying child at the next minute. In this regard, one can go for dealing with gifted children along with normal children; however, once again it will be a tiring experience and will require a huge amount of efforts. Moreover, gifted children’s needs would not be in any diffe rent from that of normal children; however, case studies have identified a few problems and issues with the gifted children. For instance, gifted children will need a higher amount of care and consideration in terms of their emotional development (Distin, pp. 157). In addition, most of the gifted children show impatient characteristics, as they are always full of ideas. However, they expect same abilities from others and when they do not get similar responses; it results in impatience and irresistible behaviors at times that can be troublesome. Another important thing to consider while dealing with gifted children is their resistance against directions.

Uses of Bt insect resistance in agriculture Essay

Uses of Bt insect resistance in agriculture - Essay Example Uses of Bt insect resistance in agriculture This remarkable finding which happened in 1911 was not the first time Bt went under close inspection; in the Far East, ten years before, a Japanese scientist who was investigating the almost instantaneous death of silkworms first discovered it. More than a century has now passed since Bt's discovery, and for more than half of it, Bt has been used as a natural insecticide, being sprayed onto crops. (Shelton 2008) But just how does Bt work in the first place' Unlike Dichlorodiphenyltricloroethane, which has been known to be a three-letter acronym for the words notorious killer because of its infamousness in inflicting damage to organisms it should not, Bt is not a contact poison. Bt has to be eaten first before it can poison any unsuspecting insect. B. thuringiensis has spores which contain crystal proteins or cry proteins. When ingested by an insect, the active insecticidal crystal protein or (ICP) breaks down in the insect's gut and releases a toxin called delta-endotoxin. This delta-endotoxin then reacts with certain receptors on the intestinal lining and makes pores causing the leakage of its contents and paralyzation of the insect's digestive system resulting to insect death. The killing is a slow process that may take hours or even days. (Shelton 2008) However, it must be noted that because of the paralysis of the insect’s digestive system, the insect soon stops eating. Immediately dead or not, the goal of saving the crops fr om mass mastication of unwanted living forms is definitely achieved. (Office of Biotechnology at Iowa State University 2008) Bt may not be as fast a killer as the conventional insecticides are, but in this ever health conscious world, speed is not the only thing to consider. Synthetic insecticides such as those whose active ingredient is DDT have been banned in many countries and for a number of good reasons. And it is because of such reasons why many farmers choose Bt over it; human safety, of course, is the primary concern. (Bassein 2008) As mentioned, Bt has been used for more than 50 years now as an effective insecticide. So far, there are no reports of it harming anyone. And the underlying reason according to experts is the fact that Bt toxins are toxic only to certain insects; truly, this is good news for bees and beekeepers alike. The rationale' The receptors which are present in the insects' guts are not found in most other organisms, in mammals, and most importantly, in humans. (Federal Ministry of Education and Research 2008) The different strains of B. thuringiensis produce different delta-endotoxins, each "catering" to a specific order of insect. The most common of Bt's cry proteins are those that belong to the Cry1 class which are toxic to lepidopterous insects (e.g. moths such as the European corn borer, butterflies). It is also the most active ingredient in most Bt-based commercial insecticides today. Other proteins belong to the Cry2 class which unlike their Cry1 counterparts, produce a single, smaller crystal per cell. This class is toxic to insects belonging in both the Lepidoptera and Diptera (e.g. flies and mosquitoes) orders. There is also the Cry3 class which poisons the coleopterous (e.g. beetles like the

Information system Assignment Example | Topics and Well Written Essays - 3000 words

Information system - Assignment Example In this report I have capably compared information systems development methodologies SSADM and ETHICS using the NIMSAD framework. I hope this report will offer a better overview of those methodologies and main differences between them. 17 A methodology can be described as a set of actions, techniques, tools as well as documentation support which will facilitate systems developers in their efficient employment along with practice of the new information system. Additionally, a methodology is composed of stages themselves which are then divided into sub-stages that will proficiently give direction to all the developers of information system in their inclination of the practices that might be handy as well as suitable at each phase of the development. In addition, this methodology moreover facilitates them to effectively handle, formulate, control and appraise various projects of information systems. Moreover, the methodologies enclose models and reveals particular viewpoints of ‘reality’ foundational on a set of theoretical paradigms. However, a methodology must inform the developers ‘what’ phases to obtain as well as ‘how’ to achieve those steps though the majority significantly t he causes ‘why’ those phases should be taken, in that particular order (Gasson, 1995; Yaghini, 2009) and (Avison & Taylor, 1997). In this research I will present a detailed analysis and comparison of two most well known information systems development methodologies SSADM (Structured Systems Analysis and Design Method) and ETHICS (Effective Technical and Human Implementation of Computer-based Work Systems). This research and evaluation will be formulated on the origin of the NIMSAD framework that will facilitate us in clearly analyzing and understanding the area of problem solving (in general). Here NIMSAD framework will also help us in case of overall functioning as well as proficient evaluation of the information system methodologies, their arrangements,

On-Site Executive MBA Program Assignment Example | Topics and Well Written Essays - 1750 words

On-Site Executive MBA Program - Assignment Example On-Site Executive MBA Program A growing number of business proficient’s prefer to get their MBAs over the internet. Getting an MBA degree is a big achievement for many students. Countless undergraduates after graduating progress to get their Masters Degree in their most wanted field. This marketing plan points up the market fragments and the line of attack of employing to get consumers and generate a compact income stream. Our exclusive emphasis is giving out chances for the round-the-clock working undergraduate that is unable to go to a university grounds for courses. A twist that gives us a benefit over our opponents is of giving pupils more preferences of what is accessible in selection from a more range of majors. From experience, many virtual universities have a very rudimentary collection of MBA degree majors. In the present day business biosphere, the importance and standing of clienteles is not something that would be put to one side by businesses. In defining a target market you need to decide if your item for consumption is worldwide or countrywide in choice? Or is it more prospective that you will vend it principally in your own district or public? In the circumstance of an online MBA Program, the key market is essentially nationwide and worldwide. Pupils want to go to the United States from all around the world to go to a USA school. In addition, there is a marketplace for students in the States that wish to go to school overseas. The secondary market is native people who have kinfolks and are too busy to join a campus and go to lecture.(Advantage and Disadvantage of Distance Learning, 2011) Likewise, we would be targeting the middle class i.e. students who cannot afford to pay huge amounts of fees to get a degree. An online Program

Foundation Certificate in Human Resource Practice Essay Example for Free

Foundation Certificate in Human Resource Practice Essay 1. Collecting and recording HR data is vitally important to an organisation. The collecting of the data could be to monitor that laws and regulations are being adhered to for example the Health and Safety at work act 1974, ensuring that all staff are maintaining high health and safety awareness and complying to the law. The data would need to be collected to enable the organisation to prove that it is adhering to current law and legislation. Another example could also be to monitor employee absence levels across the organisation and looking for any pattern or trend relating to individual absences. This data could be used in Absence review meetings and having all the correct and accurate data could be vital in a dispute with an employee. It could highlight issues with employee welfare and enable the company to offer support in order to support the employee back to work. 2. Storing Records There are many methods of storing records, an example is: Electronic which includes hard disks drive – PC, CD – recorder, DVD, databases and spreadsheets, internet or intranet, USB devices, emails and virtual learning environments. Electronic storage can have pros and cons. Advantages can be the speed and accuracy that it provides, spellcheckers etc can all help the documents to be stored accurately. Vast amounts of data can be stored on a computer software system and therefore not take up and physical office space. The electronic way of storing data can also be protected by a password meaning that it is secure and accurate at the same time and protected from anyone outside the HR function, and it means that a variety of colleagues can have access to update and amend the records at the same time, even updating at the same time as colleagues. Manual Storage. Manual storage can be personnel files, absence forms, reports, filing cabinets etc There are lots of benefits to manual storage including having documents which need a physical signature and provide proof of identity like bank details etc. Also should a computer system crash or wipe the documents the paper copy is always accessible. Manual storage is easy to move around and is easy to keep protected and confidential via a lock/key etc although staff with access must ensure it is securely locked away. 3. UK Legislation The Data Protection Act 1998 is about respecting individual rights when processing/collecting and storing their personal information. This is achievable for the company by being honest with employees about the use of their information and by following good data handling procedures. The act is compulsory and all organisations that hold or process personal data must adhere to this. Personal data should be processed fairly and lawfully, the data should be adequate, relevant and not excessive, it should be accurate and where necessary kept up to date, any data should not be kept for longer than necessary, data should be kept secure. All staff has responsibilities under the Act to ensure that their activities comply with the Data Protection Principles Employees do have a right legally to access information that an organisation may hold on them. This could include information regarding any grievances or disciplinary action, or information obtained through performance monitoring processes. Processes should be in place to deal with a data request from an employee as a 40 day time limit is compulsory. The health and safety at work at 1974 is legislation relating to protecting employees from injury or illness as a direct result of their job. All data relating to health and safety must be recorded and stored securely, including accident books. This data may be called upon many years after an employee has left the organisation so staff should ensure documents and information are kept in a secure adequate accessible place. The Freedom of Information Act which came into force in 2000 gives you the right to ask any public sector organisation for all the recorded information they have on any subject. Anyone can make a request for information – there are no restrictions on your age, nationality or where you live. If you ask for information about yourself, then your request will be handled under the Data Protection Act 1998. Recording, Analysing and using Human Resources information is highly important and ensuring it is accurate and efficient will support the organisation strategy in many ways. The Analysis can change the way the organisation moves forward and affect future plans/decisions.

Introduction to E-learning: Types, Benefits and Strategies

Introduction to E-learning: Types, Benefits and Strategies Chapter 2. Background and Related Work Introduction During the last decade the amount of literature published in the field of eLearning has grown noticeably, as has the diversity in attitudes and viewpoints of people who work on this subject. The general background presented here with regard to eLearning includes the definition, details of different types and the concept of quality. Information quality within information systems (IS), web mining and information extracting techniques are the main areas on which supporting literature is primarily focused. However, an in-depth explanation of each branch of these research fields is outside the scope of this literature review. The literature presented here is particularly focused on the subtopics of these large research areas which are directly applicable to this research. The structure of this chapter is divided into three main parts: a general view of eLearning including definitions of eLearning, an overview of eLearning types and the concept of quality in eLearning; information quality (IQ) within ISs; and information extraction methods. Each section includes a number of subsections which address the factors that are relevant to this research. ELearning In this part of the literature review, we focus on eLearning by providing a discussion about the definitions of eLearning, eLearning types and the concept of quality in eLearning. Moreover, in this section we lay the foundation for the general concept of quality in eLearning upon which the research will be based. This section also presents a discussion about the relationships between technology, users and content in an eLearning context. ELearning Definition The term eLearning is used in the literature and in business to describe many fields, such as online learning, web-based training, distance learning, distributed learning, virtual learning, or technology-based training. During recent decades, eLearning has been defined in several instances in different ways. In any publication in the field of eLearning, it is important to ensure that the authors understanding exactly matches that of the majority of the readers, therefore, the specific definition used should be stated first. Moreover, to reach a clearer understanding of what eLearning is, in this part of the thesis we present numerous definitions of eLearning as mentioned in the literature. In general, most of the definitions of the term eLearning are used to express the exploitation of technologies which can be used to deliver learning (or learning materials) in an electronic format, most likely via the World Wide Web (WWW). Psaromiligkos and Retalis consider eLearning to be the systems which utilise the WWW as a delivery medium for static learning resources, such as instructional files, or as an interface onto interactive The previous definitions look at eLearning in general; in more detail, eLearning can be in the form of courses or in the form of modules and smaller learning materials it also could take various forms. Romiszowski takes these details into account and summarises the definitions encountered in the literature in a way that emphasises that eLearning can be a solitary, individual activity, or a collaborative group activity. It also suggests that both synchronous and asynchronous interactive forms can be engaged. Naidu also takes into consideration the differences in the forms of interaction when trying to formulate a general definition of eLearning: educational processes that utilize information and communications technology to mediate asynchronous as well as synchronous learning and teaching activities. The position adopted in this research is that eLearning entails the technology used to distribute the learning materials, the quality of these materials, and the interaction with learners. The definition of eLearning used in this research addresses these dimensions in terms of: the use of new multimedia technologies and the Internet to improve the quality of learning by facilitating access to resources and services as well as remote exchange and collaborations ELearning Types As mention earlier, eLearning takes many different forms and includes numerous types of systems. In the extant literature eLearning types are defined following two main axes: the user context (individuals, groups or a community of users) and users engagement and interactivity. Romiszowski takes these details into account and summarises the definitions encountered in the following table, which emphasises that eLearning can be a solitary, individual activity, or a collaborative group activity. It also suggests that both synchronous and asynchronous interactive forms can be engaged. Looking more deeply at the division of the forms of interactivity used in eLearning systems, there are two main types of eLearning: asynchronous and synchronous, depending on learning and teaching activities. Synchronous eLearning environments require tutors and learners, or the online classmates, to be online at the same time, where live interactions take place between them. In this context, Doherty describes an Asynchronous Learning Network (ALN) as a variety of eLearning systems which distribute learning materials and concepts in one direction at a time. Moreover, Spencer and Hiltz express ALN as a place where learners can interact with learning materials, tutors and other learners, through the WWW at different times and from different places. The focus of this research will be on a case where students log-in to and use the system independently of other students and staff members, as well as using asynchronous methods regarding learning content, quality management and delivery which fit firmly into the general definition of the asynchronous eLearning environment. Quality Concept in ELearning The definition of eLearning adopted in this thesis represents three fundamental dimensions: technology, access and quality. The focus in this research will be on quality, which is considered a crucial issue for education in general, and for eLearning in particular. This section of the literature review will discuss concepts of quality in eLearning generally, and highlight the importance of content as the most critical factor for the overall quality. Currently, there are two recognised challenges in eLearning: the demand for overall interoperability and the request for (high) quality. However, quality cannot be expressed and set by a simple definition, since in itself quality is a very abstract notion. In fact, it is much easier to notice the absence of quality than its presence. Despite efforts to reach a comprehensive, universal definition of quality in eLearning, there is still a fundamental ambiguity surrounding the issue. One position is to consider quality as an evaluation of excellence, a stance which is primarily adopted by universities and education institutions. For example, in universities quality teaching and learning are promoted as the top priority, giving less attention to criteria or measurements regarding teaching input into courses, the learning outcomes, and the interactivity with the system. Another trend is to consider the improvement in quality, where quality is improved by moving beyond the set conceptions applied, and generally moving in the direction of a flexible process of negotiation, which needs a very high level of quality capability from those involved. Furthermore, quality can be viewed and considered from different aspects. Here, the SunTrust Equitable report illustrates what they perceive to be the value chain in eLearning in the form of a pyramid. The content is the most critical factor of eLearning. Indeed, to be able to use the internet as a tool to improve learning, the content should not distract learners, but increase their interest for learning. Learning tools and enablers are also important in the learning procedure. In reality, providers of learning platforms and knowledge management systems are key in the successful delivery of content. These companies provide the necessary infrastructure to deliver learning content. Moreover, learning service providers (LSP) are the distribution channels for content providers. One of the challenges facing these knowledge hubs and LSPs is to ensure that the learners are receiving fresh content. Companies focused on educational e-tailing then complete the value pyramid of eLearning. Looking at the pyramid it can be clearly observed that content is the most critical component of learning through the internet. In a similar manner, Henry stated that eLearning is composed of three main aspects: content, technology and services, he also emphasised that content is the most significant factor. Although this thesis will focus on the quality of content delivered by eLearning as the most important criteria and the most influential in the overall level of learning quality, the specified context and the perspectives of users also need to be taken into account when defining quality in eLearning. It is also essential to classify suitable criteria to address this quality. ELearning Technology, Users and Content Although most eLearning explanations focus on the technology and not on the learning, it is important to keep the people eLearning is designed for in mind. Moreover, individual learning styles and required learning materials should be addressed first. Then a suitable electronic delivery method can be adopted. On their website (agelesslearner.com), Karl and Marcia Conner commented, in this regard, that Maybe the e should actually follow the word learning'. Henry describes the content in a way that includes all delivered materials, including the materials which are usually offered in classroom-based learning and that are tailored for eLearning, in addition to any other knowledge the developer might offer. In fact, eLearning systems are considered to be user-adaptive systems, where systems are designed to react with user performance and choices. Webber, Pesty and Balacheff express user modelling as a central issue in the development of user-adaptive systems, whose behaviour is usually based on the users preferences, goals, interests and knowledge. Moreover, they declare that a system can be considered user-adaptive when changes in its functionality, structure or interface can be monitored, in order to consider the different needs of users and, ultimately, their changing needs. In the area of eLearning Heift and Nicholson believe that eLearning systems as adaptive systems are designed to meet the diverse requirements of students who have different levels of knowledge and backgrounds [19]. There is a significant base of literature and research in the area of adaptive systems, which usually base their behaviour on user models. In more detail, Kobsa explained that the user model often depends on one user or a group of users sharing the same profile and it characterises users preferences, goals, interests and knowledge. Webber, Pesty and Balacheff notice that with regard to this point there are two main problems relating to user modelling: to identify the relevant information to be modelled and to decide which method is more suitable to apply in order to determine the relevant information about the user. In fact, personalisation plays an important role in all areas of the e-era, especially in eLearning, as stated by Esposito, Licchelli and Semeraro, where the main issue is student modelling. This is the analysis of student behaviour and the prediction of future activities and learning performance . Furthermore, Ong and Ramachandran perceive that the literature on adaptive systems shows that by modelling the learner, the human tutor and the knowledge domain of instructional content, powerful pedagogical outcomes can be obtained. Although eLearning systems are considered types of adaptive systems, the difference between the concept of the user and the concept of the student creates a fundamental problem in the eLearning area. In this context, Esposito, Licchelli and Semeraro believe that in a general web system the user is free to surf and the system attempts to predict future user steps using the user model in order to improve the interaction between the user and the system, while in the eLearning system the modelling has to improve the educational route, adapting it to the model of the student. As a result it is essential to control and to assess student browsing. The systems should not give the students absolute freedom to decide their way through the content and learning materials, rather, the system should provide a specific educational path and offer a continuous evaluation activity of student performance, towards a defined pedagogical goal. Although delivering web-based educational materials can be very useful as the same content is distributed to a number of students and can be accessed regardless of time and place, this delivery would not be beneficial from a pedagogical point of view if the students, their level of knowledge and their learning style was not known. In fact, Sanatally and Senteni observe that the widely held principle of using the web simply as a form of distributed medium for learning materials does not add significant value to the learning process. This argument leads to the conviction of the importance of developing adaptive eLearning systems. Even if adaptive systems are focused on the interaction with users and changing the course and the content dynamically with their needs, and not on controlling the set sequence of a course, eLearning can exploit adaptive technologies to build learning environments that form user-specific sequencing. Tang and McCalla use the example of the Paper Recommender Sys tem as a good example of this exploitation: the system was designed to give recommendations to students about what conference or journal papers to read, based on their level of understanding and knowledge. We can see more clearly, as suggested by Conati and VanLehn, that the aim of adaptive systems is to build precise, interactively changing models of individual student learning, in order to use them as representations of how learners are progressing within the content of the course. Moreover, Papanikolaou et al. describe adaptivity as being system-controlled and in most cases assists in: planning the content, planning the delivery and presentation of the learning materials, supporting student navigation throughout the field of knowledge and problem solving. From this, it can be deduced that learner models generally characterise learner knowledge levels on the concepts of domain knowledge, pedagogical goals and learning preferences towards diverse styles of learning materials. In this context, they suggest that the domain model should be used in parallel with the learner model to provide a structure for the representation of learner knowledge of the defined domain. Using this procedure , tailored learning materials can be distributed to specific learners to be consistent with their requirements. This corresponds with the vision of Mittal et al., who realised that by creating several broad groups into which it is possible to segment target learners, it can be ensured that the content of learning materials for an absolute beginner student is not the same for that of a student getting ready for an exam. Nowadays, most student modelling systems follow the same method, in which the systems starting point is to create a reference template for a student, thus, the expertise or intelligence encoded into the system can adapt the course organisation and content to the individual student. The use of this method to decide the style and level of content that a student should be offered, according to how students interact with the system, will lead to a more personalised learning experience. In the case of this research, the student and domain model did not entail the complexity of those built in adaptive systems; however, several of the underlying principles of available student and domain modelling techniques proved to be useful. The key issue in most adaptive systems that feature student and domain modelling is a sequence of complex data repositories that give highly precise values about student performance and completion against learning materials. The focus in this research will be on measuring the quality of the content of learning materials distributed via eLearning systems, and establishing how the student will interact with the materials, how they will be able to extract the relevant information from the content and how the context of the online materials will help students to recognise the underlying structure of the content and easily access the parts in which they are interested. This research will gather empirical evidence using online questionnaires, which can be used to directly ask students about their preferences and perspectives. Summary This part of the literature review provided a general overview of eLearning, including definitions of eLearning, a note of eLearning types and consideration of the concept of quality in eLearning. It also identified the definition adopted for eLearning in this study and considered the type upon which this research will focus. Moreover, in this section we laid the foundation for the general concept of quality in eLearning upon which the research will be based. Finally, it presented a brief discussion about the relationships between technology, users and content in an eLearning context. The next part of this chapter will discuss the concept of IQ within ISs; this will be used later on to set standards for IQ in the context of eLearning systems. Information Quality in Information Systems In this part of the literature review we will start with a brief discussion of the terms data quality and information quality, and will shed some light on the concept of IQ within ISs and how it could be defined. We will also provide a comprehensive review of the major historical developments of IQ frameworks. Data Quality(DQ) vs. Information Quality During recent years, much work has been done to build quality frameworks for IQ dimensions. In the past, research focused on DQ, but due to the recent development of internet technologies, ISs today are providing users with information, not only data. Therefore, research attention has shifted to focus on IQ frameworks. While, some researchers explicitly distinguish between the terms data and information and explain information as data which has been processed in some way, sometimes, it may be difficult to discriminate between them in practice . Still, in some studies the term information is interchangeable with data. Likewise, the term data quality is often used synonymously with information quality. Consequently, in this study, the concept of information will be used in a broad sense, which covers the concept of data. Before reviewing the researches that were conducted to formulate (data/information) quality frameworks within ISs, first we will discuss the meaning of IQ and how it could be defined. How Information Quality Could be Defined Although it is important to set standards for IQ, it is a difficult and complex issue, particularly in the area of ISs, because there is no formal definition of IQ, as quality is dependent on the criteria applied to it. Furthermore, it is dependent on the targets, the environment and from which viewpoint we look at the IQ, that is, from the provider or the consumer perspective. Moreover, IQ is both a task-dependent and a subjective concept. Juran summarises these aspects of quality in his quality definition as fitness for use. Similarly, Wang described DQ (which could apply to IQ) as data that is fit-for-use. This description has been adopted by researchers because it brings to light the fact that IQ cannot be defined and evaluated without knowing its context. Defining IQ in a contextual approach seems to be logical because quality criteria, which could be used to assess IQ, can differ according to the context. In fact, IQ is expressed in the literature to be a multi-dimensional concept with varying attributed characteristics depending on the context of the information. However, taking into account the complexity of the IQ concept and that its measurement is expected to be multi-dimensional in nature, the prime issue in defining the quality of any IS is identifying the criteria by which the quality is determined. The criteria result from the multi-dimensional and interdependent nature of quality in ISs, and are dependent on the objectives and the context of the system. Thus, it is common to define IQ on the internet by identifying the main dimensions of the quality, for that purpose IQ fr ameworks are widely used to identify the important quality dimensions in a specific context, these dimensions can be used as benchmark to improve the effectiveness of information systems, as described by Porter. Information Quality Frameworks Today, for any IS to be judged successfully it has first to satisfy additional predefined quality criteria. An eLearning system is a special type of IS so it is important to examine the literature relating to the traditional IS success models and the proposed quality frameworks, in order to test the possibility of extending these success models to identify eLearning content quality criteria in an eLearning context. Much of the work done in IS success has its origins in the well-known DeLone and McLean (DM) IS Success Model.This model provided a comprehensive taxonomy on IS success based on the analysis of more than 180 studies on IS success and it identified over 100 IS success measures during the analysis. It established that system quality, IQ, use, user satisfaction, individual and organisational impact were the most distinct elements of the IS success equation. In a later work, the authors confirmed the original taxonomy and their conclusion, namely that IS success was a multidimensional and interdependent construct. Their model makes two important contributions to the understanding of IS success. First, it provides a scheme for categorising the multitude of IS success measures that have been used in the literature. Second, it suggests a model of temporal and causal interdependencies between the categories. The updated model, which was proposed in 2003, consists of six dimensions: Information quality, which concerns the system content issue. Web content should be personalised, complete, relevant, easy to understand and secure. System quality, which measures the desired characteristics of a web based system such as usability, availability, reliability and adaptability. Service quality Usage, which measures visits to a website, navigation within the site and information retrieval. User satisfaction, which measures users opinions of the system and should cover the entire user experience cycle. Net benefits, which capture the balance of positive and negative impacts of the system on the users. Although this success measure is very important, it cannot be analysed and understood without system quality and IQ measurements. In their model, DeLone and McLean defined three main dimensions for the quality: IQ, systems quality and service quality. Each one has to be measured separately, because singularly or jointly, they will affect subsequent system usage and user satisfaction. In 1996, Wang and Strong proposed their DQ framework, which will be discussed in more detail in the following section. In their framework they categorised characteristics/attributes in to four main types/factors: intrinsic, accessibility, contextual and representational. This method of categorising IQ factors and attributes proved to be a valuable methodology for defining IQ. Lately, several quality management projects in business and government have successfully used this framework. After Wang Strong DQ framework, diverse research efforts were spent in order to identify IQ dimensions in deference contexts. Although these frameworks varied in their approach and application, they shared some of the same characteristics concerning their classifications of the dimensions of quality. In 1996, Gertz focused on finding possible solutions for the problems regarding modeling and managing data quality and integrity of integrated data. H proposed a taxonomy of data quality characteristics that includes important attributes such as timeliness and completeness of local information sources. While Redmans work aimed to set up practical guidelines to analyze and improve information quality within business processes, h proposed a number of quality attributes grouped into six categories: Privacy, Content, Quality of Values, Presentation, Improvement and Commitment. In the same year, Zeist Hendricks identified 32 IQ sub-characteristics grouped in 6 main IQ characteristics which covered functionality, reliability, efficiency, usability, maintainability and portability. Unlike general purpose IQ framework, in 1997 Jarke proposed a special purpose framework where he used the same hierarchical design established by Wang Strong. He defined IQ criteria depending on the context and requirements for specific application; Data Warehouse Quality (DWQ). In his framework, Jarke linked each operational quality goals for data warehouses to the criteria which describe this goal. The main defined criteria are accessibility, interpretability, usefulness, believability, and validation. In 1998, Chen gave a list of IQ criteria with no special taxonomy. He, however, proposed a goal-oriented framework focusing mainly on time-oriented criteria such as response time and network delay. One year later, Alexander Tate proposed their framework for IQ IN Web environment. This framework consisted of 6 main criteria; authority, accuracy, objectivity, currency, orientation and navigation. In the same year, Katerattanakul Siau adapted Wang Strong DQ framework to propose their four categories IQ framework of individual websites. Furthermore, Shanks Corbitt recommended a semiotic-based quality framework for information on the Web. This framework includes four semiotic levels. Syntactic level to insure that information is consistent whiles the Semantic level focuses on the information completion and accuracy. Pragmatic level is the third level which covers the usability and the usefulness of the information. The forth level is the social level ensures information understandabil ity. Within their framework there are 11 quality dimension distributed within the identified levels. Dedeke in 2000 developed a conceptual IS quality framework that includes 5 categories; ergonomic, accessible, transactional, contextual and representational quality. Each category consists of number of quality dimensions such as; availability, relevancy and conciseness. Whilst Zhu Gauch described 6 quality metrics for information retrieval on the web; these are availability, authority, currency, information-to-noise ratio and cohesiveness. Leung adapted Zeist Hendrickss quality framework in 2001 and applied it to Intranet applications. He defined 6 main IQ characteristics; functionality, reliability, usability, efficiency, maintainability and portability. Each quality characteristic in the proposed framework includes numbers of sub-characteristics. Several research in IS quality were undertaken in 2002, Eppler Muenzenmayer suggested two main manifestations for their proposed framework; content quality and media quality. The content quality is focused on the quality of the presented information and it consists of two categories; relevant information and sound information. Whereas media quality is focused on the quality of the medium used to deliver the information and it includes optimized process category and reliable infrastructure category. Each category in the framework contains number of quality dimensions. Khan categorised IQ depending on the context of the system. The framework divided IQ into two main quality types; product and service quality. Moreover, it divided these two types into 4 quality classifications and each classification into number of quality dimensions. The quality classifications are sound information, useful information, dependable information and usable information. In addition, Klein conducted a research in the same year to identify five IQ dimensions chosen Wang Strongs DQ framework to measure IQ in Web context; accuracy, completeness, relevance, timeliness and amount of data. Mecella also proposed an initial framework for quality management in Cooperative Information System (CIS). This framework includes a model for quality data exported by cooperating organizations and the design of an infrastructure service and improving quality. More recent, in 2005 Liu Huang mentioned 6 key dimensions for IQ; source (focused on information availability), content (focused on information completeness), format and presentation (focused on information consistency), currency (focused on information currency and timeliness), accuracy (focused on information accuracy and reliability) and speed (focused on how easily information is downloadable). Besiki et all introduced in 2007 a general framework for IQ assessment. This framework consists of a comprehensive taxonomy of IQ dimensions, and provides a straightforward and powerful predictive method to study IQ problems and reason through them in a systematic and meaningful way. Lately, Kimberly et all presented in 2009 a model for how to think about IQ depending on the application context; they identified number of common IQ metrics. Kargar Azimzadeh also presented an original experimental framework for ranking IQ on the Web log. The results of their research revealed 7 IQ dimensions for IQ in Web log. For each quality dimension, quality variables associated coefficients were calculated and used so that the proposed framework is able to automatically assess IQ of Web logs. In the same year Thi Helfert conducted a research aimed to propose a quality framework based on IS architecture. In their research they identified quality factors for different construct levels of IS architecture. Moreover, they also presented impacts amongst different quality factors which help to analyze the cause of IS defects. In this part we gave a brief review of the researches conducted to formulate (data/information) quality frameworks within ISs. However in the next section we will focus on Wang and Strongs DQ framework as we will use it as a base for this research to measure IQ in eLearning systems along the dimensions of the framework. Wang and Strongs Data Quality Framework Wang Strongs DQ framework, one of the most comprehensive, popular, remarkable and cited DQ frameworks, was established by Richard Wang and Diana Strong in 1996. Their framework was designed empirically by asking users to give their viewpoints about the relevance of the IQ dimensions to capture the most important aspects of DQ to the data consumer. In their framework, Wang and Strong classified quality dimensions into four groups: Intrinsic DQ: refers to the quality dimensions originating from the data on its own. This aspect of quality is independent of the users perspective and context. Contextual DQ: focuses on the aspect of IQ within the context of the task at hand. In this group, the quality dimensions are subjective preferences of the user. Contrary to the first group, DQ dimensions cannot be assessed without considering the users viewpoint about their use of provided information. Representational DQ: is related to the representation of information within the systems. Accessibility DQ: refers

Artificial Intelligence In Military Application Information Technology Essay

Artificial Intelligence In Military Application Information Technology Essay Since the dawn of civilizations, humans have endeavored to be in control of their environments and surroundings. This quest resulted in many discoveries and inventions, most notably among them are machines. Human used machines as an aid to make ones life comfortable, effective and efficient and aimed to develop machines capable of working like human beings, if possible. Computer is one of the most important machines which has not only raised hopes in this regard but has also contributed significantly in every sphere of human endeavor. Human approach to problem solving is one of its kinds. It is based on abstract thought, logic, reasoning and recognizing of pattern. Computers and humans are different. A computer is yet to understand all situations and simultaneously adapt to an evolving situations. The military systems including weapons will be smart; too fast, too small, too many, and will create a complex environment for humans to monitor, control and direct them. Information-based systems will lead to a data overload that will make it a challenge for humans to directly intervene in decision making. Weapons and other military systems already under development will function at increasingly higher levels of complexity and responsibility, without meaningful human intervention and control. In future military conflicts, norm of engagement will be to act rapidly. The military architectures of tomorrow will consist of a new array of sea, ground and space based sensors, unmanned combat aerial vehicles (UCAV), and missile defence technologies. These will take advantage of directed energy weapons. Military forces will be both faster and agile. Opponents will take advantage by operating faster than a defender can observe, orient, decide how to respond and act on that decision. The attacker will thus place himself inside the defenders Observe, Orient, Decide and Act (OODA) loop, destroying an adversarys ability to conduct an active defence  [1]  . To execute the OODA process faster than the enemy is at the core concept of future digital and information warfare. Automated systems, assisted by artificial intelligence in some form or the other, may be a way out for this problem. The advances gained in the field of artificial intelligence technology can be utilized by unmanned systems to be able to assess operational and tactical situations and decide an appropriate action. Information will drive success of command and control. These systems will collect data, have the ability to analyze data and provide recommendations to the commander. The difference between providing a recommendation and acting on a recommendation may be only a software twist. Artificial Intelligence (AI) is the branch of computer science focusing on creating machines that can engage on behaviour that humans consider intelligent. AI aims to improve machine behaviour in tackling complex tasks. Smart machines have now become a reality and researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and achieve many other advantages. With the introduction of web-enabled infrastructure rapid developments have been made in the application of Artificial Intelligence techniques in the recent past. AI is the key technology in many of todays applications in all field including military. AI methodologies are being applied to support decision making at all levels of military operations such as assessment of force readiness, reliability and capability, complex missions planning and integration of data from multiple sources  [2]  . Research in the field of AI is also addressing the challenges presented by supporting such decision making in rapidly changing environments. The use of such technology opens up endless possibilities in the military. This paper aims to trace the contours of AI, examine current efforts to utilise Artificial Intelligence and explore its potential applications in military. Genesis and Recent Past   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚     Ã‚  Ã‚   The first Electronics computer was developed in 1941; however, the field of AI research was formally founded at a conference at Dartmouth College in 1956 only. Early work in AI focused on using cognitive and biological models to simulate and explain human information processing skills. In the 1990s and early 21st century, AI achieved its greatest successes. AI has advanced rapidly in the past decade. This happened due to greater use of the scientific method in experimenting with and comparing approaches that systematises and automates intellectual tasks. Thus it is relevant to any sphere of intellectual activities of human. The success can be attributed to the incredible power of modern computers, a greater emphasis on solving specific sub-problems, the creation of new ties between AI and other fields working on similar problems. AI is seen and perceived by different people or groups of people differently. The definitions of artificial intelligence can be broadly put into two approaches: one centred around humans and other centred on rationality  [3]  . The human centred approach must be an empirical science involving hypothesis and experimental confirmation while a rationalist approach involves a combination of mathematics and engineering. There have been efforts to introduce new creative approaches and refine the best one. Recent progress in understanding the theoretical basis for intelligence has gone hand in hand with improvements in the capabilities of real systems. Various subfields of AI have become more integrated. AI has found some common ground with other disciplines. A better understanding of the problems and their complex properties, combined with increased mathematical sophistication has led to workable research agendas. Fields of AI In AI the problem of intelligence simulation is generally divided into a number of specific sub-problems. These consist of particular capabilities that researchers like an intelligent system to display. For difficult problems, most of the algorithms require large computational resources and the amount of memory or computer time required become very high. With rapid strides in computer technology, research and utilization, the field of AI witnessed new frontiers. Russell and Norvig explains, AI encompasses a large variety of subfields ranging from general purpose area such as learning and perception to such specific tasks as playing chess, proving mathematical theorems, writing poetry, and diagnosing diseases. AI systematises and automates intellectual tasks and is therefore potentially relevant to any sphere of human intellectual activity. In a sense, it is a truly universal field  [4]  The various fields and subfields that received more attention in order to solve larger problem s are: Learning The centrality of learning was discussed by Turing in 1950. From the beginning itself machine learning has been central to AI research. The ability to find a pattern in a stream of input is called unsupervised learning where as supervised learning includes classification and numerical regression both. Classification is used to determine what category something belongs in. This is done after seeing a number of examples of things from several categories. Regression takes a set of numerical input and output examples and attempts to discover a continuous function that would generate the outputs from the inputs. In case of reinforcement learning, the agent is rewarded or punished based on good or bad responses. Natural Language Processing It gives machines the ability to read and understand the languages spoken by human beings. Text mining and machine translation are example of some basic applications of natural language processing. Perception Perception provides agents with information about the world in which they exist. Perception is initiated by sensors. Machine perception is the ability to use input from various sensors such as cameras, microphones, sonar etc to deduce aspects of the world. Computer vision is the ability to analyse visual input. Facial recognition, object recognition and speech recognition are some of the selected sub-problems Social Intelligence In order to obtain social intelligence capability, Artificial intelligence has to establish able human interaction and also possess the emotions that people have during their everyday lives. Social skills and emotion play two important roles for an intelligent agent. First, it should be able to foresee the actions of others, by knowing their motives and state of emotions. This involves elements of game theory, decision theory, as well as the ability to model human emotions and also the perceptual skills to detect emotions. Also, it is expected that for good human-computer interaction, emotions need to be displayed by an intelligent machine also. It must appear polite and sensitive to the humans it interacts with. At best, it should have normal emotions and at least it should appear polite. Creativity Artificial Intelligence that deals with the development and exploration of systems that exhibit creativity. It includes systems capable of such things as scientific invention, visual artistry, music composition and story generation etc. A section of AI addresses creativity both theoretically from a psychological perspective and practically via specific implementations of systems that generate outputs that can be considered creative. Artificial Intuition and Artificial Imagination are the areas related with computational research. General Intelligence Many of the researchers hope that their work will finally be included into a machine with general intelligence, combining all the other skills and exceeding human abilities at most of them. Knowledge Representation knowledge representation is one of the important and most familiar concepts in AI. Most of the problems that machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are objects, properties, categories and relations between objects, situations, events, states and time, causes and effects, and many other less well researched domains. Knowledge representation and knowledge engineering are central to AI research Planning Planning are the subfields of AI devoted to finding action sequences that achieve the agents goals. Intelligent agents should be able to lay down goals and accomplish them. They need a way to imagine the future and be able to select choices that maximize the value of the available choices. They should have a representation of the state of the world and be able to make predictions about how their actions will change it. Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. Tools Used to Solve Problems of AI In the course of years of research, AI has developed a large number of tools to solve the difficult problems in computer science. A few of the most common of these methods are mentioned: Search and Optimisation Search is the subfield of AI devoted to finding action sequences that achieve the agents goal. Several problems in AI can be solved in theory by intelligently searching through many possible solutions. Reasoning can be reduced to simply perform a search operation. Planning algorithms search through trees of goals and sub-goals, attempting to find a path to a target goal. This process is called means-ends analysis. Robotics algorithms for moving limbs and grasping objects use local searches in configuration space. Several learning algorithms use search algorithms based on optimization. In case of most of the real world problems, simple exhaustive searches are rarely sufficient. Therefore, heuristics supply the program with a best guess for the path on which the solution lies on.   Also in case of many problems, it is possible to begin the search with some form of a guess and then incrementally refine the guess until no more refinements can be made. Logic Logic is the primary vehicle for representing knowledge. It is used for knowledge representation and problem solving. However, it can be applied to other problems also. AI uses several different forms of logic research. Propositional or sentential logic is the logic of statements which can be true or false. There is well developed technology for reasoning in proportional logic First-order logic also permits the use of quantifiers and predicates. It can express details about objects, their properties, and their relations with each other. Fuzzy logic is a version of first-order logic. It allows the truth of a statement to be represented as a value between 0 and 1, rather than simply True or False. Fuzzy systems have been widely used in modern industrial and consumer product control systems and can be used for uncertain reasoning. Several extensions of logic have been intended to handle many domains of knowledge. Other forms of logic designed to help with default reasoning and the qualification problem include default logics, non-monotonic logics and circumscription Probabilistic Methods For Uncertain Reasoning A large number of problems in AI such as learning, reasoning, planning, perception and robotics call for the agent to operate either with uncertain or incomplete information. A number of powerful tools using methods from probability theory and economics have devised by AI researchers to solve these problems. Bayesian networks are a very common tool that can be used for a large number of problems likes learning, reasoning, planning and perception etc. Probabilistic algorithms can also be used for filtering, prediction and finding explanations for streams of data, helping perception systems to analyse processes that occur over time. Mathematical tools have been developed that analyse how an agent can make choices and plan, using decision theory, decision analysis, information value theory. Classifiers and Statistical Learning Methods Classifiers and Controllers are two types of AI applications. Classification forms a central part of many AI systems however, controllers do also classify conditions before inferring actions. Classifiers are functions that make use of pattern matching to determine a closest match. They can be tuned as per examples, making them very attractive for use in AI. These examples are known as patterns or observations. Each pattern belongs to a certain predefined class in case of supervised learning. All the observations combined with their class labels are known as a data set. When a new observation is received, that observation is classified based on earlier experience. A classifier can be trained in many ways. Neural networks A neuron is a cell in the brain whose principal function is the collection, processing, and dissemination of electrical signals. The brains image processing capacity is considered to emerge mainly from network of neurons. A neural network is an interconnected group of nodes, similar to the large network of neurons in the human brain. Neural networks are designed to distinguish patterns in data and forecast an output from a given set of data. Neural networks need to be trained on the data before it can predict or learn. In this way they learn from examples similar to the way a child learns. Computer learning skills that are developed for neural networks are used in a class of computer programs called expert systems. Expert systems also learn from experience and get better at their job, the longer they are doing it. Control Theory Control theory is the foundation of AI and deals with designing devices that act optimally on the basis of feedback from the environment. Initially, the mathematical tools of control theory were quite different from AI, but the fields are coming closer together. Control theory, has many important applications, especially in robotics. Languages AI researchers have developed several specialized languages for AI research, including Lisp and Prolog. In AI, the automation or programming of all aspects of human cognition is considered from its foundations in cognitive science through approaches to symbolic and sub-symbolic AI, natural language processing, computer vision, and evolutionary or adaptive systems. It is inherent to this very complex problem domain that in the initial phase of programming a speci ¬Ã‚ c AI problem, it can only be speci ¬Ã‚ ed poorly. Only through interactive and incremental re ¬Ã‚ nement does more precise speci ¬Ã‚ cation become possible. This is also due to the fact that typical AI problems tend to be very domain speci ¬Ã‚ c therefore, heuristic strategies have to be developed.. Applications of AI General The probable applications of Artificial Intelligence are plenty. Application of AI is possible in all fields, requiring intelligent analysis, precision and automation. They stretch from the military to the entertainment industry, to big establishments dealing with large amount of information such as banks, hospital and insurances. AI can also be used to predict customer behavior and detect the trends. There are many general fields where AI can be very usefully utilized for Autonomous planning and Scheduling, Autonomous Control, Medical Diagnosis, Logistics Planning, and Language Understanding, Problem Solving, Game Playing  [5]  . Some of the important applications are appended below: Pattern Recognition Pattern recognition is the area of research that studies the operation and design of systems that identify patterns in data. When a program makes observations of some kind, it is often programmed to compare what it sees with pattern e.g face, fingerprint or handwriting recognition. Important application areas are image analysis, character recognition, speech analysis, man and machine diagnostics and person identification. Bio-Informatics Bioinformatics is the application of computer technology for the management of biological information. AI provides several powerful algorithms and techniques for solving important problems in bioinformatics. Approaches like Neural Networks, Hidden Markov Models, Bayesian Networks and Kernel Methods are ideal for areas with more data but very less theory. The goal in applying AI to bioinformatics is to extract useful information from the wealth of available data by building good probabilistic models. Data Mining An AI powered tool that can discover useful information within a database that can then be used to improve actions. Data mining  is the process of extracting patterns from  data. Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. It is currently used in a wide range of profiling practices such as marketing,  surveillance,  fraud  detection, and scientific discovery. Expert Systems An expert system is a computer program that represents the reason with knowledge of some specialist subject with a view to solve problems or give advice  [6]  . It is the knowledge-based applications of artificial intelligence that have enhanced productivity in almost all fields such as business, science, engineering, and the military. With advances in the last decade, todays expert systems clients can choose from dozens of commercial software packages with easy-to-use interfaces. Diagnosis and Trouble-shooting explain the development and testing of a condition-monitoring sub-module of an integrated plant maintenance management application based on AI techniques. It is mainly knowledge-based systems, having several modules, sub-modules and sections. Computer Vision It is essential for computer to perceive the objects. Vision includes the acquisition and processing of visual information both. AI enabled technologies have made possible many amazing achievements. Vehicles that are able to steer themselves safely along highways, and computers that can recognize and interpret speech or facial expressions. AI supported vision technology has made many applications possible. Some of them are like 3D modeling, image stabilization, image synthesis, surgical navigation, handwritten document recognition, and vision based computer interfaces. While explaining success of an autonomous system trial supported by computer vision Russel and Norvig mentioned: The ALVIN computer vision system was trained to steer a car to keep it following a lane.   It was tried in the Carnegie Melon University (CMU) NAVLAB computer controlled minivan and used to navigate across the United States for 2850 miles it was in control of steering the vehicle 98% of the time. A human took over the other 2% mostly at the exit ramps. NAVLAB has video cameras that transmit road images to ALVIN, which then computes the best direction to steer, based on experience from previous training runs.  [7]   Image Processing Perception appears to be an effortless activity for humans however, it requires significant amount of sophisticated computation. The team associated with image formation and processing is concerned with research issues related to the acquisition, manipulation, and synthesis and distribution of images. In AI, applications include video phone, video conferencing, teleconferencing, and multimedia databases. Progressively, this research has combined image or vision with audio or speech. For example in the video indexing project, the group is using both visual and audio cues to derive semantic labels for video shots. Robotics Robots are physical agents that perform tasks by manipulating the physical world. Robots are comprised of several systems working together as a whole. Robots are widely used in assembly plants, space stations, and hospitals and now in homes also. Other type of mobile robots includes unmanned land vehicle, unmanned aerial vehicles and autonomous underwater vehicle. Knowledge Representation and Reasoning The representation of knowledge and the reasoning processes that bring knowledge to life are the two concepts, central to the field of AI. The knowledge representation means encoding real world, commonsense etc in a format that is both readable and understandable by the computer. Logical Agents is the representation of knowledge and the reasoning processes that bring knowledge to life. Logic is the primary vehicle for representing the knowledge throughout and Semantic webs describe things in a way that computer applications understand. Gaming Game playing was one of the first tasks taken by AI. Games, unlike other problems, are interesting because they are too difficult to solve. Games like the real world require the ability to make some decisions even when calculating the optimal decision is not feasible. Games also penalize inefficiency severely. Game playing research has contributed in many ideas on how to make best possible use of time. AI techniques are used in computer and video games to produce the illusion of intelligence in the behaviour of non-player characters. The techniques used typically draw upon existing methods from fields that include control theory, robotics etc. IBMs Deep Blue became the first computer programme to defeat the world champion in a chess match when it performed better than Garry Kasparov in an exhibition match. Military Applications The military applications of Artificial Intelligence are spread over large areas of military functions. Some of the military functions where AI techniques are being used or have potential use are given below. Operations Command and Control Command and Control is considered as one of the most important functions of military operations. In a networked centered scenario of battlefield with host of sensors deployed at different stages and the amount of data flowing between various centres, the time available for decision making is at premium. The information overload sometimes can impair the decision making hence require intelligent filtering of information to take timely and appropriate decisions. AI is used in playing a decisive role in reducing the load on the human beings in the loop and at times taking autonomous decisions as and when warranted. Navigation The availability of Global Positioning Satellites (GPS), Inertial Navigation Systems (INS) and autopilot along with host of sensors and On-board computers has helped in overcoming certain human limitations and resulted in safe and efficient management of flying aircrafts. ISR Intelligence, Surveillance and Reconnaissance are the key elements of battlefield management. Over time the battlefield scenario has undergone dramatic change and so as the means of identification, surveillance and reconnaissance. Advancement in technology in many spheres has offered sensors with high sensitivity, small sizes and better visibility. AI has contributed significantly in this regard in terms of ground, aerial, space and underwater ISR capabilities.   Unmanned Aerial Vehicles (UAV) using AI offer tremendous potential as intelligence, surveillance and reconnaissance platforms for early detection of security threats and for acquisition and maintenance of situational awareness in the crisis condition. Using their capabilities effectively requires addressing a range of practical and theoretical problems. Developments in the field of hardware and software technologies, as well as economies of scale, make UAVs feasible for increasingly diverse airborne observation mission s. Expert systems are promising technologies that manage information demands and provide required expertise. Thus they are well suited to many of the tasks associated with environmental impact assessment. While highlighting the contribution of artificial intelligence in battlefield surveillance using geographical information system, Maj Jagmohan Singh of Project Management organization, Battlefield surveillance system , Army HQ concludes: Transparency of the battlefield is a critical factor influencing the outcome of future battles. Battlefield transparency would provide a framework for `scientific and deliberate decision making. The dependence of commanders on paper maps and sand models for operational planning will have to be replaced by the latest GIS tools. These tools permit dynamic visualization of a 3D terrain model for seamless access, query and analysis across multiple types of military geographical data. Mapping and analysis is done using various GIS technologies incorporating satellites and aerial imagery, and photography of the target area. The future technologies would further enhance the visualization techniques and enable the commanders to take timely decisions to defeat the adversaries. However, emphasis needs to focus on refinement of some critical technologies such as Multi Sensor Data Fusion (MSDF), Artificial Intelligence and Interoperability issues.   [8]   Weapon System The weapon technology has seen constant change and has gained more lethality and effectiveness in its evolution. A host of modern weapons are in use or in process of development which can change the landscape of the battlefield. Missiles, Directed energy weapons, Standoff weapons, autonomous weapons etc are few examples of intelligent weapons and have even greater potential in future. Communications and Computers Communication is the core of all activities. In the age of modern communication, the geographical boundaries have come closer and visibility has improved to a great extent. The advent of satellite and availability of internet has revolutionized the communication. In future the success of battlefield will depend on maintenance of network connectivity and management of information from a large variety of sources. This will also made real time communication more important. The non availability of real time information can hamper the decision making ability of soldiers fighting the war. It may result in the failure of mission and even danger to personal survival. Wren, Ichalkaranje and Jain commented on the contribution and maturity of AI: Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly partly due to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications.  [9]   Network centric environment facilitates leveraging Artificial Intelligence to allow soldiers to access and share information throughout the entire network. Network centric environment provides coordination, where each node in the network helps provide a flawless, decentralized organization of intelligent resources. Maintenance Repair and Overhaul The fighting capability of the forces depends upon the serviceability and availability of the range of equipment held in its inventory. Most of the modern days equipments used for military application have certain defined life span. Also the demand of battlefield has ensured that highly sophisticated equipments should be made available for combat. This demands a system with quick fault diagnostic capability, easy maintainability and highly trained human resources along with modern ground facilities. Presently the expert systems are in use to analyze the faulty Printed Circuit Boards (PCB) of Radars or aircraft avionics using Automatic Test Equipments (ATE). Built-in Test systems are encouragingly being used with modern development of weapons. The techniques such as expert system and robotics are fairly in use in military application however has the potential to be exploited at much greater scale to expedite automation. Logistics Logistics is the life line in case of military operations. The various models of operations research have been employed in effective management of the logistics operation. The system of simulation has helped in optimizing the operation and AI has a great potential in assisting in planning and keeping the supply chain effective and efficient. Russell and Norvig highlighted that: During the Persian Gulf crisis of 1991, US forces deployed a Dynamic Analysis and Replanning Tool (DART) to do automated logistics planning and scheduling for transportation. This involved up to 50000 vehicles, cargo and people at a time and had to account for starting point, destinations, routes, and conflict resolution among all parameters. The AI planning techniques allowed a plan to be generated in hours that would have taken weeks with older methods. The Defence Advanced Research Project Agency (DARPA) stated that this single application more than paid back its 30 year inv