How the Presidential Candidates Views on Education Could Change College

The 2016 candidates for the Oval Office differ widely in their views, including what they believe about higher education. The countrys choice of a new president could greatly impact your ability to attend college or university and how much you pay for your college education. Donald Trump - (R, UPenn 68) Despite his vocal opinions on many topics, Trump has been surprisingly silent on the topic of higher education. In 2005, he began a non-accredited, for-profit college, although the school did not provide attendees with a degree. As a result, the New York State Department of Education requested that he rename Trump University, and he complied, changing it to Trump Entrepreneur Initiative. Trump also shared a social media comment in support of opening doors for international students to attend higher education institutions across the nation. However, he hasnt specifically spoken about any policies that he plans to implement when it comes to universities. Determining future implications for students proves challenging under Trump since he has no specific plans for change. Without some type of intervention, student debt would continue to rise with interest rates reflecting the market. Potential students might find the cost of college prohibitive, possibly keeping some of the brightest and best out of university. Bernie Sanders - (D, UChicago 64)) Sanders agrees with Clinton about the excessive costs of higher education and is well known for his belief that everyone should be able to attend school without incurring massive amounts of student debt. He plans to accomplish this by offering free tuition at all public higher education institutions, citing the model of countries such as Norway and Germany. Students with the lowest incomes should receive subsidies for books, living expenses and room and board, partly through work study programs. Furthermore, he wants to eliminate government profit on student loans by slashing related interest rates. He wants to permit those who have already amassed student debt to refinance at reduced rates. Wall Street speculators would bear the burden of this expense through a small tax. Similar to Clintons plan, new taxes will pay for Sanders proposal, although they will come from a different source. Again, his goal is to open the door for anyone who wants to attend college. Ben Carson - (R, Yale 73) As a retired neurosurgeon, Ben Carson has outlined some education plans as part of his campaign. He wants to use the education department to look into higher education institutions that are pushing any political biases. If they are found in violation, he proposes cutting their federal aid. He insists that colleges and universities should not be imposing their political beliefs on students, calling the practice propaganda. He thinks that the Department of Education should stop loaning students money for college and wants an easier process that streamlines financial aid and reduces student debt. However, he does not provide specifics on what that program will look like. Without details on what steps Carson will take to implement student loan debt reduction, its difficult to determine how higher education will be affected should he be elected. Hillary Clinton - (D, Wellesley 69) Clinton believes that the prohibitive costs of higher education keep people from achieving their dreams. She proposes no-loan tuition plans through the states, supported by federal grants. Furthermore, she says that the maximum that students should pay is 10 percent of their income when it comes to loan repayment. While the plan will cost an estimated $350 billion over the course of a decade, she plans to cut some tax breaks, including itemization, for the highest earners, which would need the approval of Congress. Clinton admits that taxes will pay for her proposal. Her plan opens the door for university attendance to students across the nation who cannot afford school. Ted Cruz - (R, Princeton 92) For the most part, Cruz has remained quiet about the topic of higher education. However, he supports academic merits and opposes affirmative action for college admission. When it comes to his personal Ivy League education, he claims that some liberals credit his academic success to affirmative action, which he vehemently denies. The removal of affirmative action would mean that race would no longer be a significant factor when it comes to a college application as students would now be admitted on the merits of their grades. He has not commented further on plans to change college education. Martin OMalley - (D, Catholic University of America 85) Martin OMalley has strong views on education and a detailed plan to make college debt-free for all students at an in-state, public higher learning institution. He believes that students and their families should be able to refinance their loans so that they can rid themselves of the burden of crushing student debt. Furthermore, he supports income-based plans, including basing public school tuition on the average state income and helping students with other significant expenses, such as room and board. In addition to advocating for loan forgiveness, he wants to see public schools freeze their tuition rates immediately. OMalleys plans would make college more affordable by increasing state funding for tuition. He makes no mention of taxes or other methods of supporting his plan. Looking to go to the same schools that these distinguished candidates attended? 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nam Chamsky essays

nam Chamsky essays His theories are about humans right, equalities, atrocity, genocide, effects of media in real life. We should begin by recognizing that for a good part of the population of the world, and probably the vast majority, it's been a crisis for a long time. It's now called one because it's starting to affect the interests of rich and powerful people. Up until then it was just starving people. According to Noam Chomsky by Micheal C. Haley, his ideas focus on how we treat people. It should begin by recognizing that for a good part of the population of the world, and probably the vast majority, it's been a crisis for a long time. It's now called one because it's starting to affect the interests of rich and powerful people. Up until then it was just starving people. Nowadays, We're dealing with real human beings who are suffering and dying and being tortured and starving because of policies that we are involved in. We as citizens of democratic societies are directly involved in and are responsible for, and what the media are doing is ensuring that we do not act on our responsibilities, and that the interests of power are served, not the needs of the suffering people, and not even the needs of the American people who would be horrified if they realized the blood that's dripping from their hands because of the way they are allowing themselves to be deluded and manipulated by t he system. The struggle for freedom and independence never is completely over. With him, people rely very crucially on a very slim margin for survival that's provided by dissidence and turbulence within the imperial societies, and how large that margin is, is for us to determine. About the atrocity, in the interview at MIT where he works, he said: I mean the great act of genocide in the modern period is Pol Pot, 1975 through 1978-that atrocity-I think it would be hard to find any example of a comparable outrage and outpouring of fury and so on and ...

Science and the Epidemiology of AIDS Essay Example | Topics and Well Written Essays - 1250 words

Science and the Epidemiology of AIDS - Essay Example To date low income nations are using the effects of the disease as strategies for intervention from industrialized nations and access to funds from donor agencies working hard to try and save millions of lives, leaving the questions open, "how far should aid go Is it true that donor agencies are using the situation for control of nations by manipulating the flow of aid" In 1983, prompted by the number of Africans living in Europe with clinical cases of AIDS, investigations began in Africa to determine the extent of the clinical problem of AIDS and transmission patterns in the region. What was of note to researchers was the nearly equal ratio of male to female cases of the disease with 90% having no high risk factors (Quinn 1986). In contrast, the industrial world exhibited higher cases in homosexual males and injection drug users. Over the proceeding two years, results from a studies done by Van der Perre P et , Vandepitte J et al and Serwadda D et al in Zaire (as cited in Quinn 2001), showed the presence of Aids in several urban areas in equatorial Africa. "Slim disease" was often the documented outward sign of the disease mainly prevalent in sex workers and their clients. This raised several discussions on the mode of transmission of the disease. It was not until the introduction of the test for HIV-1 was there greater understanding leading to be tter epidemiological study of the modes of transmission of the disease. The disease, considered endemic then, reached epidemic proportions in the 1970's and '80's with statistics for the year 1986 almost trebling the figures predicted by early researchers. Quinn's retrospective report (2001) shows just how far and fast the disease had ravaged the continent. Today one has only to get on the internet, watch the news or read a local paper to get a glimpse of the effects of the disease in Africa. It was evident as early as the 1980's that unless drastic measures were taken; Africa was losing her most productive age group to the effects of the aids epidemic. By 1987 statics listed by Sabatier in the article on Aids in the Developing World showed the highest number of new cases of HIV and AIDs were from central and eastern Africa with most of the cases being young sexually active adults both male and female in the age groups of between 15 and 40 years (1987 p 99 -103). In the same year the World Health Organization Aids Surveillance Report (as cited in Sabatier 1987) had statistics for over 40 countries, 36 reporting to WHO. It is difficult to get accurate statistics, as some countries are wary of the industrialized world especially after reports of scientific findings linking the origins of the disease to Africa. Over and above this, poor health delivery systems as well as lack of accurate demographic figures make it impossible to get accurate statistics. The modes of transmission are well documented and known to all, for Africa and the earliest recorded document being that of Quinn T.C, Mann J.M, Curran J.W and Piot P (1986). The main modes of transmission in African countries are mainly by heterosexual, blood transfusions as well as mother-to-child transmissions at birth or through wrong breast feeding practices (Sabatier 1987). This however does not discount the presence of gay communities on the continent. Gender, sexuality age and socioeconomic status play an important role in structuring vulnerability of a person to HIV infection. Ruganga A.O and Aggletoon P

Statutory Interpretation Business Law Assignment Essay

Statutory Interpretation Business Law Assignment - Essay Example Since statutes are presented in written form, it is within the court’s power to translate the written word into the actionable form of law i.e. known as breathing life to the law. However, due to the complexities of language and the imperfect nature of legislation, sometimes the intention or purpose of the law may not be conveniently passed in the wordings of the various Acts. This is where the courts derive their power; ensuring that the intention of Parliament is carried into the law. The power of the court to interpret statutes i.e. statutory interpretation has generated controversy for as long as Parliament has been in existence. This is because of the subjective nature of interpretation which relies heavily on the beliefs and understanding of the presiding judge. Over time, judges have been accused of usurping the role of Parliament and ‘making law’ by giving interpretation to statutes in a manner that suits their version of the law. Lord Denning himself once drew criticism in Magor and St Mellons v Newport Borough Council (1952) HL when he remarked that We do not sit here to pull the language of Parliament to pieces and make nonsense of it. We sit here to find out the intention of Parliament and carry it out and we do this better by filling in the gaps and making sense of the enactment than by opening it up to destructive analysis (pg. 25). While he well intended to maintain Parliament’s supremacy by attempting to interpret acts based on its intention, he went a bit overboard by suggested that the courts could ‘fill in the gaps’ in the law which in itself would be tantamount to making law. On appeal to the House of Lords, Lord Simonds described Denning’s interpretation of the powers of the courts as a â€Å"naked usurpation of the legislative function under the thin guise of interpretation.† The House of Lords instead stated that gaps disclosed in laws can only be remedied through appeals. The extent o f the judicature’s power to interpret law remains blurred which is a major reason judges have often been accused of making law; a role not within their mandate. In Fischer v Bell (1961) and Stock v. Frank Jones (Tipton) Ltd. [1978] 1 WLR 231, the interpretation of the courts of statutes was so distasteful to Parliament that the rulings themselves were overturned through statutes in the same year they were made. This shows that the powers of interpretation are sometimes abused as judges attempt to ‘redefine’ statutes which in their opinion are ambiguous, unfair or unjust. Over the years, several rules of interpretation have come up all in an attempt to guide the courts in the correct usage of their power or in a manner respectful of the separation of powers doctrine. Despite these rules, Twining and Miers (2010) state that over 50 percent of High Court cases and 90 percent of cases before the House of Lords involve aspects of interpretation of the law. Since the c ourt’s interpretation of the law determines how they apply it e.g. in criminal law for purposes of sentencing, the interpretation of the law continues to be a major cause of appeals and a major driving force for litigation. At this juncture, it is necessary to state that the courts may have powers to apply the law; this power is merely incidental to the interpretation that the court makes of the pertinent law. In fact, this power is often

MyReligionLab Assignment Week 2 Essay Example | Topics and Well Written Essays - 250 words

MyReligionLab Assignment Week 2 - Essay Example They also believe in the karma, the law of cause and effects that make an individual to create his own destiny by thoughts, words, and deeds. In the context of Vellaringat (2002), religion is a set of beliefs (Hindu beliefs) that that relate humanity to supernatural realities. This brings the art of worship and ritual practices as observed by the Hindus. Self seeking, through the intense meditation in order to realize the whole self identity does involve acknowledging the gods, according to the Hindu religion and beliefs. Many of the Hindus have a primary focus on fulfilling their social, moral, political, as well as cultural duties and responsibilities appropriately to their gods in order establish their positions in life. As it may seem, there are similarities with other religious traditions and beliefs in this context. The Christians and the Muslims societies as well believe in the supreme God who determines destiny and affect their social, cultural, as well as moral motives. Considering the Hindus beliefs, practices, and holidays, one similar fact that connects these religions to the people’s daily lives is the ir commitments to devotion, liberation, and knowledge on what they believe in their respective religions. It is therefore true that religious practices centers daily lives of many and dictates their social, traditional, and cultural

Information Filtering System Based on Clustering Approach

Information Filtering System Based on Clustering Approach A PRIVATE NEIGHBOURHOOD BASED INFORMATION FILTERING SYSTEM BASED ON CLUSTERING APPROACH ABSTRACT The quantity of web information has been increased day by day due to fast development of internet. Now-a-days people make their decision based on the available information from the internet. But the problem is how the people successfully choose or filter the useful information from the enormous amount of information. This problem is referred as information overload. Recommendation System is a supportive tool to resolve the information overload problem. It is part of information filtering system used to recommend the user based on their own interest, neighborhood similarity and past history. Collaborative Filtering is one of the popular techniques widely used recommendation system. Every recommendation system should ensure privacy for both user’s neighbour and their data. To overcome the scalability and model reconstruction problem, a power graph based private neighborhood recommendation system is proposed to ensure the user’s privacy. First, the compressed network is constructed and then the feature set is extracted from the compressed network using transformed data. The data is transformed using hybrid transformation fuses principal component analysis and rotation transformation to protect users privacy with accurate recommendations. Finally the item to be recommended is predicted which achieve better performance than the existing technique. MovieLens Dataset is used to evaluate this method. INTRODUCTION Recommendation System is one of the information filtering system which provides valuable information to the users by filtering the information according to user’s interest. Traditional approaches of recommendation systems are collaborative filtering, content based filtering and hybrid Approach. Content Based Filtering (CBF) approach predicts the recommendation based on the rating given by the user for the similar items in past history. Collaborative Filtering (CF) recommends the user based on rating of that item by similar users. Hybrid approach combines both the approaches. All the approaches have their own advantage and disadvantage. CF mainly classified as memory based CF and model based CF. Memory based CF first calculate the similarities between the requested user and all other user to find the neighbors then calculate the prediction based on identified neighbors rating pattern. Model based method first built a model based on the preference of the user. Main aim of the recommender system is to minimize the prediction error. The main issues in CF recommender system are scalability, sparsity and privacy. Scalability: Large number of users and items in the network led to the increase in the computational complexity of the system. In E-commerce, scalability plays a important issue because it contain huge number of users. Sparsity: All the users dont show their interest to rate all the items they interact private, which will lead to data sparseness in the system. This will not give exact recommendation to the seekers. Cold Start: Lack of information for new items and users in recommendation system will leads to unpredictable items in the system. Privacy: Users may provide false information inorder to protect their personal information. This leads to inaccurate recommendation. The proposed work mainly focuses on two fundamental issues in CF namely scalability and privacy. The first challenge is how to improve the scalability of CF, because these systems should search the entire user for finding the neighbors. The second problem is how to protect the individual users privacy while prediction. Both an issues lead to poor performance of the system. So the important challenge is to handle both a situation properly for better performance. LITERATURE SURVEY Recommendation system helps the people to get exact information based on neighbors’ pattern. Remarkable growth in e-commerce site makes the online vendors to develop their sales and profits. They use this technique which suggests product to users’ by their neighbors’ preference about the item. Scalability issue in RS mainly due to enormous growth in users tends to decline in accuracy of prediction on recommendation. Clustering approach reduces scalability problem by grouping the similar users. Recommender System may demand the users’ to expose their ratings to recommendation server to give a proper recommendation. But exposing the rating may allow the recommenders to learn the private information about users. Revealing rating may also direct to do violent behavior by several competitive companies’. CLUSTERING IN RECOMMENDER SYSTEM Several different clustering methods are adapted to reduce the scalability problem in RS. A new cluster based matrix tri-factorization is proposed to cluster the user and item simultaneously to get a better recommendation in model based CF. But when the new user enter the system it is necessary to rebuilt the whole model again for other user [].In [0] a cluster based binary tree is built by splitting the dataset and the recommendation is predicted based on the average rating of cluster. Later [] a combined k-means bisecting clustering is performed to overcome the scalability problem while preprocessing and pseudo prediction is adapted. But performance is not much better. Community based clustering model based CF is proposed [] to predict the recommendation but it underperform on outliers. Multilevel clustering is adapted to extract the subgraph which is clustered and propagated to reduce scalability which improved the performance than existing approach. But it will be more complicate d when the aspect of the network increases. Therefore it is necessary to group the data in all the aspects to reduce the scalability. PRIVACY PRESERVING RECOMMENDER SYSTEM In CF, neighbors are identified by collecting the information for the entire user. Thus the server maintain user preference, purchase, usage data etc which may contain identifiable information may violate the privacy. There are several techniques to protect the user’s sensitive information []. Initial method to ensure the privacy protection in CF was proposed by canny (2002a, 2002b), mainly focus on aggregation. In this method sensitive data are aggregated with some common distribution. In cryptographic approach, Individual user data can be protected using homomorphic encryption to avoid exposing of individual data but it requires high computational cost [5]. In perturbation approach, users mask their data before storing it in a central server. The central server collects the disguised data instead of original data to provide predictions with decent accuracy [18]. In [2] a randomized response techniques (RRT) is proposed to preserve users’ privacy by generating naive Ba yesian classifier (NBC) based private recommendations. Another technique, data obfuscation was used to implement privacy preserving collaborative filtering algorithm [16]. In this technique, sensitive data are obfuscated through additive or multiplicative noise in order to protect individual privacy before allowing for analysis. The actual data can be revealed in this technique by applying reverse engineering process [7]. Sensitive information is either concealed or eliminated for the purpose of analyzing the data to extract the knowledge in anonymization technique. The major fault of this technique is some distinctive data may lead to the re-identification of data [1]. In proposed work, a scalable privacy preserving recommendation system is proposed. First the user to user network is constructed from the user preference then compressed network is formed based on the power graph approach. Then feature set extracted from the compressed network based on transformed rating to ensure the privacy during prediction. Finally the linear prediction model is adopted instead of similarity prediction to improve the accuracy besides reduces the complexity. OBJECTIVE To protect the individual’s neighbour information while prediction based on clustering approach this reduces complexity of model reconstruction. To protect the individual data using data transformation technique. PROBLEM FORMULATION A cluster based approach is proposed to protect the individual neighborhood privacy and hybrid data transformation technique is proposed to protect the individual data with accurate recommendation using feature extraction based linear regression prediction. MODULES Data Transformation Experiment is performed using MovieLens Public (MLP) dataset which is the standard dataset to show the better performance of the proposed method. MovieLens dataset is collected by the GroupLens Research Project at the University of Minnesota. This data set consists of three different files of three different sizes 10M, 1M and 10K which mainly contain ratings of different movies provided by the users. To evaluate the proposed method 1M size dataset is used which contains 6040 users, 1 million ratings and 3900 items. The rating values are on five star scales, with five stars being the best and one star being the least. Data collected consist of four attributes separated with double colon as the delimiter [userid :: itemid ::rating :: Timestamp]. To evaluate the proposed work userid, itemid, rating is extracted from the dataset and then extracted data is converted into user x item matrix with dimension (6040 x 3952).Unrated items are filled with value zero to overcome computation comple xity. Data Transformation A hybrid data transformation technique which fuses Principal Component Analysis (PCA) and Rotation Transformation (RT) is proposed to transform the data in order to protect the user’s data. The input to the PCA technique is the rating matrix. This technique first finds the principal components and then rotates these components which cannot be reverted easily. Rotation transformation will be efficient by identifying the appropriate range of angle such that to satisfy the least privacy requirement. Optimum privacy threshold is determined from range of angle which leads to good privacy protection effect. To determine the range of angles, sequence rotation should be performed on vectors with successive angles. For each pair of attributes, pairwise optimum privacy threshold is assigned by multiplying the privacy threshold and the privacy angle which should be maximum. To determine the privacy angle, calculate the variance of each attribute. For each pair of attribute, minimum varia nce will be considered as privacy angle. After determining pairwise optimum privacy threshold, select the range of angles to transform the pair of attribute. While choosing the range of angle make sure that it satisfying the following constraint which is mentioned in Eqn(1) Var(Pi-Pi) ≠¥PoptEqn(1) An angle is randomly chosen from the interval to rotate each and every pair of principal component. After rotating the principal component, it is multiplied with normalized data in order to obtain the transformed data. The Transformed value of the original data for the data is shown in Table 2. Private Neighborhood Network Construction Original network is compressed using power graph analysis. Power graph analysis is a representation of complex network which represent the graph into power graph without loss of information. Graph can be clustered to construct a power graph using modular decomposition method in which modules represents the nodes with same neighbour. Power graph cluster both, the nodes and edges to obtain the most compressed network. Power graph analysis is widely used several biological networks such as protein-protein interactionnetworks, domain-peptide binding motifs,Gene regulatory network and Homology/Paralogy networks. Matrix R can be used to represent the social relationship between the users. If any two users rate the same item then there will be a relationship between them. Thus the user-user network is represented as where U is the set of users represented as nodes and is the set of relationship denoted as edges, and then a power graph is a graph defined on the power set of nodes which are connected by power edges. The concepts of power graphs are as follow: if there is a power edge between two power nodes, then nodes in one power nodes are connected to all the nodes in the second power node. In same way if all the nodes are connected to each other which is represented as power node with self loop. Based on power graph analysis this module involves two steps, power node identification and power edge search. Power nodes are recognized using hierarchical clustering based on jaccard index. The greedy search is performed to identify the power edge. Feature Set Extraction After construction of private network, feature set of each user is extracted by categorizing the users into cold start user, powerful user, and malicious user. Cold start is a user who rate exactly twenty items. Powerful user is user who rate more than thirty five items and malicious user who rate less than twenty five items but the difference between any ratings of a particular item and the standard deviation of that item is greater than one. For the constructed compressed network following features are extracted for each category of the users to predict the rating of unrated item. Feature set of particular user includes features of directly connected power node and Friend Of A Friend (FOAF) in the other power nodes. Each category is measured according to number of particular category of user present in the power node and their joint probability of that particular category. Bayes theorem is used to calculate the most probable rating each category of user. The following Table shows t he feature set measured for each user. Table 5.2 Feature Set of User X Linear Regression prediction From the above extracted features a linear predictive model is constructed which is user for predicting particular item. Then top predicted items are given as recommendation to user. The model takes the following form as in Equation. (5.6) (5.6) where ÃŽ ± represents the slope of the dependent variables, X represent the feature vectors and represents the error vector which is assumed to be zero. In linear regression, the value to be predicted is commonly computed from the best fitting line which reduces error in prediction. PERFORMANCE ANALYSIS: The proposed method is preserves both the individual neighbors privacy and data privacy. It also reduces the scalability issues and give accurate recommendation when compared to the previous work (privacy preserving information filtering system). MAE obtained is compared with the proposed method in previous Chapter TRPC as in Table 5.7. Figure shows that MAE is reduced to 0.62 because of coupling of clustering approach with data transformation to handle large volume of data. CONCLUSION The power graph analysis helps to overcome the scalability problem by compressing the original network and results better recommendation to users. The existing methods apply power graph analysis to various domains for analyzing complex networks in a simpler way. And at the same time it also preserves the communities’ information. Therefore, in proposed work this type of clustering approach is used to preserve the neighbours information which also results better prediction. The efficiency of the proposed methodology is evaluated with the experimental results using MovieLens dataset. It performs better compared data transformation and clustering approach. This type of cluster based collaborative filtering recommendation helps to reduce the edges in the original network without loss of any information.

Corporate Social Responsibility Essay -- Social Responsibility Essays

Business organizations regularly run into demands from various stakeholders groups when conducting day-to-day business. These demands are generated from employees, customers, suppliers, community groups, governments, and shareholders. Thus, according to Goodpaster, any person or group of people that can shape or can be shaped by attainment of the objectives by an organization is considered a stakeholder. Most business organizations recognize and understand their responsibilities to these groups and endeavor to honor and fulfill them. These responsibilities are often communicated to the public by a statement of principles or beliefs. For many business organizations, corporate social responsibility (CSR) has become an essential and integral part of their business. Thus, this paper discusses the two CSR views: the classical view and the stakeholder view. Furthermore, I believe that the stakeholder view has brought ethical concerns to the forefront of businesses, and an argument shall be made that businesses would improve both socially and economically if CSR, guided by God’s love, was integrated into their strategic planning. The classical view of CSR is a prominent ideology which business organizations are seen merely as profit-driven organizations. Simply put, businesses work for the sole purpose of making a profit. Thus, this profit motive is the sufficient and unique social identifier that separates a business organization from other institutions in society. These business organizations have a limited, yet essential role in society. Social concerns are considered important, but businesses, in the classical view, are focused solely on the economic activities and are judged accordingly. By having a limited role in society (i.e.,... ...oncerns to the forefront of businesses. In this paper I have suggested that business can improve both socially and economically by incorporating and integrating a CSR program, guided by God’s love, into their strategic planning. Strategic planning of CSR creates a mutual beneficial relationship between a community and a business organization. The community wins by having a business that is sensitive to their needs and responsive to their concerns, and the business wins by developing competitive advantage in the market that leads to long-term profitability. A business needs to incorporate God’s love when developing CSR policies in order to maintain the trust and the integrity of the relationship with the community. With solid strategic planning coupled with CSR, businesses can set the direction that provides the greatest benefit to themselves and communities.