The Essay The Consequential Concerto - 1206 Words

The Consequential Concerto â€Å"Without Freedom of Thought, there can be no such Thing as Wisdom; and no such Thing as publick Liberty, without Freedom of Speech†¦ And this is the only Check it ought to suffer, and the only Bounds it ought to know,† Benjamin Franklin (Benjamin Franklin, Silence Dogwood, No. 8). Throughout the course of human history, clans of people have turned against another from a mere bigoted belief. This usually constitutes physical abuse, humiliation, death, and perhaps most importantly, denying self expression. Two instances of these groups being denied self expression would be the Jews of the Holocaust and the LGBTQ+ community. Although though LGBTQ+ members today do not suffer even a fraction of what Holocaust victims†¦show more content†¦This was a direct contradiction to article 19 as the Nazi’s forced the Jews into a tranced state of internal affliction . In the same light, Elie yet again questioned his own mental and emotional foundation when he stated , â€Å"Blessed be God s name? Why†¦ would I bless Him? Every fiber in me rebelled†¦ Because in His great might, He had created†¦ factories of death? How could I say to Him: Blessed be Thou†¦ who chose us among all nations to be tortured day and night, to end up in the furnaces?†(Wiesel 33). This excerpt illustrates how the Nazi’s use of death camps indirectly smothered Elie’s humanity and moral psyche. By eradicating so many people of his affiliation and restricting his religious practice, the Nazi’s destroyed all humanity left in Elie Wiesel. Equally important would not only be Elie’s experiences during Night, but also a minor character’s experiences, Juliek. Juliek was a magnificent violin player as well as Elie’s friend during his incarceration in the music block of Buna. Juliek was fond of playing an unnamed concerto by Beethoven however, during his imprisonment in Buna, he was punished for performing this because the Nazi’s proclaimed Jews were below people of German descent (Wiesel 49). Beethoven was German. Juliek’s emotional outlet and form of expression was music, so by restricting what he could play, the Nazi’s took his morale while simultaneously breaking article 19. This was depicted in Night: The darkness

Othello and the Virtue of Love Essay - 2758 Words

Othello and the Virtue of Love The love of the protagonist and his wife in William Shakespeare’s trgedy Othello can not stand up against the repeated assaults of the sinister Iago. Let us in this essay search for and comment on the examples of love found in the play. Helen Gardner in â€Å"Othello: A Tragedy of Beauty and Fortune† highlights the love between the hero and his beloved: The love between Othello and Desdemona is a great venture of faith. He is free; she achieves her freedom, and at a great cost. Shakespeare, in creating the figure of her wronged father, who dies of grief at her revolt, sharpened and heightened, as everywhere, the story in the source. Her disobedience and deception of him perhaps†¦show more content†¦Act 1 Scene 1 shows Roderigo, generous in his gifts to the ancient, questioning Iago’s love for the former, whose concern has been the wooing of Desdemona. Roderigo construes Iago’s love for him as based on the ancient’s hatred for the Moor. Thus the wealthy suitor says accusingly, â€Å"Thou toldst me thou didst hold him in thy hate.† And Iago responds, â€Å"Despise me, if I do not.† Partly out of hatred for the general and partly out of proving his faithfulness to Roderigo’s cause, Iago asserts in detail the reasons for his hatred of Othello, who has given the lieutenancy to Michael Ca ssio, a Florentine. Secondly, Iago suggests that Roderigo and he awake and disturb Brabantio, the father of Desdemona: Call up her father, Rouse him: make after him, poison his delight, Proclaim him in the streets; incense her kinsmen, And, though he in a fertile climate dwell, Plague him with flies: though that his joy be joy, Yet throw such changes of vexation ont, As it may lose some colour. (1.1) Thus a hue and cry is raised in front of the senator’s residence – partly for the sake of Iago proving his love for Roderigo so that the financial rewards will continue coming to the soldier. Once the senator has been awakened, Iago makes a series of loud, crude, bawdy allegations against both the general and Desdemona. Strangely, the senator is not incensed by these, but rather by the fact that his daughter hasShow MoreRelated Redemption in Death in Othello Essay1562 Words   |  7 PagesRedemption in Death in Othello      Ã‚   The brilliance of a tragedy lies in its ability to maintain its moral and the values it explores even in the tragic ending or in the downfall of its heroes. William Shakespeare does just this Othello, so quintessentially that the deaths in the end do not only refrain from undermining or canceling out the virtues of the play, but they actually restore them to the deceased, who have died because they have lost them.   In this play, love, loyalty, and honestyRead Moreâ€Å"Othello’s Virtue and Valour Ultimately Make Him Admirable.† to What Extent Do You Agree with This View?1031 Words   |  5 Pagesone often associated with virtue, courage and valour. 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Whites argument is followed by a series of points, each of which is aimed to help his audience realize that the character they most readily identify with is not Othello (the tragic hero of the drama)Read MoreThemes in Othello Essays994 Words   |  4 PagesThemes in Shakespeares Othello Throughout Shakespeares play, Othello, there are many themes interwoven to describe the authors perspective of the true nature of a mans soul. Three themes critical to the play are doubt versus trust, monstrous imagery and the fallible love of man. One central theme of the play is the major contrast of doubt versus trust. For whatever reason, Othellos trust of Desdemona is too weak to resist Iagos accusations. As happens in many of Shakespeares works, miscommunicationRead MoreOthello : Racism And The Moor1013 Words   |  5 Pages Othello: Racism and the Moor William Shakespeare’s Othello uses the racial tensions of the period to enhance the execution of the play subtly. At the time of his writing, ethnic minorities were so disregarded, almost to the point of being ignored, yet Shakespeare chooses to make the protagonist a black male who rises to power. Repeatedly throughout the play, the contrast of black and white as opposites permeates almost every plotline. When referring to Othello, the otherRead MoreOthello : Vulnerability Destroys Virtues Of A Great Leader1601 Words   |  7 PagesOthello: Vulnerability Destroys Virtues Of A Great Leader Thesis: Even though Othello considers to be vulnerable is a weakness, his temperance and prudence should never come in conflict with his leadership principles because Iago despises Othello and manipulates him therefore, Othello becomes vulnerable resulting in his death. 1. Othello believes that being vulnerable is a sign of weakness. A. 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The question then arises whether there is sufficient evidence to all-together condemn Othello as a malevolent and innately evil man, or such evidence that he was simply deceived by Iagos treachery and should be excused for his actions. Yet, as the playRead MoreThe Human Mind Is A Death Trap862 Words   |  4 Pagesmoney or love, influence and harm the choices they make. In Othello’s case the self-destruction that harmed him was letting the people around him manipulate his decisions. He also let love that became jealousy consumed him. Othello made bad decisions that affected and destroyed not only the people who matters in his life but most importantly t his led to his own self-destruction. Othello let his demons get through him and thinks about false accusations about his wife. In act 3 scene 3, Othello furiously

Business Intelligence with Data Mining Free Essays

Business Intelligence with Data Mining Abstract Banking and finance institutions are growing very fast in this globalization era. Mergers, acquisitions, globalization have made these institutions bigger. No doubt, the data also grow real huge and more varied. We will write a custom essay sample on Business Intelligence with Data Mining or any similar topic only for you Order Now Big data storage such as data warehouse and data marts are provided to give a solution on big data storage. On the other sides, those data are needed to be analyzed. Business intelligence finally comes in as a solution in analyzing those huge data. Business intelligence especially with data mining can create a solution in further decision making. With various tools and techniques, data mining has been proven in many aspects of business. Hidden informations that stored inside either data warehouse or data marts can be gained easily. In example, those hidden informations are market and economy trens, competitor trends, competitive price, good products and services and also can provide better customer relationship management. There is still one benefit in business intelligence with data mining that this paper will focus on, i. e. risk management and frauds and losses prevention. One of product from banking and finance institutions is credit loans. It is really a high risk business, but with business intelligence with data mining especially classification and clustering techniques, it can be maintained and implemented safely and of course with low risks, minimized frauds and losses and increased profits and revenues. Keywords : Banking and Finance, Business Intelligence, Data Mining, Risk Management, Credit Loans Introduction Banking and Finance institutions are growing rapidly nowadays. For one institution, there are more than one offices or branches in one country or even in different country. Globalization, mergers, acquisitions, competitions, market changes are some of the reasons behind why are they growing fast. As those banking and finance institutions grow, so do the data. In this case, banking and finance institutions probably have much more data than other institutions. Every single customer or people has one or more accounts in one institution or more. The challenge is how to maintain those data easily, how to make good decision among those data, how to create good product for customers and how to retain good customers that can bring much more profits and increase revenues. For those that can not maintain data and make a decision for further movement without analyze the data before will find it hard to be success or even lose in competition with other banking and finance institutions. Some of key success factors in banking and finance institutions, such as : 1. Customer satisfaction Good customer management and good product are the key to satisfy customer. If the institution could manage the customer well and offer good product that can produce benefit to both sides then it will guarantee customer will be very satisfied. 2. Customer loyalty There is no guarantee that satisfied customers will be loyal. Strategies and tactics are needed to retain those customers. 3. Increased profit revenue Similar with business institutions, gaining profit and increase revenue are the most important thing. 4. Minimal risk With many customers, banking and finance institutions need to analyze the risks that probably could happen. Not all of customers are good customer. Fraud or loss might happen. 5. Readiness for new markets to increase customer Markets are changing rapidly. Winning the competition means winning the customer. Offered products are the key here such as higher interest, free admin cost etc. 6. Efficiency of operations Since banking and finance institutions have several branches and many customers, the challenge is to make operations in daily transactions become efficient. Problems in Banking and Finance Institutions Similar with other institutions in business, banking and finance institutions also have some of problems in their business. Below are some of those problems : 1. Separated data instance Data are separated through branches all over the place. The banking and finance institution will find it hard to collect and analyze the data. This will also impact in decision making because decision should be made after analyzing all of the data. . High risk Banking and finance institutions have many customers and not all of those customers are good customer. Need to find out whether the customer is realible or not. 3. How to detect fraud and prevent loss Frauds and losses might happen in banking and finance institutions. Fraud in credit loans will cause loss to the institution. 4. How to create good customer relationship To compete in the market and winning customer, banking and finance institutions need to create good customer relationship to satisfy customers and make them loyal. 5. How to create good product Product is one the aspect that customers consider. Create a good product and can compete with others product will impact in customer winning. 6. How to find the hidden information inside those data to ease the decision making Huge data are needed to be analyzed and there are some hidden informations in those data that could affect the decision maker in making the decision. If the decision made is crucial one, it could lead to future success. Business Intelligence Business Intelligence can be defined as an ability of an enterprise to comprehend and use information in order to increase the performance. Business intelligence has several activities, procedures and applications. Some of those that mostly used are : Data Warehousing, Data Marts, OLAP Tools, tools for Extract Transform and Load (ETL), Information Portals, Data Mining, Business Modelling, etc (Katarina Curko, 2007). Business Intelligence can also defined as the process of gathering high-quality and meaningful information about the subject matter being researched that will help the individual(s) analyzing the information, draw conclusions or make assumptions (Muhammad Nadeem, 2004). In this paper, we shall focus more in data mining. Data mining works with data warehouse and data marts for data storage and extract transform and load (ETL) tools. Some of advantages by using business intelligence with data mining: 1. Gain profit and revenue for enterprise With business intelligence, the enterprise can gain the data access easily and integrated inside data warehouse data marts. So the enterprise can service customers better and quicker which will impact in profit and revenue increment. 2. Decision making With data mining in business intelligence, the enterprise can gain the hidden informations in those huge data and can make quick and easy decisions. . Expand the market segment With the ease of decision making, the enterprise can make decision in markets such as price, discount, etc which will impact in winning the market competition. Data Mining Data mining refers to computer-aided pattern discovery of previously unknown interrelationships and recurrences across seemingly unrelated attributes in order to predict a ctions, behaviours and outcomes. Data mining, in fact, helps to identify patterns and relationships in the data (Bhasin, 2006). Some of goal examples in using Data mining: 1. Forecasting market price With data mining, enterprise can predict the market price and decide on the best price to compete the price in market. 2. Cross-selling and up-selling analysis Data mining can be used to analyze market based on products. It means enterprise can make cross-selling or up-selling to their products to optimize or increase the sales. 3. Profiling customers Data mining can be used to segment customers depends on the category. For example we categorize customers by their profit or revenue. 4. Manage customer retention Not only enterprises data, data mining can be used to manage customer data which will impact in better customer relationship management. [pic] Figure 1. Overview of Business Intelligence with Data Mining Source of data that we shall process come from various sources such as customer data, market data, transaction data, product data, service data etc. As mentioned above, those huge and heterogeneous data will be stored in data warehouse and data marts. Before entering either data warehouse and data marts, those data will be extracted, cleaned up and sometimes transformed into different types of data. Then it will load the results into data warehouse and data marts. In this data warehouse and data marts, the data will be stored. Once the user want to analyze the data using data mining, the system will gather the data stored in data warehouse and data marts. With some of slicing and dicing techniques, data mining process the required data and resulting in enterprise reports. With these reports, management of enterprise then decides what to do next. Data Mining Techniques According to (Larissa T. Moss, 2003), data mining itself has many models and various methods in analyzing data. When to use one of these models or methods depend on the requirements. Below are some of those models or methods : †¢ Associations Discovery Is used to identify the behaviour of specific events or processes. Associations discovery links occurrences within a single event. Example of use in discovering when a person buys a toothbrush then may also buy a toothpaste or a person buys a cigarette may also buy the lighter. †¢ Sequential Pattern Discovery Is similar to associations discovery except that a sequential pattern discovery links events over time and determines how items relate to each ther over time. Example of use in predicting a person who buys a couple sets of computer may also buy a switch or router within three months. †¢ Classification Is the most common data mining technique. Classification looks at the behaviour and attributes of predetermined groups. Data mining tool can classify to new data by examining the existing data that has been classified before. Ex ample of use in classifying characteristics of customers. †¢ Clustering Is used to find different groupings within the data. Clustering is similar to classification except that no groups have yet been defined at the outset of running the data mining tool. Clustering divides items into groups based on the similarities the data mining tool finds. Clustering is used for problems such as detecting manufacturing defects or finding affinity groups for credit cards. †¢ Forecasting Is used to forecasting market or forecasting products in manufacturing enterprise. Comes in two types: regression analysis (predict future based on whole past trends) and time sequence discovery (predict future based on time-dependent data values). Business Intelligence in Banking and Finance Banking and finance in this paper, is the institution that require to adapt in globalization, flexible in market, keep growing, create innovations to gain more customers that will increase profit and revenue. The challenging questions is how to achieve those requirements. Those institutions also do risk management to handle frauds and losses. With high profit and revenue, it will be useless if the institution can not handle possible risks, in this case frauds and losses are the most possible risks. They need customers but after customers increased so do the risks. So the possible way is to manage those risks. The same question as above, how to make the risk management easily and cover up all the risks. With business intelligence, all of those things can be achieved. Banking and finance institutions can depend on business intelligence in many aspects. Efficiency of analyzing the data, detection of frauds and losses, risk management, customer management and product management are some of these aspects. Striving for success, banking and finance institutions always trying to create new innovation either in products or services. Mergers and acquisitions have inevitable made those institutions have really huge and heterogeneous data. Impossible to maintain those data without new technologies (Katarina Curko, 2007). Using Data Mining as Solution in Credit Loans for Banking and Finance As mentioned above, this paper will focus more on data mining in business intelligence. After discussing the benefit of business intelligence in banking and finance institutions, at last we go to the last important question, how to extract the hidden informations from those huge and heterogeneous data. In this section, we shall focus more on how to predict frauds, losses and risks that might happen in credit loans. Being able to predict risks, frauds and losses are the main concern these days in banking and finance institutions. Credit loans nowadays have been growing rapidly. Almost every single shop or business center allows payment with credit card, but we shall focus more on credit loans such as loan for business, vehicle etc. Credit loans have been the most interesting product for banking and finance institutions. Many customers are looking for credit availability to help them financially. With the credit interests, the banking and finance institutions gain profits. Quite interesting business when they can offer credit and gain the profit from the credit interests, but the most important question is how to guarantee that the customer is a good one or at least make sure the customer will pay back including the credit interests so those institutions will not get frauds and losses. We can say to prevent frauds and losses is a kind of risk management. Risk management really is a crucial step to do especially in banking and finance institutions. Risk management in banking and finance institutions itself covers many aspects such as liquidity risk, operational risk and concentration risk. Today, integrated measurement of different kinds of risk (market and credit risk) is moving into focus. These all are based on models representing single financial instruments or risk factors, their behaviour, and their interaction with overall market (Dass, 2006). We shall focus more on credit risk. Credit risk assessment is key component in the process of commercial lending (Dass, 2006). The institution has money to lend but to decide which customer or borrower is not an easy matter. We shall learn more about the customer or borrower, find their background, their market transaction, their current income, and in more extreme way is learning their current life. To make those tasks possible, we can use classification or clustering in data mining technique. These data mining tools can provide a grouping of customer or borrower. Let’s say there are three groups of customer or borrower that we want to manage. First, high valued customers, middle valued customers and low valued customers. Before put customers into those groupings, there are many things to consider and analyze. Different institutions use different kinds of classification and analysis. But in general, things to consider and analyze are customer background, customer history transaction, customer credit history, customer account at another banking or finance institution, customer income. Those are from credit customer or borrower perspective. They also consider and analyze market and economy trends to calculate and manage the possible profit gained before make a decision to lend or give the credit. [pic] Figure 2. Overview of Data Mining Process (Classification Clustering) in Credit Loans With these data mining tools, the analyst from those institutions can easily decide to approve the credit or not. Logically, analyst or management inside institutions will decide to lend or approve the credit requested by customers in high valued customer then it goes down until low valued customer. But not all decisions are correct, many aspects can cause wrong decision such as incomplete data or unconsistent data of customers, market economy trends changing, or other aspects. But these tools surely help a lot to do risk management in credit loans which will impact in minimized rauds and losses and increased profits and revenues. Conclusion Banking and finance institutions have so many products and services offered to customers. One of those are credit loans. Credits that offered to customers or borrowers are not directly approved if one of the customer or borrower makes a request of credit. Many aspects to consider and analyze. With business intelligence especially with data minin g including data warehouse and data marts, those important aspects are collected, stored and analyzed. Specifically we use a couple of data mining technique i. e. classification and clustering. The purpose is to group the customer or borrower into groups that are easily to read and analyzed by institution analyst or management to ultimately decide to approve the requested credit or not. In this paper we suggest three groupings of customers or borrowers such as high valued customer, middle valued customer and low valued customer. Analyst or management also analyze the market and economy trends beside customer aspects. In the end, these business intelligence and data mining tools are used to ease in decision making to make the best decision for whole enterprise. References Journals: [1] Dass, R. (2006). Data Mining In Banking And Finance: A Note For Bankers. Indian Institute of Management, Ahmedabad . [2] Katarina Curko, M. P. (2007). Business Intelligence and Business Process Management in Banking Operations. Information Technology Interfaces . [3] Muhammad Nadeem, S. A. (2004). Application of Business Intelligence In Banks (Pakistan). CoRR . Textbooks: [1] Bhasin, M. L. (2006). The Chartered Accountant, Banking and Finance, Data Mining: A Competitive Tool in the Banking. Oman. [2] Larissa T. Moss, S. A. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Addison Wesley. How to cite Business Intelligence with Data Mining, Papers

Gay Marriage Essay Research Paper THE OPPRESSED free essay sample

Gay Marriage Essay, Research Paper THE OPPRESSED GENDER It has been said that adult females are a universally oppressed gender. Unfortunately, I feel that this statement is wholly true. The position that adult females are oppressed merely because work forces and most adult females excessively, have the incorrect thoughts about adult females can be excessively optimistic. Emancipating adult females is seen as merely a affair of persuasion and instruction, of explicating to work forces that they have got it incorrect and that they truly should portion the housekeeping and the top occupations because it would be more just. History shows that all thoughts can alter. For illustration, the thought that black people are inferior belongs to societies that exploit black people. They see black people as no more than slaves or as inexpensive labour. To acquire rid of this thought, we have to acquire rid of the system that started this sad thought. We will write a custom essay sample on Gay Marriage Essay Research Paper THE OPPRESSED or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Anarchists believe that the nucleus job confronting adult females is category society. Overliing that nucleus job is a job of male chauvinist thoughts. The thought that adult females are inferior comes from societies that are divided into categories. When misss answered out of bend, they were more likely to be told off, while male childs were likely to be praised for demoing intelligence or enterprise. Given this it was non surprising that in ulterior categories misss seldom spoke unless specifically asked a inquiry while male childs frequently spoke out or chatted with the instructor. Women experience diffident as to what their rights are. Besides diffident as to how many fusss they are expected by society to set up with. Womans are invariably given cues that they are in some manner inferior. This conditioning is a symptom of the place of adult females in society, non the cause but a symptom with far making effects. Womans are invariably conditioned to believe that we do non hold a right to an sentiment, to be politically active, or to talk out. That is why the first measure against this conditioning is to form individually from work forces. Some adult females felt that work forces being more confident and more self-confident tend to rule treatments. Even some adult females feel that when work forces are present they are more likely to take a soundless function and leave the reasoning up to them. Women? ? s forming together is an exercising in authorization. It is a positive response to the conditioning of society. Its function should be to do it possible for adult females to take part as peers with work forces. However, jobs rise when this exercising is taken into drama along with run. This identifies work forces as the root job, when they are non the job. It besides isolates work forces from the battle, when it is obvious that in order to alter society we must work aboard them. Within many Unions and the British Labor Party there exist adult females merely conferences, A job with this is that adult females? ? s issues are frequently referred to these conferences as a manner of avoiding the issues and burying about them. Rape is an illustration of adult females? ? s issue and its is referred to as a adult females? ? s conference. In decision, I feel that adult females are get downing to come on. For illustration, our New York Senator Hilary Clinton is a adult female. This is merely the start ; shortly possibly we will hold a adult females president.