Vertical analysis free essay sample

A strategy for fiscal report examination wherein every section for every one of the three significant classifications of records (resources, liabilities and values) in a monetary record is spoken to as an extent of the all out record. The principle favorable position of vertical investigation is that the accounting reports of organizations of all sizes can without much of a stretch be thought about. It additionally makes it simple to see relative yearly changes inside one business. For instance, assume XYZ Corp. has three resources: money and money counterparts (worth $3 million), stock (worth $8 million), and property (worth $9 million). In the event that vertical investigation is utilized, the benefit segment will resemble: Cash and money reciprocals: 15% Inventory: 40% Property: 45% This strategy for examination stands out from level investigation, which utilizes one years worth of passages as a pattern while each other year speaks to contrasts regarding changes to that standard. Vertical Analysis of Financial Statements Vertical investigation of budget summaries is a method where the connection between things in the equivalent money related is distinguished by communicating all sums as a rate an aggregate sum. We will compose a custom exposition test on Vertical investigation or then again any comparable point explicitly for you Don't WasteYour Time Recruit WRITER Just 13.90/page This strategy looks at changed things to a solitary thing in a similar bookkeeping period. The fiscal summaries arranged by utilizing this strategy are known as regular size budget summaries. This investigation is performed on the pay articulation just as the asset report. Monetary record: When applying this technique on the asset report, the entirety of the three significant classes accounts (I. e. resources, liabilities, and value) are contrasted with the all out resources. The entirety of the accounting report things are introduced as an extent of the absolute resources. These rates are appeared alongside the total money sums. For instance, assume an organization has three resources; money worth $4 million, stock worth $7 million and fixed resources worth $9million. The vertical examination strategy will show these as Cash: 20% Inventories: 35% Fixed Assets: 45% Income Statement: And while applying this procedure to the pay proclamation, every one of the cost is contrasted with the absolute deals income. The costs are introduced as an extent of all out deals income alongside the outright sums. For instance, if the business income of an organization is $10 million and the expense of deals is $6 million, the expense of deals will be accounted for as 60% of the business income. The primary preferred position of utilizing vertical examination of fiscal reports is that salary explanations and monetary records of organizations of various sizes can be analyzed. Correlation of outright measures of organizations of various sizes doesn't give helpful decisions about their monetary exhibition and budgetary position. Normally the vertical examination is performed for a solitary bookkeeping period to see the overall extents of various record adjusts. In any case, it is additionally valuable to perform vertical examination over various periods to recognize changes in accounts after some time. It can assist with distinguishing strange changes in the conduct of records. For instance, in the event that the expense of deals has been reliably 45% in the history, at that point an abrupt new level of 60% should grab the eye of examiners. Purposes for this change ought to be researched and afterward measures ought to be taken to take this rate back to its ordinary level. Segment 3: VERTICAL ANALYSIS (COMMON-SIZE ANALYSIS) Vertical/Common-size examination communicates things in a budget summary as a level of a solitary or base sum. This permits investigation of at least two organizations of fluctuating sizes. The computations used to decide the responses for the vertical investigation must be remembered for the index. I. For an Income Statement, things are normally communicated as a level of income. Perform vertical investigation comparable to income for the accompanying things in the Income Statement for the current year for every one of the two partnerships. Current Year Revenue 100% COGS Operating Expense Interest Expense Income Tax Expense Net Income Based on the examination, how have every one of the organizations performed comparative with the accompanying: †¢ Product or Service Cost Control †¢ Operating Cost Control †¢ Debt Servicing †¢ Tax trouble †¢ Profitability II. For a Balance Sheet, vertical examination is performed by communicating sums as a level of all out resources. These rates are then contrasted with rates determined for another enterprise (between organization examination). Perform normal size examination of the accompanying for every one of the two companies. Current Year Current Assets Property, Plant and Equipment All Other Assets TOTAL ASSETS 100% Current Liabilities Total Liabilities Stockholder’s Equity Vertical Analysis of the Income Statement The most widely recognized utilization of vertical examination in a pay proclamation is to show the different cost details as a level of deals, however it can likewise be utilized to show the level of various income details that make up absolute deals. A case of vertical examination for a pay proclamation is appeared in the extreme right section of the accompanying dense salary articulation: $ Totals Percent Sales $1,000,000 100% Cost of products sold 400,000 40% Gross edge 600,000 60% Salaries and wages 250,000 25% Office lease 50,000 5% Supplies 10,000 1% Utilities 20,000 2% Other costs 90,000 9% Total costs 420,000 42% Net benefit 180,000 18% The data gave by this pay explanation position is valuable for spotting spikes in costs, yet additionally for figuring out which costs are little to such an extent that they may not be deserving of much administration consideration. Vertical Analysis of the Balance Sheet The focal issue while making a vertical examination of an asset report is the thing that to use as the denominator in the rate count. The standard denominator is the benefit all out, however you can likewise utilize the aggregate of all liabilities while ascertaining all obligation detail rates, and the aggregate of all value accounts while computing all value detail rates. A case of vertical examination for an asset report is appeared in the extreme right section of the accompanying consolidated monetary record: $ Totals Percent Cash $100,000 10% Accounts receivable 350,000 35% Inventory 150,000 15% All out current resources 600,000 60% Fixed resources 400,000 40% Total resources $1,000,000 100% Accounts payable $180,000 18% Accrued liabilities 70,000 7% Total current liabilities 250,000 25% Notes payable 300,000 30% Total liabilities 550,000 55% Capital stock 200,000 20% Retained income 250,000 25% Total value 450,000 45% Total liabilities and value $1,000,000 100% The data gave by this monetary record position is helpful for noticing changes in a companys interest in working capital and fixed resources after some time, which may show an adjusted plan of action that requires an alternate measure of progressing financing.

Comparative Political Science Essay Example | Topics and Well Written Essays - 500 words

Relative Political Science - Essay Example Basically, the political viciousness experienced was because of various ethnic gatherings looking for political prevalence (O’Neil 2). In certain occurrences, political brutality may happen when individuals challenge poor administration by their legislatures or in any event, when governments neglect to make a move where important. Considering this, religion and political savagery are not so much related in light of the fact that religion doesn't really cause political viciousness. It is wrong to presume that strict homogeneity can ensure partisan harmony. Actually, strict homogeneity can't ensure partisan harmony. Strict homogeneity has to do with equality in every single strict conviction, assessments, tenets, and contemplations. In the event that there is equivalence in all parts of religion, the probability of sectarianism and different strict contrasts is significantly decreased. Regardless of whether everybody was to have a place with one specific religion, there would at present be sectarianism since they would in any case have different contrasts, for example, race, ethnicity, and culture to quarrel over. Consequently, it would in any case be hard to accomplish partisan harmony (O’Neil 78). Partisan clash doesn't generally happen because of strict assorted variety. The distinctions in convictions and conclusions among religions can be utilized to clarify strict assorted variety. Various religions may have various convictions and thoughts, however that doesn't generally prompt partisan clash. The scorn and segregation that emerges from the various convictions among religions are what can be called sectarianism. Strict assorted variety doesn't generally mean partisan clash in light of the fact that various religions have figured out how to endure one another and get along for the general great. A genuine model is America, which has differing religions, for example, Christianity, Judaism, Islam, Baha’i, Buddhism, Hinduism, Jainism, Sikhism, and Taoism among others (O’Neil 99).â â

How to Write a Resume To Make It More Appealing For The Employer

How to Write a Resume To Make It More Appealing For The Employer When you go somewhere, you have to introduce yourself, In the same manner, when you want to seek a job you have to introduce yourself to the employers. Here are the top tips on how to write a resume. Since you can’t meet the employers directly in the first meeting you have to introduce yourself through a resume or a bio-data having all the information about you that an employer wants to know. We are here to guide you about How to write a resume. Qualities of a resume Summary Qualities of a resumeFormats Of a ResumeReverse chronological resume formatSkill-based resume formatCombination resume formatBest Resume layoutHow to write a Resume :Contact detailsExperience DetailsYour skills and ProficiencyEducational or technical QualificationPersonal Details Your resume must be in simple and understandable language.Your resume must have all the necessary information about you that an employer may be found.A resume must provide all the correct information about you. How to write a resume meant that writing a resume in accordance with your skills and the need of the employer. Formats Of a Resume A Resume is of different kinds of,  to make a resume there are different kinds of formats available here on how to write a resume. They are as follows: Reverse chronological resume format This format of resume is more popular and is taken by those with plenty of work experience which is relevant to the role or job they are seeking for. Skill-based resume format This kind of resume format is good an option for those who have less work experience and best skills to perform any work. This is best because in it one may give a summary of all the skills a person is having in him. This type of format is for students and undergraduates because they have less work experience but are packed with lots of skills. Combination resume format This type of resume format is best if you are more skilled and have more working experience with you. That’s why it is called a combination work format. Best Resume layout Whenever you appear for a job interview the first thing the employer notices is that the layout of your resume. The layout of a resume is a part of how to write a resume. Hence, here are some tips for a good layout of a resume.One page length (maximum three)Your headings should be clear and understandable.The pages you are opting up for your resume must be clean and white in color.                       Font should be easy to read.A clean white space  especially around margins. How to write a Resume : Contact details A resume must have your contact details on it, so as the employer can contact you through those details. Contact details may be your mobile no., your address, your email address along with your name. Experience Details To attract the employer more towards you, you must ensure that your resume must have your experience details somehow related to that field of work. This experience detail put up a great impact on your employer. Your skills and Proficiency After giving details about your experience, you are likely to tell about your skills and proficiency in that field. Skills are in your favor since you will tell all the good points in this part of your resume. Educational or technical Qualification Every job must be limited to some qualification. So,  giving your educational and technical qualification is necessary. In this part of your resume, you must explain your qualification area. Personal Details Personal details of your’s must be given at last in a resume.  This is just to know your employer, more about you. Get the best assignment help services from our experts at nominal charges.

Ethical Issues Of Target Corporation - 2478 Words

Target Corporation is an American retailing company, founded in 1902 and headquartered in Minneapolis, Minnesota. It is the second-largest discount retailer in the United States. The company is ranked 36th on the Fortune 500 as of 2013. The first Target store was opened in 1962 in Roseville, Minnesota. Today Target operates 1,934 stores in the United States with over 347,000 team members worldwide. Ethics Ethics, in business, refers to moral principles and standards that define acceptable behavior in the world of business. Ethical decisions foster trust among individuals and in business relationships. Recognizing ethical issues is important in the workplace. An ethical issue is an identifiable problem requiring a person or organization to choose from among several actions that may be evaluated as ethical or unethical. When you’re determining is a situation is ethical or not, there are three factors to take into consideration. Individual factors, organizational factors, and opportunity. Individual factors are sets of principles that describe what a person believes are the right way to behave. Organizational factors include the influence of managers, coworkers, and the work group. Opportunity is a set of conditions that punish unfavorable behavior or reward favorable behavior. â€Å"Target thrives on competing to win in the marketplace. We compete and negotiate active ly, but always with integrity. Taking advantage of anyone by manipulating or concealingShow MoreRelatedEthical Guidelines Should Corporations Follow When Using Social Media Marketing1392 Words   |  6 Pages What ethical guidelines should corporations follow when using social media marketing? What exactly does this question mean? It means that corporations should use good judgment when using social media for marketing. Corporations should not take advantage of their consumers by being unethical with their choice of how to market themselves through social media. According to Vinjamuri, there are five main unethical behaviors of corporations when they utilize social media marketing (2011)Read MorePersonal Ethical Standards And Corporate Culture Essay1480 Words   |  6 Pagescorporate culture. Personal ethical standards should be aligned with the company’s values and goals, especially as people move up the organisation hierarchy. Although the majority of organisations behave ethically, sometimes organisations break away from ethical standards for a variety of reasons. This document will discuss personal ethical standards and corporate culture. It will describe how businesses don’t always behave ethically and how this damages personal ethical standards. It will give examplesRead MoreSocial Engineering1052 Words   |  5 Pagesresearch paper is primarily based on information gathered from secondary sources explaining what the term â€Å"social engineering† is, how it is perpetrated, and the impact it has on individuals and corporations. It will also discuss ethical issues and action that can be taken by both individuals and corporations respectively to mitigate and minimize the risk of social engineering attacks. Social engineering, in the context of information technology, is defined as â€Å"gaining unauthorized access or obtainingRead MoreCompany Code of Ethics Essay827 Words   |  4 PagesEthics The Company code of ethics will cover all employees within our organization. The Code of ethics is essential for corporations today to remain in business and abide by their federal and state government regulations. Ethical training programs will exist ever corporation and are given to each employee usually the first day of employment and renewed on the annual basics. An ethical conflict occurs when people will encounter situations that they cannot easily control or resolved. In such situationsRead MoreSuccessful Marketing Strategies Essay1019 Words   |  5 Pagesadvantageous for some businesses (EStartup business blog and contributors, 2010). Identified will be the role that marketing plays in a successful business demonstrated by use of two examples, the importance of developing a marketing plan, and ethical and legal issues that surround marketing practices (EStartup business blog, 2010). To be a successful business, the owner of the business should use the marketing mix and the results of market research; having identified its key audience a company has toRead MoreBackground Information: The Tolapp Corporation1223 Words   |  5 PagesTolapp Corporation 1. The Tolapp identity and mission statement The Tolapp Corporation has been a long lasting presence within the American market place, creating a wide array of products, such as power tools, lawn furniture and lawn mowers, microwaves and so on. The companys business model is focused on the in-house manufacturing of the items, and their retail through established retailers, such as Wal-Mart, Sears or Best Buy. The company as such does not engage in direct sale efforts, butRead MoreMarketing Is The Core Of Communication Between A Corporation And Its Target Audience1428 Words   |  6 PagesMarketing is the core of communication between a corporation and its target audience, facilitated by widespread consumption and significantly influenced by consumer demand. It also serves as a platform that allows a company’s message to exploit media platforms in the attempt to gain a successful customer response and induce behaviours that will propel economic expansion. Despite the indisputable benefits of marketing to companies and c onsumers, the occasional antagonistic motives behind its evidentRead MoreCsr Continues To Gain Awareness As Globalization Offers1616 Words   |  7 Pagesdifference in their communities. Consequently, as Target continues to increase its efforts toward CSR activities to remain competitive, so does its competitors. For example, similar companies that compete directly with Target include Walmart and Costco. However, Target’s consistent activities toward CSR are in line with its competitors (See Table 3). Therefore, to maintain its competitive advantage, Target must continue to review its business and societal issues. For instance, it should work with its stakeholdersRead MoreCorporate Strategy Of The Business Diversification1608 Words   |  7 Pagesperformance under a single umbrella rather than diverse business units (SNU, 2016). A business diversification is to build the company shareholder value when the independent business units can perform under a single corporation as an umbrella organization instead of independent parents or a corporation. A diversified organization has many business units and each business units have its own business level strategy irrespective of whether they are related or not. A successful business diversification not onlyRead MoreWhy Toshiba Is Getting Hit With A Record Fine1599 Words   |  7 Pagesrevealed accounting discrepancies totaling 58. 9 million dollars. Well known for various home electronics (TV, VCRs, etc.) and household appliances (dishwasher, washing machines, etc.) the Toshiba Corporation has been operating since 1875. An analysis of what happened to Toshiba demonstrate a lack of ethical standards in leadership, transparency, and finance. Leadership The corporate culture dictates how employee’s behavior and that old saying â€Å"lead by example† did not apply for employees working

Imagery and Symbolism in the Yellow Wallpaper - 764 Words

On my first reading of Charlotte Perkins Gilman s The Yellow Wallpaper, I found the short story extremely well done and the author, successful at getting her idea across. Gilman s use of imagery and symbolism only adds to the reality of the nameless main character s sheltered life and slow progression into insanity or some might say, out of insanity. The short story is written in first person and it is from our nameless character s writing s that we are introduced to her world and her life. It is through this that we see our main characters transition into a world that only she has access to. She changes dramatically from our first meeting while everyone else stays very flat and unaffected. This method is very effective in†¦show more content†¦It is the wallpaper, alive and a character in itself, that charges our main character s mind and helps her break free from the dull and husband driven life she has been living. The wallpaper itself, so marvelously described, becomes our storyteller s best enemy and best friend. More like a mirror, this yellow consuming wallpaper reflects what our main character is really going through and feeling and the woman that stirs and creeps within the wall is literally herself which is found out by us, the readers, when the housekeeper mentions the yellow stains on all of her clothes. She wants to tear the confining wallpaper down that holds this imaginary woman in just as she wants to tear the confining way of life her husband has chosen for her. The story continues to progress as she deconstructs and analyses the wallpaper until the climax when our main character locks herself in the yellow room to finally tear all of the wallpaper down so that the woman can never be put back and imprisoned forever. The story concludes with her husband fainting, and our main character creeping and paying him no concern at all except that once again he is in her way but this time, not able to stop her voyage along the wall and for the rest of her life. For some, this insanity seems without reason, but it is a long and overdue release ofShow MoreRelatedThe Yellow Wallpaper By Charlotte Perkins Gilman1472 Words   |  6 Pagesâ€Å"The Yellow Wallpaper,† written by Charlotte Perkins Gilman in 1892, is a great example of early works pertaining to feminism and the disease of insanity. Charlotte Gilman’s own struggles as a woman, mother, and wife shine through in this short story capturing the haunting realism of a mental breakdown.The main character, much like Gilman herself, slips into bouts of depression after the birth of her child and is prescribed a ‘rest cure’ to relieve the young woman of her suffering. Any use of theRead MoreRhetorical Analysis Of Charlotte Perkins Gilman1700 Words   |  7 PagesIn literature, there are many different components that create a timeless and classic text, such as personification, imagery, or symbolism. In some texts an author uses overbearing amounts of imagery to giv e us a vivid description of what is happening in the story, in others an author may give very little visual details, but instead incorporate countless allusions to help the reader better understand their story by alluding other popular works. Through the use of themes and symbols, however, an authorRead MoreThe Yellow Wallpaper by Charlotte Perkins Gilman1099 Words   |  5 PagesThe Yellow Wallpaper, has an autobiographical element to it. It was written by Charlotte Perkins Gilman. The piece of work concentrates on many different aspects of literature. The Yellow Wallpaper, has an autobiographical element to it. It was written by Charlotte Perkins Gilman. The piece of work concentrates on many different aspects of literature. It can be evaluated with ten different types of literary criticism: formalist, biographical, historical, psychological, mythological,Read MoreAnalysis Of The Yellow Wallpaper Short Story1174 Words   |  5 Pages â€Å"The Yellow Wallpaper† Analysis Short Story Fiction Whether a story is fictional or not there’s a significance to the author or anything that could relate to today’s society of life, back in time, or it’s a story written to entertain the reader. Some authors write stories to tell the reader how one must look deeper into their story to be able to interpret their story to fully comprehend and to realize how the author is trying to make a point. After reading â€Å"The Yellow Wallpaper† the reader couldRead MoreThe Yellow Wallpaper By Charlotte Perkins Gilman846 Words   |  4 PagesThe dignified journey of the admirable story â€Å"The Yellow Wallpaper† created by Charlotte Perkins Gilman’s, gave the thought whether or not the outcome was influenced by female oppression and feminism. Female oppression and feminist encouraged a series of women to have the freedom to oppose for their equal rights. Signified events in the story â€Å"The Yellow Wallpaper† resulted of inequality justice for women. Charlotte Perkins Gilman gave the reader different literary analysis to join the unjustifiableRead MoreAnalysis Of The Story Of An Hour And Charlotte Perkins Gilman s The Yellow Wallpaper908 Words   |  4 Pagesâ€Å"The Story of an Hour† and Charlotte Perkins Gilman’s â€Å"The Yellow Wallpaper† are two short stories that share similar themes and ideas. The authors’ use of point of view, symbolism, and imagery are different but still convey the same basic idea. Both stories cover the theme of marriage and share the idea that marriage is oppressive. The stories focus on two wives desperate to break from the control of their husbands. In â€Å"The Yellow Wallpaper† the woman’s husband is a doctor therefore he believes heRead MoreThe Yellow Wallpaper By Charlotte Perkins Gilman1205 Words   |  5 PagesCharlotte Perkins Gilman’s â€Å"The Yellow Wallpaper†, written in 1892, is a short story told from the perspective of a woman believed to be â€Å"crazy†. The narrator believes her craziness to be a form of sickness. However, the narrator’s husband, John, believes her to be suffering from a temporary nervous depression. As the narrator’s condition worsens, she begins to see a woman moving from behind the yellow wallpaper in their bedroom. The wallpaper captures the narrator’s attention and as a result drivesRead More The Yellow Wallpaper1466 Words   |  6 Pagessurrounding. Gilman’s â€Å"The Yellow Wallpaper† was first published in 1892, about a white middle -class woman who was confined to an upstairs room by her husband and doctor, the room’s wallpaper imprisons her and as well as liberates herself when she tears the wallpaper off at the end of the story. On the other hand, Crane’s 1893 Maggie: A Girl of the Streets is the realist account of a New York girl and her trials of growing up with an alcoholic mother and slum life world. The imagery in Charlotte PerkinsRead MoreHumble Items that Trap a Woman Essay1569 Words   |  7 PagesHumble Items That Trap a Woman Author Charlotte P. Gilman’s, â€Å"The Yellow Wallpaper† is a complex short story that discusses the thoughts and feelings of a woman who is kept confined in a small upstairs bedroom by her husband. The woman suffers from depression and anxiety, yet her spouse whom is a physician claims that she is not terribly ill. Despite all the strange thoughts she acquires, she continues to force herself to accept her new life style and awkward place of living. As she comes to findRead MoreSymbolism Of A Street Car Named Desire And The Yellow Wallpaper1487 Words   |  6 PagesSymbolism of One’s True Nature in A Street Car Named Desire and â€Å"The Yellow Wallpaper† What is humanity s true nature? Are people basically good, or basically evil? Over the centuries, many people have tried to find the answers to these questions, to no avail. Author Charlotte Perkins Gilman and Tennessee Williams take a definite stance on the issues throughout their work, arguing that people are basically evil hiding their truths. Many times, this theme is obviously stated in the stories, but sometimes

How to Work in Singapore - 652 Words

Wondering how to acquire an employment pass for a company in Singapore? Here are the some ways you can do so. Generally, EP (Employment Pass) is a kind of pass usually issued to professional employees, foreign directors, and managers who are planning to work in Singapore. Likewise, an Employment Pass holder is not qualified for a levy or CPF (Central Provident Fund), and the pass being issued is only valid for 1-2 years and should be renewed after. One of the many benefits of acquiring this is it allows the applicant to work, stay, and travel in Singapore without the need to apply for a VISA just to enter the country. For those who are planning to set up a company in Singapore, they could opt for an Entrepreneur Pass Singapore prior to moving there. Though, it could be more cumbersome when it comes to the renewal of an Entrepreneur Pass Singapore after some time. In order to be certain, check out the criteria when applying for an Entrepreneur Pass: The following are the fees scheduled for application of the Employment Pass: ï€ ­ Initial Processing Fees: S$850 (non-refundable processing fees) ï€ ­ MOM License: 06C3628 ï€ ­ Extra Approval Fees: S$1500 (The approval fees given after the approval of the Employment Pass Singapore, which is the receipt of IPA Employment Pass Singapore). Though, the medical check-up fees are not included. The Criteria for Singapore Employment Pass: With effect on 1 July 2011, every applicant of an Employment Pass must have a fixed salary not less thatShow MoreRelatedEconomy of Singapore 1077 Words   |  5 PagesIntroduction In this essay we look in-depth on how government strategies and economic policy play a crucial role in the success of High Performance Asian Economies (HPAEs) during 1960 to 1990 (World Bank 1993).There are eight countries within HPAEs: South Korea, Taiwan, Hong Kong, Singapore, Thailand, Malaysia, Indonesia and Japan. Its economic development has significantly rise that it was name ‘East Asia Miracle’ (World Bank, 1993). Out of the eight country, Singapore, Hong Kong, Taiwan and South Korea wereRead More business in asia Essay1320 Words   |  6 Pages DOING BUSINESS IN SINGAPORE BACKGROUND Founded as a British trading colony in 1819, Singapore joined Malaysia in 1963, but withdrew two years later and gained its independence. 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There may have some challenges and opportunities of using technology for the Singapore Armed forces.Read MoreThe Term Policy And Its Effect On Development And Daily Activities Within Industry1542 Words   |  7 PagesThe term Policy refers to a principal of action that is adopted by an organisation or an individual. In an organisation Policy is fundamentally important as it gives control and stability to employees to work effectively. Ritchie (1997) states that policy is a set of rules, regulations, guidelines and directives which provide a framework within which collective and individual decisions affecting development and daily activities within industry are taken. In agreement, Sharma (2009) states that policyRead MoreTopic . The Goals Of My Research Strive To Assess The Biopolitical1457 Words   |  6 PagesTopic The goals of my research strive to assess the biopolitical construction of a socially embedded hierarchy of otherness in Singapore, with specific regards to its impact on the reproduction of low-skilled migrant workers. More concretely, this essay seeks to address the restriction and stratification of reproduction amongst low-skilled migrant workers in Singapore, illuminating and analyzing the key structural factors that contribute to this reality. As fertility levels in developed nationsRead MoreSingapore s Success As A Nation Essay1199 Words   |  5 Pagesnation refers to how Singapore has managed to climb from third world status to first world status today and also how Singapore has managed to handle the continued unrest to maintaining the peace and stability it has today. Hence, I agree to the above statement that the two factors have successfully built a Singapore nation and will continue to be fundamental to Singapore’s future success as a nation. Sustained economic gr owth has successfully built a Singapore nation as it enables Singapore to have sufficientRead MoreInfluence Of Developed Nations During The Development Of Post Colonial States1420 Words   |  6 PagesCountries. Singapore believes in the importance of ODA and promotes continued support for countries in need. Singapore recognizes how ODA contributed to the early development of Singapore, and is dedicated to giving back. However, Singapore is a small nation with limited resources, and cannot provide the same level of assistance as larger countries. Singapore does not give monetary aid, but has, over the past two decades, provided educational assistance to developing countries through the Singapore CooperationRead MoreSingapore s Future Success As A Nation Essay1237 Words   |  5 Pagessuccessfully built a Singapore nation. These two factors will continue to be fundamental to Singapore’s future success as a nation.† Discuss. In my opinion, Singapore’s success as a nation refers to how Singapore has managed to climb from third world status to first world status today and also how Singapore has managed to handle the continued unrest to maintaining the peace and stability it has today. Hence, I agree to the above statement that the two factors have successfully built a Singapore nation andRead MoreSingapore : A Very Interesting Place1154 Words   |  5 PagesMason Vargas January 13, 2017 Period 3 History Essay Singapore History Essay Singapore is a very interesting place. For quite a while people did not even know what to call it, a city, a country or just a territory. It is currently called an island city state. It is located off of the coast of Malaysia and Singapore is a very large center of global finance. Its currency is the Singapore dollar, its GDP is 55,182 United States dollar. And, its official languages are English, Tamil, Malay and standardRead MoreAn Effective Leadership At Starwood Hotels Resorts Worldwide Inc.1539 Words   |  7 PagesHaving the ability to influence is a power that not many people possess. Mastering how to influence is the key component in becoming an effective leader. It is a necessary skill to have in order to achieve support from your followers. Without a support system leaders will have a hard time implementing new ideas and even decision making. I learned in these last few modules that influencing is an art. One must learn to tailor their behavior and approach accordin gly to their target audience. Influencing

Various Employment Opportunities to the Students Irrespective

Question: a) Demonstration of ability to reflect on chosen subjects to highlight the skills acquired and emphasise how improvement in performance is being achieved.? b) Exhibit motivation and confidence in engaging in personal and career development and planning.? c) Demonstrate progressive learning through a series of agreed milestones.? Answer: Introduction:- The human resource study is a vast field which offers various employment opportunities to the students irrespective of any kind of certificate, diploma or degree (either bachelor or masters). Besides different types of management studies, the human resource studies are also related to various social sciences like economics, sociology, political science, psychology etc. Now-a-days the human resource (HR) management is a most popular and significant subject in the field of human resource. A student of human resource management may work as managers and professionals. As a manager the duties of a human resource professional is to handle the administrative work and to help in hiring and providing training to new employees. In various sectors like government offices, business firms, health care organizations, technical companies etc (Barker and Kellen, 1998). Definition of the skills and knowledge needed to succeed in this field:- Knowledge needed to succeed in this field:- Bachelor Degree in human resource:- To build a succeed career in this field, an individual must earn bachelor degree in human resource management. It is a minimum requirement of knowledge in this field. In case of bachelor degree, two common degrees are the Bachelor of Science in Human Resources and the Bachelor of Business Administration in Human Resources. In this case student should learn about the employment development, labour management, employment law and compensation etc. Core classes of accounting, statistics and information technology should also be provided to the students (Burke, 2002). Internship participation:- To be familiar with the practices of human resource management, it will be helpful for the students to participate in internship programmes. These types of internship programmes not only help the students to develop their experience in this field, but it helps to develop the organizational skills of the students (Greenhaus, Callanan and Godshalk, 2010). Earn training on Human Resources Information Systems (HRIS):- In order to get job in human resource management field, the technological knowledge may help the individual in this field as at present, this field is very much technological dependent. Earn certificates and diplomas relevant with this field:- As most of the employers in this field prefer professional certificates and diplomas in this field, to get a job in this field, student should earn various certificates and diplomas in this field. This kind of certificates and diplomas not only include the professional knowledge, but also some professional experience in human resource field. Gain Work Experience:- Work experience is necessary for the students to get job in this field as experience help the students to develop their skill in HR management. Students can earn some work experiences from the internship, HR certification or by working in a small company at the initial stage of his or her career (Greenhaus, Callanan and Godshalk, 2010). Pursue advance study:- An individual may also go for the master degree in human resource study or in human resource management to earn more knowledge in this field. A master degree holder of business resource management is considered as more skilled and more valuable labour for the company and most of the time recruited as a manager. Skills needed to succeed in this field:- Good Communication skill:- To be a good professional in human resource management, one should have a good communication skill both in official and regional language as they have to deal with the labourers and the employers of the company. Managers also act as a bridge between employers and the employees, as they maintain the relationship between them by convey their massages through communication. So, for a human resource manager, the learning and listening power should be strong (Mymajors.com, 2015). Good management and administrative skill:- As the human resource managers have to manage the employees and the business profit of the firm, it should have good management and administration skills. Only a good manager can maintain a good relationship between employers and the employees which will lead to an increase in the production level of the company. Good leadership quality:- A professional in human resource management, should have good leadership quality to control the work of the employees and to train the new employees (Stone, 2002). Time management and man management is skills:- To manage the work and the employees of a company in a given time period, the human resource manager should learn how to manage its work efficiently at a particular or at a given time period. Skill of multi-tasking:- A human resource manager has to deal with various issues of the companies and of the employees at a same time. So the manager should have the ability to perform different tasks at a specific time (Mondy, Noe and Premeaux, 2002). Ways of developing skills and knowledge in human resource management program:- There are different ways, which help to develop the skills and knowledge of the country in HR management field. These can be explained as follows:- Earning work experience:- HR professionals can improve their skills by reducing their previous mistakes. And this is only possible if they gather some experiences by working in a company. Earning theoretical, technical and practical knowledge:- To increase their knowledge and improve their expertise in this field, HR professionals can gather more theoretical, technical and practical knowledge in this field (Mathis and Jackson, 2000). Regular practice of presentation and public speaking:- To improve their communication skill, HR professionals should regularly involve in public speaking and always should try to present their views in front of others clearly. Taking some professional and personal development training:- To improve their professional and personal skills, HR professionals should engage in some professional and personal development training programs which are relevant for this particular field (Hrdailyadvisor.blr.com, 2015). Creating good relationship among the employees:- A HR professional can automatically develop his/her leadership skill if he/she can maintain good relationship among the other employees and the employers. Creating a working environment:- Finally, a good working environment is always helpful for the development of the skill of the employees. Conclusion:- Hence, from the above analysis it can be said that if a student want to succeed in a particular field (such as human resource), then he/she has to plan first a suitable career path to build a secure and strong career in future. Families, friends and teachers should provide proper guidance to him/her on choosing the specific learning and training programs. However, after getting the job, it is the humble duty of the employers to guide and provide proper training to the employees of the company to get more skilled labour and to earn more profit. References Barker, J. and Kellen, J. (1998). Career planning. Upper Saddle River, N.J.: Merrill. Burke, A. (2002). Career planning. Hollywood, FL: Frederick Fell Publishers. Greenhaus, J., Callanan, G. and Godshalk, V. (2010). Career management. Thousand Oaks: Sage Publications. Hrdailyadvisor.blr.com, (2015). The 9 Essential Skills of Human Resources Management - How Many Do You Have? | HR Daily Advisor. [online] Available at: https://hrdailyadvisor.blr.com/2006/07/18/the-9-essential-skills-of-human-resources-management-how-many-do-you-have-2/# [Accessed 10 Jul. 2015]. Mathis, R. and Jackson, J. (2000). Human resource management. Cincinnati, Ohio: South-Western College Pub. Mondy, R., Noe, R. and Premeaux, S. (2002). Human resource management. Upper Saddle River, N.J.: Prentice Hall. Mymajors.com, (2015). Human Resources ManagerSkills and Knowledge. [online] Available at: https://www.mymajors.com/career/human-resources-managers/skills/ [Accessed 10 Jul. 2015]. Stone, R. (2002). Human resource management. Milton, Qld.: Wiley Australia.

Strategy of Goggle

Analysis of Goggle Larry and Brinn founded this entity in the 1990s. However, the entity had a different name, Back Rub. The founders of the entity were undergraduates at Stanford University. The two students developed a search engine that could rate website relevance via examination of back links.Advertising We will write a custom case study sample on Strategy of Goggle specifically for you for only $16.05 $11/page Learn More The above innovation would support the undertakings of countless entities in the Information technology (IT) sector. The founders later registered the entity in California. The entity generated its income only as search engines. Nonetheless, the entity currently has diversified its operations into an assortment of subsectors in the computer industry (Clay Esparza, 2012). What is going on? In the previous decade, Goggle has made some shrewd acquisitions. The acquisitions have entailed entities that would complement Goggle’s operations. Additionally, the acquired entities would enable diversification and creation of new products. Goggle’s income originates predominately from advertisements despite the entity dealing in mobile phone software and other merchandise. The entity also sells search appliances. In 2010, Goggle was the favourite search device. This denotes the entity’s domination of the market. In America, the entity serves over sixty percent of the search requests. The trend is similar internationally. Goggle also has an enormous workforce that executes its daily operations. The entity’s management of the work force has culminated in innovations like YouTube, a music search engine. Such a project has earned the entity enormous returns. The entity has developed numerous data centres. The data centres will facilitate penetration into lucrative markets in Asia. Additionally, they have revealed Goggle’s commitment towards a clean environment. Generally, innovations and p roduct creation have facilitated expansion in Goggle. SWOT Analysis Strengths The entity has managed its personnel in a shrewd manner allowing the entity to benefit from their expertise. Projects like You Tube have emanated from the creativity of its employees. However, the entity has earned phenomenal revenues from such innovations. Additionally, the global community is utilizing the internet greatly. Consequently, there is a sustainable demand for Goggle’s products globally. Google has diversified its products reducing its risk as an entity. Therefore, failure of a product would have minimal implication on the entities fortunes.Advertising Looking for case study on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Weaknesses The entity loses income through counterfeiting of its products. This is common practice especially in relation to application product. Therefore, Goggle should petition authorities to enforce c ounterfeit legislation to minimize its losses. Opportunities Innovations are critical to the survival of this entity. Therefore, Goggle has to provide the clientele with better products always hence, winning more clientele. Additionally, there are lucrative markets in the emerging economies that the entity can harness. Threats The entity operates in an exceedingly competitive market. Therefore, Goggle has to ensure that it is at par with its rivals. It should ensure that it improves its products persistently. Google is predominantly dependent on proceeds emanating from advertising. Accordingly, fluctuation in such incomes would affect the firm considerably. PEST Analysis Strengths Advancement in technology will affect this entity positively. Technological progression will have considerable impacts in the emerging markets that are lagging behind technologically. Such advancements will create demand for Goggle’s products. Its personnel management strategy is unique hence, allow ing the entity to utilize the creativity of its employees rather than issuing repetitive duties that do not support career growth. Weaknesses Google operates in an industry which changes rapidly. Consequently, the entity requires sustained research on product improvement. Failure to do so will allow its rival’s products to surpass its own. This would be detrimental since the clientele always opt for the best products. References Clay, B. Esparza, S. (2012). Search engine optimization all in one for dummies. California, CA: Wiley publication. This case study on Strategy of Goggle was written and submitted by user Casey Carter to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Age of the Euro essays

Age of the Euro essays On the 1st of January 1999 the euro became the official currency of over 300 million Europeans in 11 of the worlds most developed nations. Austria, Belgium, Finland, Germany, Greece, Ireland, Italy, Luxemburg, the Netherlands, Portugal and Spain have all opted to gradually phase out their national currencies and join the euro-zone, in a move that will lead to the largest European monetary union since the Roman Empire. The concept of a single European currency is not a new one. It was first proposed in the 1970s but was abandoned until 1991, when it was given the go ahead by the European Union. This decision was taken with the view of completing the single market for goods, services, people and capital in Europe, and of enhancing the welfare of citizens within the EU. Since then there has been an on going debate over the soundness of this decision and the effects it is likely to have on both the European and World economies. One of the most obvious advantages of the euro is the resulting ease of transactions across the countries of the EU. For businesses this means that they no longer have to pay the hedging costs, which they do today in order to insure themselves against the threat of exchange rate fluctuations. Businesses will also find it easier to expand their operations within the member states. This is because rather than having to set up separate accounting systems, banks, etc. for transactions in countries other than their native one, the euro will make it simple to operate from a single central accounting office and use a single bank. The elimination of exchange rate variations would benefit consumers as well. Consumers would not have to change money when traveling within the euro zone, and would encounter fewer problems and legal constraints when transferring large sums of money across borders. Travelers and tourists would also no longer be forced to change their money into other currencies and pay banks the com...

Women in the City of the Dead Essay Example | Topics and Well Written Essays - 500 words

Women in the City of the Dead - Essay Example It implies that every woman has a city within her heart, a city that she nurtures from the cradle to the grave and from the womb to the tomb. The stories in this book explain how the women in Cairo (in that era) have to cope with their personal problems, domestic issues and the sociological challenges. It is a tough call viewed from any angle. It has been succinctly described by Helen Watson (1992, p.7) â€Å"Conflict and change tend to have a catastrophic effect on any highly structured system. Women’s increasing presence in the male world of work and money provides great potential for disruption of the complementary nature of male and female roles. This is a cause for considerable concern to both men and women.† The vast cemetery close to the centre of Cairo is the reality as well as the symbol of the past and present life there. The departed souls resting in peace in a number of graves must be watching with concern the developments taking place in the city due to the impact of industrialization, materialistic civilization, and the ambitions of the combustible generation, thousands who migrate to the cities in search of employment to better their prospects and adopt new lifestyles. The author describes about the worst part of this unchecked urbanization thus: â€Å"Families have moved into tomb buildings and ceremonial ante-rooms, and additional dwellings and extensions have been tackled on as required.†(p.4)

Carbon footprint assigment Assignment Example | Topics and Well Written Essays - 500 words

Carbon footprint assigment - Assignment Example At present, the outstanding challenge that is facing the human race is global warming, and its most pressing requirement is radically reducing our carbon footprint (Stuart 3) Daily driving cause’s carbon footprint in that fuel is burnt by the engine when driving thus, creating a certain amount of CO2 depending on the distance of driving and the car’s fuel consumption. For people who drive long distances daily, travel could be the largest part of their carbon footprint. The daily driving range is the most polluting thing that is done by most people. When burning gasoline, it releases pollutants that cause water pollution, global warming, and smog. The scientific press is full of dire warnings as to our collective fate if we fail to effect a very substantial reduction in carbon emission and to do so quickly (Stuart 4) In order to change this, the focus should be on saving the energy and reducing the carbon cause. First, it is vital improving fuel economy of the car. This can be achieved by reducing the energy used when overcoming resistance from road and air, braking, and accelerating. Additionally, public transport such as trains and buses should be used instead since compared to driving they are a less carbon-intensive way to travel. Moreover, people should drive less to reduce their driving footprint. Driving and cycling are also good substitutes for short driving distance that are carbon intensive. There may be no easy solution to the problem generating the carbon footprint but the parameters of the debate do not need to be established, different and all, so that we can determine what most at issue is (Stuart 18) There are various challenges that will be faced when changing the daily driving distance that causes carbon emission. We must address urgently the dilemma of ways to persuade trade-off that is possibly the best between survivals economically and ecological disaster (Stuart 21). From a

Beer as a social drink and its subsequent acceptance across the globe.

Beer as a social drink and its subsequent acceptance across the globe. Introduction The study will start with looking at the evolution of beer as a social drink and its subsequent acceptance across the globe. The study will also investigate how different brands came in to channelize communication of beer and incorporated community activities like football, rugby and food as moments for beer consumption to increase product acceptance. We will also look at various international festivals like the Oktoberfest and the Great British Beer festival in UK which have developed as a part of beer culture and helped in the spread of the product through replicated festivals in various parts of the world. Primary research will be done through online surveys and interviews with respondents across Europe, North and South America, and Asia to understand consumer attitudes towards beer in these regions and a comparative analysis will be done on their responses. Based on the insights, the study will investigate whether a similar model can be replicated in India for the nascent beer industry under the following heads: Which of the marketing and communication strategies used in other countries would / wouldnt work in India, and why? Opportunities for replication of festival models from other countries. Implications for the Indian beer manufacturers and marketers, based on a comparative analysis of beer positioning and communication in different cultures. Literature Review A preliminary study of literature on beer industry globally and consumer behaviour revealed the following salient points: * Research shows that beer is a non-food specific drink compared to wine. It is more of a masculine and non-formal occasion drink and associated with fun and social events. When it comes to different brands of beer, it is important for them to focus on positioning and consumer engagement. Beer has slowly become more fashionable to drink with its association with activities like football, rugby and rock music. * Peer pressure plays a huge role on the consumption of alcohol. Alcohol is associated with a list of values which are belonging, excitement, warm relationships, self-fulfilment, well-respected, fun and enjoyment, security, self-respect, and sense of accomplishment. These are important cues for any company while designing their marketing and communication strategy for their brand. * In America, beer joints stress on forming communities through engaging events and activities. The ambience of the place is also very critical since beer consumption is all about having a good time. * Forming a connect with the brand is also an important parameter when it comes to selling beer. As quoted by Mike Bristol, owner-founder of Bristol Brewing Co. in Colorado Springs a lot more people want to spend on a company that they have some common association with. Theyre local, theyre in the community, and theyre visible. Import beers dont seem to be doing well in theirr market or nationally, and he think thats a shift. Beer is also seen as a product, consumption of which does not go down even in economic crisis times. * As per Culinary Currents, Beer, Wine and Spirits. (2008, September 15). Nations Restaurant News, some myths about beer are: Dark beer is heavy Ale is stronger than lager Stout is a meal in a glass Imported beer is better than domestic beer Wine is more complex than beer Fruit beers are girly beers All beer is best served ice-cold Beer and fine dining dont mix  · Some craft beer makers have also tried to mix beer with specially crafted menu like cheese and seasonal food. The restaurants have even started experimenting with beer to create cocktails to increase penetration and frequency of beer consumption. This, though, could dilute the product personality of beer which does not reflect classy, fine dining experience but a more rugged and aggressive environment. This food and beer mix is primarily targeted towards non-regular beer drinkers and first timers.  · Some stats from the US market for March-April 2008 reveal interesting facts (Category Insight, Beverage: Beer Demographics. (2008, April). RETAIL MERCHANDISER, 10.) Beer was the fourth largest in terms of US dollar sales in edible grocery supermarket category. 37% of US adults are regular beer consumers 52% of total beer drinkers are age 28 to 49, but versus their size in the beer-consuming population, 41% of beer volume is consumed by 21 to 27 year olds 32% of beer drinkers shop for beer one to three times each week 47% of beer shoppers buy wine in addition to beer; 41% add spirits 70% are male 84% are White, 10% Latino, 6% African American 59% have an income above $59,000 Grocery is the most common beer channel choice at 46% When available, shoppers overwhelmingly prefer to buy cold beer * A brand study in one of the highest beer consuming nations of the world, Czech Republic and Britain suggests that branding played an important role in the development of the organised beer market in these countries at a national level. The entire system was well structured with organisational hierarchies in place as well as streamlined distribution channels. The regional brands on the other hand, do not follow a very structured nation-wide campaign. Although the brand development in case of national brands in both these countries are at similar levels, as we go down the bracket, the branding of regional markets in Czech becomes lesser developed compared to Britain. For the Czech consumers unlike British, brands were not a consideration in making the choice for public houses as much as the taste and freshness of the beer was. To sustain these smaller breweries, a rule was enacted in which the local public houses were obliged to sell the product from the local breweries restricting t he entry of national brands into these places. This rule though, is not present in Czech Republic making branding more important for them. To keep the beer industry safe in Czech, the breweries have kept the price of their beer lower than the other West European countries. * In 2007, 7 million litres of beer was consumed at the Oktoberfest in Munich in Germany. The biggest cultural context of this festival is the symbolism of equality that is shown as people from all classes and categories sit on the same table to enjoy their beer. The fair is the worlds largest fair which attracts visitors in excess of 7 million from all over the world. Such is the pull of this festival, that similar concepts have been replicated in other countries like Canada, Brazil, USA, and India. * The â€Å"whassup† campaign by Anheuser-Busch for Bud Light revolutionised beer advertising as it targeted the core group of 21-27 year old males who loved to hang out with friends over sporting events. * The Indian consumer mindset can be divided into the following sub heads: Mind over Matter The Functional over the Ornamental Fear of Tomorrow Enjoying the Ordinary The Desire to Fit In * In UK, beer advertising has been moving towards more engaging media like the internet from televisions to deepen their customers experience. Companies like Stella Artois have invested in multi-layer brand experience which tries to connect more with the customers and at a personal level. * Taking the case of Heineken, a lot of its global success can be attributed to its consistency in quality and uniformity in brand message everywhere. The marketing of Heineken is a combination of global feeling and local execution. * In its 2004 report, Global Status on Alcohol, the World Health Organisation (WHO) estimated there were 2 billion drinkers of alcohol on the planet. Trends suggest that for brands to become bigger, globalisation is the way forward. This becomes slightly easier as the consumers in most developed countries and emerging economies are now well informed and despite the cultural differences, are more open to international brands. * The study of global drinking trends suggests emerging markets have much better growth rates than developed markets where the growth is static. Urbanisation, affluence and influence of mass media is playing a major role in this growth. The availability of alcohol in supermarkets is also driving consumption. Beer stands fourth after carbonated drinks, tea and water in terms of share of throat in the world. The off-premise locations are drivers of volume whereas value drivers are the on-premise outlets. In mature markets, growth will be driven by experiential marketing. Barman and barista in urban areas are acquiring celebrity chef status. * In traditional drinking alcohol essentially signified a males entry into adulthood and was associated with food. In the modern day, drinks have become more of an individuals style statement and identity. It is important now to be seen with the right drink for the right occasion. Communities and association with them has become more important than before. Another newly developing phenomenon is that of post modern drinking where connoisseurship, novelty and exclusivity are taking predominance. Themed drinking associated with specific cultures is also seeing a good interest amongst the travelling class who get exposed to different cultures frequently. Some of the names like Guinness and Scotch whiskey have become iconic as they are seeped deep in the local culture. * According to the Euromonitor report of 2005, the following are the key drivers in the beverage industries in the major countries Australia convenience and health, mature market needing to add value. Alcohol part of the culture Brazil status, sociability and convenience, developing market with opportunities for growth and adding value. Market vulnerable to economic volatility, beer and football key to national culture China affordability, convenience and status in cities, developing market with huge urban potential, rural areas remain largely unchanged France convenience, sociability and status, traditional drinking culture being eroded by changing demands and globalisation Germany price, convenience and health, mature market opportunities to add value. Interest in discounters among affluent and poor Italy sociability, status and health, mature market adapting to changes but traditional infrastructure Japan convenience, status and health, mature market, highly fragmented and source of innovation Russia affordability, convenience, status, high consumption of locally produced spirits as well as increasing presence of global brands in the cities, high beer and vodka consumption. Alcohol dependence an issue among rural male Russians Spain status, sociability and health, directional market in terms of youth drinking trends older drinkers stick to traditional drinking, young driving the post-modern UK convenience, sociability and health, mature market adding value through novelty concentrated retail infrastructure US convenience, sociability and health, mature market adding value through segmentation and premiumisation * A few of the future trends which can be seen in the global drinks industry are health awareness, fusion drinking, artisan brands and connoisseurship experiential marketing and sociability. * Specific to Germany which has the 3rd highest beer per capita consumption in the world, the consumption of beer has been slowly going down. This is attributed to rising prices and the health consciousness of the drinking population. In turn, flavoured beer, non-alcoholic beer and malt-based Ready to Drinks are showing growth in consumption. * A major development in recent years has been the role and involvement of women in purchasing the drinks. Some of the international brands have started targeting women by creating flavoured beers for them. The communication strategy still targets the male predominantly though. * Econometrics study in the US by Franke and Wilcox suggests that there is no significant correlation between the beer advertising and alcohol consumption. All advertising does is make people aware of the brands available but does not really affect the amount of beer consumed overall. A study by Waterson in UK, shows that although advertising spends increased 80% between 1978 to 1987, the actual sale of beer in this period fell by 14%. The study also included Sweden which has banned alcohol advertising since 1979 with similar results. * The April 2009 Euromonitor report on beer shows a global demand of 184.6 billion litres. In the mature markets volumes are declining but in terms of value consumption is increasing. Laws on drinking and driving are encouraging growth of low/non-alcoholic beer and currently it accounts for 2% of global beer market but is showing high growth rate especially in Muslim countries. In Spain, this category already accounts for 20% of beer volumes. There is also a trend of moving away from the conventional beer type to niche segments like wheat beer and craft beer. Dark beer is also seeing a healthy revival in growth. * Specific to India, beer consumption has registered an increase of 700% between the period of 1995-2007. The per capita expenditures on alcohol have grown at twice the rate of the average growth in the rate of expenditure in this period. The average of 24 in the country with affluence, access to mass media and information, lowering of entry barriers and high awareness levels means a goldmine of an opportunity for alcohol companies. Retailing for wine and beer is now allowed in supermarkets on a lot of states thereby reaching out to more potential consumers, especially the women. This has also resulted in more and more urban households stocking alcohol at their homes unlike earlier times. Finally, the major beer manufacturers will have to compete for an expanding but challenging global market, which will ask hard questions of the positions that global players occupy by category, price point and geography. India will form a major part of this strategy shift and it is already visible with the number of beer brands that have entered the Indian market in the past 2 years. All the research done above talks about beer as a part of the popular culture in developed markets. The challenge is to try and suggest a workable strategy for India based on consumer insight to tap the enormous potential that it offers. India today stands at the forefront of this opportunity and hence it is important for these international players to understand the cultural nuances of the Indian consumer before formulating their strategies for the market. Conceptual Framework/Problem Definition India has one of the lowest annual per capita consumption levels of beer in the world, at 1 litre. The biggest international names like InBev/Anheuser-Busch, Heineken and Carlsberg have already started making investments in the market. Carlsberg has already invested close to $ 200 milion in production facilities in the country. The other companies are also entering the market through tie-ups with local players or setting up their own breweries. The growing affluence and increased disposable incomes along with the low average age of Indians presents a huge potential waiting to be tapped by these players. The increased global travel and exposure to western media has led to changing attitudes towards alcohol. This is expected to boost beer sales, while shifting government policy regarding alcohol and reductions in taxes and duties present interesting opportunities for large domestic and multinational players alike. Some of the states have already allowed beer to be sold in supermarket f ormats thus increasing penetration of beer substantially. For international players, the race is on to establish local manufacturing facilities and distribution networks, in order to gain first-mover advantage over other entrants. Currently the Indian market is dominated by local players but lack of other options has a major role to play in this. Curiosity and aspirational value attached to imported beer presents a unique market for these international players. Clear opportunities exist for those companies which are partnering with local companies or setting up their own breweries to get a head start in this dynamic market. At this juncture it is of paramount importance for these companies to get their marketing and communication strategy right. This is all the more important because the Indian market and consumer presents a challenge which is different from any other country in the world. Even within India, the cultural diversity is such that different strategies might be needed for different parts of the country. The current literature reviewed primarily consists of work which has been done in the developed beer markets or talks about projected figures based on empirical data. The biggest gap in such projections is the lack of understanding of the Indian consumer. Launches of a number of successful international products in India backed by such research have failed because of this. This research will try and understand the cultural differences between the Indian beer drinker and the western beer drinker and do a comparative analysis to gain insights which can be used to design the marketing and communications strategy for these international companies. Beer as a product has been successful in developed countries because of the community culture they have created amongst the consumers. The research will help determine key drivers and key characteristics of the Indian beer market. Proposed Research Design The research will be carried out through administering questionnaires to the beer drinking community in urban India as well as respondents in USA, Canada, Germany, UK, Columbia, Brazil, China, France, Poland, Finland, Slovakia, Lithuania and Korea. Detailed interviews will be carried out with some respondents in all these locations through telephonic interview/online interaction to understand the culture of beer consumption there. An analysis will also be done to compare the communication of the top 3 brands of the world in all these countries to see the differences and similarities and how these consumers absorb it. The Indian respondents will then be shown the communication used in all these countries and insights will be taken on their response to each communication. This will give us insights on the cultural differences and similarities between the Indian consumer and their international counterparts. The sample size will consist of at least 10 detailed interviews of international respondents and 10 in depth interviews on Indian consumers. The questionnaires will be administered to 150 beer drinkers in India and 50 based abroad. The sample size of the questionnaire might increase based on the response of the target group. Expected Contribution The study as earlier mentioned will give a deep insight into the mindset of the urban Indian consumer with respect to beer. It will also look at what are the associations that the Indian consumer has with the alcohol industry in terms of perceptions and specifically with beer. Their responses to international communication will be recorded and analysed to define the key drivers and the key characteristics of the Indian market. The final output as mentioned in the introduction would address at the following heads: Which of the marketing and communication strategies used in other countries would / wouldnt work in India, and why? Opportunities for replication of festival models and other community building activities from other countries. Implications for the Indian beer manufacturers and marketers, based on a comparative analysis of beer positioning and communication in different cultures.

Desi Arnaz :: Essays Papers

Desi Arnaz Cuban bandleader and singer-turned savvy TV mogul who, after his marriage to comedienne Lucille Ball in 1940, parlayed their successful "I Love Lucy" series into the Desilu TV production empire, which in its heyday also produced the successful and highly lucrative "The Untouchables" and "Star Trek" series. *p*Desiderio Alberto Arnaz y de Acha III was born in 1917 to wealthy Cuban landowners. His father was also the mayor of the town they lived in, but that soon changed. At the age of 16, Desi and his mother had to flee to Miami because of Batista's overthrow of the Machado Government in 1933. *P**BR*When Desi arrived in America, it was a struggle for he and his mother. But soon after he arrived, he joined the Siboney Septet at the Roney Plaza. Later, he started working with Xavier Cugat's band in 1937 and later put together his own rhumba band. His youthful good-looks and engaging presence soon won him a featured spot in the 1939 Broadway musical and theatrical version of "Too Many G irls" and the following year he was signed by RKO. On the movie set, he met his future wife, Lucille Ball. Later that year Desi and Lucy eloped to Connecticut and got married in a country club. Arnaz was featured in several films, mostly as a colorful Latin. Joining MGM, he won attention for his sole dramatic role in the war drama, "Bataan" (1942), but gave up films for touring with his successful band. The marriage was subject to the road most of the time and to Lucy's movie career. When the couple came up with the idea for a television series, they fought to do it together to save their marriage. But the network didn't think the television series would work with Desi being Cuban. But that didn't stop Lucy and Desi. In the summer of 1950, they went on tour, performing for live audiences to prove that the show would work. Well, as you know, the rest is television history!*P**BR*Desi made the first 5,000 dollars spent into millions in just four years. He convinced the show's sponsor, Phillip Morris, that Lucy having a baby on the show would give them great publicity. He was right: the birth of Little Ricky drew 44 million viewers (the swearing in of the President that year only drew 22 million), and the story made headlines everywhere across America. With Desi as a successful executive, and head of the couple's production company, DesiLu, Arnaz pioneered a new way of producing TV shows, shooting each episode of I

Based Data Mining Approach for Quality Control

Classification-Based Data Mining Approach For Quality Control In Wine Production GUIDED BY: | | SUBMITTED BY:| Jayshri Patel| | Hardik Barfiwala| INDEX Sr No| Title| Page No. | 1| Introduction Wine Production| | 2| Objectives| | 3| Introduction To Dataset| | 4| Pre-Processing| | 5| Statistics Used In Algorithms| | 6| Algorithms Applied On Dataset| | 7| Comparison Of Applied Algorithm | | 8| Applying Testing Dataset| | 9| Achievements| | 1.INTRODUCTION TO WINE PRODUCTION * Wine industry is currently growing well in the market since the last decade. However, the quality factor in wine has become the main issue in wine making and selling. * To meet the increasing demand, assessing the quality of wine is necessary for the wine industry to prevent tampering of wine quality as well as maintaining it. * To remain competitive, wine industry is investing in new technologies like data mining for analyzing taste and other properties in wine. Data mining techniques provide more than summary, but valuable information such as patterns and relationships between wine properties and human taste, all of which can be used to improve decision making and optimize chances of success in both marketing and selling. * Two key elements in wine industry are wine certification and quality assessment, which are usually conducted via physicochemical and sensory tests. * Physicochemical tests are lab-based and are used to characterize physicochemical properties in wine such as its density, alcohol or pH values. * Meanwhile, sensory tests such as taste preference are performed by human experts.Taste is a particular property that indicates quality in wine, the success of wine industry will be greatly determined by consumer satisfaction in taste requirements. * Physicochemical data are also found useful in predicting human wine taste preference and classifying wine based on aroma chromatograms. 2. OBJECTIVE * Modeling the complex human taste is an important focus in wine industries. * The main purpose of this study was to predict wine quality based on physicochemical data. * This study was also conducted to identify outlier or anomaly in sample wine set in order to detect ruining of wine. 3. INTRODUCTION TO DATASETTo evaluate the performance of data mining dataset is taken into consideration. The present content describes the source of data. * Source Of Data Prior to the experimental part of the research, the data is gathered. It is gathered from the UCI Data Repository. The UCI Repository of Machine Learning Databases and Domain Theories is a free Internet repository of analytical datasets from several areas. All datasets are in text files format provided with a short description. These datasets received recognition from many scientists and are claimed to be a valuable source of data. * Overview Of Dataset INFORMATION OF DATASET|Title:| Wine Quality| Data Set Characteristics:| Multivariate| Number Of Instances:| WHITE-WINE : 4898 RED-WINE : 1599 | Area:| Business| Attrib ute Characteristic:| Real| Number Of Attribute:| 11 + Output Attribute| Missing Value:| N/A| * Attribute Information * Input variables (based on physicochemical tests) * Fixed Acidity: Amount of Tartaric Acid present in wine. (In mg per liter) Used for taste, feel and color of wine. * Volatile Acidity: Amount of Acetic Acid present in wine. (In mg per liter) Its presence in wine is mainly due to yeast and bacterial metabolism. * Citric Acid: Amount of Citric Acid present in wine. In mg per liter) Used to acidify wine that are too basic and as a flavor additive. * Residual Sugar: The concentration of sugar remaining after fermentation. (In grams per liter) * Chlorides: Level of Chlorides added in wine. (In mg per liter) Used to correct mineral deficiencies in the brewing water. * Free Sulfur Dioxide: Amount of Free Sulfur Dioxide present in wine. (In mg per liter) * Total Sulfur Dioxide: Amount of free and combined sulfur dioxide present in wine. (In mg per liter) Used mainly as pres ervative in wine process. * Density: The density of wine is close to that of water, dry wine is less and sweet wine is higher. In kg per liter) * PH: Measures the quantity of acids present, the strength of the acids, and the effects of minerals and other ingredients in the wine. (In values) * Sulphates: Amount of sodium metabisulphite or potassium metabisulphite present in wine. (In mg per liter) * Alcohol: Amount of Alcohol present in wine. (In percentage) * Output variable (based on sensory data) * Quality (score between 0 and 10) : White Wine : 3 to 9 Red Wine : 3 to 8 4. PRE-PROCESSING * Pre-processing Of Data Preprocessing of the dataset is carried out before mining the data to remove the different lacks of the information in the data source.Following different process are carried out in the preprocessing reasons to make the dataset ready to perform classification process. * Data in the real world is dirty because of the following reason. * Incomplete: Lacking attribute values, lacking certain attributes of interest, or containing only aggregate data. * E. g. Occupation=â€Å"† * Noisy : Containing errors or outliers. * E. g. Salary=â€Å"-10† * Inconsistent : Containing discrepancies in codes or names. * E. g. Age=â€Å"42† Birthday=â€Å"03/07/1997† * E. g. Was rating â€Å"1,2,3†, Now rating â€Å"A, B, C† * E. g. Discrepancy between duplicate records * No quality data, no quality mining results! Quality decisions must be based on quality data. * Data warehouse needs consistent integration of quality data. * Major Tasks in done in the Data Preprocessing are, * Data Cleaning * Fill in missing values, smooth noisy data, identify or remove outliers, and resolve inconsistencies. * Data integration * Integration of multiple databases, data cubes, or files. * The dataset provided from given data source is only in one single file. So there is no need for integrating the dataset. * Data transformation * Normalization a nd aggregation * The dataset is in Normalized form because it is in single data file. * Data reduction Obtains reduced representation in volume but produces the same or similar analytical results. * The data volume in the given dataset is not very huge, the procedure of performing different algorithm is easily done on dataset so the reduction of dataset is not needed on the data set * Data discretization * Part of data reduction but with particular importance, especially for numerical data. * Need for Data Preprocessing in wine quality, * For this dataset Data Cleaning is only required in data pre-processing. * Here, NumericToNominal, InterquartileRange and RemoveWithValues filters are used for data pre-processing. * NumericToNominal Filter weka. filters. unsupervised. attribute. NumericToNominal) * A filter for turning numeric attribute into nominal once. * In our dataset, Class attribute â€Å"Quality† in both dataset (Red-wine Quality, White-wine Quality) have a type †Å"Numeric†. So after applying this filter, class attribute â€Å"Quality† convert into type â€Å"Nominal†. * And Red-wine Quality dataset have class names 3, 4, 5 †¦ 8 and White-wine Quality dataset have class names 3, 4, 5 †¦ 9. * Because of classification does not apply on numeric type class field, there is a need for this filter. * InterquartileRange Filter (weka. filters. unsupervised. attribute. InterquartileRange) A filter for detecting outliers and extreme values based on interquartile ranges. The filter skips the class attribute. * Apply this filter for all attribute indices with all default options. * After applying, filter adds two more fields which names are â€Å"Outliers† and â€Å"ExtremeValue†. And this fields has two types of label â€Å"No† and â€Å"Yes†. Here â€Å"Yes† label indicates, there are outliers and extreme values in dataset. * In our dataset, there are 83 extreme values and 125 outliers i n White-wine Quality dataset and 69 extreme values and 94 outliers in Red-wine Quality. * RemoveWithValues Filter (weka. filters. unsupervised. instance.RemoveWithValues) * Filters instances according to the value of an attribute. * This filter has two options which are â€Å"AttributeIndex† and â€Å"NominalIndices†. * AttributeIndex choose attribute to be use for selection and NominalIndices choose range of label indices to be use for selection on nominal attribute. * In our dataset, AttributeIndex is â€Å"last† and NominalIndex is also â€Å"last†, so It will remove first 83 extreme values and then 125 outliers in White-wine Quality dataset and 69 extreme values and 94 outliers in Red-wine Quality. * After applying this filter on dataset remove both fields from dataset. * Attribute SelectionRanking Attributes Using Attribute Selection Algorithm| RED-WINE| RANKED| WHITE-WINE| Volatile_Acidity(2)| 0. 1248| 0. 0406| Volatile_Acidity(2)| Total_sulfer_Diox ide(7)| 0. 0695| 0. 0600| Citric_Acidity(3)| Sulphates(10)| 0. 1464| 0. 0740| Chlorides(5)| Alcohal(11)| 0. 2395| 0. 0462| Free_Sulfer_Dioxide(6)| | | 0. 1146| Density(8)| | | 0. 2081| Alcohal(11)| * The selection of attributes is performed automatically by WEKA using Info Gain Attribute Eval method. * The method evaluates the worth of an attribute by measuring the information gain with respect to the class. 5. STATISTICS USED IN ALGORITHMS * Statistics MeasuresThere are Different algorithms that can be used while performing data mining on the different dataset using weka, some of them are describe below with the different statistics measures. * Statistics Used In Algorithms * Kappa statistic * The kappa statistic, also called the kappa coefficient, is a performance criterion or index which compares the agreement from the model with that which could occur merely by chance. * Kappa is a measure of agreement normalized for chance agreement. * Kappa statistic describe that our predicti on for class attribute for given dataset is how much near to actual values. * Values Range For Kappa Range| Result| lt;0| POOR| 0-0. 20| SLIGHT| 0. 21-0. 40| FAIR| 0. 41-0. 60| MODERATE| 0. 61-0. 80| SUBSTANTIAL| 0. 81-1. 0| ALMOST PERFECT| * As above range in weka algorithm evaluation if value of kappa is near to 1 then our predicted values are accurate to actual values so, applied algorithm is accurate. Kappa Statistic Values For Wine Quality DataSet| Algorithm| White-wine Quality| Red-wine Quality| K-Star| 0. 5365| 0. 5294| J48| 0. 3813| 0. 3881| Multilayer Perceptron| 0. 2946| 0. 3784| * Mean absolute error (MAE) * Mean absolute error (MAE)  is a quantity used to measure how close forecasts or predictions are to the eventual outcomes. The mean absolute error is given by, Mean absolute Error For Wine Quality DataSet| Algorithm| White-wine Quality| Red-wine Quality| K-Star| 0. 1297| 0. 1381| J48| 0. 1245| 0. 1401| Multilayer Perceptron| 0. 1581| 0. 1576| * Root Mean Squared Erro r * If you have some data and try to make a curve (a formula) fit them, you can graph and see how close the curve is to the points. Another measure of how well the curve fits the data is Root Mean Squared Error. * For each data point, CalGraph calculates the value of  Ã‚  y from the formula. It subtracts this from the data's y-value and squares the difference. All these squares are added up and the sum is divided by the number of data. * Finally CalGraph takes the square root. Written mathematically, Root Mean Square Error is Root Mean Squared Error For Wine Quality DataSet| Algorithm| White-wine Quality| Red-wine Quality| K-Star| 0. 2428| 0. 2592| J48| 0. 3194| 0. 3354| Multilayer Perceptron| 0. 2887| 0. 3023| * Root Relative Squared Error * The  root relative squared error  is relative to what it would have been if a simple predictor had been used. More specifically, this simple predictor is just the average of the actual values. Thus, the relative squared error takes the to tal squared error and normalizes it by dividing by the total squared error of the simple predictor. * By taking the square root of therelative squared error  one reduces the error to the same dimensions as the quantity being predicted. * Mathematically, the  root relative squared error  Ei  of an individual program  i  is evaluated by the equation: * where  P(ij)  is the value predicted by the individual program  i  for sample case  j  (out of  n  sample cases);  Tj  is the target value for sample case  j; andis given by the formula: * For a perfect fit, the numerator is equal to 0 and  Ei  = 0.So, the  Ei  index ranges from 0 to infinity, with 0 corresponding to the ideal. Root Relative Squared Error For Wine Quality DataSet| Algorithm| White-wine Quality| Red-wine Quality| K-Star| 78. 1984 %| 79. 309 %| J48| 102. 9013 %| 102. 602 %| Multilayer Perceptron| 93. 0018 %| 92. 4895 %| * Relative Absolute Error * The  relative absolute error  is very similar to the  relative squared error  in the sense that it is also relative to a simple predictor, which is just the average of the actual values. In this case, though, the error is just the total absolute error instead of the total squared error. Thus, the relative absolute error takes the total absolute error and normalizes it by dividing by the total absolute error of the simple predictor. Mathematically, the  relative absolute error  Ei  of an individual program  i  is evaluated by the equation: * where  P(ij)  is the value predicted by the individual program  i  for sample case  j  (out of  n  sample cases);  Tj  is the target value for sample case  j; andis given by the formula: * For a perfect fit, the numerator is equal to 0 and  Ei  = 0. So, the  Ei  index ranges from 0 to infinity, with 0 corresponding to the ideal.Relative Absolute Squared Error For Wine Quality DataSet| Algorithm| White-wine Quality| Red-wine Quality | K-Star| 67. 2423 %| 64. 5286 %| J48| 64. 577 %| 65. 4857 %| Multilayer Perceptron| 81. 9951 %| 73. 6593 %| * Various Rates * There are four possible outcomes from a classifier. * If the outcome from a prediction is  p  and the actual value is also  p, then it is called a  true positive  (TP). * However if the actual value is  n  then it is said to be a  false positive  (FP). * Conversely, a  true negative  (TN) has occurred when both the prediction outcome and the actual value are  n. And  false negative  (FN) is when the prediction outcome is  n while the actual value is  p. * Absolute Value | P| N| TOTAL| p’| True positive| false positive| P’| n’| false negative| True negative| N’| Total| P| N| | * ROC Curves * While estimating the effectiveness and accuracy of data mining technique it is essential to measure the error rate of each method. * In the case of binary classification tasks the error rate takes and components under consideration. * The ROC analysis which stands for Receiver Operating Characteristics is applied. * The sample ROC curve is presented in the Figure below.The closer the ROC curve is to the top left corner of the ROC chart the better the performance of the classifier. * Sample ROC curve (squares with the usage of the model, triangles without). The line connecting the square with triage is the benefit from the usage of the model. * It plots the curve which consists of x-axis presenting false positive rate and y-axis which plots the true positive rate. This curve model selects the optimal model on the basis of assumed class distribution. * The ROC curves are applicable e. g. in decision tree models or rule sets. * Recall, Precision and F-Measure There are four possible results of classification. * Different combination of these four error and correct situations are presented in the scientific literature on topic. * Here three popular notions are presented. The introduction of the se classifiers is explained by the possibility of high accuracy by negative type of data. * To avoid such situation recall and precision of the classification are introduced. * The F measure is the harmonic mean of precision and recall. * The formal definitions of these measures are as follow : PRECSION = TPTP+FP RECALL = TPTP+FNF-Measure = 21PRECSION+1RECALL * These measures are introduced especially in information retrieval application. * Confusion Matrix * A matrix used to summarize the results of a supervised classification. * Entries along the main diagonal are correct classifications. * Entries other than those on the main diagonal are classification errors. 6. ALGORITHMS * K-Nearest Neighbor Classifiers * Nearest neighbor classifiers are based on learning by analogy. * The training samples are described by n-dimensional numeric attributes. Each sample represents a point in an n-dimensional space. In this way, all of the training samples are stored in an n-dimensional pattern space. When given an unknown sample, a k-nearest neighbor classifier searches the pattern space for the k training samples that are closest to the unknown sample. * These k training samples are the k-nearest neighbors of the unknown sample. â€Å"Closeness† is defined in terms of Euclidean distance, where the Euclidean distance between two points, , * The unknown sample is assigned the most common class among its k nearest neighbors. When k = 1, the unknown sample is assigned the class of the training sample that is closest to it in pattern space. Nearest neighbor classifiers are instance-based or lazy learners in that they store all of the training samples and do not build a classifier until a new (unlabeled) sample needs to be classified. * Lazy learners can incur expensive computational costs when the number of potential neighbors (i. e. , stored training samples) with which to compare a given unlabeled sample is great. * Therefore, they require efficient indexing techniqu es. As expected, lazy learning methods are faster at training than eager methods, but slower at classification since all computation is delayed to that time.Unlike decision tree induction and back propagation, nearest neighbor classifiers assign equal weight to each attribute. This may cause confusion when there are many irrelevant attributes in the data. * Nearest neighbor classifiers can also be used for prediction, i. e. to return a real-valued prediction for a given unknown sample. In this case, the classifier returns the average value of the real-valued labels associated with the k nearest neighbors of the unknown sample. * In weka the previously described algorithm nearest neighbor is given as Kstar algorithm in classifier -> lazy tab. The Result Generated After Applying K-Star On White-wine Quality Dataset Kstar Options : -B 70 -M a | Time Taken To Build Model: 0. 02 Seconds| Stratified Cross-Validation (10-Fold)| * Summary | Correctly Classified Instances | 3307 | 70. 6624 % | Incorrectly Classified Instances| 1373 | 29. 3376 %| Kappa Statistic | 0. 5365| | Mean Absolute Error | 0. 1297| | Root Mean Squared Error| 0. 2428| | Relative Absolute Error | 67. 2423 %| | Root Relative Squared Error | 78. 1984 %| | Total Number Of Instances | 4680 | | * Detailed Accuracy By Class | TP Rate| FP Rate | Precision | Recall | F-Measure | ROC Area | PRC Area| Class| | 0 | 0 | 0 | 0 | 0 | 0. 583 | 0. 004 | 3| | 0. 211 | 0. 002 | 0. 769 | 0. 211 | 0. 331 | 0. 884 | 0. 405 | 4| | 0. 672 | 0. 079 | 0. 777 | 0. 672 | 0. 721 | 0. 904 | 0. 826 | 5| | 0. 864 | 0. 378 | 0. 652 | 0. 864 | 0. 743 | 0. 84 | 0. 818 | 6| | 0. 536 | 0. 031 | 0. 797 | 0. 536 | 0. 641 | 0. 911 | 0. 772 | 7| | 0. 398 | 0. 002 | 0. 883 | 0. 398 | 0. 548 | 0. 913 | 0. 572 | 8| | 0 | 0 | 0 | 0 | 0 | 0. 84 | 0. 014 | 9| Weighted Avg. | 0. 707 | 0. 2 | 0. 725 | 0. 707 | 0. 695 | 0. 876 | 0. 787| | * Confusion Matrix| A | B | C | D | E | F| G | | Class| 0 | 0 | 4 | 9 | 0| 0 | 0 | | | A=3| 0| 30| 49| 62| 1 | 0 | 0| | | B=4| 0 | 7 | 919| 437| 5 | 0 | 0 | | | C=5| 0 | 2 | 201| 1822| 81 | 2 | 0 | || D=6| 0 | 0 | 9 | 389 | 468 | 7 | 0| || E=7| 0 | 0 | 0 | 73 | 30 | 68 | 0 | || F=8| 0 | 0 | 0 | 3 | 2 | 0 | 0 | || G=9| * Performance Of The Kstar With Respect To A Testing Configuration For The White-wine Quality DatasetTesting Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 99. 6581 %| 100 %| 70. 6624 %| 63. 9221 %| Kappa statistic| 0. 9949| 1| 0. 5365| 0. 4252| Mean Absolute Error| 0. 0575| 0. 0788| 0. 1297| 0. 1379| Root Mean Squared Error| 0. 1089| 0. 145| 0. 2428| 0. 2568| Relative Absolute Error| 29. 8022 %| | 67. 2423 %| 71. 2445 %| * The Result Generated After Applying K-Star On Red-wine Quality Dataset Kstar Options : -B 70 -M a | Time Taken To Build Model: 0 Seconds| Stratified Cross-Validation (10-Fold)| * Summary | Correctly Classified Instances | 1013 | 71. 379 %| Incorrectly Classified Instances| 413 | 28. 9621 %| Kappa Stat istic | 0. 5294| | Mean Absolute Error | 0. 1381| | Root Mean Squared Error | 0. 2592| | Relative Absolute Error | 64. 5286 %| | Root Relative Squared Error | 79. 309 %| | Total Number Of Instances | 1426 | | * Detailed Accuracy By Class | | TP Rate | FP Rate | Precision | Recall | F-Measure | ROC Area | PRC Area| Class| | 0 | 0. 001 | 0 | 0 | 0 | 0. 574 | 0. 019 | 3| | 0 | 0. 003 | 0 | 0 | 0 | 0. 811 | 0. 114 | 4| | 0. 791| 0. 176 | 0. 67| 0. 791| 0. 779 | 0. 894 | 0. 867 | 5| | 0. 769 | 0. 26 | 0. 668 | 0. 769 | 0. 715 | 0. 834 | 0. 788 | 6| | 0. 511 | 0. 032 | 0. 692 | 0. 511 | 0. 588 | 0. 936 | 0. 722 | 7| | 0. 125 | 0. 001 | 0. 5 | 0. 125 | 0. 2 | 0. 896 | 0. 142 | 8| Weighted Avg. | 0. 71| 0. 184| 0. 685| 0. 71| 0. 693| 0. 871| 0. 78| | * Confusion Matrix | A | B | C | D | E | F| | Class| 0 | 1 | 4| 1 | 0 | 0 | | | A=3| 1 | 0 | 30| 17 | 0 | 0| | | B=4| 0 | 2| 477| 120 | 4 | 0| | | C=5| 0 | 1 | 103 | 444| 29 | 0| || D=6| 0 | 0 | 8 | 76 | 90 | 2 | || E=7| 0 | 0 | 0 | 7 | 7 | 2| || F=8| Performance Of The Kstar With Respect To A Testing Configuration For The Red-wine Quality Dataset Testing Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 99. 7895 %| 100 % | 71. 0379 %| 70. 7216 %| Kappa statistic| 0. 9967| 1| 0. 5294| 0. 5154| Mean Absolute Error| 0. 0338| 0. 0436| 0. 1381| 0. 1439| Root Mean Squared Error| 0. 0675| 0. 0828 | 0. 2592| 0. 2646| Relative Absolute Error| 15. 8067 %| | 64. 5286 %| 67. 4903 %| * J48 Decision Tree * Class for generating a pruned or unpruned C4. 5 decision tree. A decision tree is a predictive machine-learning model that decides the target value (dependent variable) of a new sample based on various attribute values of the available data. * The internal nodes of a decision tree denote the different attribute; the branches between the nodes tell us the possible values that these attributes can have in the observed samples, while the terminal nodes tell us the final value (class ification) of the dependent variable. * The attribute that is to be predicted is known as the dependent variable, since its value depends upon, or is decided by, the values of all the other attributes.The other attributes, which help in predicting the value of the dependent variable, are known as the independent variables in the dataset. * The J48 Decision tree classifier follows the following simple algorithm: * In order to classify a new item, it first needs to create a decision tree based on the attribute values of the available training data. So, whenever it encounters a set of items (training set) it identifies the attribute that discriminates the various instances most clearly. * This feature that is able to tell us most about the data instances so that we can classify them the best is said to have the highest information gain. Now, among the possible values of this feature, if there is any value for which there is no ambiguity, that is, for which the data instances falling wi thin its category have the same value for the target variable, then we terminate that branch and assign to it the target value that we have obtained. * For the other cases, we then look for another attribute that gives us the highest information gain. Hence we continue in this manner until we either get a clear decision of what combination of attributes gives us a particular target value, or we run out of attributes.In the event that we run out of attributes, or if we cannot get an unambiguous result from the available information, we assign this branch a target value that the majority of the items under this branch possess. * Now that we have the decision tree, we follow the order of attribute selection as we have obtained for the tree. By checking all the respective attributes and their values with those seen in the decision tree model, we can assign or predict the target value of this new instance. * The Result Generated After Applying J48 On White-wine Quality Dataset Time Taken To Build Model: 1. 4 Seconds| Stratified Cross-Validation (10-Fold) | * Summary| | | Correctly Classified Instances| 2740 | 58. 547 %| Incorrectly Classified Instances | 1940 | 41. 453 %| Kappa Statistic | 0. 3813| | Mean Absolute Error | 0. 1245| | Root Mean Squared Error | 0. 3194| | Relative Absolute Error | 64. 5770 %| | Root Relative Squared Error| 102. 9013 %| | Total Number Of Instances | 4680| | * Detailed Accuracy By Class| | TP Rate| FP Rate| Precision| Recall| F-Measure| ROC Area| Class| | 0| 0. 002| 0| 0| 0| 0. 30| 3| | 0. 239| 0. 020| 0. 270| 0. 239| 0. 254| 0. 699| 4| | 0. 605| 0. 169| 0. 597| 0. 605| 0. 601| 0. 763| 5| | 0. 644| 0. 312| 0. 628| 0. 644| 0. 636| 0. 689| 6| | 0. 526| 0. 099| 0. 549| 0. 526| 0. 537| 0. 766| 7| | 0. 363| 0. 022| 0. 388| 0. 363| 0. 375| 0. 75| 8| | 0| 0| 0| 0| 0| 0. 496| 9| Weighted Avg. | 0. 585 | 0. 21 | 0. 582 | 0. 585 | 0. 584 | 0. 727| | * Confusion Matrix | A| B| C| D| E| F| G| || Class| 0| 2| 6| 5| 0| 0| 0| || A=3| 1| 34| 55| 44| 6| 2| 0| || B=4| 5| 50| 828| 418| 60| 7| 0| || C=5| 2| 32| 413| 1357| 261| 43| 0| || D=6| | 7| 76| 286| 459| 44| 0| || E=7| 1| 1| 10| 49| 48| 62| 0| || F=8| 0| 0| 0| 1| 2| 2| 0| || G=9| * Performance Of The J48 With Respect To A Testing Configuration For The White-wine Quality Dataset Testing Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 90. 1923 %| 70 %| 58. 547 %| 54. 8083 %| Kappa statistic| 0. 854| 0. 6296| 0. 3813| 0. 33| Mean Absolute Error| 0. 0426| 0. 0961| 0. 1245| 0. 1347| Root Mean Squared Error| 0. 1429| 0. 2756| 0. 3194| 0. 3397| Relative Absolute Error| 22. 0695 %| | 64. 577 %| 69. 84 %| * The Result Generated After Applying J48 On Red-wine Quality Dataset Time Taken To Build Model: 0. 17 Seconds| Stratified Cross-Validation| * Summary| Correctly Classified Instances | 867 | 60. 7994 %| Incorrectly Classified Instances | 559 | 39. 2006 %| Kappa Statistic | 0. 3881| | Mean Absolute Error | 0. 1401| | Root Mean Squa red Error | 0. 3354| | Relative Absolute Error | 65. 4857 %| | Root Relative Squared Error | 102. 602 %| |Total Number Of Instances | 1426 | | * Detailed Accuracy By Class| | Tp Rate | Fp Rate | Precision | Recall | F-measure | Roc Area | Class| | 0 | 0. 004 | 0 | 0 | 0 | 0. 573 | 3| | 0. 063 | 0. 037 | 0. 056 | 0. 063 | 0. 059 | 0. 578 | 4| | 0. 721 | 0. 258 | 0. 672 | 0. 721 | 0. 696 | 0. 749 | 5| | 0. 57 | 0. 238 | 0. 62 | 0. 57 | 0. 594 | 0. 674 | 6| | 0. 563 | 0. 64 | 0. 553 | 0. 563 | 0. 558 | 0. 8 | 7| | 0. 063 | 0. 006 | 0. 1 | 0. 063 | 0. 077 | 0. 691 | 8| Weighted Avg. | 0. 608 | 0. 214 | 0. 606 | 0. 608 | 0. 606 | 0. 718 | | * Confusion Matrix | A | B | C | D | E | F | | Class| 0 | 2 | 1 | 2 | 1 | 0 | | | A=3| 2 | 3 | 25 | 15 | 3 | 0 | | | B=4| 1 | 26 | 435 | 122 | 17 | 2 | | | C=5| 2 | 21 | 167 | 329 | 53 | 5 | | | D=6| 0 | 2 | 16 | 57 | 99 | 2 | | | E=7| 0 | 0 | 3 | 6 | 6 | 1 | | | F=8| Performance Of The J48 With Respect To A Testing Configuration For The Red-wine Qual ity Dataset Testing Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 91. 1641 %| 80 %| 60. 7994 %| 62. 4742 %| Kappa statistic| 0. 8616| 0. 6875| 0. 3881| 0. 3994| Mean Absolute Error| 0. 0461| 0. 0942| 0. 1401| 0. 1323| Root Mean Squared Error| 0. 1518| 0. 2618| 0. 3354| 0. 3262| Relative Absolute Error| 21. 5362 %| 39. 3598 %| 65. 4857 %| 62. 052 %| * Multilayer Perceptron * The back propagation algorithm performs learning on a multilayer feed-forward neural network. It iteratively learns a set of weights for prediction of the class label of tuples. * A multilayer feed-forward neural network consists of an input layer, one or more hidden layers, and an output layer. * Each layer is made up of units. The inputs to the network correspond to the attributes measured for each training tuple. The inputs are fed simultaneously into the units making up the input layer. These inputs pass through the input layer and are then weighted an d fed simultaneously to a second layer of â€Å"neuronlike† units, known as a hidden layer. The outputs of the hidden layer units can be input to another hidden layer, and so on. The number of hidden layers is arbitrary, although in practice, usually only one is used. The weighted outputs of the last hidden layer are input to units making up the output layer, which emits the network’s prediction for given tuples. * The units in the input layer are called input units. The units in the hidden layers and output layer are sometimes referred to as neurodes, due to their symbolic biological basis, or as output units. * The network is feed-forward in that none of the weights cycles back to an input unit or to an output unit of a previous layer.It is fully connected in that each unit provides input to each unit in the next forward layer. * The Result Generated After Applying Multilayer Perceptron On White-wine Quality Dataset Time taken to build model: 36. 22 seconds| Stratifi ed cross-validation| * Summary| Correctly Classified Instances | 2598 | 55. 5128 %| Incorrectly Classified Instances | 2082 | 44. 4872 %| Kappa statistic | 0. 2946| | Mean absolute error | 0. 1581| | Root mean squared error | 0. 2887| |Relative absolute error | 81. 9951 %| | Root relative squared error | 93. 0018 %| | Total Number of Instances | 4680 | | * Detailed Accuracy By Class | | TP Rate | FP Rate | Precision | Recall | F-Measure | ROC Area | PRC Area | Class| | 0 | 0 | 0 | 0 | 0 | 0. 344 | 0. 002 | 3| | 0. 056 | 0. 004 | 0. 308 | 0. 056 | 0. 095 | 0. 732 | 0. 156 | 4| | 0. 594 | 0. 165 | 0. 597 | 0. 594 | 0. 595 | 0. 98 | 0. 584 | 5| | 0. 704 | 0. 482 | 0. 545 | 0. 704 | 0. 614 | 0. 647 | 0. 568 | 6| | 0. 326 | 0. 07 | 0. 517 | 0. 326 | 0. 4 | 0. 808 | 0. 474 | 7| | 0. 058 | 0. 002 | 0. 5 | 0. 058 | 0. 105 | 0. 8 | 0. 169 | 8| | 0 | 0 | 0| 0 | 0 | 0. 356 | 0. 001 | 9| Weighted Avg. | 0. 555 | 0. 279 | 0. 544 | 0. 555 | 0. 532 | 0. 728 | 0. 526| | * Confusion Matrix |A | B | C | D | E | F | G | | Class| 0 | 0 | 5 | 7 | 1 | 0 | 0 | | | A=3| 0 | 8 | 82 | 50 | 2 | 0 | 0 | | | B=4| 0 | 11 | 812 | 532 | 12 | 1 | 0 | | | C=5| 0 | 6 | 425 | 1483 | 188 | 6 | 0 | | | D=6| 0 | 1 | 33 | 551 | 285 | 3 | 0 | | | E=7| 0 | 0 | 3 | 98 | 60 | 10 | 0 | | | F=8| 0 | 0 | 0 | 2 | 3 | 0 | 0 | | | G=9| * Performance Of The Multilayer perceptron With Respect To A Testing Configuration For The White-wine Quality DatasetTesting Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 58. 1838 %| 50 %| 55. 5128 %| 51. 3514 %| Kappa statistic| 0. 3701| 0. 3671| 0. 2946| 0. 2454| Mean Absolute Error| 0. 1529| 0. 1746| 0. 1581| 0. 1628| Root Mean Squared Error| 0. 2808| 0. 3256| 0. 2887| 02972| Relative Absolute Error| 79. 2713 %| | 81. 9951 %| 84. 1402 %| * The Result Generated After Applying Multilayer Perceptron On Red-wine Quality Dataset Time taken to build model: 9. 14 seconds| Stratified cross-validation (10-Fold)| * Summary | Co rrectly Classified Instances | 880 | 61. 111 %| Incorrectly Classified Instances | 546 | 38. 2889 %| Kappa statistic | 0. 3784| | Mean absolute error | 0. 1576| | Root mean squared error | 0. 3023| | Relative absolute error | 73. 6593 %| | Root relative squared error | 92. 4895 %| | Total Number of Instances | 1426| | * Detailed Accuracy By Class | | TP Rate | FP Rate | Precision | Recall | F-Measure | ROC Area | Class| | 0 | 0 | 0 | 0 | 0 | 0. 47 | 3| | 0. 42 | 0. 005 | 0. 222 | 0. 042 | 0. 070 | 0. 735 | 4| | 0. 723 | 0. 249 | 0. 680 | 0. 723 | 0. 701 | 0. 801 | 5| | 0. 640 | 0. 322 | 0. 575 | 0. 640 | 0. 605 | 0. 692 | 6| | 0. 415 | 0. 049 | 0. 545 | 0. 415 | 0. 471 | 0. 831 | 7| | 0 | 0 | 0 | 0 | 0 | 0. 853 | 8| Weighted Avg. | 0. 617 | 0. 242 | 0. 595 | 0. 617 | 0. 602 | 0. 758| | * Confusion Matrix | A | B | C | D | E | F | | Class| | 0 | 5 | 1 | 0 | 0| || A=3| 0 | 2 | 34 | 11 | 1 | 0 | | | B=4| 0 | 2 | 436 | 160 | 5 | 0 | | | C=5| 0 | 5 | 156 | 369 | 47 | 0 | | | D=6| 0 | 0 | 10 | 93 | 73 | 0 | | | E=7| 0 | 0 | 0 | 8 | 8 | 0 | | | F=8| * Performance Of The Multilayer perceptron With Respect To A Testing Configuration For The Red-wine Quality Dataset Testing Method| Training Set| Testing Set| 10-Fold Cross Validation| 66% Split| Correctly Classified Instances| 68. 7237 %| 70 %| 61. 7111 %| 58. 7629 %| Kappa statistic| 0. 4895| 0. 5588| 0. 3784| 0. 327| Mean Absolute Error| 0. 426| 0. 1232| 0. 1576| 0. 1647| Root Mean Squared Error| 0. 2715| 0. 2424| 0. 3023| 0. 3029| Relative Absolute Error| 66. 6774 %| 51. 4904 %| 73. 6593 %| 77. 2484 %| * Result * The classification experiment is measured by accuracy percentage of classifying the instances correctly into its class according to quality attributes ranges between 0 (very bad) and 10 (excellent). * From the experiments, we found that classification for red wine quality using  Kstar algorithm achieved 71. 0379 % accuracy while J48 classifier achieved about 60. 7994% and Multilayer Perceptron classifier ac hieved 61. 7111% accuracy. For the white wine, Kstar algorithm yielded 70. 6624 % accuracy while J48 classifier yielded 58. 547% accuracy and Multilayer Perceptron classifier achieved 55. 5128 % accuracy. * Results from the experiments lead us to conclude that Kstar performs better in classification task as compared against the J48 and Multilayer Perceptron classifier. The processing time for Kstar algorithm is also observed to be more efficient and less time consuming despite the large size of wine properties dataset. 7. COMPARISON OF DIFFERENT ALGORITHM * The Comparison Of All Three Algorithm On White-wine Quality Dataset (Using 10-Fold Cross Validation) Kstar| J48| Multilayer Perceptron| Time (Sec)| 0| 1. 08| 35. 14| Kappa Statistics| 0. 5365| 0. 3813| 0. 29| Correctly Classified Instances (%)| 70. 6624| 58. 547| 55. 128| True Positive Rate (Avg)| 0. 707| 0. 585| 0. 555| False Positive Rate (Avg)| 0. 2| 0. 21| 0. 279| * Chart Shows The Best Suited Algorithm For Our Dataset (Measu res Vs Algorithms) * In above chart, comparison of True Positive rate and kappa statistics is given against three algorithm Kstar, J48, Multilayer Perceptron * Chart describes algorithm which is best suits for our dataset. In above chart column of TP rate & Kappa statistics of Kstar algorithm is higher than other two algorithms. * In above chart you can see that the False Positive Rate and the Mean Absolute Error of the Multilayer Perceptron algorithm is high compare to other two algorithms. So it is not good for our dataset. * But for the Kstar algorithm these two values are less, so the algorithm having lowest values for FP Rate & Mean Absolute Error rate is best suited algorithm. * So the final we can make conclusion that the Kstar algorithm is best suited algorithm for White-wine Quality dataset. The Comparison Of All Three Algorithm On Red-wine Quality Dataset (Using 10-Fold Cross Validation) | Kstar| J48| Multilayer Perceptron| Time (Sec)| 0| 0. 24| 9. 3| Kappa Statistics| 0. 5294| 0. 3881| 0. 3784| Correctly Classified Instances (%)| 71. 0379| 60. 6994| 61. 7111| True Positive Rate (Avg)| 0. 71| 0. 608| 0. 617| False Positive Rate (Avg)| 0. 184| 0. 214| 0. 242| * For Red-wine Quality dataset have also Kstar is best suited algorithm , because of TP rate & Kappa statistics of Kstar algorithm is higher than other two algorithms and FP rate & Mean Absolute Error of Kstar algorithm is lower than other algorithms. . APPLYING TESTING DATASET Step1: Load pre-processed dataset. Step2: Go to classify tab. Click on choose button and select lazy folder from the hierarchy tab and then select kstar algorithm. After selecting the kstar algorithm keep the value of cross validation = 10, then build the model by clicking on start button. Step3: Now take any 10 or 15 records from your dataset, make their class value unknown(by putting ’? ’ in the cell of the corresponding raw ) as shown below. Step 4: Save this data set as . rff file. Step 5: From â€Å"tes t option† panel select â€Å"supplied test set†, click on to the set button and open the test dataset file which was lastly created by you from the disk. Step 6: From â€Å"Result list panel† panel select Kstar-algorithm (because it is better than any other for this dataset), right click it and click â€Å"Re-evaluate model on current test set† Step 7: Again right click on Kstar algorithm and select â€Å"visualize classifier error† Step 8:Click on save button and then save your test model.Step 9: After you had saved your test model, a separate file is created in which you will be having your predicted values for your testing dataset. Step 10: Now, this test model will have all the class value generated by model by re-evaluating model on the test data for all the instances that were set to unknown, as shown in the figure below. 9. ACHIEVEMENT * Classification models may be used as part of decision support system in different stages of wine productio n, hence giving the opportunity for manufacturer to make corrective and additive measure that will result in higher quality wine being produced. From the resulting classification accuracy, we found that accuracy rate for the white wine is influenced by a higher number of physicochemistry attribute, which are alcohol, density, free sulfur dioxide, chlorides, citric acid, and volatile acidity. * Red wine quality is highly correlated to only four attributes, which are alcohol, sulphates, total sulfur dioxide, and volatile acidity. * This shows white wine quality is affected by physicochemistry attributes that does not affect the red wine in general. Therefore, I suggest that white wine manufacturer should conduct wider range of test particularly towards density and chloride content since white wine quality is affected by such substances. * Attribute selection algorithm we conducted also ranked alcohol as the highest in both datasets, hence the alcohol level is the main attribute that d etermines the quality in both red and white wine. * My suggestion is that wine manufacturer to focus in maintaining a suitable alcohol content, may be by longer fermentation period or higher yield fermenting yeast.