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The topic i have selected: Abstract: I will be going with the subject "Fraud detection using Data Mining" Fraud affirmation is an approach to manage shield others from being attacked by designers or to get secure from the cash desperado and cheats with the assistance of progression. Information Mining (DM) blueprint systems in recognizing firms that issue fraudulent financial statements (FFS) and manages the obvious affirmation of parts related to FFS. This evaluation explores the settlement of Decision Trees, Neural Networks, and Bayesian Belief Networks in the prominent proof of sham spending summaries. The information vector is made out of degrees got from budgetary outlines. Introduction: Data uncovering is looking for secured, significant, and possibly supportive models in huge enlightening lists. Data Mining is connected to finding unsuspected/already dark associations among the data. It is a multi-disciplinary fitness that usages AI, estimations, AI, and database advancement. Types of data mining Relational database Data warehouse Text mining data mining Distributed database Operational database End-user database Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data mining techniques for the detection of fraudulent financial statements. Expert systems with applications, 32(4), 995-1003 .

Operational database
End-user database
Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data
mining techniques for the detection of fraudulent financial
statements. Expert systems with applications, 32(4), 995-1003

Abstract: I will be going with the subject "Fraud detection using Data Mining" Fraud affirmation is an approach to manage shield others from being attacked by designers or to get secure from the cash desperado and cheats with the assistance of progression. Information Mining (DM) blueprint systems in recognizing firms that issue fraudulent financial statements (FFS) and manages the obvious affirmation of parts related to FFS. This evaluation explores the settlement of Decision Trees, Neural Networks, and Bayesian Belief Networks in the prominent proof of sham spending summaries. The information vector is made out of degrees got from budgetary outlines. Introduction: Data uncovering is looking for secured, significant, and possibly supportive models in huge enlightening lists. Data Mining is connected to finding unsuspected/already dark associations among the data. It is a multi-disciplinary fitness that usages AI, estimations, AI, and database advancement. Types of data mining Relational database Data warehouse Text mining data mining Distributed database Operational database End-user database Assignment Instructions: 1. No ZIP file 2. The submitted assignment must be typed by ONE Single MS Word/PDF file. 3. At least 10 pages (not including heading and content list pages) and 5 references. 4. Use 12-font size and 1.5 lines space 5. No more than 4 figures and 3 tables 6. Follow APA style and content format: UC follows the APA (American Psychological Association) for writing style in all its courses which require a Paper or Essay. .

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Fighting Money Laundering With Statistics and Machine Learning. Shakas Technologies ( Galaxy of Knowledge) #11/A 2nd East Main Road, Gandhi Nagar, Vellore - 632006. Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723 Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication | Email : info@shakastech.com | shakastech@gmail.com | website: www.shakastech.com Facebook: https://www.facebook.com/pages/Shakas-Technologies

Data minig with Big data analysis

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Posting 1 Reply required for belowBusiness costs or risks of p.docx

harrisonhoward80223

Posting 1 : Reply required for below Business costs or risks of poof data quality: Poor data quality may lead chiefs to not have the capacity to settle on poor choices or not have the capacity to settle on choices by any stretch of the imagination. Poor data may prompt lost deals and different opportunities, misallocation of assets, defective methodologies, and orders might not be right, inventory levels perhaps incorrect, and clients may wind up noticeably disappointed and headed out. The cost of poor quality data spreads all through the organization influencing frameworks from transportation and accepting to bookkeeping and client administrations. Extra costs are acquired when representatives must set aside opportunity to chase down and correct data errors. The improvement of information innovation amid the most recent decades has empowered organizations to gather and store enormous measures of data. Nonetheless, as the data volumes increment, so does the multifaceted nature of overseeing them. Since bigger and more unpredictable information assets are being gathered and overseen in organizations today, this implies the danger of poor data quality builds (Watts and Shankaranarayanan, 2009). Another often specified data related issue is that organizations often oversee data at a nearby level (e.g. division or area). Data mining: Data mining, likewise called learning disclosure in databases, in software engineering, the way toward finding intriguing and valuable examples and connections in extensive volumes of data. The field consolidates apparatuses from insights and counterfeit consciousness, (for example, neural networks and machine learning) with database administration to examine substantial computerized accumulations, known as data sets. Data mining is broadly utilized as a part of business (protection, saving money, retail), science inquire about (space science, prescription), and government security (location of hoodlums and terrorists). Text mining: Text Analytics, otherwise called text mining, is the way toward examining extensive accumulations of composed assets to create new information, and to transform the unstructured text into organized data for use in assist examination. Text mining distinguishes actualities, connections and statements that would somehow stay covered in the mass of textual huge data. These realities are removed and transformed into organized data, for investigation, perception (e.g. by means of html tables, mind maps, graphs), mix with organized data in databases or distribution centers, and further refinement utilizing machine learning (ML) frameworks. Posting 2 : Reply required for below What Are The Business Costs Or Risks Of Poor Data Quality? Financial effect – Poor data quality impacts organizations negatively regarding finances by raising the cost of operations which in turn reduces the revenue as well as the profit realized by the company over a given period. Also, poor data quality results in inapp.

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Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. 1 Data mining is an interdisciplinary sub field of computer science and statistics with an overall goal to extract from a data set and transform the information into a comprehensible structure for further use. 1 2 3 4 The process of digging through data to discover hidden connections and predict future trends has a long history. Sometimes referred to as 'knowledge discovery' in databases, the term data mining wasn't coined until the 1990s. What was old is new again, as data mining technology keeps evolving to keep pace with the limitless potential of big data and affordable computing power. Over the last decade, advances in processing power and speed have enabled us to move beyond manual, tedious and time consuming practices to quick, easy and automated data analysis. The more complex the data sets collected, the more potential there is to uncover relevant insights. Rupashi Koul "Overview of Data Mining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31368.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31368/overview-of-data-mining/rupashi-koul

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The thought that the continents had coastlines that looked like they.docx

gloriab9

The thought that the continents had coastlines that looked like they could fit together like pieces of a puzzle, especially in the case of South America and Africa, has persisted ever since the continents were mapped out (even Magellan took note of this). However, Alfred Wegener was the first to propose the theory of continental drift formally . The idea was met with much resistance and controversy in his time because Wegener could not explain the driving force of the plate movement. The year after Wegener died (1930), Arthur Holmes published his idea that thermal convection in the Earth's mantle could cause continents to move. In the 1960s, Harry Hess offered an additional explanation of plate movement by describing the process of seafloor spreading , which carries off older sediment and fossils, and moves the continents as new ocean crust spreads away from the ridges. In this way, he substantiated Wegener's theory of continental drift, and explained how the once-joined continents had separated into the seven that exist today. Respond to the following: Name a place on Earth where two plates are converging. Name a place where two plates are diverging. Name a place where two plates are sliding past each other. Must be at least 250-300 in length. APA Format. Remember, if you provide a quote or information from a source ( e.g. , your textbook or the Internet), you must include the correct citation and reference in APA style. Make the post engaging, interesting, and long enough to cover the material completely. It is helpful to think of the post as more of a mini-paper than a simple contribution to a discussion. .

The Theory of Moral SentimentsAdam SmithCopyright © Jo.docx

gloriab9

The Theory of Moral Sentiments Adam Smith Copyright © Jonathan Bennett 2017. All rights reserved [Brackets] enclose editorial explanations. Small ·dots· enclose material that has been added, but can be read as though it were part of the original text. Occasional •bullets, and also indenting of passages that are not quotations, are meant as aids to grasping the structure of a sentence or a thought. Every four-point ellipsis . . . . indicates the omission of a brief passage that seems to present more difficulty than it is worth. Longer omissions are reported between brackets in normal-sized type.—In Adam Smith’s day a ‘sentiment’ could be anything on a spectrum with feelings at one end and opinions at the other. This work of his is strongly tilted in the ‘feeling’ direction [see especially the chapter starting on page 168), but throughout the present version the word ‘sentiment’ will be left untouched. First launched: July 2008 Contents Part I: The Propriety of Action 1 Section 1: The Sense of Propriety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1: Sympathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 2: The pleasure of mutual sympathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Chapter 3: How we judge the propriety of other men’s affections by their concord or dissonance with our own . . 6 Chapter 4: The same subject continued . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Chapter 5: The likeable virtues and the respectworthy virtues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Section 2: The degrees of the different passions that are consistent with propriety . . . . . . . . . . . . . . . . . . . . . 13 Chapter 1: The passions that originate in the body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Smith on Moral Sentiments Chapter 2: The passions that originate in a particular turn or habit of the imagination . . . . . . . . . . . . . . . 16 Chapter 3: The unsocial passions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Chapter 4: The social passions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Chapter 5: The selfish passions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Section 3: How prosperity and adversity affect our judgments about the rightness of actions; and why it is easier to win our approval in prosperity than in adversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Chapter 1: The intensity-difference between joy and sympathy with joy is less than the intensity-difference between sorrow and sympathy with sorrow . . . . . . . . . . . . . . . . . . . .

The terrorist attacks on September 11, 2001 forever changed U.S..docx

gloriab9

The terrorist attacks on September 11, 2001 forever changed U.S. foreign and domestic policy. Has the "War on Terror" been largely successful or not? By what criteria has it been effective or not? What else could U.S. leaders do to make sure that the general public is safe from either foreign or domestic terrorists? Should the U.S. continue to use its military as a prime foreign policy tool or should more diplomacy be used first? Explain .

The term used to denote the beliefs that people have about political.docx

gloriab9

The term used to denote the beliefs that people have about political issues, events, institutions, and personalities is public opinion. Underlying public opinion, people's beliefs and ideologies ____________ A) prevent liberals and conservatives from sharing similar core values. B) force them to think carefully about each opinion that they hold. C) are established when they are young and rarely change as they grow older. D) color their perceptions so that they often make automatic judgments. .

The TermsMany terms mean different things in our common language a.docx

gloriab9

The Terms Many terms mean different things in our common language and in scientific language, which leads to misunderstandings about what they mean. This is especially true with terms like theory and law. The table below shows a few terms about scientific knowledge, defined in both our common language and scientific language. Commonly Misunderstood Terms Term Common Definition Scientific Definition hypothesis an educated guess a testable explanation used to guide research theory an idea a set of ideas supported by multiple experiments, done by multiple scientists that describe why something occurs law an absolute truth a description of what occurs (not why it occurs) supported by multiple experiments Please read the article HERE to better understand the differences between these terms. Example Situation: I have asked a few friends to help me with a little experiment. I have asked them to put a white rose in a small vase filled almost to the top with water and add a few drops of blue food coloring. They are to make observations while the flower changes. What has occurred? We have put it in water and left it for a few hours. When we came back we all had the same outcome. The flower had turned blue. This is what we will call Scientific law. It is the happenings of a certain experiment. If you put a flower in colored water the flower will take on the color of the water. It simply says WHAT will happen. But why did it occur? My friends and I believe it is because the colored water is drawn up through the flower's stem. This is what we call a scientific theory. It tries to explain WHY something occurs. A scientific theory is not less true than a scientific law. However, a scientific law is a direct result of the results of the experiment. Since in order to become a scientific law it must be proven many times, it is unlikely that somehow new results will occur and a law will be disproved. However, a scientific theory is based on interpretation of experimental results. The results are not usually proven wrong, just the conclusions drawn from the observations. As new and different information becomes available we may realize that we did not draw the correct conclusion and we need to adjust our theory accordingly. Just a Theory When arguing against a scientific theory, like the theory of evolution, people will sometimes say, "but its just a theory." That means that they do not understand that scientific theories are the strongest explanations offered by science. Theories are not scientific laws "in training," like how bills can be ratified into laws. A scientific theory does not ever turn into a scientific law. Instead laws describe what happens, frequently with an equation, while theories explain why it happens. Theories are built on the work on many scientists who conduct many different experiments. Not all of these experiments have the same goal, but through their combined work theories are constantly revised.

The term 21st century skills suggests that there is a new set of.docx

gloriab9

The term 21st century skills suggests that there is a new set of skills that individuals need to possess to be successful as learners, citizens, and employees in the competitive, global economy. Compare and contrast what the authors identify as twenty-first century skills with what you would identify as twenty-first century skills. Lastly, discuss how these skills fit into the traditional element of schooling that focuses on ensuring that all students develop the basic skills of reading, writing, and mathematics. .

The term network economy” is used to emphasize the features of the .docx

gloriab9

The term “network economy” is used to emphasize the features of the new, technology-enhanced economy within the information society. It stems from a key attribute— products and services that are created through networks operating on large or global scales, enabled by the current status of the global networks. What are the principal impacts of the network economy for both established organizations and upstarts? Identify and provide examples of the most important recent technology and business innovations in the network economy. How has the adaptation of the new technologies affected the organizations from your examples? The network economy introduces information-intensive goods, such as downloadable music and software. Information, as an economic entity, differs in behavior compared to traditional goods. How do information-intensive goods differ from traditional information goods? Provide two examples of each. What is the principal economic characteristic of information? What are the principal implications for strategic decisions? What are the principal enablers for the continued importance of e-commerce trends? What does the term e-commerce 2.0 refer to? What are main principles of e-commerce 2.0? Give real-life examples of e-commerce 2.0 principles. Do you think that your set of e-commerce 2.0 principles is comprehensive? Why? Are these principles congruent with your personal understanding of e-commerce? .

The term narcissist gets overused. I define it as not having empathy.docx

gloriab9

The term paper it should be of professional quality and be in th.docx

gloriab9

The term paper it should be of professional quality and be in the format of an IEEE transaction style. Figures must be clear and drawn by you. Proper citation of references must be embedded in the term paper. All term report should be printed in 8.5x11in format, 10 size, time new roman font, two-column, about 8 pages, left, right, top, bottom margin 1 inch, and contain the following: 1. Title page. 2. Abstract (summary of the paper). 3. Introduction (problem motivation, background materials, related work, summary of objectives and methods). 4. (i) Description of existing algorithms/protocols for survey papers; (ii) system model, assumptions, and/or formal problem formulation for research-oriented papers. 5. (i) Comparison among existing algorithms/protocols and discussion on possible improvements/enhancements; (ii) project results (derivation, proof, justification, or detailed design/simulation) in one or more numbered sections for research-oriented papers. 6. Conclusions (evaluation of results, suggestions for improvements, or future work). 7. References must follow IEEE Transactions format (at least 10 references). Proper citation of references must be embedded in the term paper. Note: Please, follow the above-mentioned guidelines and prepare my term paper report accordingly. Also, I'm attaching my mid-term report document .

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1. The topic i have selected: Abstract: I will be going with the subject "Fraud detection using Data Mining" Fraud affirmation is an approach to manage shield others from being attacked by designers or to get secure from the cash desperado and cheats with the assistance of progression. Information Mining (DM) blueprint systems in recognizing firms that issue fraudulent financial statements (FFS) and manages the obvious affirmation of parts related to FFS. This evaluation explores the settlement of Decision Trees, Neural Networks, and Bayesian Belief Networks in the prominent proof of sham spending summaries. The information vector is made out of degrees got from budgetary outlines. Introduction: Data uncovering is looking for secured, significant, and possibly supportive models in huge enlightening lists. Data Mining is connected to finding unsuspected/already dark associations among the data. It is a multi-disciplinary fitness that usages AI, estimations, AI, and database advancement. Types of data mining Relational database Data warehouse Text mining data mining Distributed database

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