...What is data mining: * Data mining (knowledge discovery from data) * Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) patterns or knowledge from huge amount of data * data processing using sophisticated data search capabilities and statistical algorithms to discover patterns and correlations in large preexisting databases; a way to discover new meaning in data. 2. KDD process * General functionality * Descriptive data mining * Predictive data mining * Different views lead to different classifications * Data view: Kinds of data to be mined * Knowledge view: Kinds of knowledge to be discovered * Method view: Kinds of techniques utilized * Application view: Kinds of applications adapted Data mining issues * Mining methodology * Mining different kinds of knowledge from diverse data types, e.g., bio, stream, Web * Performance: efficiency, effectiveness, and scalability * Pattern evaluation: the interestingness problem * Incorporation of background knowledge * Handling noise and incomplete data * Parallel, distributed and incremental mining methods * Integration of the discovered knowledge with existing one: knowledge fusion * User interaction * Data mining query languages and ad-hoc mining * Expression and visualization of data mining results * Interactive mining of knowledge at multiple...
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...Similarity based Analysis of Networks of Ultra Low Resolution Sensors Relevance: Pervasive computing, temporal analysis to discover behaviour Method: MDS, Co-occurrence, HMMs, Agglomerative Clustering, Similarity Analysis Organization: MERL Published: July 2006, Pattern Recognition 39(10) Special Issue on Similarity Based Pattern Recognition Summary: Unsupervised discovery of structure from activations of very low resolution ambient sensors. Methods for discovering location geometry from movement patterns and behavior in an elevator scheduling scenario The context of this work is ambient sensing with a large number of simple sensors (1 bit per second giving on-off info). Two tasks are addressed. Discovering location geometry from patterns of sensor activations. And clustering activation sequences. For the former, a similarity metric is devised that measures the expected time of activation of one sensor after another has been activated, on the assumption that the two activations are resulting from movement. The time is used as a measure of distance between the sensors, and MDS is used to arrive at a geometric distribution. In the second part, the observation sequences are clustered by training HMMs for each sequence, and using agglomerative clustering. Having selected an appropriate number of clusters (chosen by the domain expert) the clusters can be used to train new HMM models. The straightforward mapping of the cluster HMMs is to a composite HMM, where each branch of...
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...quantified since and assigns numerical values to responses and measure statics. With this said Proverbs, the bible verse, supports that research methods can be Godly. I interpret that verse as meaning that it is important to know and confirm in your mind that you know something, but it is better to research the topic in a biblical since rather thas a secular or worldly since. the glory of kings is researching and becomeing stronger on a topic. Pshycologists often study peoples behavior in how and why they do things. These psycologists can us Qualitative research to learn how to tell why people do the things they do. Statement 2 Romans 12:2 says,"Do not conform to the pattern of this world, but be transformed by the renewing of your mind. Then you will be able to test and approve what God's will is--his good, pleasing and perfect will. In Quantitative research people study others behavior based on statics and numbers. Research methods can be ungodly because like the verse discribed, we are not suppost to conform to the patterns on this worl we live in. With quantitative reseach it is easy to follow the crowd and look at the statoics of what everyone else is going. The staticas give the answers to Peoples behaivio and that in my opinion is ungodly. What the majority does is not proper research on behavior.W e are too have a renewing of mind. Statement 1 The purpose of Qualitative Research is to create ideas or insights for a hypothesis for Quantitative...
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...This is a brief compilation on the DISTRICT FOCUS FOR RURAL DEVELOPMENT.It contains information gathered from various sources and quoted direct. District Development Committees were created in 1983 through the District Focus for Rural Development (DFRD) as a way to decentralize mobilization of resources, provision of public services and planning. The policy did however fail but the DDCs remained and continue to lead development planning and implementation at the district level. Decentralization policy: Adopted in 1982, the decentralization policy is implemented in Kenya through the District Focus for Rural Development (DFRD). The District Commissioners (DCs) are responsible for implementing all government development programs and handling the related funding from the district to the grassroots level. The Development Committees, set up at the district, division and location levels, not only implement programs identified by the Government but also spearhead similar programs and recommend them to the Government for financial and technical support. The District Focus for Rural Development (DFRD), adopted in 1983, was an attempt to coordinate development activities and service delivery at the district level. The DFRD has been until recently the key system for the planning, implementation and management of development activities. However, it has been argued that, “the DFRD was a mere dispersal of Central Government control outside the national capital without tangible...
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...Accounting Frauds and the Timing of Analyst Coverage Decisions and Recommendation Revisions: Evidence From the US Susan M. Young* Associate Professor Fordham University New York, NY 10019 syoung16@fordham.edu Emma Peng Assistant Professor Fordham University New York, NY 10019 ypeng@fordham.edu *Corresponding author We thank workshop participants at the AAA annual meeting, City University of New York, CUNY Baruch College Emory University, and the editor for their helpful comments. We are grateful for the data provided by an anonymous reviewer and research assistance of Aili Weng and Xiaolan Wang. We appreciate funding from Fordham University. Electronic copy available at: http://ssrn.com/abstract=2202393 An Analysis of Accounting Frauds and the Timing of Analyst Coverage Decisions and Recommendation Revisions: Evidence From the US Abstract: This paper provides a comprehensive exploration of the types of accounting fraud committed by firms over the period 1995 – 2009. Using detailed data from US SEC Accounting and Auditing Enforcement Releases (AAER), we examine the likelihood and timing of analyst coverage decisions and recommendation revisions related to fraud firms versus firms without accounting fraud. We find that analysts have a higher probability of taking the more severe action of dropping coverage rather than only revising down recommendations for firms with any type of accounting fraud and also for specific egregious types of accounting fraud. Through...
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...Kuo-Tay Chen and Ronald M. Lee Monograph No. RM-1992-08-1 (August 11, 1992) EURIDIS Research Monograph Erasmus University Rotterdam, The Netherlands © Kuo-Tay Chen and Ronald M. Lee Permission to copy this monograph without fee is granted provided that (1) the copies are not distributed for the direct commercial purpose and (2) this copyright page including the copyright notice, the EURIDIS monograph number, and date appear. TABLE OF CONTENTS CHAPTER 1. INTRODUCTION ...................................... 1 1.1 BACKGROUND .......................................... 1 1.2 MOTIVATION ............................................. 3 1.3 OBJECTIVE OF THE STUDY .......................... 4 1.4 ISSUES OF INTEREST .................................. 6 1.5 SCOPE OF THE STUDY................................. 7 1.6 CONTRIBUTIONS OF THE STUDY .................. 8 CHAPTER 2. DECISION AIDS RESEARCH FOR INTERNAL CONTROL EVALUATION ............................................ 9 2.1 A REVIEW OF PAST APPROACHES................. 9 2.1.1 MATHEMATICAL MODELING ............ 9 2.1.2 SIMULATION ................................. 12 2.1.3 EXPERT SYSTEMS .......................... 14 2.1.4 OTHER COMPUTER DECISION AIDS . . . 15 2.2 SCHEMATIC EVALUATION - THE PROPOSED APPROACH .................................................... 16 2.2.1 SCHEMA-BASED REASONING .......... 16...
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...Azikiwe University, P. M. B. 5025 Awka, Nigeria. 3 Department of Business Management, Covenant University, P. M. B. 1023 Ota, Nigeria. 4 Department of Religion and Human Relations, Nnamdi Azikiwe University, P. M. B. 5025, Awka, Nigeria. 5 Department of Political Science, Nnamdi Azikiwe University, P. M. B. 5025, Awka, Nigeria. 2 1 Accepted 6 August, 2013 This study is designed to address social problems associated with Information Communication Technologies (ICTs) and implications they portend on studentship in a Private Christian Mission University, Southern Nigeria. It tries to find out how the engagement of ICT devices results in social vices on campus. Drawing from recorded data between 2006 and 2012 academic year, the study reported six ICT tools associated with eight social- ills. Relying on raw data of 900 students disciplined within this period, the study reported that 187 students were expelled while 46 were advised to withdraw due to their involvement in ICT-related vices. Moreover, the study shows that 78 students served 1 year suspension while 589 students were suspended for one month. Findings of the study also revealed loss of all student rights infinitely for expelled students, nearly all rights for those advised-to-withdraw and all...
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...York, Brooklyn, NY, USA Abstract Objectives: We examine the emerging health analytics field by describing the different health analytics and providing examples of various applications. Methods: The paper discusses different definitions of health analytics, describes the four stages of health analytics, its architectural framework, development methodology, and examples in public health. Results: The paper provides a broad overview of health analytics for researchers and practitioners. Conclusions: Health analytics is rapidly emerging as a key and distinct application of health information technology. The key objective of health analytics is to gain insight for making informed healthcare decisions. Keywords: Data warehousing; ETL; Descriptive analytics; Discovery Introduction analytics; Health analytics; Informed decision; Insight; Predictive analytics; Prescriptive analytics management, and preventive care. In one scenario, for example, the use of health analytics technologies can ensure that emergency room doctors are briefed and ready to treat patients prior to their arrival by ambulance. Diagnostic and current health data can be downloaded by hospital staff from a wide variety of systems to develop a patient profile that includes past illnesses, chronic conditions, allergies, blood and tissue typing. With this information as well as a constant stream of vital sign data fed directly by paramedics en route to the hospital, receiving doctors can make better...
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...techniques and more specific diagnostic criteria than in the past, classification system is far from perfect ● Classification system said to be valid when it is able to classify a real pattern of symptoms, which can lead to an effective treatment ● However, problem with this is that the classification system is descriptive and doesn’t identify any specific causes for disorders Paragraph 2 (Study 1): Sane or Insane-Rosenhan (1973) Aim: test reliability of psychiatric diagnosis Procedure: field experiment Part 1 ● 8 healthy people (5 men, 3 women) gained admission to 12 different psychiatric hospitals ● Complained of hearing unclear, unfamiliar voices of same sex repeating words “thud” and “empty” ● Participants said they felt fine after admission to hospital (no more symptoms) Part 2 ● Rosenhan told staff at psychiatric hospital that pseudopatients will try to get admitted ● No pseudopatients were actually sent Results: Part 1 ● 7 diagnosed with schizophrenia ● Took average 19 days for discharge and were classified as “schizophrenia in remission” (possibility of symptoms coming back) upon discharge Part 2 ● 41 real patients were judged to be pseudopatients with confidence by at least 1 member of staff ● 19 were suspected to be frauds by 1 psychiatrist and 1 member of staff Conclusion: ● Not possible to distinguish sane from insane in psychiatric hospitals ● Demonstrated lack of scientific evidence on...
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...Section A: Audit Practice Part b (i): Why is the audit of cash important part of the audit? From an auditing standpoint, cash is an important account because cash transactions affect all other business and financial processes. Businesses acquire cash by selling goods or services, disposing of fixed assets, or acquiring debt or equity. The same businesses put their cash to use through purchasing, paying employees, and buying inventory. Audits are an important part of business. Cash audits check that money has been handled properly, and performance audits ascertain whether employees are doing their jobs properly. Corporations are likely to undergo tax audits to ensure proper tax reporting and withholding. Audits may be performed in-house by management or human resources, by a third-party consulting firm hired specifically to perform the audits or by IRS agents who are auditing company tax records. The audit of cash is considered an important part of an audit mainly due to almost all business transactions will be ultimately settled through the cash accounts, the audit of cash accounts also assists in the verification of other asset and liability accounts as well as revenue and expenses. Some of the investor relies on the accuracy of the cash account to evaluate the financial health of the company. They use current asset which include the cash account to compute several financial measures. Other than that, cash is the highly liquid asset in a company and it is an area of high...
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...MEDWAY SCHOOL OF ENGINEERING Programme: Msc. Information Technology Management for Business Course: Knowledge Management and Exploitation Course Tutor: Dr. A.A.F. Al-Shawabkeh Topic Using Data Mining and Knowledge Management to Improve Business Performance By Nurudeen Babatunde Lawal 000620744 Table of Contents Content Page No. Table of Contents 2 List of Figures 3 Abstract 4 Chapter One 5 1.1 Overview of Business 5 1.2 Nature of Business 5 1.3 Business Challenges 6 Chapter Two 2.1 Knowledge and Knowledge Management 8 2.1.1 Knowledge 8 2.1.2 Knowledge management 9 2.1.3 Knowledge Management Process 9 2.1.4 Knowledge Discovery from Database 10 2.2 Data Mining 12 2.2.1 Data Mining Tasks in Knowledge Management 12 2.2.2 Data Mining and Knowledge Management in Business 14 Chapter Three 17 3.1 Implementation Challenges of KM in Business 17 3.2 Limitations of Data Mining Applications 18 3.3 Conclusion 18 References 19 List of Figures Figure No. Description Page No. Figure 1 Forms of Knowledge Organisation 8 Figure 2 Integration of KM Technologies with KM Process Cycle 10 Figure 3 DM and KDD Process 11 Figure 4 Intersection of DM and KM 14 Abstract ...
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...HIM141 Test 4 Chapters 8-10 Please completely answer the following questions. 1. What is the MPI and what types of information are contained in the MPI? MPI-master patient index, sometimes called a master person index, link a patient’s medical record number with common identification data elements, for example: patient’s complete name, date of birth, gender, mother’s maiden name and social security number. Because most health care facilities house patient records according to a medical record number, the MP becomes the key to locating paper based records in the health information department file system. Thus, the MPI is retained permanently because it serves as the key to finding the patients record, it can be automated or manual. According to the American Health Information Management Association (AHIMA), some recommended core data elements for indexing and searching records include: * Internal patient Identification * Patient Name * DOB * DOB qualifier * Gender * Race * Ethnicity * Address * Alias/pervious name * SS# * Facility identification * Universal patient identifier (if available) * Account number * Admission date * Discharge date * Service type * Patient disposition 2. What are registers and indexes? Registers and registries contain information about a disease or event and are maintained by individual health care facilities, federal and state government agencies and private organizations...
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...customers, but other stakeholders such as the media, investors, regulatory agencies, channel members, trade associations, as well as others. It is important when addressing marketing ethics to recognize that it should be examined from an individual, organizational, and societal perspective. Examining marketing ethics from a narrow issue perspective does not provide foundational background that provides a complete understanding of the domain of marketing ethics. The purpose of this chapter is to define, examine the nature and scope, identify issues, provide a decision-making framework, and trace the historical development of marketing ethics from a practice and academic perspective. DEFINITION OF MARKETING ETHICS Ethics has been termed the study and philosophy of human conduct, with an emphasis on the determination of right and wrong. For marketers, ethics in the workplace refers to rules (standards, principles) governing the conduct of organizational members and the consequences of marketing decisions (Ferrell, 2005). Therefore, ethical marketing from a normative perspective approach is defined as “practices that emphasize transparent, trustworthy, and responsible personal and organizational marketing policies and actions that exhibit...
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...customers, but other stakeholders such as the media, investors, regulatory agencies, channel members, trade associations, as well as others. It is important when addressing marketing ethics to recognize that it should be examined from an individual, organizational, and societal perspective. Examining marketing ethics from a narrow issue perspective does not provide foundational background that provides a complete understanding of the domain of marketing ethics. The purpose of this chapter is to define, examine the nature and scope, identify issues, provide a decision-making framework, and trace the historical development of marketing ethics from a practice and academic perspective. DEFINITION OF MARKETING ETHICS Ethics has been termed the study and philosophy of human conduct, with an emphasis on the determination of right and wrong. For marketers, ethics in the workplace refers to rules (standards, principles) governing the conduct of organizational members and the consequences of marketing decisions (Ferrell, 2005). Therefore, ethical marketing from a normative perspective approach is defined as “practices that emphasize transparent, trustworthy, and responsible personal and organizational marketing policies and actions that exhibit...
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...customers, but other stakeholders such as the media, investors, regulatory agencies, channel members, trade associations, as well as others. It is important when addressing marketing ethics to recognize that it should be examined from an individual, organizational, and societal perspective. Examining marketing ethics from a narrow issue perspective does not provide foundational background that provides a complete understanding of the domain of marketing ethics. The purpose of this chapter is to define, examine the nature and scope, identify issues, provide a decision-making framework, and trace the historical development of marketing ethics from a practice and academic perspective. DEFINITION OF MARKETING ETHICS Ethics has been termed the study and philosophy of human conduct, with an emphasis on the determination of right and wrong. For marketers, ethics in the workplace refers to rules (standards, principles) governing the conduct of organizational members and the consequences of marketing decisions (Ferrell, 2005). Therefore, ethical marketing from a normative perspective approach is defined as “practices that emphasize transparent, trustworthy, and responsible personal and organizational marketing policies and actions that exhibit...
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