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    Data Gathering

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    Data Gathering ➢ used to discover business information details to define the information structure ➢ helps to establish the priorities of the information needs ➢ further leads to opportunities to highlight key issues which may cross functional boundaries or may touch on policies or the organization itself ➢ highlighting systems or enhancements that can quickly satisfy cross-functional information needs ➢ a complicated task especially in a large and complex system ➢ must

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    Data Structures

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    EE2410: Data Structures Cheng-Wen Wu Spring 2000 cww@ee.nthu.edu.tw http://larc.ee.nthu.edu.tw/˜cww/n/241 Class Hours: W5W6R6 (Rm 208‚ EECS Bldg) Requirements The prerequites for the course are EE 2310 & EE 2320‚ i.e.‚ Computer Programming (I) & (II). I assume that you have been familiar with the C programming language. Knowing at least one of C++ and Java is recommended. Course Contents 1. Introduction to algorithms [W.5‚S.2] 2. Recursion [W.7‚S.14] 3. Elementary data structures: stacks‚ queues

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    Data Analysis

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    c. ratio scale d. interval scale 2. Data obtained from a nominal scale a. must be alphabetic b. can be either numeric or nonnumeric c. must be numeric d. must rank order the data 3. In a post office‚ the mailboxes are numbered from 1 to 4‚500. These numbers represent a. qualitative data b. quantitative data c. either qualitative or quantitative data d. since the numbers are sequential‚ the data is quantitative 4. A tabular summary of a set of data showing the fraction of the total number

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    Data Representation

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    Data Representation Data and instructions that are presented in a written or typed format can only be understood by the user. If the data is not in the user’s language‚ s/he will not be able to understand it. It is the same way with the computer; the computer’s language is binary 0s and 1s. The computer cannot understand typed or written instructions or data. Whenever data or instructions or input to the computer it is first converted to 0s and 1s‚ these are called binary digits (bits). There

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    Big Data

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    .......................................................................................... 3 2.1.2 Non-functional requirement ............................................................................................. 5 3. Logical design: Data Modeling (ERD) .................................................................................... 6 4. Logical design: Process Modeling (DFD) ............................................................................... 9 5. Decision

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    Data Projectors

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    Data Projectors Amy Shipman $50- $66‚525 What is a data projector? It is “a device that projects computer output onto a white or silver fabric screen that is wall‚ ceiling or tripod mounted." The three most common types of data projectors are the LCD‚ DLP‚ and the LCoS. Each type of projector will project your audio and video‚ they just have different ways to process the output of your audio and video. DLP stands for Digital Light Processing. This type of data projector has a light that

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    Data Security

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    Subnetting __________. b. is also called subnet addressing 2. A virtual LAN (VLAN) allows devices to be grouped __________. a. logically 3. Convergence combines voice‚ data‚ and video traffic __________. a. over a single IP network 4. Each of the following is a convergence security vulnerability except __________. a. convergence resource attacks (CRA) 5. Which of the following is not true regarding a demilitarized zone (DMZ)? a. It contains servers that are only used by

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    Walmart Data

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    The scenario is the number of Wal-Mart stores for each year from 2003 - 2010. The data is (2003‚ 4906)‚ (2004‚ 5289)‚ (2005‚ 6141)‚ (2006‚ 6779)‚ (2007‚ 7262)‚ (2008‚ 7720)‚ (2009‚ 8416)‚ (2010‚ 8970). Each of these graphs is plotted with these points. With this plot I need to formulate a curve of best fit using the correlation coefficient. This graph is about the number of Walmart employees. The X-axis is the Time ( years after 2002). The Y-axis is the number of Walmart employees (in thousands)

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    Data Analysis

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    Research methods: Data analysis G Qualitative analysis of data Recording experiences and meanings Distinctions between quantitative and qualitative studies Reason and Rowan’s views Reicher and Potter’s St Paul’s riot study McAdams’ definition of psychobiography Weiskrantz’s study of DB Jourard’s cross-cultural studies Cumberbatch’s TV advertising study A bulimia sufferer’s diary G Interpretations of interviews‚ case studies‚ and observations Some of the problems involved in drawing

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    Data Mining

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    Nagham Hamid‚ Abid Yahya‚ R. Badlishah Ahmad & Osamah M. Al-Qershi Image Steganography Techniques: An Overview Nagham Hamid University Malaysia Perils (UniMAP) School of Communication and Computer Engineering Penang‚ Malaysia nagham_fawa@yahoo.com Abid Yahya University Malaysia Perlis (UniMAP) School of Communication and Computer Engineering Perlis‚ Malaysia R. Badlishah Ahmad University Malaysia Perlis (UniMAP) School of Communication and Computer Engineering Perlis‚ Malaysia

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