"Automatic identification and data capture" Essays and Research Papers

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    Data Analytics

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    You Can Do With Data/The Information Architecture of an Organization What is the difference between data and information? Give examples. Data = discrete‚ unorganized‚ raw facts Quantity Sold‚ Course Enrollment‚ Customer Name‚ Discount‚ Star Rating. Information = transformation of those facts into meaning. Financial data (deposits)‚ daily loans. What is a transaction? Action performed in a database management system What are the characteristics of an operational data store? Stores

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    Be Data Literate

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    Be Data Literate – Know What to Know by Peter F. Drucker             Executives have become computer literate. The younger ones‚ especially‚ know more about the way the computer works than they know about the mechanics of the automobile or the telephone. But not many executives are information-literate. They know how to get data. But most still have to learn how to use data.             Few executives yet know how to ask: What information do I need to do my job? When do I need it? In what

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    Data Collection

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    Data Collection QNT/351 July 10‚ 2014 There are many times when companies have to collect data to come to a conclusion about an issue. The data may be collected from their employers‚ their competition or their consumers. BIMS saw that there had been an average turnover that was larger then what the company had seen in the past. Human Resources decided that they would conduct a survey to see what had changed in the company from the employee’s point of view. They attached

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    Identification of Macromolecules Introduction The purpose of this lab is to test for the presence of macromolecules in various foods. Tests are performed to describe the basic structure of proteins‚ lipids‚ glycerides‚ and carbohydrates. We are to recognize the positives and negatives in these macromolecules. Also we are to identify the roles that proteins‚ lipids‚ minerals‚ vitamins‚ and carbohydrates play in the body’s construction and metabolism. Procedure / Results 5.1 Carbohydrate

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    Data Sonification

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    Turnage‚ Bonebright‚ Buhman‚ Flowers (1996) showed that untrained participants can listen to shapes. That is‚ they used data sonification – musical representation of two dimensional space‚ with pitch as the vertical dimension and time as the horizontal dimension – to present participants the visual and auditory representation of waveforms. In two conditions‚ they showed the participants could match one visual presentation to one of two auditory representations‚ or match one auditory presentation

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    Big Data

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    Table of Contents 1. VARIABLES- QUALITATIVE AND QUANTITATIVE......................3 1.1 Qualitative Data (Categorical Variables or Attributes) ........................... 3 1.2 Quantitative Data............................................................................................... 4 DESCRIPTIVE STATISTICS.................................................6 2.1 Sample Data versus Population Data ................................................................... 6 2.2 Parameters and Statistics

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    Data Communications

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    and cross talk on a cabling medium are factors that prevent the accuracy of transmitted data to be intact. For these reasons different encoding methods exist. An example is when 2 wires are used to transmit music data to a speaker Digital signals don’t always have to be carried over to the receiving end by electricity‚ light can also be used for digital communication. Fibre Optics use light to transmit data through optical fibre within the cable. The strength of the light ray can also be a determining

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    Data Analys

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    of variables Qualitative Quantitative • Reliability and Validity • Hypothesis Testing • Type I and Type II Errors • Significance Level • SPSS • Data Analysis Data Analysis Using SPSS Dr. Nelson Michael J. 2 Variable • A characteristic of an individual or object that can be measured • Types: Qualitative and Quantitative Data Analysis Using SPSS Dr. Nelson Michael J. 3 Types of Variables • Qualitative variables: Variables which differ in kind rather than degree • Measured

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    aureus)‚ the serum will coagulate‚ resulting in a clot (sometimes the clot is so pronounced that the liquid will completely solidify). * If negative‚ the plasma remains liquid. The negative result may be S. epidermidis but only a more detailed identification test can confirm this‚ using biochemical tests as in API tests and BBL CRYSTAL methods. MATERIALS Sterile swab‚ oxidase strap‚ microorganisms (Pseudomonas aeruginosa‚ E. coli) METHODS A. Catalase 1. A drop of 3% H2O2 was placed

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    Data Interpretation

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    Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or

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