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    Data Encryption Standard

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    Data Encryption Standard In 1972‚ the NBS Institute for Computer Sciences and Technology (ICST) initiated a project in computer security‚ a subject then in its infancy. One of the first goals of the project was to develop a cryptographic algorithm standard that could be used to protect sensitive and valuable data during transmission and in storage. Prior to this NBS initiative‚ encryption had been largely the concern of military and intelligence organizations. The encryption algorithms‚ i.e.‚ the

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    BMW Financial Data

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    Emissions (CO2e) Scope 2 Emissions Ret Certs Low Carbon Emissions from Travel Emissions from Distribution CDP Level of Uncertainty Scope 1 Emissions CDP Level of Uncertainty Scope 2 Emissions CDP Percentage Data Verified Scope 1 CDP Percentage Data Verified Scope 2 CDP Percentage Data Verified Scope 3 Financial Emissions Intensity Activity Rel Emissions Intensity   Energy Use Electricity Use CDP Fuel Used - Gas & Diesel Oil Emissions Avoided via Use of Goods and Services Cost of Total

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    employed at a large store. The review questions whether the research problem was clearly stated. It then considers the purpose of the research. Next‚ it examines suitability of the choice of methods‚ and the reliability and validity of the research data. Furthermore‚ it questions whether the statements made by the researcher follow from the records that were used. It goes on to consider what ethical problems arose and whether the researcher properly addressed those problems. Additionally‚ there are

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    Data commentary on obesity

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    Colin Andridge Professor Murphy Eng 201 MWF 2:00 3 March 2014 Data Commentary Introduction After reading and evaluating six articles written by experts on obesity‚ the data seems to imply that better educating people about how their behavioral lifestyle choices effect their future and current health is the best solution. The six journal articles evaluated and analyzed include: David Freedman’s article‚ “How to Fix the Obesity Epidemic‚” published in Scientific American in 2011. Green Gregory’s

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    Transforming Logical Data Models into Physical Data Models Susan Dash Ralph Reilly IT610-1404A-01 According to an article written by Tom Haughey the process for transforming a logical data model into a physical data model is: The business authorization to proceed is received. Business requirements are gathered and represented in a logical data model which will completely represent the business data requirements and will be non-redundant. The logical model is then transformed into a first cut physical

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    Data link layer

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    Chapter 5: The Data Link Layer Our goals: ❒ understand principles behind data link layer services: ❍ ❍ ❍ ❍ ❒ error detection‚ correction sharing a broadcast channel: multiple access link layer addressing reliable data transfer‚ flow control: done! instantiation and implementation of various link layer technologies 5: DataLink Layer 5-1 Link Layer ❒ ❒ ❒ ❒ ❒ 5.1 Introduction and services 5.2 Error detection and correction 5.3Multiple access protocols 5

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    Multivariate Data Analysis

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    Introduction This document presents the regression analysis of customer survey data of Hatco‚ a large industrial supplier. The data has been collected for 100 customers of Hatco on 14 parameters. The 14 variables are as follows: * Perceptions of Hatco: This data was collected on a graphic measurement rating scale consisting of a 10cm line ranging from poor to excellent. Indicator | Variable | Description | X1 | Delivery speed | amount of time it takes to deliver the product once an order

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    Qantas Data Book

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    Qantas Data Book 2012 DISCLAIMER The information contained in this investor Data Book is intended to be a general summary of Qantas Airways Limited (Qantas/Qantas Group) and its activities as at 17 October 2012 or otherwise the date specified in the relevant information and does not purport to be complete in any respect. The information in this document is not advice about shares in Qantas (or any other financial product)‚ nor is it intended to influence‚ or be relied upon by‚ any person in

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    Data mining and warehousing and its importance in the organization Data Mining Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue‚ cuts costs‚ or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles‚ categorize it‚ and summarize the relationships identified. Technically‚ data

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    Data Flow Diagram

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    In the late 1970s data-flow diagrams (DFDs) were introduced and popularized for structured analysis and design (Gane and Sarson 1979). DFDs show the flow of data from external entities into the system‚ showed how the data moved from one process to another‚ as well as its logical storage. Figure 1 presents an example of a DFD using the Gane and Sarson notation. There are only four symbols: Squares representing external entities‚ which are sources or destinations of data. Rounded rectangles

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