DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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Introduction Data communications (Datacom) is the engineering discipline concerned with communication between the computers. It is defined as a subset of telecommunication involving the transmission of data to and from computers and components of computer systems. More specifically data communication is transmitted via mediums such as wires‚ coaxial cables‚ fiber optics‚ or radiated electromagnetic waves such as broadcast radio‚ infrared light‚ microwaves‚ and satellites. Data Communications =
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Citizen-generated data Diedre Brown‚ Dawn Claggett‚ Emmanuel Lea‚ Peggy Sasso‚ and Lucretia William HCS/535 May 25‚ 2015 Jamila Jones‚ Instructor The health care industry is committed to supporting its communities. The industry continues to seek avenue to keep professionals and the public informed. The use of citizen-generated data is proving to be an increasing avenue to increase this awareness. The purpose of this paper is to provide a Team discussion about citizen-generated data and its advantages
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CHAPTER 12 ROUTING IN SWITCHED NETWORKS A NSWERS TO Q UESTIONS 12.1 The average load expected over the course of the busiest hour of use during the course of a day. 12.2 The tradeoff is between efficiency and resilience. 12.3 A static routing strategy does not adapt to changing conditions on the network but uses a fixed strategy developed ahead of time. With alternate routing‚ there are a number of alternate routes between source and destination and a dynamic choice of routes is
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Module 815 Data Structures Using C M. Campbell © 1993 Deakin University Module 815 Data Structures Using C Aim After working through this module you should be able to create and use new and complex data types within C programs. Learning objectives After working through this module you should be able to: 1. Manipulate character strings in C programs. 2. Declare and manipulate single and multi-dimensional arrays of the C data types. 3. Create‚ manipulate and manage C pointers
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Introduction to Data Modeling and MSAccess CONTENT 1 2 3 4 5 6 Introduction to Data Modeling ............................................................................................................... 5 1.1 Data Modeling Overview ............................................................................................................... 5 1.1.1 Methodology .......................................................................................................................... 6 1.1.2 Data Modeling
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Troy Wilson* suggest a way for preserving and enhancing the value of exploration data E very year explorationists‚ industrywide‚ collect billions of dollars worth of data. Yet‚ when it comes time for geologists to extract value from their information‚ they often find that value has been lost through poor practices in data management. There is no reliable record of the data that has been collected or data is not where it should be - it has been misplaced or corrupted. Re-assembling information
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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DATA COMMUNICATION (Basics of data communication‚ OSI layers.) K.K.DHUPAR SDE (NP-II) ALTTC ALTTC/NP/KKD/Data Communication 1 Data Communications History • 1838: Samuel Morse & Alfred Veil Invent Morse Code Telegraph System • 1876: Alexander Graham Bell invented Telephone • 1910:Howard Krum developed Start/Stop Synchronisation ALTTC/NP/KKD/Data Communication 2 History of Computing • 1930: Development of ASCII Transmission Code • 1945: Allied Governments develop the First Large Computer
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and Kimball’s definition of Data Warehousing. Bill Inmon advocates a top-down development approach that adapts traditional relational database tools to the development needs of an enterprise wide data warehouse. From this enterprise wide data store‚ individual departmental databases are developed to serve most decision support needs. Ralph Kimball‚ on the other hand‚ suggests a bottom-up approach that uses dimensional modeling‚ a data modeling approach unique to data warehousing. Rather than building
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