channel. Each signal is assigned a different frequency (subchannel) within the main channel. * Useful bandwidth of medium exceeds required bandwidth of channel * e.g. broadcast radio and cable television * Channel allocated even if no data Frequency Division Multiplexing Diagram * Each signal is modulated to a different carrier frequency * Carrier frequencies separated by guard bands (unused bandwidth) – to prevent interference so signals do not overlap. 3 FDM System FDM
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Data Security in Healthcare Data Security in Healthcare In the world of technology today‚ consumers often purchase items through the internet using their personal information such as name‚ date of birth and credit card numbers. This information can easily be stolen from someone who seeks to exploit weakness in a computer network. According‚ to (Gagne‚ 2012)‚ “data breaches often occur through technical vulnerabilities‚ malware‚ compromised user credentials or opportunist attackers”
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CIS 501: Information Systems for Managers Data Mining Problems Introduction Problem 1: Data-Based Decision Making Problem 2: Market Basket Analysis: Association Analysis Problem 3: Market Basket Analysis: Concept Tree/Sequence Analysis Problem 4: Decision Tree Problem 5: Clustering/Nearest Neighbor Classification Problem 6: Clustering Problem 1: Data-Based Decision Making Supermarket Product Placement Suppose that we are responsible for managing product placement within a
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Effectiveness of Health Data Exchange Introduction: The major goal for moving towards the electronic health care exchange is to have improvement in the health care and also have the lowering of costs. The health care is seen to be one of the largest segments which account for 20% of the US GDP. Research has shown that Health Information Exchanges (HIEs) has provided the HITECH (Health Information Technology for Economic and Clinical Health) which gas made more than $15.5 billion available to the
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Fig: Architecture of data warehouse Operations Conceiving data as a cube with hierarchical dimensions leads to conceptually straightforward operations to facilitate analysis. Aligning the data content with a familiar visualization enhances analyst learning and productivity.[5] The user-initiated process of navigating by calling for page displays interactively‚ through the specification of slices via rotations and drill down/up is sometimes called "slice and dice". Common operations
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do you mean by data communication? Ans: It is the exchange of data between two devices via some form of transmission medium such as wire cable. The communicating system must be part of a communication system made up of a combination of hardware and software. The effectiveness of a data communication system depends on three fundamental characteristics: delivery‚ accuracy and timeliness. 2. What is simplex? Ans: It is the mode of communication between two devices in which flow of data is unidirectional
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Data‚ Information‚ and Knowledge – Interwoven To explore the concepts of Data‚ Information‚ and Knowledge independently is to attempt building a large and complex puzzle with only a few pieces from the box. While the relationships between these concepts can be as elusive as finding their universal definitions‚ it is within these relationships that data‚ information‚ and knowledge are most meaningful. In the broadest sense‚ data exists in the form of unorganized and raw facts about the environment
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Data Depth and Optimization Komei Fukuda fukuda@ifor.math.ethz.ch Vera Rosta rosta@renyi.hu In this short article‚ we consider the notion of data depth which generalizes the median to higher dimensions. Our main objective is to present a snapshot of the data depth‚ several closely related notions‚ associated optimization problems and algorithms. In particular‚ we briefly touch on our recent approaches to compute the data depth using linear and integer optimization programming. Although
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student’s performance data and use it as a metric to measure a student’s ability to keep on a track that has worked for previous students. The universities collect the data from students from many years to help improve the learning experience of future students so that they may determine a students a current progress in a class and how it compares to others that have preceded them to allow the university to counsel the student if they are falling behind. In “Ethics‚ Big Data‚ and Analytics: A Model
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Microarray Technology | 7 | | 1.2.1 Measuring mRNA levels | 7 | | 1.2.2 Pre-processing of Gene Expression Data | 8 | | 1.2.3 Applications of Clustering Gene Expression Data | 9 | | 1.3 Mutual Information | 10 | | 1.4 Introduction to Clustering Techniques | 11 | | 1.4.1 Clusters and Clustering | 11 | | 1.4.2 Categories of Gene Expression Data Clustering | 11 | | 1.5 Semi-supervised Learning | 12 | | 1.5.1 Semi-supervised Classification |
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