Gel electrophoresis Gel electrophoresis is a method for separation and analysis of macromolecules (DNA, RNA and proteins) and their fragments, based on their size and charge. It is used in clinical chemistry to separate proteins by charge and/or size (IEF agarose, essentially size independent) and in biochemistry and molecular biology to separate a mixed population of DNA and RNA fragments by length, to estimate the size of DNA and RNA fragments or to separate proteins by charge.[1] Nucleic acid
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Data Mining Nabeel Ahmed University of Northern Virginia Abstract ‘The vein of research data is almost always richer than it appears to be on the surface, but it can only be of value if mined.—Morris Rosenberg’ (AGOSTA, 2000) Recent years, Data Mining has become hot topic of enterprises. More and more companies intend to introduce data mining techniques. One report from the United States treats data mining as one of the ten favorable fields in the 21st century, of which by means shows its
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Assignment 4: Data Mining CIS 500 Dr. Besharatian Submitted by: Eric Spurbeck December 7, 2013 Abstract This paper will discuss the process of data mining, how it is used, for what purpose it is used and what information can be gathered from the data, which is compiled from data mining. Assignment 4: Data Mining Webopedia (2013) defines data mining as, "A class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. For
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paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from a meteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipients, when needed. Data mining techniques have been used for adding data-driven, customized intelligence into agents. The architecture of the developed system, its domain ontology
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in the business ! Data mining is defi ned as “the nontrivial extraction of implicit, previously unknown, and potentially useful information (patterns) from data.” This is called knowledge discovery. The most important thing is to identify the patterns, whcich allow us to deine the structure ; We can say tjat data mining gives us knowledge. The most common application of data mining are : classification, prediction, cluster analisis (objetcs that have similars featurs) , mining association rules
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many factors such as; grades and achievements, personality and expectations, and academic environments. This work uses data mining techniques to investigate the effect of socio-economic or family background on the performance of students using the data from one of the Nigerian tertiary institutions as case study. The analysis was carried out using Decision Tree algorithms. The data comprised of two hundred forty (240) records of students. The academic performance of students was measured by the students’
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Case study: The Rise of Wal-Mart Wal-Mart demonstrates how a physical product retailer can create and leverage a data asset to achieve world-class supply chain efficiencies targeted primarily at driving down costs. Wal-Mart isn’t just the largest retailer in the world, over the past several years it has popped in and out of the top spot on the Fortune 500 list—meaning that the firm has had revenues greater than any firm in the United States. Wal-Mart is so big that in three months it sells
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Companies with the ability to foresee their business needs and their workforce needs – especially for high skills – will gain the decisive competitive advantage. Keywords: Human Resource Management, Globalization, Data Analytics, Data Warehouse, Online Analytical Processing, Data Mining, Key Performance Indicators, Dashboards, Scorecards. INTRODUCTION Human Resources departments are transforming as the modern business faces numerous and complex challenges, and exploit opportunities. The transformation
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Marketing Segmentation Theory” Defining the Segmentation: Segmentation can be defined as “the term given to the grouping of customers with similar needs by a number of different variables”. In simple words it can also be define as “the act of dividing or partitioning; separation by the creation of a boundary that divides or keeps apart”. What Does Market Segmentation Mean? “A marketing term refers to the aggregating of prospective buyers into groups (segments) that have common needs and will
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An Introduction to Data Mining Kurt Thearling, Ph.D. www.thearling.com 1 Outline — Overview of data mining — What is data mining? — Predictive models and data scoring — Real-world issues — Gentle discussion of the core algorithms and processes — Commercial data mining software applications — Who are the players? — Review the leading data mining applications — Presentation & Understanding — Data visualization: More than eye candy — Build trust in analytic results 2 1
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