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C-TREND: Temporal Cluster Graphs for Identifying and Visualizing Trends in Multi-attribute Transactional Data

Organizations and firms are capturing increasingly more data about their customers, suppliers, competitors, and business environment. Most of this data is multi-attribute (multidimensional) and temporal in nature. Data mining and business intelligence techniques are often used to discover patterns in such data; however, mining temporal relationships typically is a complex task. We propose a new data analysis and visualization technique ....etc

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The tag is a brand new, malleable, casual communicator, which is not only soft but also flexible so that you can easily wrap it around your arm. special shape-memorizing material and multiple pressure sensors pressure sensors are utilised by it to remember the latest shape. It is a malleable, casual communicator. It is so flexible that it can be hung from a belt or wrapped around the user's arm. The rubbery material is able to remember its previous shape. The user can also alternate the mode by changing the shape due to multiple pressure senso ....etc

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The gasoline-powered internal combustion engine has seen more improvement in the last five years than in the last twenty, Quieter timing chain technology, direct fuel injection, and variable intake and exhaust valve timing, among others, have led to better fuel efficiency and reduced emissions.

Everyone knows that, in the case of a gasoline-powered ICE, three things are needed, compressed air, fuel, and spark, which are facilitated by, respectively, the crank and pistons, the injection system, and the ignition system.

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http://seminarsprojects.net/Thread-c-trend-temporal-cluster-graphs-for-identifying-and-visualizing-trends

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C-TREND:Temporal Cluster Graphs for Identifying and Visualizing Trends in Multi-attribute Transactional Data

Organizations and firms are capturing increasingly more data about their customers, suppliers, competitors, and business environment. Most of this data is multi-attribute (multidimensional) and temporal in nature. Data mining and business intelligence techniques are often used to discover patterns in such data; however, mining temporal relationships typically is a complex task. We propose a new data analysis and visualization techniqu ....etc

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