Apache Hadoop is a Java based distributed computing framework built for applications implemented using MapReduce programming model. In recent years, Hadoop technology has experienced an unprecedented growth in its ado...
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ISBN:
(纸本)9781450312028
Apache Hadoop is a Java based distributed computing framework built for applications implemented using MapReduce programming model. In recent years, Hadoop technology has experienced an unprecedented growth in its adoption. From single-node clusters to clusters with well over thousands of nodes, Hadoop technology is being used to perform myriad of functions - search optimizations, datamining, click stream analytics, machinelearning to name a few. Although setting up Hadoop clusters and building applications for Hadoop is a well understood area, tuning Hadoop clusters for optimal performance is still a black art. In this demo paper, we will attempt to provide the audience with a holistic approach of Hadoop performance tuning methodologies and best practices. We discuss hardware as well as software tuning techniques including BIOS, OS, JVM and Hadoop configuration parameters tuning. Copyright 2012 ACM.
This book constitutes the refereed proceedings of the 7th IFIP TC 12 internationalconference on Intelligent Information Processing, IIP 2012, held in Guilin, China, in October 2012. The 39 revised papers presented to...
ISBN:
(数字)9783642328916
ISBN:
(纸本)9783642328909
This book constitutes the refereed proceedings of the 7th IFIP TC 12 internationalconference on Intelligent Information Processing, IIP 2012, held in Guilin, China, in October 2012. The 39 revised papers presented together with 5 short papers were carefully reviewed and selected from more than 70 submissions. They are organized in topical sections on machinelearning, datamining, automatic reasoning, semantic web, information retrieval, knowledge representation, social networks, trust software, internet of things, image processing, and patternrecognition.
This paper describes how to use a posture sensor to validate human daily activity and by machinelearning algorithm - Support Vector machine (SVM) an outstanding model is built. The optimal parameter sigma and c of RB...
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ISBN:
(纸本)9783037853696
This paper describes how to use a posture sensor to validate human daily activity and by machinelearning algorithm - Support Vector machine (SVM) an outstanding model is built. The optimal parameter sigma and c of RBF kernel SVM were obtained by searching automatically. Those kinematic data was carried out through three major steps: wavelet transformation, Principle Component Analysis (PCA) -based dimensionality reduction and k-fold cross-validation, followed by implementing a best classifier to distinguish 6 difference actions. As an activity classifier, the SVM (Support Vector machine) algorithm is used, and we have achieved over 94.5% of mean accuracy in detecting differential actions. It shows that the verification approach based on the recognition of human activity detection is valuable and will be further explored in the near future.
In the April 2010 Nature research report, it was announced that biological physicists only very recently discovered that there exists a leadership pattern in flocks of pigeon birds. The most authoritative birds of the...
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ISBN:
(纸本)9783642310201
In the April 2010 Nature research report, it was announced that biological physicists only very recently discovered that there exists a leadership pattern in flocks of pigeon birds. The most authoritative birds of the pigeons' flock take the lead, and followers follow the leaders' directions. Pigeon leaders' roles vary over time. Following this unprecedented discovery made by zoologists at the University of Oxford and Eotvos University, we extend in this paper the flocking model largely used in computer science. We define a new biologically inspired clustering algorithm entitled "FlockbyLeader" that detects hierarchical leaders, discovers their followers, and enables them to flock based on local proximity in an artificial virtual space to create clusters. We offer empirical evidence that the algorithm outperforms both the existing flocking algorithm and the K-means algorithm. We analyze the performance of the algorithm based on widely used datasets in the literature.
One major task of the control centre operator is to identify the global system state of the transmission system. However, during the past couple of years, the complexity of transmission system operation has increased ...
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ISBN:
(纸本)9781467325950;9781467325967
One major task of the control centre operator is to identify the global system state of the transmission system. However, during the past couple of years, the complexity of transmission system operation has increased significantly. The operator in the control room has to observe wider external areas to fully evaluate system security. Along with the development of information technology and functionality of SCADA systems, the amount of data the operator has to monitor has augmented notably. The focus of this work is to develop a visualization of the global system state and to analyse and enhance situation awareness in wide area electrical transmission systems. In addition first versions of this new MMI are implemented into the SCADA system of the German TSO, Amprion. Thereby the study also enables usability engineering of variant new visualizations in the control centre. The proposed solution allows the operator to observe the global system state at a glance and enables intuitive situation awareness by improving visual perception like patternrecognition.
This book constitutes the refereed proceedings of the internationalconference on Artificial Intelligence and Computational Intelligence, AICI 2012, held in Chengdu, China, in October 2012. The 163 revised full papers...
ISBN:
(数字)9783642342400
ISBN:
(纸本)9783642342394
This book constitutes the refereed proceedings of the internationalconference on Artificial Intelligence and Computational Intelligence, AICI 2012, held in Chengdu, China, in October 2012. The 163 revised full papers presented were carefully reviewed and selected from 724 submissions. The papers are organized in topical sections on applications of artificial intelligence; applications of computational intelligence; datamining and knowledge discovering; evolution strategy; intelligent image processing; machinelearning; neural networks; patternrecognition.
Ontology is a formal, explicit specification of a shared conceptual model and provides a way for computers to exchange, search and identify characteristics. datamining is a drawing work from areas including database ...
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We can face with the patternrecognition problems where the influence of hidden context leads to more or less radical changes in the target concept. This paper proposes the mathematical and algorithmic framework for t...
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In this paper, we study the computer recognition of emotions involved in facial expressions. We propose a recognition system based on a support vector machine (SVM) system as a classifier for detecting of spontaneous ...
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Nowadays, internet becomes useful source of information in day-to-day life. It creates huge development of World Wide Web in its quantity of interchange and its size and difficulty of websites. Web Usage mining (WUM) ...
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ISBN:
(纸本)9781467324816;9781467313445
Nowadays, internet becomes useful source of information in day-to-day life. It creates huge development of World Wide Web in its quantity of interchange and its size and difficulty of websites. Web Usage mining (WUM) is one of the main applications of datamining, artificial intelligence and so on to the web data and forecast the user's visiting behaviors and obtains their interests by investigating the samples. Since WUM directly involves in large range of applications, such as, e-commerce, e-learning, Web analytics, information retrieval etc. Weblog data is one of the major sources which contain all the information regarding the users visited links, browsing patterns, time spent on a particular page or link and this information can be used in several applications like adaptive web sites, modified services, customer summary, pre-fetching, generate attractive web sites etc. There are several problems related with the existing web usage mining approaches. Existing web usage mining algorithms suffer from difficulty of practical applicability. So, a novel research is necessary for the accurate prediction of future performance of web users with rapid execution time. WUM consists of preprocessing, pattern discovery and pattern analysis. Log data is characteristically noisy and unclear. Hence, preprocessing is an essential process for effective mining process. In this paper, a novel pre-processing technique is proposed by removing local and global noise and web robots. Anonymous Microsoft Web dataset and *** Anonymous Web dataset are used for estimating the proposed preprocessing technique.
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