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International Conference on computer sciences and Convergence Information Technology (ICCIT)

作者： Chayanan Nawapornanan Veera Boonjing Software Systems Engineering Laboratory Department of Mathematics and Computer Science Faculty of Science King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

The share measure has been proposed as an important measure for mining association rules. The value of share itemsets provides useful information such as total profits and total customer purchased quantities associated with itemsets in database. The share-frequent itemsets mining problems become a very important research issue in data mining. Existing share-frequent itemsets mining algorithms are based on static database so knowledge must be rebuilded when the minimum share threshold is changed or database is modified either appended or updated. This paper proposes a novel BitTable knowledge for incremental and interactive share-frequent itemsets mining in multiple minimum share thresholds without rebuilding BitTable knowledge. It is effective for incremental and interactive mining to take advantage of the previous BitTable knowledge and the previous mining results.

关键词： Itemsets Algorithm design and analysis Association rules computer science

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Heart Disease Classification Using Neural Network and Feature Selection

Heart Disease Classification Using Neural Network and Featur...

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IEEE International Conference on systems engineering

作者： Anchana Khemphila Veera Boonjing Software Systems Engineering Laboratory Department of Mathematics and Computer Science Faculty of Science King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart disease. Clinical diagnosis is done mostly by doctor's expertise and experience. But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis. In many cases, not all the tests contribute towards effective diagnosis of a disease. Our work is to classify the presence of heart disease with reduced number of attributes. Original, 13 attributes are involved in classify the heart disease. We use Information Gain to determine the attributes which reduces the number of attributes which is need to be taken from patients. The Artificial neural networks is used to classify the diagnosis of patients. Thirteen attributes are reduced to 8 attributes. The accuracy differs between 13 features and 8 features in training data set is 1.1% and in the validation data set is 0.82%.

关键词： Diseases Data mining Heart Accuracy Medical diagnostic imaging Neurons Databases

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Tuning of Unscented Kalman Filter Based Biogeography-Based Optimization for UGVs Navigation

Tuning of Unscented Kalman Filter Based Biogeography-Based O...

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The 2011 International Conference on Automation and Robotics(ICAR 2011)

作者： Kuifeng Su Zhidong Deng Zhen Huang Department of Computer Science State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and TechnologyTsinghua University Academy of Armored Force Engineering

In the case of linear systems, corrupted by white Gaussian noise, the Kalman filter is proved to be an optimal filter in the mean least square sense. When the system model and measurements are non-linear, variation of Kalman filter like extended Kalman filter(EKF), Unscented Kalman filters(UKF) and Particle filter( PF) are used. However, the best performance of UKF is achieved when the random variables only are Gaussian, and affected seriously by the estimation precision of noise covariance. In this paper, we give a noise covariance estimation method based Biogeography-based Optimization(BBO). The experimental results obtained from real-world road tests validate the performance of our approach.

关键词： Unmanned ground vehicle Unscented Kalman filter Noise Covariance Biogeography-based Optimization

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Enhance Top-down method with Meta-Classification for Very Large-scale Hierarchical Classification 5

Enhance Top-down method with Meta-Classification for Very La...

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5th International Joint Conference on Natural Language Processing, IJCNLP 2011

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China

ISBN: (纸本)9789744665645

Recent large-scale hierarchical classification tasks typically have tens of thousands of classes as well as a large number of samples, for which the dominant solution is the top-down method due to computational complexity. However, the top-down method suffers from accuracy deficiency, that is, its accuracy is generally lower than that of the flat approach of 1-vs-Rest. In this paper, we employ meta-classification technique to enhance the classifying procedure of the top-down method. We analyze the proposed method on the aspect of accuracy, and then test it with two real-world large-scale data sets. Our method both maintains the efficiency of the conventional top-down method and provides competitive classification accuracies. © 2011 AFNLP

关键词： Natural language processing systems

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Optimizing for large time delay systems by BP neural network and evolutionary algorithm improving

Journal of Software

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Journal of software 2011年第10期6卷 2050-2055页

作者： Lin, Fan Zeng, Wenhua Xiahou, Jianbing Jiang, Yi Fujian Key Laboratory of the Brain-Like Intelligent Systems Cognitive science department Xiamen China Cognitive science department Xiamen University Xiamen China School of software Xiamen University Xiamen China Department of Computer Science Xiamen University Xiamen China

BP artificial neural network is a non-feedback network. This paper utilizes the initial weights of neural network to choose controller performance. Simultaneously according to the characteristics that process of central air-conditioning energy saving control is the system of multi-parameter and nonlinear time-varying complexity, we analysis and study its algorithm and system architecture. The experimental results demonstrate that new control system gets better results and energy saving. © 2011 ACADEMY PUBLISHER.

关键词： Evolutionary algorithms

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SMICloud: A Framework for Comparing and Ranking Cloud Services

SMICloud: A Framework for Comparing and Ranking Cloud Servic...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Saurabh Kumar Garg Steve Versteeg Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia CA Technologies Melbourne Australia

With the growth of Cloud Computing, more and more companies are offering different cloud services. From the customer's point of view, it is always difficult to decide whose services they should use, based on users' requirements. Currently there is no software framework which can automatically index cloud providers based on their needs. In this work, we propose a framework and a mechanism, which measure the quality and prioritize Cloud services. Such framework can make significant impact and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their Quality of Services (QoS).

关键词： Quality of service Time factors Cloud computing Organizations Measurement Security Indexes

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Color-mood-aware clothing re-texturing

Color-mood-aware clothing re-texturing

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12th International Conference on computer-Aided Design and computer Graphics, CAD/Graphics 2011

作者： Shen, Jianbing Sun, Hanqiu Mao, Xiaoyang Guo, Yanwen Jin, Xiaogang Beijing Laboratory of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing 100081 China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong University of Yamanashi Japan National Key Lab. for Novel Software Technology Nanjing University China State Key Lab. of CAD and CG Zhejiang University Hangzhou 310027 China

ISBN: (纸本)9780769544977

In this paper, we present a novel color-mood-aware technique to re-texture clothing in a photograph. An efficient classification algorithm is developed to classify clothing textures using color mood scheme. To re-texture the clothing, our approach first computes the gradient maps for the cloth region to be replaced and then calculates the texture distortion coordinates on the projected cloth region according to the gradient maps. After the user selects a target clothing texture from the classified clothing texture database, the lighting and shading effects on the original photograph is transferred using the HSV color space. Experimental results show that the proposed approach successfully re-textures the clothes in photographs while preserving the geometry and lighting features. © 2011 IEEE.

关键词： Color

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Face recognition using skin color segmentation and template matching algorithms

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Information Technology Journal 2011年第12期10卷 2308-2314页

作者： Wang, Zhiwen Li, Shaozi Department of Computer and Engineering Guangxi University of Technology Liuzhou China Department of Cognitive Science Xiamen University Xiamen China Key Laboratory of the Brain-Like Intelligent Systems Xiamen University Xiamen China

Currently, relatively popular and representative face recognition algorithms are algorithm based on template matching and algorithms based on skin-color segmentation. The computation of recognition algorithm based on template matching is very high and the recognition rate of recognition algorithms based on skin color segmentation is low and is vulnerable to the impact of background which is similar with skin color, In order to overcome these deficiencies, face recognition using skin color segmentation and template matching algorithm is presented in this study. According to the clustering properties that the skin-color of human faces emerge in the YCbCr color space, the regions closing to facial skin color are separated from the image by using Gaussian mixture model in order to achieve the purpose of rapidly detecting the external face of human face. Adaptive template matching is used to overcome the affect of the backgrounds which are similar with skin color on face detection and recognition. Computation in the matching process is reduced by using the second matching algorithm. Extraction of face images by using singular value features is used to identify faces and to reduce the dimensions of the eigenvalue matrix in the process of facial feature extraction. Experimental results show that proposed method can rapidly detect and recongnise human faces and improve the accuracy of face detection and recognition. © 2011 Asian Network for Scientific Information.

关键词： Template matching

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Cooperative navigation for heterogeneous autonomous vehicles via approximate dynamic programming

Cooperative navigation for heterogeneous autonomous vehicles...

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IEEE Conference on Decision and Control

作者： Silvia Ferrari Michael Anderson Rafael Fierro Wenjie Lu Laboratory for Intelligent Systems and Controls Department of Mechanical Engineering & Materials Science Duke University Durham NC USA MARHES Laboratory Electrical & Computer Engineering Department University of New Mexico Albuquerque NM USA

ISBN: (纸本)9781612848006;9781612848013

Unmanned ground and aerial vehicles are becoming crucial to many applications because of their ability to assist humans in carrying out dangerous missions. These vehicles can be viewed as networks of heterogeneous unmanned robotic sensors with the goal of exploring complex environments, to search for and, possibly, pursue moving targets. The robotic vehicle performance can be greatly enhanced by implementing future sensor actions intelligently, based both on prior knowledge and on the information obtained by the sensors on line. In this paper, we present an approximate dynamic programming (ADP) approach to cooperative navigation for heterogeneous sensor networks. The mobile sensor network consists of a set of robotic sensors modeled as hybrid systems with processing capabilities. The goal of the ADP algorithm is to coordinate a team of heterogeneous autonomous vehicles (i.e., ground robot and quadrotor UAV) to navigate within an obstacle populated environment while satisfying collision avoidance constraints and searching for stationary and mobile targets. It is assumed that the ground vehicle has a small sensor footprint with high resolution. The quadrotor, on the other hand, has a large sensor field-of-view but low resolution. The UAV provides a low resolution look-ahead map to the ground robot which in turn uses this information to plan its actions. The proposed navigation strategy combines artificial potential functions for target pursuing with ADP for learning C-obstacles on line. The efficacy of the proposed methodology is verified through numerical simulations.

关键词： Robot sensing systems Geometry Vehicles Robot kinematics Collision avoidance

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A conceptual framework for semantic case-based safety analysis

A conceptual framework for semantic case-based safety analys...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Olawande Daramola Tor Stålhane Thomas Moser Stefan Biffl Department of Computer and Information Science Norwegian University of Science and Technology Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

Hazard and Operability (HAZOP) Analysis and Failure Mode and Effect Analysis (FMEA) are among the most widely used safety analysis procedures in the development of safety-critical and embedded systems. These analyses are generally perceived as complex and time-consuming, hindering an effective reuse of previous results or experiences. In this paper we present a conceptual semantic case-based framework for safety analysis, which facilitates the reuse of previous HAZOP and FMEA experiences in order to reduce the time and effort associated with these analyses. We present the core technologies of the conceptual framework and evaluated a prototype of the framework, KROSA, in an experiment with domain experts at ABB Norway. Initial results confirm the viability of the conceptual framework for industrial application.

关键词： Ontologies Semantics Natural language processing Libraries Hazards Humans

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