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Int Joint Conference of 10th IEEE Int Conf on Trust, Security and Privacy in Computing and Communications (TrustCom) / 8th IEEE Int Conf on Embedded Software and Systems (ICESS) / 6th Int Conf on Frontier of Computer Science and Technology (FCST)

作者： Liu, Weiguo OuYang, Jia Cent South Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9780769546001

Data stream clustering is confronted with great challenges due to the memory usages and the processing speed. Besides, lots of stream data are high-dimensional in natural and high-dimensional data are inherently more complex in clustering. This paper proposes an effective clustering algorithm referred as HSWStream for high dimensional data stream over sliding windows. This algorithm handles the high dimensional problem with projected clustering technique, deals with the in-cluster evolution with exponential histogram of cluster feature called EHCF and eliminates the influence of old points with the fading temporal cluster features. Meanwhile, via the mechanism of exponential histogram, we save more information of recent data but less information of old data, which is fit for the thought of data stream evolution. The projected clustering brings higher quality of clusters and higher speed of execution, while the sliding window brings higher quality and less memory usage. In addition, in order to bring more efficiency, we use a fast computational method to maintain EHCF. Main idea of the fast computational method indicates that we have no need to handle the new data point immediately until we should delete a FTCF in corresponding EHCF. The evolving data streams in the experiments use KDD-CUP' 98 and KDD-CUP' 99 real data sets and synthetic data sets. The experimental results demonstrate that proposed method is of higher quality, less memory and faster processing speed than other algorithms.

关键词： clustering algorithm data stream sliding window projected clustering exponential histogram

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Improved K-Means algorithm Based on Hybrid Fruit Fly Optimization and Differential Evolution 12

Improved K-Means Algorithm Based on Hybrid Fruit Fly Optimiz...

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12th International Conference on Computer Science and Education (ICCSE)

作者： Hu, Jixiong Wang, Chunzhi Liu, Chuan Ye, Zhiwei Hubei Univ Technol Sch Comp Sci Wuhan Hubei Peoples R China

ISBN: (纸本)9781509025084

Fruit fly optimization algorithm (FOA) is a new method for finding global optimization based on food finding behavior of the fruit fly. The original FOA can only solve problems that have optimal solutions in zero vicinity. To make FOA more universal for the continuous optimization problems, especially for those problems with optimal solution that are not zero. This paper proposes a hybrid fruit fly optimization and differential evolution (DEFOA) by modifying the expression of the smell concentration judgment value and by introducing a differential vector to replace the stochastic search. In this paper, we propose an improved K-Means algorithm based on hybrid FOA and Differential Evolution (DE).

关键词： Fruit fly optimization Differential Evolution K-means algorithm clustering algorithm

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Novel Control Strategy and Modeling of Air Source Heat Pump for Consuming PV Power 2

Novel Control Strategy and Modeling of Air Source Heat Pump ...

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2nd International Conference on Power and Renewable Energy (ICPRE)

作者： Jin, Lu Zhang, Xinyi Cheng, Ling Zhong, Ming Li, Guangbin Kong, Liang China Elect Power Res Inst Beijing Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang Liaoning Peoples R China

ISBN: (纸本)9781538621561

The rapid development of PV power generation has led to numerous problems of system operation and PV power consumption. As a new type of heat pump, the air source heat pump has advantages of energy saving, environment protection and good flexibility. In this paper, PV generation power during generation peak time is consumed by air source heat pumps to produce and storage heat. First, this paper establishes a basic thermophysical model of air source heat pump and analyzes the method of using air source heat pumps to consume PV generation power. Second, a control strategy for consuming PV generation power by clustering air source heat pumps with different parameters is proposed. Then, a multi-objective scheduling model of air source heat pumps is presented. Finally, NSGA-II is used to solve the multi-objective model, and the corresponding Pareto optimal solutions are obtained. The simulation results show that the model proposed in this paper can well follow the PV generation output, reduce the PV power curtailment and heating cost of users.

关键词： PV power generation air source heat pump power consumption clustering algorithm NSGA-II Multi-objective model

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Protein Complex Detection from PPI Networks on Apache Spark 9

Protein Complex Detection from PPI Networks on Apache Spark

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9th International Conference on Information and Knowledge Technology (IKT)

作者： Joodaki, Mehdi Ghadiri, Nasser Atashkar, Amir Hossein Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran

ISBN: (纸本)9781538625477

Protein-Protein Interaction (PPI) network is a network of biomolecular interactions which plays a major role in modeling and analyzing biological activities. Studies of functional modules from PPI networks provide a better understanding of biological mechanisms. Recent advances in both biological and computer sciences demands for the vast amount of PPI networks data to be processed by experimental and computational methods. This could be a great challenge to find functional modules within these large networks. Existing methods are used to identify the functional modules, but some of them do not consider overlapping between functional module clusters. Moreover, most of the methods run on a single machine. Also, many existing algorithms only focus on topological features of PPI networks. In this paper, we introduce a new way for detecting the functional modules. It considers overlapping between clusters and runs on Apache Spark - a distributed processing platform. Our algorithm also considers both topological and biological features of PPI networks. The evaluation results show improved execution speed as well as more accurate results compared to classic methods.

关键词： component - Data mining Graph mining clustering algorithm Distributed processing Protein complex detection

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A Energy-Efficient clustering Routing algorithm Based on Distance and Residual Energy for Wireless Sensor Networks

A Energy-Efficient Clustering Routing Algorithm Based on Dis...

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International Workshop on Information and Electronics Engineering (IWIEE) / International Conference on Information, Computing and Telecommunications (ICICT)

作者： Yong, Zhu Pei, Qing Heilongjiang Univ Haerbin 150080 Peoples R China

Aiming at the problem of limited energy of sensors in Wireless Sensor Network, based on the classic clustering routing algorithm LEACH, a distance-energy cluster structure algorithm considering both the distance and residual energy of nodes is presented in the dissertation, which improves the process of cluster head election and the process of data transmission. It reduces the adverse effect on the energy consumption of the cluster head, resulting from the non-uniform distribution of nodes in network and avoids the direct communication between the base station and cluster head, which may has low energy and far away from base station The results of simulation indicate that the improved algorithm effectively balances the energy consumption, prolongs 31% of the lifetime, reduces 40% of the energy consumption and has a better performance than the original LEACH protocol. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology

关键词： Wireless Sensor Network clustering algorithm LEACH protocol low energy consumption

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Efficient Machine Layout Design Method with a Fuzzy Set Theory within a Bay in a TFT-LCD Plant

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Procedia Manufacturing 2017年 11卷 1863-1870页

作者： Su, Teng-Sheng Hwang, Ming-Hon Department of Marketing and Logistics Management Chaoyang University of Technology 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan

In this paper, we propose an efficient machine layout design method with a fuzzy set theory within a bay in a TFT-LCD plant. An intelligent hybrid heuristic algorithm with a mixed integer linear programming (MILP) model is developed. The objective aimed to achieve is to maximize in-sequence movements and minimize backtracking movements, the total flow distance, and the total backtracking flow distance. An example is given to illustrate the proposed layout procedure. It is our hope that the proposed approaches from this study benefits TFT-LCD designers to deal with both quantitative and linguistic variables for their machine layout problems. © 2017 The Authors

关键词： clustering algorithm facilities planning and design fuzzy sets and systems machine layout problem TFT-LCD plant

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NodeTrix-Community Hierarchy: Techniques for Finding Hierarchical Communities for Visual Analytics of Small-world Networks 12

NodeTrix-Community Hierarchy: Techniques for Finding Hierarc...

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12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP)

作者： Sreevalsan-Nair, Jaya Agarwal, Shivam Int Inst Informat Technol Graph Visualizat Comp Lab Bangalore Karnataka India

ISBN: (纸本)9789897582288

While there are several visualizations of the small world networks (SWN), how does one find an appropriate set of visualizations and data analytic processes in a data science workflow? Hierarchical communities in SWN aid in managing and understanding the complex network better. To enable a visual analytics workflow to probe and uncover hierarchical communities, we propose to use both the network data and metadata (e.g. node and link attributes). Hence, we propose to use the network topology and node-similarity graph using metadata, for knowledge discovery. For the construction of a four-level hierarchy, we detect communities on both the network and the similarity graph, by using specific community detection at specific hierarchical level. We enable the flexibility of finding non-overlapping or overlapping communities, as leaf nodes, by using spectral clustering. We propose NodeTrix-CommunityHierarchy (NTCH), a set of visual analytic techniques for hierarchy construction, visual exploration and quantitative analysis of community detection results. We extend NodeTrix-Multiplex framework (Agarwal et al., 2017), which is for visual analytics of multilayer SWN, to probe hierarchical communities. We propose novel visualizations of overlapping and non-overlapping communities, which are integrated into the framework. We show preliminary results of our case-study of using NTCH on co-authorship networks.

关键词： Small-world Networks NodeTrix Similarity Matrix Hierarchical Communities Workflow Visual Analytics clustering algorithm

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An energy efficient improved RPL routing protocol

An energy efficient improved RPL routing protocol

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International Conference on Intelligent Computing and Control (I2C2)

作者： Rao, Seelam Srinivasa Reddy, N. Chenna Keshava Nalla Narasimha Reddy Educ Soc Grp Inst ECE Dept Hyderabad Telangana India Jothishmati Coll Engn & Technol ECE Dept Hyderabad India

ISBN: (纸本)9781538603741

For battery powered wireless sensor networks, energy is the vital resource. The challenging problem is to make a protocol which is an energy efficient. In this paper, the drawbacks of the IPv6 Routing Protocol for Low power and Lossy networks and the energy dissipation and energy load balance problems of routing protocol RPL are overcome. An improved and relatively balanced routing protocol (IRPL) is developed based on an efficient clustering algorithm. the optimal number of clustering heads can be determined by assuming network model. And the clustering process in wireless sensor network can be completed by integrate the node competition mechanism and clustering probability model by using the cluster head node. In the control model, the wireless sensor network was split into concentric rings and each concentric ring is having equal area. In this paper the optimal forwarding communication area is considered based on different levels of concentric ring domain which determines the best network route. Our experimental simulation results shows that the IRPL routing protocol can reduce overall network energy consumption, significant improvement in energy balance and network lifetime.

关键词： Wireless sensor network Low-Power and Lossy Networks LLN IRPL clustering algorithm Topology control model Ring domain Optimal forwarding communication area

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Exploring Solution Methods for Fault Trees Constrained by Location

Exploring Solution Methods for Fault Trees Constrained by Lo...

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Annual Reliability and Maintainability Symposium (RAMS)

作者： Hanes, Jeff Wiegand, R. Paul Appl Res Associates Inc 956 W John Sims Pkwy Niceville FL 32578 USA Univ Cent Florida Inst Simulat & Training 4000 Cent Florida Blvd Orlando FL 32816 USA

ISBN: (纸本)9781509052844

Fault Tree Analysis (FTA) is used extensively to evaluate the logical dependency of a system on its constituent components. Fault trees (FTs) can be used to identify and correct weaknesses in a design before a system goes to production. Effective methods have been developed over the course of several decades for finding minimal cut sets (MCS). Cut sets identify combinations of component failures that cause the system to fail. Other methods focus on probability risk assessment, in which component failure probabilities are evaluated to determine which failure events are most probable under normal operating conditions. However, traditional FTs do not contain information about the physical location of the components that make up the system. Thus, they cannot identify vulnerabilities induced by the proximity relationships of those components. Components that are sufficiently close to each other could be defeated by a single event with a large enough radius of effect. Events such as the Deepwater Horizon explosion and subsequent oil spill demonstrate the potentially devastating risk posed by such vulnerabilities. Adding positional information to the logical information contained in the FT can capture proximity relationships that constitute vulnerabilities in the overall system but are not contained in the logical structure alone. Thus, existing FTA methods cannot address these concerns. Making use of the positional information would require extensions to existing solution methods or possibly new methods altogether. In practice, fault trees can grow very large, exceeding one thousand components for a large system, which causes a combinatorial explosion in the number of possible solutions. Traditional methods cope with this problem by limiting the number of solutions;generally this is an acceptable limitation since those methods will find the most likely events capable of defeating the fault tree. However, adding more information to the tree and searching for different crit

关键词： Fault tree analysis clustering algorithm Lindenmeyer systems

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Video data image retrieval using - BRICH

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WORLD JOURNAL OF ENGINEERING 2017年第4期14卷 318-323页

作者： Devaraj, Saravanan IFHE Univ Dept Operat & IT Hyderabad Andhra Pradesh India

Purpose - Data mining is the process of detecting knowledge from a given huge data set. Among the data set, multimedia is the data which contains diverse data such as audio, video, image, text and motion. In this growing field of video data, mining the video data plays vital role in the field of video data mining. In video data mining, video data are grouped into frames. In this vast amount of video frames, the fast retrieval of needed information is important one. This paper aims to propose a Birch-based clustering method for content-based image retrieval. Design/methodology/approach - In image retrieval system, image segmentation plays a very important role. A text file, normally, is divided into sections, that is, piece, sentences, word and character for this information which are organized and indexed effectively like in a video, the information is dynamic in nature and this information is converted to static for easy retrieval. For this, video files are divided into a number of frames or segments. After the segmentation process, images are trained for retrieval process, and from these, unwanted images are removed from the data set. The noise or unwanted image removal pseudo-code is shown below. In the code image, pixel value represents the value of the difference between the two adjacent image pixel values. By assuming a threshold for the image value, the duplicate images are found. After finding the duplicate image, it is removed from the data set. clustering is used in many applications as a stand-alone tool to get insight into data distribution and as a pre-processing step for other algorithms (Ester et al., 1996). Specifically, it is used in pattern recognition, spatial data analysis, image processing, economic science document classification, etc. Hierarchical clustering algorithms are classified as agglomerative or divisive. BRICH uses clustering attribute (CA) and clustering feature hierarchy (CA_Hierarchy) for the formation of clusters. It perform multi

关键词： clustering Data mining clustering algorithm Hierarchical clustering Video data

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