International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications最新文献
Pub Date : 2010-08-01DOI: 10.1109/ICNC.2010.5582471
Jinzhao Deng
Organizational citizenship behavior (OCBs) be characterized with going beyond formal role requirements and wide participation for organizational interests. Previous research on organizational citizenship behavior draw a general conclusion that organizational citizenship behavior had a critical relation with organizational functioning. But little work recovers the internal mechanism by which organizational citizenship behavior facilitate organizational performance and effectiveness. Based on social embeddedness theory, this paper proposes that organizational citizenship behavior, especially, the social participation, advocacy participation, functional participation and focus on tasks contribute to internal learning, explorative learning, emergent learning, and exploitation learning between individual, and consequently enhance organizational functioning and performance. In the last section the paper briefly discussed the theoretical contributions of the analysis framework and give suggestion about future research direction.
{"title":"Learning through organizational citizenship behavior","authors":"Jinzhao Deng","doi":"10.1109/ICNC.2010.5582471","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5582471","url":null,"abstract":"Organizational citizenship behavior (OCBs) be characterized with going beyond formal role requirements and wide participation for organizational interests. Previous research on organizational citizenship behavior draw a general conclusion that organizational citizenship behavior had a critical relation with organizational functioning. But little work recovers the internal mechanism by which organizational citizenship behavior facilitate organizational performance and effectiveness. Based on social embeddedness theory, this paper proposes that organizational citizenship behavior, especially, the social participation, advocacy participation, functional participation and focus on tasks contribute to internal learning, explorative learning, emergent learning, and exploitation learning between individual, and consequently enhance organizational functioning and performance. In the last section the paper briefly discussed the theoretical contributions of the analysis framework and give suggestion about future research direction.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"7 1","pages":"2125-2128"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91048966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a classical problem of computational molecular biology, the multiple sequence-structure alignment is also important foundational process. RNA is one of biological polymer, and is different from protein and DNA that the secondary structure of RNA is more conservative than its primary sequence. Therefore, RNA multiple sequences alignment requires not only information of sequences, but also information of secondary structures which those sequences will form. Here, a program—QEA-MRNA, which based on Quantum-inspired Evolutionary Algorithm to align RNA sequences, is proposed. The program introduce a full crossover operator and a fitness function which considering the information of RNA primary sequence and secondary structure, and improving on premature controlling and the convergent speed. The effectiveness and performance of QEA-MRNA are demonstrated by testing cases in BRAliBase.
{"title":"Quantum-Inspired Evolutionary Algorithm for RNA Multiple Sequence-Structure Alignment","authors":"Yingjie Zhao, ZhengZhi Wang","doi":"10.1109/ICNC.2009.68","DOIUrl":"https://doi.org/10.1109/ICNC.2009.68","url":null,"abstract":"As a classical problem of computational molecular biology, the multiple sequence-structure alignment is also important foundational process. RNA is one of biological polymer, and is different from protein and DNA that the secondary structure of RNA is more conservative than its primary sequence. Therefore, RNA multiple sequences alignment requires not only information of sequences, but also information of secondary structures which those sequences will form. Here, a program—QEA-MRNA, which based on Quantum-inspired Evolutionary Algorithm to align RNA sequences, is proposed. The program introduce a full crossover operator and a fitness function which considering the information of RNA primary sequence and secondary structure, and improving on premature controlling and the convergent speed. The effectiveness and performance of QEA-MRNA are demonstrated by testing cases in BRAliBase.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"45 1","pages":"534-537"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85083408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The traditional evolutionary algorithm (EA) for solving the multi-objective optimization problem (MOP) is difficult to accelerate convergence and keep the diversity of the achieved Pareto optimal solutions. A novel EA, i.e., Immune Multi-objective Optimization Algorithm (IMOA), is proposed to solve the MOP in this paper. The special evolutional mechanism of the artificial immune system (AIS) prevents the prematurity and quickens the convergence of optimization. The method combined by the random weighted method and the adaptive weighted method guarantee the acquired solutions to distribute on the Pareto front uniformly and widely. An external set for storing the Pareto optimal solutions is built up and updated by a novel approach. By graphical presentation and examination of selected performance metrics on two difficult test functions, the proposed IMOA is found to outperform four other algorithms in terms of finding a diverse set of solutions and converging near the true Pareto front.
{"title":"A Novel Multi-objective Optimization Algorithm Based on Artificial Immune System","authors":"Chun-hua Li, Xin-Jan Zhu, Wan-Qi Hu, G. Cao","doi":"10.1109/ICNC.2009.285","DOIUrl":"https://doi.org/10.1109/ICNC.2009.285","url":null,"abstract":"The traditional evolutionary algorithm (EA) for solving the multi-objective optimization problem (MOP) is difficult to accelerate convergence and keep the diversity of the achieved Pareto optimal solutions. A novel EA, i.e., Immune Multi-objective Optimization Algorithm (IMOA), is proposed to solve the MOP in this paper. The special evolutional mechanism of the artificial immune system (AIS) prevents the prematurity and quickens the convergence of optimization. The method combined by the random weighted method and the adaptive weighted method guarantee the acquired solutions to distribute on the Pareto front uniformly and widely. An external set for storing the Pareto optimal solutions is built up and updated by a novel approach. By graphical presentation and examination of selected performance metrics on two difficult test functions, the proposed IMOA is found to outperform four other algorithms in terms of finding a diverse set of solutions and converging near the true Pareto front.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"31 1","pages":"569-574"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79191451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Neural Network Modeling for Bio-enzymatic Degumming on Kenaf","authors":"Laijiu Zheng, Bing Du","doi":"10.1109/ICNC.2009.29","DOIUrl":"https://doi.org/10.1109/ICNC.2009.29","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"34 1","pages":"223-226"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80121478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Filter-SQP Algorithm Based on Semidefinite Programming","authors":"Shulin Yang, Xiaorong Zhu, Dianchun Wang","doi":"10.1109/ICNC.2009.575","DOIUrl":"https://doi.org/10.1109/ICNC.2009.575","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"15 1","pages":"443-447"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81890822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The reentry process of reusable launch vehicle is very complex, so extrapolating the landing area based on original state has significant meaning for the launch vehicle reentry trajectory. This paper presents a method of calculating the landing area based on dynamic programming. The method traces out a nominal resistance boundary curve in energy-resistance space on the premise of meeting all the constraint conditions of reentry trajectory, then tracks it by using feedback linearization to get the feasible boundary, finally attains a resistance project by using interpolation method. Longitudinal trace is also attained by using feedback linearization, while transverse control is achieved by tilting motion at different times. Select the largest and the least resistance values as the top and the bottom point of the reentry landing area, and at the same time choose the point that its tilting angle is constant plus or minus as the left or right side of the reentry landing area. All these above compose the boundary of the reentry landing area. At last, validate the feasibility of the method by computer simulation, and achieve a superior predictive result.
{"title":"Footprint Calculation for a Reusable Launch Vehicle Based on Dynamics Programming","authors":"Bo Yang, C. Wu, Dawei Li, Jing Hu","doi":"10.1109/ICNC.2009.592","DOIUrl":"https://doi.org/10.1109/ICNC.2009.592","url":null,"abstract":"The reentry process of reusable launch vehicle is very complex, so extrapolating the landing area based on original state has significant meaning for the launch vehicle reentry trajectory. This paper presents a method of calculating the landing area based on dynamic programming. The method traces out a nominal resistance boundary curve in energy-resistance space on the premise of meeting all the constraint conditions of reentry trajectory, then tracks it by using feedback linearization to get the feasible boundary, finally attains a resistance project by using interpolation method. Longitudinal trace is also attained by using feedback linearization, while transverse control is achieved by tilting motion at different times. Select the largest and the least resistance values as the top and the bottom point of the reentry landing area, and at the same time choose the point that its tilting angle is constant plus or minus as the left or right side of the reentry landing area. All these above compose the boundary of the reentry landing area. At last, validate the feasibility of the method by computer simulation, and achieve a superior predictive result.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"74 1","pages":"376-381"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85923313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of Flexural Rigidity and Tension of Short Hangers with Adding Mass and Neural Network","authors":"Xu Xie, Liangfeng Sun, Haiyan Huang, Jilong Li","doi":"10.1109/ICNC.2009.320","DOIUrl":"https://doi.org/10.1109/ICNC.2009.320","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"34 1","pages":"372-376"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72849078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Novel BP Neural Network Model for Traffic Prediction of Next Generation Network","authors":"Li Zhu, Lei Qin, K. Xue, Xinyan Zhang","doi":"10.1109/ICNC.2009.673","DOIUrl":"https://doi.org/10.1109/ICNC.2009.673","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"32 1","pages":"32-38"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83023960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variable Step Size Algorithm for Blind Source Separation Using a Combination of Two Adaptive Separation Systems","authors":"S. Ou, Ying Gao, Gang Jin, Xuehui Zhang","doi":"10.1109/ICNC.2009.544","DOIUrl":"https://doi.org/10.1109/ICNC.2009.544","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"3 1","pages":"649-652"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87299351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Soil Sampling Intelligent System Based on Elastic Algorithm and GIS","authors":"Yunping Chen, Xiu Wang, Chunjiang Zhao","doi":"10.1109/ICNC.2009.545","DOIUrl":"https://doi.org/10.1109/ICNC.2009.545","url":null,"abstract":"","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"55 1","pages":"202-206"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73856832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications
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