{"title":"Study on Fire Detection Model Based on Fuzzy Neural Network","authors":"Quanmin Guo, J. Dai, Jian Wang","doi":"10.1109/IWISA.2010.5473248","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473248","url":null,"abstract":"The fire signal detection is a non-structural problem and difficult to be precise described by mathematical model, which increase the difficulty of fire detection. According to the special type of signal detection technique such as fire signal detection, a fire detection model based on fuzzy-neural network is presented. This paper described the design method of the model, as well as its learning algorithm. In standard fire test rooms, simulation experiments were carried out for smoldering fire SH1 and flaming fire SH3 of the china national standard test fires, the model can make right judgment. Theory analysis and simulation study show that the model combines the advantages of fuzzy system and neural network, and improves the intelligence of fire detection, has a stronger ability to adapt the environment. It effectively solves the problems of mistake and failure in the fire alarm, and improves the sensibility of fire detection.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133583509","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":"Automatic Clustering with Differential Evolution Using Cluster Number Oscillation Method","authors":"Wei-Ping Lee, Shen-Wei Chen","doi":"10.1109/IWISA.2010.5473289","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473289","url":null,"abstract":"In this paper, an improved Differential Evolution algorithm (ACDE-O) with cluster number oscillation for automatic crisp clustering has been presented. The proposed algorithm needs no prior knowledge of the number of clusters of the data. Rather, it finds the optimal number of clusters on the processing with stable and fast convergence, cluster number oscillation mechanism will search more possible cluster number in case of bad initial cluster number caused bad clusters. Superiority of the proposed algorithm is demonstrated by comparing it with one recently developed partitional clustering algorithm. Experimental results over three real life datasets and the performance of proposed algorithm is mostly better than the other one.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127670006","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}
Miao Wang, Xuequn Shang, Xiao-gang Lei, Zhanhuai Li
{"title":"Mining Maximal Frequent Dense Subgraphs without Candidate Maintenance in PPI Networks","authors":"Miao Wang, Xuequn Shang, Xiao-gang Lei, Zhanhuai Li","doi":"10.1109/IWISA.2010.5473237","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473237","url":null,"abstract":"The prediction of protein function is one of the most challenging problems in bioinformatics. Several studies have shown that the prediction using PPI is promising. However, the PPI data generated from high-throughput experiments are very noisy, which renders great challenges to the existing methods. In this paper, we propose an algorithm, MFC, to efficiently mine maximal frequent dense subgraphs without candidate maintenance in PPI networks. It adopts several techniques to achieve efficient mining. We evaluate our approach on four human PPI data sets. The experimental results show our approach has good performance in terms of efficiency.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127737178","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":"Designing Product to Improve Affective Communication","authors":"Lei Shi, Z. Xie","doi":"10.1109/IWISA.2010.5473552","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473552","url":null,"abstract":"Human being has been involved in a new information environment combining with embedded computing product and network. This combination is changing the relationships not only between human and product but also person to person. Information communication is required to be an important facet in product innovation. It is considered that the physical, cognitive and affective are the three levels of information communication. While the physical and cognitive levels of information design have been greatly improved in the last decade, it is important to rethink how affective design can improve interactions between human and products or interpersonal relationships. The paper discusses the evolution in information communications from three levels of the physical, cognitive and affective, and proposes design strategies approaching the affective design in product innovation.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132808139","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":"Knowledge Sharing Behavior in Organization: An Empirical Investigation","authors":"W. Lv","doi":"10.1109/IWISA.2010.5473500","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473500","url":null,"abstract":"Effective knowledge sharing cannot be forced or mandated. Organizations desiring to institutionalize knowledge sharing behaviors must foster facilitative work context. The aim of this paper is to develop a deeper understanding of the factors inhibiting individuals' knowledge sharing intentions, and suggest a method to shape appropriate work context. To reach this goal, this paper focus on the inner knowledge externalization process, and formulate a research model which integrate self-concept-based model and theory of reasoned action to explain how contextual forces can transform into the triggers of inner motivations. Using the Structural Equation Modeling (SEM) method, data analysis showed that most of the research hypotheses were supported. The research findings show that the firm should (1) make the employees regard knowledge sharing as an enjoyment; (2) enforce their sense of belonging ; (3) induce employees' focus on long term return rather than shore term wins; (4) leverage centrality and promote individual reputations may also be helpful.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133279267","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":"Fuzzy Immune Adaptive Smith-PID Control for Water Quality Adjusting System of Thermal Power Plant","authors":"Shuhua Peng, C. Hao, Denghua Li","doi":"10.1109/IWISA.2010.5473245","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473245","url":null,"abstract":"Water quality adjusting system of thermal power plant is a large time-delay and time-varying controlled object. The control quality of the Fuzzy immune adaptive control and conventional Smith control is not satisfied. In order to solve the time-delay and time-varying problem, a fuzzy immune adaptive Smith-PID controller is presented. The controller combines biological immune system and fuzzy inference with Smith prediction controller. Fuzzy immune P regulator was used to setting the proportional gain of the PID controller in real-time. Fuzzy controller was used to setting the integration time constant and the differential time constant. And Smith controller was used to predict the time-delay. Simulation results showed that this control algorithm have the advantages of short settling time, strong stability, strong noise immunity.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134044824","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":"An Optimal CAC Scheme Based on GSMDP Model in Heterogeneous Wireless Networks","authors":"Wen Chen, Jinming Yu, Feng Pan","doi":"10.1109/IWISA.2010.5473251","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473251","url":null,"abstract":"This paper proposes an optimal CAC scheme in heterogeneous wireless networks called the GSMDP-based CAC (GCAC). Considering the limitations of the traditional Markov decision process for optimal CAC policy, we characterize the CAC problem through a GSMDP formulation. The performance is evaluated via simulation, and the results are compared with conventioinal GC scheme and an optimal CAC schme based on SMDP.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130305376","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":"Study of Traffic Flow Prediction Based on BP Neural Network","authors":"Fengying Cui","doi":"10.1109/IWISA.2010.5473703","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473703","url":null,"abstract":"In this paper the back propagation (BP) neural network algorithm is applied to predict the traffic flow of urban road. The neuron structure needs 48 input nodes and 48 output nodes, so the frame of 48-20-48 is selected. First train an ideal input network with lower error square sum, then take the trained weight vector as initial value of the next input vector. The network training is realized by functions of adaptive learning rate and additional momentum method. The design can forecast 5-minute vehicle flow in future by the current related traffic flow and provide effective information for traffic department. The simulation by Matlab shows that the method with power learning ability and adaptability has high application value.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115678585","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}
Cun Yang, Junhua Zhang, X. Meng, Lixin Wang, Xiaowei Lv
{"title":"Nonhyperbolic Reflection Traveltimes and Moveouts in Anisotropic VTI Media","authors":"Cun Yang, Junhua Zhang, X. Meng, Lixin Wang, Xiaowei Lv","doi":"10.1109/IWISA.2010.5473626","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473626","url":null,"abstract":"The hyperbolic approximation of P-wave reflection traveltimes in common-midpoint gathers plays an important role in conventional seismic data processing and interpretation. It is well known that the normal moveout formula is based upon homogeneous isotropic media. The familiar hyperbolic approximation of P-wave reflection moveout is exact for homogeneous isotropic or elliptically anisotropic media above a planar reflector. Any realistic combination of heterogeneity, anisotropic coefficient, and nonelliptic anisotropy will cause departures from hyperbolic moveout at large offsets. Therefore, nonhyperbolic moveout gives exact traveltimes for elliptically anisotropic media overlaying a plane dipping reflector. In this paper, we compare a theoretical description of P-wave reflection traveltimes and degree of nonhyperbolic moveout with different anisotropic parameters.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115732285","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}
Miao Wang, Xuequn Shang, Shaohua Zhang, Zhanhuai Li
{"title":"Using Direct and Indirect Neighbours to Predict Protein Function in GO-Evaluated PPI Data Set","authors":"Miao Wang, Xuequn Shang, Shaohua Zhang, Zhanhuai Li","doi":"10.1109/IWISA.2010.5473349","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473349","url":null,"abstract":"The recent development of high-throughout techniques to generate large volumes of protein-protein interaction(PPI) data, which increased the need for methods that annotate the function of protein. Some methods use indirect method to predict proteins function. However, due to the nature of noise, the relationship between proteins may not be existed in truth. In this paper, we propose a method of protein function prediction in GO-evaluated PPI data set. Firstly, the original PPI data set is evaluated by protein similarity method based on GO. Secondly, we develop an algorithm, FAW, which takes into account both direct and indirect functional association, to predict the function of proteins. Our approach is evaluated on four human PPI data sets. The experimental results show our approach has good performance in terms of efficiency.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117110703","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}