Pub Date : 2017-01-01DOI: 10.1109/ISKE.2017.8258828
Yanfeng Wang, Ningsheng Gong, Xilong Gu
{"title":"Research on method for moving shadow detection","authors":"Yanfeng Wang, Ningsheng Gong, Xilong Gu","doi":"10.1109/ISKE.2017.8258828","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258828","url":null,"abstract":"","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"71 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85077217","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}
Pub Date : 2017-01-01DOI: 10.1109/ISKE.2017.8258730
Libo Ti, Hongjun Zhou
{"title":"Characterizations of (G, N)-implications","authors":"Libo Ti, Hongjun Zhou","doi":"10.1109/ISKE.2017.8258730","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258730","url":null,"abstract":"","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"75 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73613382","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}
Pub Date : 2017-01-01DOI: 10.1109/ISKE.2017.8258829
Tao Wang, Ningsheng Gong, Guixiang Jiang
{"title":"Enhanced image algorithm at night of improved retinex based on HIS space","authors":"Tao Wang, Ningsheng Gong, Guixiang Jiang","doi":"10.1109/ISKE.2017.8258829","DOIUrl":"https://doi.org/10.1109/ISKE.2017.8258829","url":null,"abstract":"","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"28 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81999335","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}
Ester Castillo Herrera, L. Jiménez, L. Rodriguez-Benitez, Juan Giralt Muina, Juan Moreno García
The induction of classifiers by means of supervised learning techniques is one of the most common and extended applications in the field of the intelligent systems. Multi-classifier systems obtain a set of basic classifiers and uses it to predict the class of a data instance. In this work, a new method to reduce a set of classifiers to their equivalent minimal set is presented. For this purpose, a new fuzzy classifier called Atomic Fuzzy Classifier is defined. Furthermore, two different definitions of similarity, structural similarity and functional similarity, are considered. The combination of both produces a novel definition of a similarity function between two classifiers. This relation of similarity is used to obtain classes of equivalence, where each element of this class represents a subset of similar classifiers. The original set of classifiers is reduced to a new set of classifiers where only one of them is related to an unique equivalence class. In the experimental part, an application for the classification of elements of the IRIS database is presented.
{"title":"Reduction of a Set of Fuzzy Classifiers by Equivalence Classes","authors":"Ester Castillo Herrera, L. Jiménez, L. Rodriguez-Benitez, Juan Giralt Muina, Juan Moreno García","doi":"10.1109/ISKE.2015.41","DOIUrl":"https://doi.org/10.1109/ISKE.2015.41","url":null,"abstract":"The induction of classifiers by means of supervised learning techniques is one of the most common and extended applications in the field of the intelligent systems. Multi-classifier systems obtain a set of basic classifiers and uses it to predict the class of a data instance. In this work, a new method to reduce a set of classifiers to their equivalent minimal set is presented. For this purpose, a new fuzzy classifier called Atomic Fuzzy Classifier is defined. Furthermore, two different definitions of similarity, structural similarity and functional similarity, are considered. The combination of both produces a novel definition of a similarity function between two classifiers. This relation of similarity is used to obtain classes of equivalence, where each element of this class represents a subset of similar classifiers. The original set of classifiers is reduced to a new set of classifiers where only one of them is related to an unique equivalence class. In the experimental part, an application for the classification of elements of the IRIS database is presented.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"72 1","pages":"534-539"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82668411","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}
Wenliao Du, Chang Huang, Ansheng Li, Xiaoyun Gong, Liangwen Wang, Zhiyang Wang
In the fault diagnosis programs, the intelligent algorithms, such as BP neural network, genetic neural network, ant colony neural network and so on, always suffer from the slow training speed and the local minimums. In this paper, a backtracking search optimization algorithm (BSA) based neural network was put forward, which used the BSA algorithm to train the neural network weights and thresholds. And then it was utilized on the pattern recognition of rolling bearing faults, and the results show that BSA neural network can better solve the problems of slow convergence and local minimums, which has a good application value.
{"title":"Fault Diagnosis of Rolling Bearing Based on BSA Neural Network","authors":"Wenliao Du, Chang Huang, Ansheng Li, Xiaoyun Gong, Liangwen Wang, Zhiyang Wang","doi":"10.1109/ISKE.2015.34","DOIUrl":"https://doi.org/10.1109/ISKE.2015.34","url":null,"abstract":"In the fault diagnosis programs, the intelligent algorithms, such as BP neural network, genetic neural network, ant colony neural network and so on, always suffer from the slow training speed and the local minimums. In this paper, a backtracking search optimization algorithm (BSA) based neural network was put forward, which used the BSA algorithm to train the neural network weights and thresholds. And then it was utilized on the pattern recognition of rolling bearing faults, and the results show that BSA neural network can better solve the problems of slow convergence and local minimums, which has a good application value.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"65 1","pages":"424-427"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75238265","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}
Ning Cao, XingXing Bao, Hao Lu, Fei Wang, Jurong Hu
{"title":"A Sea Clutter Modeling Approach Based on Multifractal Spectrum","authors":"Ning Cao, XingXing Bao, Hao Lu, Fei Wang, Jurong Hu","doi":"10.1109/ISKE.2015.54","DOIUrl":"https://doi.org/10.1109/ISKE.2015.54","url":null,"abstract":"","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"11 1","pages":"473-479"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78776771","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":"WMV-Algebra and Its Wajsberg's form","authors":"Hongbo Wu, Ying Liang, Bin Zhao","doi":"10.1109/ISKE.2015.100","DOIUrl":"https://doi.org/10.1109/ISKE.2015.100","url":null,"abstract":"","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"1 1","pages":"526-533"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89281752","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}
Pub Date : 2013-06-19DOI: 10.1109/INES.2013.6632837
László Erdödi
Jump oriented programming is one of the most up-to-date form of the memory corruption attacks. During this kind of attack the attacker tries to achieve his goal by using library files linked to the binary, without the placing of any own code. To execute attacks like this, a dispatcher gadget is needed which does the control by reading from a given memory part the address of the subsequent command and manages its execution. Besides the dispatcher gadget also functional gadget is needed to implement an attack. Since the most widely used operation system is the Windows this study introduces the execution of jump oriented attacks by an example in Windows environment.
{"title":"Attacking x86 windows binaries by jump oriented programming","authors":"László Erdödi","doi":"10.1109/INES.2013.6632837","DOIUrl":"https://doi.org/10.1109/INES.2013.6632837","url":null,"abstract":"Jump oriented programming is one of the most up-to-date form of the memory corruption attacks. During this kind of attack the attacker tries to achieve his goal by using library files linked to the binary, without the placing of any own code. To execute attacks like this, a dispatcher gadget is needed which does the control by reading from a given memory part the address of the subsequent command and manages its execution. Besides the dispatcher gadget also functional gadget is needed to implement an attack. Since the most widely used operation system is the Windows this study introduces the execution of jump oriented attacks by an example in Windows environment.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"45 1","pages":"333-338"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87534156","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}
Pub Date : 2012-06-13DOI: 10.1109/INES.2012.6249889
L. Palma, F. Coito, P. Gil
Modeling human operator's behavior as a controller in a closed-loop control system finds applications in different areas such as training of operators by expert operator's model, tele-operation or developing warning systems for drivers. In this paper, first, an experimental setup has been developed for collecting data from human operators as they controlled a process with a DC motor, using the mouse interface on the Matlab environment. Low-order ARX models are proposed for human operator modeling. Replacing the operator by a stand-alone human controller model was one of the validation methods. Experimental results are shown to evaluate the performance of the proposed approach for human low-order modeling.
{"title":"Low order models for human controller - Mouse interface","authors":"L. Palma, F. Coito, P. Gil","doi":"10.1109/INES.2012.6249889","DOIUrl":"https://doi.org/10.1109/INES.2012.6249889","url":null,"abstract":"Modeling human operator's behavior as a controller in a closed-loop control system finds applications in different areas such as training of operators by expert operator's model, tele-operation or developing warning systems for drivers. In this paper, first, an experimental setup has been developed for collecting data from human operators as they controlled a process with a DC motor, using the mouse interface on the Matlab environment. Low-order ARX models are proposed for human operator modeling. Replacing the operator by a stand-alone human controller model was one of the validation methods. Experimental results are shown to evaluate the performance of the proposed approach for human low-order modeling.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"89 1","pages":"515-520"},"PeriodicalIF":0.0,"publicationDate":"2012-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80241475","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680831
I. Sotés, J. L. Larrabe, Miguel A. Gomez, F. J. Alvarez, M. C. Rey-Santano, V. Mielgo, E. Gastiasoro
A method to support making decision in a undersea natural gas storage plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when it's working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented.
{"title":"Support making decision using Hotelling T2 technique in an undersea natural gas storage plant","authors":"I. Sotés, J. L. Larrabe, Miguel A. Gomez, F. J. Alvarez, M. C. Rey-Santano, V. Mielgo, E. Gastiasoro","doi":"10.1109/ISKE.2010.5680831","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680831","url":null,"abstract":"A method to support making decision in a undersea natural gas storage plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when it's working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"68 1","pages":"474-477"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74560460","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}
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