Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518561
Liman Yang, Guilin Liu, Zhongwei Guo
A new control strategy based on dynamic matrix control algorithm is proposed in this paper to deal with delay and data packet dropout from sensor to controller as well as from controller to actuator in the networked control system. Through the port setting and sequence controlling at the controller and actuator, the new output of predictive model and the new sequence of predictive control are utilized effectively to compensate the delay and the probable data packet dropout so as to promote the robustness and fault-tolerance capability against the fluctuating QoS.
{"title":"Dynamic matrix control algorithm for networked control systems with delay and data packet dropout","authors":"Liman Yang, Guilin Liu, Zhongwei Guo","doi":"10.1109/ICCIS.2010.5518561","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518561","url":null,"abstract":"A new control strategy based on dynamic matrix control algorithm is proposed in this paper to deal with delay and data packet dropout from sensor to controller as well as from controller to actuator in the networked control system. Through the port setting and sequence controlling at the controller and actuator, the new output of predictive model and the new sequence of predictive control are utilized effectively to compensate the delay and the probable data packet dropout so as to promote the robustness and fault-tolerance capability against the fluctuating QoS.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127650836","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518574
Marco Paleari, R. Chellali, B. Huet
The ability to recognize emotions in natural human communications is known to be very important for mankind. In recent years, a considerable number of researchers have investigated techniques allowing computer to replicate this capability by analyzing both prosodic (voice) and facial expressions. The applications of the resulting systems are manifold and range from gaming to indexing and retrieval, through chat and health care. No study has, to the best of our knowledge, ever reported results comparing the effectiveness of several features for automatic emotion recognition. In this work, we present an extensive study conducted on feature selection for automatic, audio-visual, real-time, and person independent emotion recognition. More than 300,000 different neural networks have been trained in order to compare the performances of 64 features and 11 different sets of features with 450 different analysis settings. Results show that: 1) to build an optimal emotion recognition system, different emotions should be classified via different features and 2) different features, in general, require different processing.
{"title":"Features for multimodal emotion recognition: An extensive study","authors":"Marco Paleari, R. Chellali, B. Huet","doi":"10.1109/ICCIS.2010.5518574","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518574","url":null,"abstract":"The ability to recognize emotions in natural human communications is known to be very important for mankind. In recent years, a considerable number of researchers have investigated techniques allowing computer to replicate this capability by analyzing both prosodic (voice) and facial expressions. The applications of the resulting systems are manifold and range from gaming to indexing and retrieval, through chat and health care. No study has, to the best of our knowledge, ever reported results comparing the effectiveness of several features for automatic emotion recognition. In this work, we present an extensive study conducted on feature selection for automatic, audio-visual, real-time, and person independent emotion recognition. More than 300,000 different neural networks have been trained in order to compare the performances of 64 features and 11 different sets of features with 450 different analysis settings. Results show that: 1) to build an optimal emotion recognition system, different emotions should be classified via different features and 2) different features, in general, require different processing.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123997840","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518569
N. Chaudhari
Many fundamental problems in automated theorem proving are known to be NP-Complete. In [4], we have given a polynomial algorithm for 3-SAT, one of the first NP-Complete problems. The result is unexpected and has deep consequences for the design of intelligent systems; hence, in this paper, we review our algorithmic approach for 3-SAT, and we give simplified analysis of our approach to demonstrate the polynomial bound of O(n13) operations. We also indicate the immediate and important consequences of our polynomial algorithm for 3-SAT for the design of intelligent systems.
{"title":"Intelligent systems and polynomial solvability of NP-complete problems","authors":"N. Chaudhari","doi":"10.1109/ICCIS.2010.5518569","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518569","url":null,"abstract":"Many fundamental problems in automated theorem proving are known to be NP-Complete. In [4], we have given a polynomial algorithm for 3-SAT, one of the first NP-Complete problems. The result is unexpected and has deep consequences for the design of intelligent systems; hence, in this paper, we review our algorithmic approach for 3-SAT, and we give simplified analysis of our approach to demonstrate the polynomial bound of O(n13) operations. We also indicate the immediate and important consequences of our polynomial algorithm for 3-SAT for the design of intelligent systems.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115885914","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518548
Yu-Sheng Lu, Bing Wu
This paper presents the experimental evaluation of a fuzzy sliding-mode control scheme. The control law consists of three parts: a nominal controller, a sliding-mode disturbance observer (SMDO), and an adaptive fuzzy sliding-mode controller (AFSMC) that is based on a T-S model. The nominal controller is employed to specify the desired closed-loop dynamics whereas the SMDO as well as the AFSMC are designed to compensate for unknown perturbation. Nevertheless, the perturbation can be considered to comprise a modellable part and an unmodelable part, which are to be compensated for by the SMDO and the AFSMC, respectively. Experimental evaluations of the SMDO-AFSMC scheme are conducted by practically applying the scheme to a four-bar linkage system.
{"title":"Experimental evaluation of a T-S model-based sliding-mode control scheme","authors":"Yu-Sheng Lu, Bing Wu","doi":"10.1109/ICCIS.2010.5518548","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518548","url":null,"abstract":"This paper presents the experimental evaluation of a fuzzy sliding-mode control scheme. The control law consists of three parts: a nominal controller, a sliding-mode disturbance observer (SMDO), and an adaptive fuzzy sliding-mode controller (AFSMC) that is based on a T-S model. The nominal controller is employed to specify the desired closed-loop dynamics whereas the SMDO as well as the AFSMC are designed to compensate for unknown perturbation. Nevertheless, the perturbation can be considered to comprise a modellable part and an unmodelable part, which are to be compensated for by the SMDO and the AFSMC, respectively. Experimental evaluations of the SMDO-AFSMC scheme are conducted by practically applying the scheme to a four-bar linkage system.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909434","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518575
Himanshu Singh Michael Shell, Vipul Arora, A. Dutta, L. Behera
Face feature tracking is a well known and quite challenging area in computer vision. This paper mainly focuses on two important aspects of feature tracking, viz., automatic initialization and automatic detection of tracking failure followed by system update. We present a dynamic framework to automatically initialize and update the face feature tracking process. In addition, a novel approach to self-occlusion handling is also presented. The system consists of - initialization, feature tracking and system update modules. A reliable and efficient technique, that can quickly initialize a face feature tracking system in subject independent manner, has been presented. The initialization module relies on a scale independent accurate feature positioning algorithm based on binarized motion differencing approach. Face feature tracking module is based on the multi-resolution motion tracking algorithm. The system also enables automatic tracking failure detection and re-initialization, with practically minimal subject intervention. In the end, a new technique, to handle the problem of features occlusion, has been proposed. The combined model not only makes the tracking system more efficient and quicker but also helps it to act in a self supervised manner.
{"title":"Face feature tracking with automatic initialization and failure recovery","authors":"Himanshu Singh Michael Shell, Vipul Arora, A. Dutta, L. Behera","doi":"10.1109/ICCIS.2010.5518575","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518575","url":null,"abstract":"Face feature tracking is a well known and quite challenging area in computer vision. This paper mainly focuses on two important aspects of feature tracking, viz., automatic initialization and automatic detection of tracking failure followed by system update. We present a dynamic framework to automatically initialize and update the face feature tracking process. In addition, a novel approach to self-occlusion handling is also presented. The system consists of - initialization, feature tracking and system update modules. A reliable and efficient technique, that can quickly initialize a face feature tracking system in subject independent manner, has been presented. The initialization module relies on a scale independent accurate feature positioning algorithm based on binarized motion differencing approach. Face feature tracking module is based on the multi-resolution motion tracking algorithm. The system also enables automatic tracking failure detection and re-initialization, with practically minimal subject intervention. In the end, a new technique, to handle the problem of features occlusion, has been proposed. The combined model not only makes the tracking system more efficient and quicker but also helps it to act in a self supervised manner.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115389520","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518562
Sangeeta Jadhav, A. Bhalchandra
In a digital watermarking scheme, it is not convenient to carry the original image all the time in order to detect the owner's signature from the watermarked image. Moreover, for those applications that require different watermarks for different copies, it is preferred to utilize some kind of watermark-independent algorithm for extraction process i.e. dewatermarking. Watermark embedding is performed in the blue channel, as it is less sensitive to human visual system. This paper proposes a new color image watermarking method, which adopts Blind Source Separation (BSS) technique for watermark extraction. Single level Discrete Wavelet Transform (DWT) is used for embedding. The novelty of our scheme lies in determining the mixing matrix for BSS model during embedding. The determination of mixing matrix using Quasi-Newton's (BFGS) technique is based on texture analysis which uses energy content of the image. This makes our method image adaptive to embed the watermark into original image so as not to bring about a perceptible change in the marked image. BSS based on Joint diagonalization of the time delayed covariance matrices algorithm is used for the extraction of watermark. The proposed method, undergoing different experiments, has shown its robustness against many attacks including rotation, low pass filtering, salt n pepper noise addition and compression. The robustness evaluation is also carried out with respect to the spatial domain embedding.
{"title":"Blind Source Separation based robust digital image watermarking using wavelet domain embedding","authors":"Sangeeta Jadhav, A. Bhalchandra","doi":"10.1109/ICCIS.2010.5518562","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518562","url":null,"abstract":"In a digital watermarking scheme, it is not convenient to carry the original image all the time in order to detect the owner's signature from the watermarked image. Moreover, for those applications that require different watermarks for different copies, it is preferred to utilize some kind of watermark-independent algorithm for extraction process i.e. dewatermarking. Watermark embedding is performed in the blue channel, as it is less sensitive to human visual system. This paper proposes a new color image watermarking method, which adopts Blind Source Separation (BSS) technique for watermark extraction. Single level Discrete Wavelet Transform (DWT) is used for embedding. The novelty of our scheme lies in determining the mixing matrix for BSS model during embedding. The determination of mixing matrix using Quasi-Newton's (BFGS) technique is based on texture analysis which uses energy content of the image. This makes our method image adaptive to embed the watermark into original image so as not to bring about a perceptible change in the marked image. BSS based on Joint diagonalization of the time delayed covariance matrices algorithm is used for the extraction of watermark. The proposed method, undergoing different experiments, has shown its robustness against many attacks including rotation, low pass filtering, salt n pepper noise addition and compression. The robustness evaluation is also carried out with respect to the spatial domain embedding.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127034717","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518586
X. Qing, Zhi Ning Chen, T. See, C. K. Goh, T. M. Chiam
In this paper, the RF transmission characteristics in/through human body are investigated experimentally and numerically. An experimental methodology to characterize the RF transmission of human body is presented. The proposed method addresses the challenge to characterize the RF transmission accurately and reliably without the body tissue effect on the antennas under test. The proposed methodology of using tissue-embedded antennas is validated at 403 MHz band (Medical Implant Communication Service, MICS).
{"title":"RF transmission characteristics in/through the human body","authors":"X. Qing, Zhi Ning Chen, T. See, C. K. Goh, T. M. Chiam","doi":"10.1109/ICCIS.2010.5518586","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518586","url":null,"abstract":"In this paper, the RF transmission characteristics in/through human body are investigated experimentally and numerically. An experimental methodology to characterize the RF transmission of human body is presented. The proposed method addresses the challenge to characterize the RF transmission accurately and reliably without the body tissue effect on the antennas under test. The proposed methodology of using tissue-embedded antennas is validated at 403 MHz band (Medical Implant Communication Service, MICS).","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132446732","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518583
M. Shazri, Najib Ramlee, Chai Tong Yuen
Eye detection is an important step for face recognition and verification because it provides a reference point to normalize not only location but also the flat 2d orientation of face relative to the image border. The base technique that is referred to shows how Wavelet Transformation works hand in hand with Neural Networks. In this paper a proposition of a system that regiment the wavelet coefficient is introduced, as such it includes a reduction methods, namely Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) on top of the Wavelet Transform as a feature extraction technique and Neural Network as an eye-detector classifier. Experimental results showed an increased performance (Internal 10%, ORL 9.2% and Yale 7.5%) across three datasets by using the proposed method(PCA) and 7% overall increase of performance when changing from PCA to LDA Eigen Vectors.
{"title":"Wavelet PCA/LDA Neural Network eye detection","authors":"M. Shazri, Najib Ramlee, Chai Tong Yuen","doi":"10.1109/ICCIS.2010.5518583","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518583","url":null,"abstract":"Eye detection is an important step for face recognition and verification because it provides a reference point to normalize not only location but also the flat 2d orientation of face relative to the image border. The base technique that is referred to shows how Wavelet Transformation works hand in hand with Neural Networks. In this paper a proposition of a system that regiment the wavelet coefficient is introduced, as such it includes a reduction methods, namely Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) on top of the Wavelet Transform as a feature extraction technique and Neural Network as an eye-detector classifier. Experimental results showed an increased performance (Internal 10%, ORL 9.2% and Yale 7.5%) across three datasets by using the proposed method(PCA) and 7% overall increase of performance when changing from PCA to LDA Eigen Vectors.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"31 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115575232","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518588
Alireza Salimpour, M. Sojoodi, V. J. Majd
This paper addresses robust stability of genetic regulatory networks (GRNs) with stochastic perturbation and discrete and distributed time-varying delays. Aside from discrete delays, there are few results about stability of GRNs with distributed delay. In this paper, noise perturbation and delays have been considered in both mRNA and protein dynamics. Based on Lyapunov functional approach and linear matrix inequality (LMI) techniques, sufficient conditions are established to guarantee the robust stability of genetic regulatory networks. Stability conditions are derived in the form of LMIs, which are very easy to be verified. An example is presented to verify the theoretical results.
{"title":"Robust stability analysis of stochastic genetic regulatory networks with discrete and distributed delay in both mRNA and protein dynamics","authors":"Alireza Salimpour, M. Sojoodi, V. J. Majd","doi":"10.1109/ICCIS.2010.5518588","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518588","url":null,"abstract":"This paper addresses robust stability of genetic regulatory networks (GRNs) with stochastic perturbation and discrete and distributed time-varying delays. Aside from discrete delays, there are few results about stability of GRNs with distributed delay. In this paper, noise perturbation and delays have been considered in both mRNA and protein dynamics. Based on Lyapunov functional approach and linear matrix inequality (LMI) techniques, sufficient conditions are established to guarantee the robust stability of genetic regulatory networks. Stability conditions are derived in the form of LMIs, which are very easy to be verified. An example is presented to verify the theoretical results.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116603690","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 : 2010-06-28DOI: 10.1109/ICCIS.2010.5518564
B. Wei, R. Mandava
Image segmentation aims to partition an image into several disjointed regions that are homogeneous with regards to some measures so that subsequent higher level computer vision processing, such as object recognition, image understanding and scene description can be performed. Multi-objective formulations are realistic models for image segmentation because objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. In this paper, we present the current multi-objective nature-inspired clustering (MoNiC) techniques for image segmentation. We are able to diagnose the requirements and issues for modelling this specific technique in the image segmentation problem. Three identified important phases include intelligence, design and choice with respect to the issues of clustering problem of image segmentation and multi-objective clustering algorithm design.
{"title":"Multi-objective nature-inspired clustering techniques for image segmentation","authors":"B. Wei, R. Mandava","doi":"10.1109/ICCIS.2010.5518564","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518564","url":null,"abstract":"Image segmentation aims to partition an image into several disjointed regions that are homogeneous with regards to some measures so that subsequent higher level computer vision processing, such as object recognition, image understanding and scene description can be performed. Multi-objective formulations are realistic models for image segmentation because objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. In this paper, we present the current multi-objective nature-inspired clustering (MoNiC) techniques for image segmentation. We are able to diagnose the requirements and issues for modelling this specific technique in the image segmentation problem. Three identified important phases include intelligence, design and choice with respect to the issues of clustering problem of image segmentation and multi-objective clustering algorithm design.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126324094","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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