Pub Date : 2011-09-01DOI: 10.1109/ICAWST.2011.6163138
F. Cong, T. Ristaniemi
This study addresses an empirical study for data model conversion when using independent component analysis (ICA) to extract brain event-related potentials (ERPs). We firstly prove that in theory there is no difference to perform ICA on the concatenated EEG recordings of a number of single trials and the averaged EEG recordings over those single trials. The general assumption for such conclusion is that mixing models of linear transformations do not change along single trials. Furthermore, we explicitly illustrate that an optimal wavelet filter based on properties of an ERP can convert the underdetermined model of EEG to at least quasi-determined one, but the optimal digital filter based on that ERP cannot make it, through empirical studies. Hence, we suggest combining an optimal wavelet filter and ICA together to extract desired brain signal from the averaged EEG recordings in the ERP study.
{"title":"Data model conversion for independent component analysis to extract brain signals","authors":"F. Cong, T. Ristaniemi","doi":"10.1109/ICAWST.2011.6163138","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163138","url":null,"abstract":"This study addresses an empirical study for data model conversion when using independent component analysis (ICA) to extract brain event-related potentials (ERPs). We firstly prove that in theory there is no difference to perform ICA on the concatenated EEG recordings of a number of single trials and the averaged EEG recordings over those single trials. The general assumption for such conclusion is that mixing models of linear transformations do not change along single trials. Furthermore, we explicitly illustrate that an optimal wavelet filter based on properties of an ERP can convert the underdetermined model of EEG to at least quasi-determined one, but the optimal digital filter based on that ERP cannot make it, through empirical studies. Hence, we suggest combining an optimal wavelet filter and ICA together to extract desired brain signal from the averaged EEG recordings in the ERP study.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131721672","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163093
Zhenwei Shi, Xinya Zhai, Zhenyu An, Zhi-guo Jiang
Blind source separation (BSS) problem is often solved by using only one statistical property of original sources. In this work, a method combines non-Gaussianity and nonlinear autocorrelation for the BSS problem, which extends the previous BSS situation, is presented.We propose a fast fixed-point algorithm for BSS with nonlinear autocorrelation and non-Gaussianity in this paper. Our algorithm obtained here does not need choose any learning rate. We study its convergence property and show that its convergence speed is at least quadratic. Computer simulations for square temporal autocorrelation and non-Gaussian sources, including sub-Gaussian and super-Gaussian sources, illustrate the efficiency of the proposed approach.
{"title":"Fast fixed-point algorithm for blind separation of nonlinear autocorrelation and non-Gaussian sources","authors":"Zhenwei Shi, Xinya Zhai, Zhenyu An, Zhi-guo Jiang","doi":"10.1109/ICAWST.2011.6163093","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163093","url":null,"abstract":"Blind source separation (BSS) problem is often solved by using only one statistical property of original sources. In this work, a method combines non-Gaussianity and nonlinear autocorrelation for the BSS problem, which extends the previous BSS situation, is presented.We propose a fast fixed-point algorithm for BSS with nonlinear autocorrelation and non-Gaussianity in this paper. Our algorithm obtained here does not need choose any learning rate. We study its convergence property and show that its convergence speed is at least quadratic. Computer simulations for square temporal autocorrelation and non-Gaussian sources, including sub-Gaussian and super-Gaussian sources, illustrate the efficiency of the proposed approach.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125181546","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163094
X. Wu, Jing-jing Zhang, Xiao-xian Guo, T. Qiu
An improved mixed cryptosystem is presented by combining both random phase encoding technique based chaos and public key cryptography. The scheme provides not only good robustness of random phase encoding technique, but also a new solution of key distribution for symmetric cryptography algorithms. In additions, computer simulation is illustrated in detail. The tolerance to data loss of the encoded barcode is also studied particularly. The results show that the presented encoding method has advantage of robustness and high security, and very convenient to be popularized in practice.
{"title":"An improved secure communication based on random phase encoding technique","authors":"X. Wu, Jing-jing Zhang, Xiao-xian Guo, T. Qiu","doi":"10.1109/ICAWST.2011.6163094","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163094","url":null,"abstract":"An improved mixed cryptosystem is presented by combining both random phase encoding technique based chaos and public key cryptography. The scheme provides not only good robustness of random phase encoding technique, but also a new solution of key distribution for symmetric cryptography algorithms. In additions, computer simulation is illustrated in detail. The tolerance to data loss of the encoded barcode is also studied particularly. The results show that the presented encoding method has advantage of robustness and high security, and very convenient to be popularized in practice.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134453694","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163166
Chulgyu Song, Keo-Sik Kim, Min-Ho Kim, S. Ryu
We have investigated Photoacoustic (PA) imaging for monitoring of wound healing under a blood layer with different degree of coagulation. We embedded simulated blood vessel structure in tissue phantoms made with gelatin. A thin layer of blood with different degree of coagulation was also embedded on top of the vessel structure. Using 532 nm pulse laser, we obtained PA images of the phantoms and analyzed the image quality depending on the degree of blood coagulation. Due to the high optical absorption of blood layer, PA image of simulated blood vessel under blood layer was limited but according to optical scattering, possibility of PA imaging to monitor wound healing was confirmed.
{"title":"Investigation of Photoacoustic imaging for monitoring of Wound Healing under a Layer of Blood with Different Coagulation","authors":"Chulgyu Song, Keo-Sik Kim, Min-Ho Kim, S. Ryu","doi":"10.1109/ICAWST.2011.6163166","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163166","url":null,"abstract":"We have investigated Photoacoustic (PA) imaging for monitoring of wound healing under a blood layer with different degree of coagulation. We embedded simulated blood vessel structure in tissue phantoms made with gelatin. A thin layer of blood with different degree of coagulation was also embedded on top of the vessel structure. Using 532 nm pulse laser, we obtained PA images of the phantoms and analyzed the image quality depending on the degree of blood coagulation. Due to the high optical absorption of blood layer, PA image of simulated blood vessel under blood layer was limited but according to optical scattering, possibility of PA imaging to monitor wound healing was confirmed.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133265682","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163168
Tsendsuren Munkhdalai, Meijing Li, Erdenetuya Namsrai, Oyun-Erdene Namsrai, K. Ryu
One essential task in automated information extraction for biomedical literature is bio named entity recognition process, which basically defines the boundaries between typical words and technical terms of biomedical domain in particular text data and, classifies them based on the domain knowledge. Due to nature of bio named entity, purely defining boundary of the named entities in text data is still challenging. This paper proposes using the part-of-speech tags of tokens as target observation of name boundary definer tool. We proposed an approach for modeling finite state machine as the boundary definer. Aided by machine learning methods including frequent pattern mining method and Bayesian network, the finite state machine learns on part-of-speech tag of tokens in bio-text data. The finite state machine based on Bayesian network is named BFSM. In addition, we report the influence of part-of-speech tagger tool for learning of BFSM. Experimental results show that the named entity recognition system using the BFSM gives us high accuracy as F-score 85.8.
{"title":"BFSM: Finite state machine learned as name boundary definer for bio named entity recognition","authors":"Tsendsuren Munkhdalai, Meijing Li, Erdenetuya Namsrai, Oyun-Erdene Namsrai, K. Ryu","doi":"10.1109/ICAWST.2011.6163168","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163168","url":null,"abstract":"One essential task in automated information extraction for biomedical literature is bio named entity recognition process, which basically defines the boundaries between typical words and technical terms of biomedical domain in particular text data and, classifies them based on the domain knowledge. Due to nature of bio named entity, purely defining boundary of the named entities in text data is still challenging. This paper proposes using the part-of-speech tags of tokens as target observation of name boundary definer tool. We proposed an approach for modeling finite state machine as the boundary definer. Aided by machine learning methods including frequent pattern mining method and Bayesian network, the finite state machine learns on part-of-speech tag of tokens in bio-text data. The finite state machine based on Bayesian network is named BFSM. In addition, we report the influence of part-of-speech tagger tool for learning of BFSM. Experimental results show that the named entity recognition system using the BFSM gives us high accuracy as F-score 85.8.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124754947","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163105
Jae Kyu Lee, Jong Yeol Lee
Android has been researched in various mobile device fields such as Smartphone and Tablet PC. In here, we should remember that mobile devices have limited storage and constrained battery life. Therefore, when developers develop applications, they should do efficient programming. In this paper, we have proposed programming guidelines for an effective way to improve performance in Android applications. We have programmed Android applications using Java and Native C, and compared the performance between the two languages. The applications are composed of five categories such as JNI delay, Integer, Floating-point, Memory access algorithm and String processing. By analyzing the results, we propose a more efficient way to program Android applications.
{"title":"Android programming techniques for improving performance","authors":"Jae Kyu Lee, Jong Yeol Lee","doi":"10.1109/ICAWST.2011.6163105","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163105","url":null,"abstract":"Android has been researched in various mobile device fields such as Smartphone and Tablet PC. In here, we should remember that mobile devices have limited storage and constrained battery life. Therefore, when developers develop applications, they should do efficient programming. In this paper, we have proposed programming guidelines for an effective way to improve performance in Android applications. We have programmed Android applications using Java and Native C, and compared the performance between the two languages. The applications are composed of five categories such as JNI delay, Integer, Floating-point, Memory access algorithm and String processing. By analyzing the results, we propose a more efficient way to program Android applications.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124812124","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163169
Xiuming Yu, Meijing Li, Hyeongsoo Kim, Dong Gyu Lee, J. Park, K. Ryu
Web log mining is an important area of Web Usage Mining (WUM) for discovering useful information from web log files produced by web servers. According to the mining task, user access patterns can be extracted and the result can be applied to improve websites, business intelligence systems and other areas. In this paper, we propose a novel approach for exacting user access patterns by achieving a large event set and improving the BI-Directional Extension closure checking method (BIDE). The process of getting a large event set can filter out the more frequent events and discard the infrequent events to reduce the number of data. Compared with other methods, the BIDE method with the constraint of gap can achieve a more efficient mining process and generate more accurate results. In our experiment, the effect of the mining task is discussed and the applications of this approach are presented.
{"title":"A novel approach to mining access patterns","authors":"Xiuming Yu, Meijing Li, Hyeongsoo Kim, Dong Gyu Lee, J. Park, K. Ryu","doi":"10.1109/ICAWST.2011.6163169","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163169","url":null,"abstract":"Web log mining is an important area of Web Usage Mining (WUM) for discovering useful information from web log files produced by web servers. According to the mining task, user access patterns can be extracted and the result can be applied to improve websites, business intelligence systems and other areas. In this paper, we propose a novel approach for exacting user access patterns by achieving a large event set and improving the BI-Directional Extension closure checking method (BIDE). The process of getting a large event set can filter out the more frequent events and discard the infrequent events to reduce the number of data. Compared with other methods, the BIDE method with the constraint of gap can achieve a more efficient mining process and generate more accurate results. In our experiment, the effect of the mining task is discussed and the applications of this approach are presented.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115897328","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 : 2011-09-01DOI: 10.1109/ICAWST.2011.6163194
Qingju Liu, Wenwu Wang
Despite being studied extensively, the performance of blind source separation (BSS) is still limited especially for the sensor data collected in adverse environments. Recent studies show that such an issue can be mitigated by incorporating multimodal information into the BSS process. In this paper, we propose a method for the enhancement of the target speech separated by a BSS algorithm from sound mixtures, using visual voice activity detection (VAD) and spectral subtraction. First, a classifier for visual VAD is formed in the off-line training stage, using labelled features extracted from the visual stimuli. Then we use this visual VAD classifier to detect the voice activity of the target speech. Finally we apply a multi-band spectral subtraction algorithm to enhance the BSS-separated speech signal based on the detected voice activity. We have tested our algorithm on the mixtures generated artificially by the mixing filters with different reverberation times, and the results show that our algorithm improves the quality of the separated target signal.
{"title":"Blind source separation and visual voice activity detection for target speech extraction","authors":"Qingju Liu, Wenwu Wang","doi":"10.1109/ICAWST.2011.6163194","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163194","url":null,"abstract":"Despite being studied extensively, the performance of blind source separation (BSS) is still limited especially for the sensor data collected in adverse environments. Recent studies show that such an issue can be mitigated by incorporating multimodal information into the BSS process. In this paper, we propose a method for the enhancement of the target speech separated by a BSS algorithm from sound mixtures, using visual voice activity detection (VAD) and spectral subtraction. First, a classifier for visual VAD is formed in the off-line training stage, using labelled features extracted from the visual stimuli. Then we use this visual VAD classifier to detect the voice activity of the target speech. Finally we apply a multi-band spectral subtraction algorithm to enhance the BSS-separated speech signal based on the detected voice activity. We have tested our algorithm on the mixtures generated artificially by the mixing filters with different reverberation times, and the results show that our algorithm improves the quality of the separated target signal.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128099859","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}
Xuan Guo, Y. Toyoda, Huan Li, Jie Huang, Shuxue Ding, Yong Liu
Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we tried to use a multi-stage perceptron type neural network system for environmental sound recognition. The input data is the one-dimensional combination of instantaneous spectrum at power peak and the power pattern in time domain. Since for almost environmental sounds, their spectrum changes are not remarkable compared with speech or voice, the combination of power and frequency pattern will preserve the major features of environmental sounds but with drastically reduced data. Two experiments were conducted using an original database and a database created by the RWCP. The recognition rate for about 45 data kinds of environmental sound was about 92%. The merit of this method is the use of a one-dimensional input which combines the power pattern and the instantaneous spectrum of sound data. Comparing with the method using only instantaneous spectrum, the new method are sufficient for larger sound database and the recognition rate was increased about 12%. The results are also comparable with the methods of HMM, while those methods require 2-dimensional spectrum time series data and more complicated computation.
{"title":"Environmental sound recognition using time-frequency intersection patterns","authors":"Xuan Guo, Y. Toyoda, Huan Li, Jie Huang, Shuxue Ding, Yong Liu","doi":"10.1155/2012/650818","DOIUrl":"https://doi.org/10.1155/2012/650818","url":null,"abstract":"Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we tried to use a multi-stage perceptron type neural network system for environmental sound recognition. The input data is the one-dimensional combination of instantaneous spectrum at power peak and the power pattern in time domain. Since for almost environmental sounds, their spectrum changes are not remarkable compared with speech or voice, the combination of power and frequency pattern will preserve the major features of environmental sounds but with drastically reduced data. Two experiments were conducted using an original database and a database created by the RWCP. The recognition rate for about 45 data kinds of environmental sound was about 92%. The merit of this method is the use of a one-dimensional input which combines the power pattern and the instantaneous spectrum of sound data. Comparing with the method using only instantaneous spectrum, the new method are sufficient for larger sound database and the recognition rate was increased about 12%. The results are also comparable with the methods of HMM, while those methods require 2-dimensional spectrum time series data and more complicated computation.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132053340","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}
Speaker identification is a popular investigation that is greatly applied in many applications such as human-machine interfaced, security systems, etc. In real life, low cost and fast response are both necessary features for speaker identification in stand-alone embedded device. However, most of the responding time occupies in training phase, and the cost of general solution by employing digital signal processors is too high. In this work, security-aware VLSI design with the efficient Sequential Minimal Optimization (SMO) architecture is proposed for solving the problems in text-independent speaker identification. Our contributions are attributed to the optimal VLSI design form algorithm to architecture level. At algorithm level, the proposed Improved SMO (ISMO) algorithm is adopted for efficient data selection and it can reduce 30% computation. At architecture level, a distributed and reconfigurable computing architecture which combines parallel and pipeline designing styles is implemented, and it provides the high flexible and high performance benefits. Finally, the experimental results show that the proposed design can save 50% of memory usage, and the hardware resources can be reduced by 31% than our previous work. Furthermore, the responding time can decrease 85%.
{"title":"Security-aware VLSI design for speaker identification based on efficient SMO architecture","authors":"Jhing-Fa Wang, Jr-Shiang Peng, Po-Chuan Lin, Bo-Wei Chen, Nai-Sheng Shih","doi":"10.1109/ICAWST.2011.6163100","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163100","url":null,"abstract":"Speaker identification is a popular investigation that is greatly applied in many applications such as human-machine interfaced, security systems, etc. In real life, low cost and fast response are both necessary features for speaker identification in stand-alone embedded device. However, most of the responding time occupies in training phase, and the cost of general solution by employing digital signal processors is too high. In this work, security-aware VLSI design with the efficient Sequential Minimal Optimization (SMO) architecture is proposed for solving the problems in text-independent speaker identification. Our contributions are attributed to the optimal VLSI design form algorithm to architecture level. At algorithm level, the proposed Improved SMO (ISMO) algorithm is adopted for efficient data selection and it can reduce 30% computation. At architecture level, a distributed and reconfigurable computing architecture which combines parallel and pipeline designing styles is implemented, and it provides the high flexible and high performance benefits. Finally, the experimental results show that the proposed design can save 50% of memory usage, and the hardware resources can be reduced by 31% than our previous work. Furthermore, the responding time can decrease 85%.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121350834","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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