Pub Date : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.19
J. Siror, Guanqun Liang, Kaifang Pang, H. Sheng, Dong Wang
In this paper the impact of RFID based tracking to address the challenges of diversion of export goods into the local market in Kenya is discussed. Goods would be moved out of the export factories on pretext that it was destined to foreign markets, however, along the way the goods would be dumped and documents falsified to indicate that goods had left the country, thus evading taxes and gaining unfair advantage. An RFID based In-Transit Visibility system was designed and piloted to address the challenges. The system was used to track export cargo from the factories to the port or frontier offices. The system design, workings and pilot results are discussed in this paper. Results from the pilot demonstrated that RFID based tracking has a great impact on curbing diversion and considerable benefits to transporters and other stakeholders through increased efficiency and reduced turn-around time.
{"title":"Impact of RFID Technology on Tracking of Export Goods in Kenya","authors":"J. Siror, Guanqun Liang, Kaifang Pang, H. Sheng, Dong Wang","doi":"10.4156/JCIT.VOL5.ISSUE9.19","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.19","url":null,"abstract":"In this paper the impact of RFID based tracking to address the challenges of diversion of export goods into the local market in Kenya is discussed. Goods would be moved out of the export factories on pretext that it was destined to foreign markets, however, along the way the goods would be dumped and documents falsified to indicate that goods had left the country, thus evading taxes and gaining unfair advantage. An RFID based In-Transit Visibility system was designed and piloted to address the challenges. The system was used to track export cargo from the factories to the port or frontier offices. The system design, workings and pilot results are discussed in this paper. Results from the pilot demonstrated that RFID based tracking has a great impact on curbing diversion and considerable benefits to transporters and other stakeholders through increased efficiency and reduced turn-around time.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125440119","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.28
Zhixia Yang, Ying-jie Tian
Ordinal regression problem and general multi-class classification problem are important and on-going research subject in machine learning. Support vector ordinal regression machine (SVORM) is an effective method for ordinal regression problem and has been used to deal with general multi-class classification problem. Up to now it is always assumed implicitly that the training data are known exactly . However, in practice, the training data subject to measurement noise. In this paper, we propose the robust versions of SVORM. Furthermore, we also propose a robust multi-class algorithm based on 3-class robust SVORM with Gaussian kernel for general multi-class classification problem with perturbation. The robustness of the proposed methods is validated by our preliminary numerical experiments.
{"title":"Second Order Cone Programming Formulations for Handling Data with Perturbation","authors":"Zhixia Yang, Ying-jie Tian","doi":"10.4156/JCIT.VOL5.ISSUE9.28","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.28","url":null,"abstract":"Ordinal regression problem and general multi-class classification problem are important and on-going research subject in machine learning. Support vector ordinal regression machine (SVORM) is an effective method for ordinal regression problem and has been used to deal with general multi-class classification problem. Up to now it is always assumed implicitly that the training data are known exactly . However, in practice, the training data subject to measurement noise. In this paper, we propose the robust versions of SVORM. Furthermore, we also propose a robust multi-class algorithm based on 3-class robust SVORM with Gaussian kernel for general multi-class classification problem with perturbation. The robustness of the proposed methods is validated by our preliminary numerical experiments.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122224573","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.7
Xue Deng, Junfeng Zhao, Lihong Yang, Rongjun Li
Portfolio selection is an important issue for researchers and practitioners. Compared with the conventional probabilistic mean-variance method, fuzzy number can better describe an uncertain environment with vagueness and ambiguity. In this paper, the portfolio selection model with transaction costs and lending is proposed by means of possibilistic mean and possibilistic variance under the assumption that the returns of assets are fuzzy numbers. Furthermore, a nonlinear bi-objective programming problem is presented by maximizing the future expected return and minimizing the future risk when the returns of assets are trapezoid fuzzy numbers. By using constraint method, it is converted into a single objective programming problem. Importantly, constraint method concerns better the value ranges of the future expected return and risk for solving single objective programming problem. Finally, a numerical example of the portfolio selection problem is provided to illustrate our proposed effective possibilistic means and variances, and the efficient portfolio frontier with transaction costs and lending can be easily obtained.
{"title":"Constraint Method for Possibilistic Mean-variance Portfolio with Transaction Costs and Lending","authors":"Xue Deng, Junfeng Zhao, Lihong Yang, Rongjun Li","doi":"10.4156/JCIT.VOL5.ISSUE9.7","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.7","url":null,"abstract":"Portfolio selection is an important issue for researchers and practitioners. Compared with the conventional probabilistic mean-variance method, fuzzy number can better describe an uncertain environment with vagueness and ambiguity. In this paper, the portfolio selection model with transaction costs and lending is proposed by means of possibilistic mean and possibilistic variance under the assumption that the returns of assets are fuzzy numbers. Furthermore, a nonlinear bi-objective programming problem is presented by maximizing the future expected return and minimizing the future risk when the returns of assets are trapezoid fuzzy numbers. By using constraint method, it is converted into a single objective programming problem. Importantly, constraint method concerns better the value ranges of the future expected return and risk for solving single objective programming problem. Finally, a numerical example of the portfolio selection problem is provided to illustrate our proposed effective possibilistic means and variances, and the efficient portfolio frontier with transaction costs and lending can be easily obtained.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132313876","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.15
Minjuan Zhong, Changxuan Wan
Pseudo-relevance feedback has been perceived as an effective solution for automatic query expansion. However, a recent study has shown that traditional pseudo-relevance feedback may bring into topic drift and hence be harmful to the retrieval performance. It is often crucial to identify those good feedback documents from which useful expansion terms can be added to the query. Compared with traditional query expansion, XML query expansion needs not only content expansion but also considering structural expansion. This paper presents a solution for both identifying related documents and selecting good expansion information with new content and path constrains. Combined with XML semantic feature, a naive document similarity measurement is proposed in this paper. Based on this, kmedian clustering algorithm is firstly implemented and some related documents are found. Secondly, query expansion is only performed by two steps in the set of related documents, which key phrase extraction algorithm is carried out to expand original query in the first step and the second step is structural expansion based on the expanded key phrases. Finally a full-edged content-structure query expression which can represent user’s intention is formalized. Experimental results on IEEE CS collection show that the proposed method can reduce the topic drift effectively and obtain the better retrieval quality.
{"title":"Pseudo-Relevance Feedback Driven for XML Query Expansion","authors":"Minjuan Zhong, Changxuan Wan","doi":"10.4156/JCIT.VOL5.ISSUE9.15","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.15","url":null,"abstract":"Pseudo-relevance feedback has been perceived as an effective solution for automatic query expansion. However, a recent study has shown that traditional pseudo-relevance feedback may bring into topic drift and hence be harmful to the retrieval performance. It is often crucial to identify those good feedback documents from which useful expansion terms can be added to the query. Compared with traditional query expansion, XML query expansion needs not only content expansion but also considering structural expansion. This paper presents a solution for both identifying related documents and selecting good expansion information with new content and path constrains. Combined with XML semantic feature, a naive document similarity measurement is proposed in this paper. Based on this, kmedian clustering algorithm is firstly implemented and some related documents are found. Secondly, query expansion is only performed by two steps in the set of related documents, which key phrase extraction algorithm is carried out to expand original query in the first step and the second step is structural expansion based on the expanded key phrases. Finally a full-edged content-structure query expression which can represent user’s intention is formalized. Experimental results on IEEE CS collection show that the proposed method can reduce the topic drift effectively and obtain the better retrieval quality.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127311049","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.18
Chunchen Liu, Da-you Liu, Sheng-sheng Wang
Situation awareness is a more holistic and promising version of context awareness, which is a key to making Ambient Intelligence systems more adaptive and intelligent. A situation-aware computing system needs to represent context information, identify relevant situations based on the context, and then take appropriate actions according to situations. However, two main kinds of uncertainty need to be handled in these processes: the semantic of context or situation may be fuzzy; context is inherently imperfect. This paper proposes an innovative framework for carrying out situation-aware computing under uncertainty where fuzzy ontology based on fuzzy description logic is used to model context, several new algorithms are proposed to identify entities’ situations considering uncertainty, a fuzzy system based on fuzzy logic and fuzzy learning techniques is developed to make decisions proactively and automatically. In addition, we develop a prototype of smart home application, experimental results from it show that our new technologies are feasible and effective.
{"title":"Dealing with Uncertainty in Situation-aware Computing System","authors":"Chunchen Liu, Da-you Liu, Sheng-sheng Wang","doi":"10.4156/JCIT.VOL5.ISSUE9.18","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.18","url":null,"abstract":"Situation awareness is a more holistic and promising version of context awareness, which is a key to making Ambient Intelligence systems more adaptive and intelligent. A situation-aware computing system needs to represent context information, identify relevant situations based on the context, and then take appropriate actions according to situations. However, two main kinds of uncertainty need to be handled in these processes: the semantic of context or situation may be fuzzy; context is inherently imperfect. This paper proposes an innovative framework for carrying out situation-aware computing under uncertainty where fuzzy ontology based on fuzzy description logic is used to model context, several new algorithms are proposed to identify entities’ situations considering uncertainty, a fuzzy system based on fuzzy logic and fuzzy learning techniques is developed to make decisions proactively and automatically. In addition, we develop a prototype of smart home application, experimental results from it show that our new technologies are feasible and effective.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126060417","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.12
Fengxia Wang, Huixia Jin, Xiao Chang
In recent years, learning ranking function for information retrieval has drawn the attentions of the researchers from information retrieval and machine learning community. In existing approaches of learning to rank, the sparse prediction model only can be learned by support vector learning approach. However, the number of support vectors grows steeply with the size of the training data set. In this paper, we propose a sparse Bayesian kernel approach to learn ranking function. By this approach accurate prediction models can be derived, which typically utilize fewer basis functions than the comparable SVM-based approaches while offering a number of additional advantages. Experimental results on document retrieval data set show that the generalization performance of this approach competitive with two state-of-the-art approaches and the prediction model learned by it is typically sparse.
{"title":"Relevance Vector Ranking for Information Retrieval","authors":"Fengxia Wang, Huixia Jin, Xiao Chang","doi":"10.4156/JCIT.VOL5.ISSUE9.12","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.12","url":null,"abstract":"In recent years, learning ranking function for information retrieval has drawn the attentions of the researchers from information retrieval and machine learning community. In existing approaches of learning to rank, the sparse prediction model only can be learned by support vector learning approach. However, the number of support vectors grows steeply with the size of the training data set. In this paper, we propose a sparse Bayesian kernel approach to learn ranking function. By this approach accurate prediction models can be derived, which typically utilize fewer basis functions than the comparable SVM-based approaches while offering a number of additional advantages. Experimental results on document retrieval data set show that the generalization performance of this approach competitive with two state-of-the-art approaches and the prediction model learned by it is typically sparse.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124795451","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.14
Yu-Cheng Chen, Hsin-Hsi Lai, Heng-Chang Lin
This study explores the construction of an intermediary as a product knowledge-sharing system for design industry with the advanced features of the Extensible Markup Language (XML). In addition, to make the system an object-oriented one, Unified Modeling Language (UML) is used for the modeling of the system. With XML files serving as the foundation for exchange and storage format of the knowledge in the transaction process, the system platform is able to integrate all sorts of product information involving various concepts and related features of different fields such as the design, production, and marketing of a product into a transaction process intermediary program. Having the technology of XML as the foundation of the said transaction process intermediary program, not only will the after transaction knowledge be stored systematically but the information in the system can be transmitted conveniently amongst the heterogeneous systems of users, and can be used with uniformity. In addition, the specific text file markers and text definitions in the XML allow users to search for the information more accurately and efficiently.
{"title":"Constructing Product Knowledge-Sharing System for Internet Transaction-Matching Model","authors":"Yu-Cheng Chen, Hsin-Hsi Lai, Heng-Chang Lin","doi":"10.4156/JCIT.VOL5.ISSUE9.14","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.14","url":null,"abstract":"This study explores the construction of an intermediary as a product knowledge-sharing system for design industry with the advanced features of the Extensible Markup Language (XML). In addition, to make the system an object-oriented one, Unified Modeling Language (UML) is used for the modeling of the system. With XML files serving as the foundation for exchange and storage format of the knowledge in the transaction process, the system platform is able to integrate all sorts of product information involving various concepts and related features of different fields such as the design, production, and marketing of a product into a transaction process intermediary program. Having the technology of XML as the foundation of the said transaction process intermediary program, not only will the after transaction knowledge be stored systematically but the information in the system can be transmitted conveniently amongst the heterogeneous systems of users, and can be used with uniformity. In addition, the specific text file markers and text definitions in the XML allow users to search for the information more accurately and efficiently.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132408190","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.9
X. Xiang
An important and fundamental issue in designing structured peer-to-peer networks is the tradeoff between the number of logical links and the number of hops. We present a flexible resource location protocol called K-Chord, for KC, which is based on the idea of proportional search. We conduct indepth study on KC. We show that KC achieves an excellent tradeoff between the number of logical links and the number of hops. The performances of KC have been evaluated using both theoretical analysis and simulation.
{"title":"A Flexible Resource Location Protocol for Peer-to-Peer Network","authors":"X. Xiang","doi":"10.4156/JCIT.VOL5.ISSUE9.9","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.9","url":null,"abstract":"An important and fundamental issue in designing structured peer-to-peer networks is the tradeoff between the number of logical links and the number of hops. We present a flexible resource location protocol called K-Chord, for KC, which is based on the idea of proportional search. We conduct indepth study on KC. We show that KC achieves an excellent tradeoff between the number of logical links and the number of hops. The performances of KC have been evaluated using both theoretical analysis and simulation.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133549394","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.21
Reihaneh Khorsand Motlagh Esfahani, F. Mardukhi, N. Nematbakhsh
With an expanding of Web services giving same functionalities, Quality of Service (QoS) is becoming an important criterion for selection of the best available service. So users need to know QoS information and the reliability of this information .This article presents a new model of reputation improved Web services discovery considering the quality of services that include a reputation administrator to allocate reputation marks to the services based on customer feedback of their efficiency. The model is based on Service Level Agreements (SLAs) to ensure the standard of the process of discovery the quality specifications of the web services and it regulates perspectives from the two parties that is not the same and provides official definitions of quality of service (QoS) characteristics such that there is no vagueness in explaining characteristics. Practically we collected the present findings on SLA modeling and we presented a broker helps quality aware service discovery using the reputation marks in a service matching, ranking and selection algorithm based on our model.
{"title":"Reputation Improved Web Services Discovery Based on QoS","authors":"Reihaneh Khorsand Motlagh Esfahani, F. Mardukhi, N. Nematbakhsh","doi":"10.4156/JCIT.VOL5.ISSUE9.21","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.21","url":null,"abstract":"With an expanding of Web services giving same functionalities, Quality of Service (QoS) is becoming an important criterion for selection of the best available service. So users need to know QoS information and the reliability of this information .This article presents a new model of reputation improved Web services discovery considering the quality of services that include a reputation administrator to allocate reputation marks to the services based on customer feedback of their efficiency. The model is based on Service Level Agreements (SLAs) to ensure the standard of the process of discovery the quality specifications of the web services and it regulates perspectives from the two parties that is not the same and provides official definitions of quality of service (QoS) characteristics such that there is no vagueness in explaining characteristics. Practically we collected the present findings on SLA modeling and we presented a broker helps quality aware service discovery using the reputation marks in a service matching, ranking and selection algorithm based on our model.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131082126","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 : 2010-11-30DOI: 10.4156/JCIT.VOL5.ISSUE9.29
Hongyuan Li, Guangjie Liu, Yue-wei Dai, Zhiquan Wang
Abstract In this paper, a secure content distribution scheme is proposed which transmits the multimedia content to users in a secure manner. In server side, the content is embedded by pseudorandom sequences (the customer’s ID) and then encrypted by another pseudorandom sequence. In user side, the content is decrypted with the some sequence as the encryption process. All the pseudorandom sequences are generated by the chaotic map under the control of secure key. The decrypted content is traceable to trace the illegally redistribution of the pirate. Theoretical and experimental results show that the scheme obtains high security of the encryption, imperceptibility and traceability. Additionally, the embedded watermarks are robustness against collusion attack.
{"title":"Secure Multimedia Distribution Based on Watermarking and Encryption","authors":"Hongyuan Li, Guangjie Liu, Yue-wei Dai, Zhiquan Wang","doi":"10.4156/JCIT.VOL5.ISSUE9.29","DOIUrl":"https://doi.org/10.4156/JCIT.VOL5.ISSUE9.29","url":null,"abstract":"Abstract In this paper, a secure content distribution scheme is proposed which transmits the multimedia content to users in a secure manner. In server side, the content is embedded by pseudorandom sequences (the customer’s ID) and then encrypted by another pseudorandom sequence. In user side, the content is decrypted with the some sequence as the encryption process. All the pseudorandom sequences are generated by the chaotic map under the control of secure key. The decrypted content is traceable to trace the illegally redistribution of the pirate. Theoretical and experimental results show that the scheme obtains high security of the encryption, imperceptibility and traceability. Additionally, the embedded watermarks are robustness against collusion attack.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132056295","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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