Pub Date : 2010-03-02DOI: 10.1109/MCIT.2010.5444857
Khalid A. Darabkh, Backer Abu-Jaradeh
Sequential decoding is one of the most important convolutional code's algorithms that can work in intermediate hops efficiently. It is of interest since its error detection and correction techniques are considered to be variable and dependent to channel state. In this paper, we conduct a new buffering study over intermediate hops' systems that employ sequential decoding algorithms. As a result of that, we find a closed form expression for the expected buffer occupancy under different assumptions. Our study can be applicable to any network environments that are affected by noise which consequently leads to high packet error rate. The results are presented and explained when considering different system's parameters.
{"title":"Buffering study over intermediate hops including packet retransmission","authors":"Khalid A. Darabkh, Backer Abu-Jaradeh","doi":"10.1109/MCIT.2010.5444857","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444857","url":null,"abstract":"Sequential decoding is one of the most important convolutional code's algorithms that can work in intermediate hops efficiently. It is of interest since its error detection and correction techniques are considered to be variable and dependent to channel state. In this paper, we conduct a new buffering study over intermediate hops' systems that employ sequential decoding algorithms. As a result of that, we find a closed form expression for the expected buffer occupancy under different assumptions. Our study can be applicable to any network environments that are affected by noise which consequently leads to high packet error rate. The results are presented and explained when considering different system's parameters.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116576078","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444856
Leijia Wu, Abdallah E. AL Sabbagh, K. Sandrasegaran, M. Elkashlan
In order to support the conceptual development of Radio Access Technology (RAT) selection algorithms, the theory of Markov model has been used. Performance metrics can be derived from the steady state probabilities of a Markov model. This paper extends a User Level Markov model for a three colocated RATs system from existing two co-located RATs Markov models. The service based RAT selection algorithm has been studied using the proposed Markov model. Numerical results obtained from the proposed Markov model are presented.
{"title":"A User Level Markov model for service based CRRM algorithm","authors":"Leijia Wu, Abdallah E. AL Sabbagh, K. Sandrasegaran, M. Elkashlan","doi":"10.1109/MCIT.2010.5444856","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444856","url":null,"abstract":"In order to support the conceptual development of Radio Access Technology (RAT) selection algorithms, the theory of Markov model has been used. Performance metrics can be derived from the steady state probabilities of a Markov model. This paper extends a User Level Markov model for a three colocated RATs system from existing two co-located RATs Markov models. The service based RAT selection algorithm has been studied using the proposed Markov model. Numerical results obtained from the proposed Markov model are presented.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133682489","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444860
Y. R. Fatmehsari, A. Ghahari, R. Zoroofi
Driver support systems (DSS) of intelligent vehicles analyze the image of road scenes captured by camera and detect the road signs. Then by recognizing the type of traffic sign, it can warn the driver. Most of them use the HIS color space for detection of road signs. But in this paper the YCbCr color space is used. This paper proposes a new method for both detection and classification of red road signs. The strategy consists of three steps. In the first step the input image has been transferred from the RGB color space to the YCbCr color space and the red pixels are extracted. Then the road sign object is detected from those that had been extracted as red objects. In the second step this road sign image must be convolved with a bank of Gabor wavelets and extract the feature vectors for classification. Finally in the third step these feature vectors are classified by a hybrid classifier that is composed of one-vs.-rest support vector machines (OVR SVMs) and naive bayes (NBs) classifier. The proposed method was implemented for classification of four classes of red road signs and achieved the accuracy of 93.1%. Moreover the proposed method is robust against the translation, rotation, and scale.
{"title":"Gabor wavelet for road sign detection and recognition using a hybrid classifier","authors":"Y. R. Fatmehsari, A. Ghahari, R. Zoroofi","doi":"10.1109/MCIT.2010.5444860","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444860","url":null,"abstract":"Driver support systems (DSS) of intelligent vehicles analyze the image of road scenes captured by camera and detect the road signs. Then by recognizing the type of traffic sign, it can warn the driver. Most of them use the HIS color space for detection of road signs. But in this paper the YCbCr color space is used. This paper proposes a new method for both detection and classification of red road signs. The strategy consists of three steps. In the first step the input image has been transferred from the RGB color space to the YCbCr color space and the red pixels are extracted. Then the road sign object is detected from those that had been extracted as red objects. In the second step this road sign image must be convolved with a bank of Gabor wavelets and extract the feature vectors for classification. Finally in the third step these feature vectors are classified by a hybrid classifier that is composed of one-vs.-rest support vector machines (OVR SVMs) and naive bayes (NBs) classifier. The proposed method was implemented for classification of four classes of red road signs and achieved the accuracy of 93.1%. Moreover the proposed method is robust against the translation, rotation, and scale.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115057437","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444842
Zohreh Yaghoubi, Morteza Eliasi, K. Faez, Ardalan Eliasi
Biometrics based personal identification is regarded as an effective method for automatic identification, with a high confidence coefficient. A multimodal biometric system consolidates the evidence presented by multiple biometric sources and typically provides better recognition performance compared to systems based on a single biometric modality. So in this paper we use combination of Face and Ear characteristic to individual's authentication. In our approach, features extracted using HMAX model are translation and scale-invariant. Then we applied Support vector machine (SVM) and K-nearest neighbor (KNN) classifiers to distinguish the classes. In fusion stage we use matching-score level. Experimental results showed 96% accuracy rate on ORL Face database and 94% accuracy rate on USTB Ear database; however we achieve 98% accuracy rate on Face and Ear multimodal biometric.
{"title":"Multimodal biometric recognition inspired by visual cortex and Support vector machine classifier","authors":"Zohreh Yaghoubi, Morteza Eliasi, K. Faez, Ardalan Eliasi","doi":"10.1109/MCIT.2010.5444842","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444842","url":null,"abstract":"Biometrics based personal identification is regarded as an effective method for automatic identification, with a high confidence coefficient. A multimodal biometric system consolidates the evidence presented by multiple biometric sources and typically provides better recognition performance compared to systems based on a single biometric modality. So in this paper we use combination of Face and Ear characteristic to individual's authentication. In our approach, features extracted using HMAX model are translation and scale-invariant. Then we applied Support vector machine (SVM) and K-nearest neighbor (KNN) classifiers to distinguish the classes. In fusion stage we use matching-score level. Experimental results showed 96% accuracy rate on ORL Face database and 94% accuracy rate on USTB Ear database; however we achieve 98% accuracy rate on Face and Ear multimodal biometric.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"44 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113936867","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444846
S. Olatunji, A. Selamat, A. Raheem
This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties such as bubble-point pressure and oil formation volume factor is important in the primary and subsequent development of an oil field. In this work, we develop Sensitivity Based Linear Learning method prediction model for PVT properties using two distinct databases, while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. Empirical results from simulation show that the newly developed SBLLM based model produced promising results and outperforms others, particularly in terms of stability and consistency of prediction.
{"title":"Prediction model of reservoir fluids properties using Sensitivity Based Linear Learning method","authors":"S. Olatunji, A. Selamat, A. Raheem","doi":"10.1109/MCIT.2010.5444846","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444846","url":null,"abstract":"This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties such as bubble-point pressure and oil formation volume factor is important in the primary and subsequent development of an oil field. In this work, we develop Sensitivity Based Linear Learning method prediction model for PVT properties using two distinct databases, while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. Empirical results from simulation show that the newly developed SBLLM based model produced promising results and outperforms others, particularly in terms of stability and consistency of prediction.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115170866","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444861
Tzu-Jung Yao, Quincy Wu
Confused Document Encrypting Scheme is a technique for data hiding. It involves concealing the secret text inside the cheating text. If the cheating text is intercepted, the secret text may still be undetected.
{"title":"On the study of overhead reduction for Confused Document Encrypting Schemes","authors":"Tzu-Jung Yao, Quincy Wu","doi":"10.1109/MCIT.2010.5444861","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444861","url":null,"abstract":"Confused Document Encrypting Scheme is a technique for data hiding. It involves concealing the secret text inside the cheating text. If the cheating text is intercepted, the secret text may still be undetected.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115696375","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444848
H. Sajedi, M. Jamzad
Due to the various contents of images, the stego images produced by a steganography method may have different levels of undetectability against steganalyzers. In other words, a steganography method may cause less detectable statistical artifacts on some images compared to other images. In this paper, we analyze different features of images to find the similarity between proper cover images for each steganography method. Similarity between images is modeled in form of fuzzy if-then rules using an evolutionary algorithm. Subsequently for hiding secret data in a cover image, we suggest a reliable steganography method that results in an undetectable stego image against most recently reported steganalysis methods. Experimental results show the efficiency of the proposed method in improving the security of stego images.
{"title":"Selecting a reliable steganography method","authors":"H. Sajedi, M. Jamzad","doi":"10.1109/MCIT.2010.5444848","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444848","url":null,"abstract":"Due to the various contents of images, the stego images produced by a steganography method may have different levels of undetectability against steganalyzers. In other words, a steganography method may cause less detectable statistical artifacts on some images compared to other images. In this paper, we analyze different features of images to find the similarity between proper cover images for each steganography method. Similarity between images is modeled in form of fuzzy if-then rules using an evolutionary algorithm. Subsequently for hiding secret data in a cover image, we suggest a reliable steganography method that results in an undetectable stego image against most recently reported steganalysis methods. Experimental results show the efficiency of the proposed method in improving the security of stego images.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132015900","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444850
Siril Yella, Asif Rahman, M. Dougherty
This paper summarises the results of using a pattern recognition approach for classifying the condition of wooden railway sleepers. Railway sleeper inspections are currently done manually; visual inspection being the most common approach, with some deeper examination using an axe to judge the condition. Digital images of the sleepers were acquired to compensate for the human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features such as number of cracks, crack length etc have been extracted. Finally a pattern recognition and classification approach has been adopted to further classify the condition of the sleeper into classes (good or bad). A Support Vector Machine (SVM) using a Gaussian kernel has achieved good classification rate (86%) in the current case.
{"title":"Pattern recognition for classifying the condition of wooden railway sleepers","authors":"Siril Yella, Asif Rahman, M. Dougherty","doi":"10.1109/MCIT.2010.5444850","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444850","url":null,"abstract":"This paper summarises the results of using a pattern recognition approach for classifying the condition of wooden railway sleepers. Railway sleeper inspections are currently done manually; visual inspection being the most common approach, with some deeper examination using an axe to judge the condition. Digital images of the sleepers were acquired to compensate for the human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features such as number of cracks, crack length etc have been extracted. Finally a pattern recognition and classification approach has been adopted to further classify the condition of the sleeper into classes (good or bad). A Support Vector Machine (SVM) using a Gaussian kernel has achieved good classification rate (86%) in the current case.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"43 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132236901","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444865
Masomeh Azimzadeh, Alireza Yari, M. Kargar
Since Word Wide Web contains large set of data in different languages, retrieving language specific information creates a new challenge in information retrieval called language specific crawling. In this paper, a new approach is purposed for language specific crawling in which a combination of some selected content and context features of web documents have been applied. This approach has been implemented for Persian language and evaluated in Iranian web domain. The evaluation results show how this approach can improve the performance of crawling from speed and coverage points of view.
{"title":"Language specific crawling based on web pages features","authors":"Masomeh Azimzadeh, Alireza Yari, M. Kargar","doi":"10.1109/MCIT.2010.5444865","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444865","url":null,"abstract":"Since Word Wide Web contains large set of data in different languages, retrieving language specific information creates a new challenge in information retrieval called language specific crawling. In this paper, a new approach is purposed for language specific crawling in which a combination of some selected content and context features of web documents have been applied. This approach has been implemented for Persian language and evaluated in Iranian web domain. The evaluation results show how this approach can improve the performance of crawling from speed and coverage points of view.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":" 30","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120827591","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 : 2010-03-02DOI: 10.1109/MCIT.2010.5444859
M. Saleemi, J. Lilius
This paper explores the concepts of interactive applications, their usability and system architectural aspects in interactive mobile TV. The paper evaluates application scenarios for different interactive applications that can be supported by future Mobile TV. These application scenarios has significance because they specify overall image of mobile interactive system that will be helpful for defining common application framework based on the user's perception. We conclude the paper by providing the directions for further research in the emerging area of interactive mobile TV applications.
{"title":"Interactive applications for mobile TV","authors":"M. Saleemi, J. Lilius","doi":"10.1109/MCIT.2010.5444859","DOIUrl":"https://doi.org/10.1109/MCIT.2010.5444859","url":null,"abstract":"This paper explores the concepts of interactive applications, their usability and system architectural aspects in interactive mobile TV. The paper evaluates application scenarios for different interactive applications that can be supported by future Mobile TV. These application scenarios has significance because they specify overall image of mobile interactive system that will be helpful for defining common application framework based on the user's perception. We conclude the paper by providing the directions for further research in the emerging area of interactive mobile TV applications.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"41 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132604347","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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