Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526934
N. Chandel, S. Mishra, N. Gupta, A. Shukla
The main aim of secure cloud environment for data mining to tackle huge amount of trusted data for mining and association purpose. Handling huge amount of data is better handled by cloud environment. We can handle immense amount of data in cloud environment on pay per basis. In this paper we are rendering a framework which is dynamically created by the user according to the user need and choice. After creating a secure cloud environment we then perform data mining task on cloud environment like association mining, pattern generation and pruning. Finally taking some cloud parameter we will compare the data mining performance and efficiency in secure, non-secure and non cloud environment.
{"title":"Dynamic secure cloud creation for frequent pattern mining and association","authors":"N. Chandel, S. Mishra, N. Gupta, A. Shukla","doi":"10.1109/ISSP.2013.6526934","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526934","url":null,"abstract":"The main aim of secure cloud environment for data mining to tackle huge amount of trusted data for mining and association purpose. Handling huge amount of data is better handled by cloud environment. We can handle immense amount of data in cloud environment on pay per basis. In this paper we are rendering a framework which is dynamically created by the user according to the user need and choice. After creating a secure cloud environment we then perform data mining task on cloud environment like association mining, pattern generation and pruning. Finally taking some cloud parameter we will compare the data mining performance and efficiency in secure, non-secure and non cloud environment.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129348739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526908
R. Sharma, N. Gupta, A. Kanchan
Frequency offset introduces inter-carrier interference (ICI) in the OFDM symbol. We can investigate effective method for combating the effect of ICI. Through simulations, it is shown that for larger value of normalized frequency offset weight of the desired signal component decreases while weight of the ICI component increase. ICI self cancellation scheme gives more than 15 dB CIR improvement in the larger range of normalized frequency offset. Especially for small to medium frequency offsets range the CIR improvement can reach 17 dB.
{"title":"Carrier interference ratio analysis of efficient inter carrier interference cancellation scheme for OFDM system","authors":"R. Sharma, N. Gupta, A. Kanchan","doi":"10.1109/ISSP.2013.6526908","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526908","url":null,"abstract":"Frequency offset introduces inter-carrier interference (ICI) in the OFDM symbol. We can investigate effective method for combating the effect of ICI. Through simulations, it is shown that for larger value of normalized frequency offset weight of the desired signal component decreases while weight of the ICI component increase. ICI self cancellation scheme gives more than 15 dB CIR improvement in the larger range of normalized frequency offset. Especially for small to medium frequency offsets range the CIR improvement can reach 17 dB.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116591302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526936
A. Patel, J. Patel
Classification of the unknown dataset can be obtained by several methods. Ensemble classifier methods are proved to be the better for classification. Learn++, An incremental learning algorithm, which allows supervised classification algorithms to learn from new data without forgetting previously acquired knowledge even when the previously used data is no longer available. Learn++ suffers from inherent “out-voting problem when asked to learn new classes, which causes it to generate an unnecessarily large number of classifiers. Also, in Learn++, distribution update rule based on performance of compound hypothesis, for selecting training set of the next weak classifier, it allows an efficient incremental learning capability when new classes are introduced. Whereas, in AdaBoost distribution update rule based on individual hypothesis guarantees robustness and prevents performance deterioration. In proposed algorithm, it combines the advantages of both the methods. It provides weight updating rule based on a combination of individual hypothesis and compound hypothesis which provide optimum performance level.
{"title":"Ensemble systems and incremental learning","authors":"A. Patel, J. Patel","doi":"10.1109/ISSP.2013.6526936","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526936","url":null,"abstract":"Classification of the unknown dataset can be obtained by several methods. Ensemble classifier methods are proved to be the better for classification. Learn++, An incremental learning algorithm, which allows supervised classification algorithms to learn from new data without forgetting previously acquired knowledge even when the previously used data is no longer available. Learn++ suffers from inherent “out-voting problem when asked to learn new classes, which causes it to generate an unnecessarily large number of classifiers. Also, in Learn++, distribution update rule based on performance of compound hypothesis, for selecting training set of the next weak classifier, it allows an efficient incremental learning capability when new classes are introduced. Whereas, in AdaBoost distribution update rule based on individual hypothesis guarantees robustness and prevents performance deterioration. In proposed algorithm, it combines the advantages of both the methods. It provides weight updating rule based on a combination of individual hypothesis and compound hypothesis which provide optimum performance level.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127419374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526890
J. C. Saldanha, T. Ananthakrishna, R. Pinto
It is possible to identify voice disorders using certain features of speech signals. A complementary technique could be acoustic analysis of the speech signal, which is shown to be a potentially useful tool to detect voice diseases. The focus of this study is to formulate a speech parameter estimation algorithm for analysis and detection of vocal fold pathology and also bring out scale to measure severity of the disease. The speech processing algorithm proposed estimates features necessary to formulate a stochastic model to characterize healthy and pathology conditions from speech recordings. Speech signal features such as MFCC are extracted from acoustic analysis of voiced speech of normal and pathological subjects. A principal component analysis with minimum distance classifier (PCA+MDC) and linear discriminant analysis (LDA) classifier are designed and the classification results have been reported.
{"title":"Vocal fold pathology assessment using PCA and LDA","authors":"J. C. Saldanha, T. Ananthakrishna, R. Pinto","doi":"10.1109/ISSP.2013.6526890","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526890","url":null,"abstract":"It is possible to identify voice disorders using certain features of speech signals. A complementary technique could be acoustic analysis of the speech signal, which is shown to be a potentially useful tool to detect voice diseases. The focus of this study is to formulate a speech parameter estimation algorithm for analysis and detection of vocal fold pathology and also bring out scale to measure severity of the disease. The speech processing algorithm proposed estimates features necessary to formulate a stochastic model to characterize healthy and pathology conditions from speech recordings. Speech signal features such as MFCC are extracted from acoustic analysis of voiced speech of normal and pathological subjects. A principal component analysis with minimum distance classifier (PCA+MDC) and linear discriminant analysis (LDA) classifier are designed and the classification results have been reported.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129964470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526918
Krunal N. Patel, H. Shah
In wireless communication systems which uses OFDM as modulation technique, the prevailing trend is the dynamic assignment of resources like subcarrier and number of bits per subcarrier. In multiuser scenario, received signal strength of each user varies with the distance from the base station. The algorithms which target to maximize throughput, assigns more resources to the better channel conditioned user which may result into unfair distribution of resources. Attempts to achieve fairness sacrifice system throughput. The proportional fairness algorithm nicely handles this trade off. We have examined performance of the proportional fairness algorithm in realistic conditions with large numbers of users with scattered locations throughout the cell. Furthermore, this algorithm is examined with appropriate power allocation on each subcarrier along with subcarrier allocation. Comparison of proportional fairness algorithm is carried out with sum rate maximization algorithm. We have considered realistic conditions with variable distance from base station and LTE standard.
{"title":"Subcarrier and power allocation with proportional fairness algorithm for LTE system","authors":"Krunal N. Patel, H. Shah","doi":"10.1109/ISSP.2013.6526918","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526918","url":null,"abstract":"In wireless communication systems which uses OFDM as modulation technique, the prevailing trend is the dynamic assignment of resources like subcarrier and number of bits per subcarrier. In multiuser scenario, received signal strength of each user varies with the distance from the base station. The algorithms which target to maximize throughput, assigns more resources to the better channel conditioned user which may result into unfair distribution of resources. Attempts to achieve fairness sacrifice system throughput. The proportional fairness algorithm nicely handles this trade off. We have examined performance of the proportional fairness algorithm in realistic conditions with large numbers of users with scattered locations throughout the cell. Furthermore, this algorithm is examined with appropriate power allocation on each subcarrier along with subcarrier allocation. Comparison of proportional fairness algorithm is carried out with sum rate maximization algorithm. We have considered realistic conditions with variable distance from base station and LTE standard.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124321672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526874
M. Kulkarni, D. Kulkarni
Due to the increase in the usage of computers and internet, the demand for higher transmission speed and lower storage is increasing as well. This leads to the necessity fo r video compression. Image encoding is framed upon the fractal coding method. This method is based on the assumption that image redundancy can be efficiently explored through self-block transformability. It has shown good results in producing resolution independent, high-fidelity images. The decoding process, which has low complexity, also suggests use in real time applications. The high encoding time has unfortunately produced discouraging results. In this paper, a new approach is depicted where a comparison of range blocks with the domain pool is implemented using a parallel approach.
{"title":"Adaptive fractal intra-frame video coding technique using parallel GPU environment","authors":"M. Kulkarni, D. Kulkarni","doi":"10.1109/ISSP.2013.6526874","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526874","url":null,"abstract":"Due to the increase in the usage of computers and internet, the demand for higher transmission speed and lower storage is increasing as well. This leads to the necessity fo r video compression. Image encoding is framed upon the fractal coding method. This method is based on the assumption that image redundancy can be efficiently explored through self-block transformability. It has shown good results in producing resolution independent, high-fidelity images. The decoding process, which has low complexity, also suggests use in real time applications. The high encoding time has unfortunately produced discouraging results. In this paper, a new approach is depicted where a comparison of range blocks with the domain pool is implemented using a parallel approach.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"2 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113932728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526902
A. Bhavsar
We propose a method for super-resolution of range image. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we build upon a recent approach which reconstructs dense range images from sparse range data. We notice certain shortcomings of this approach and propose some improvements, particularly, to address the super-resolution problem. Our method only uses a single colour image in addition to the range observation in the super-resolution process. Using the proposed approach, we demonstrate super-resolution results for large factors (e.g. 4 and 8) with good localization and accuracy.
{"title":"Range image super-resolution via reconstruction of sparse range data","authors":"A. Bhavsar","doi":"10.1109/ISSP.2013.6526902","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526902","url":null,"abstract":"We propose a method for super-resolution of range image. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we build upon a recent approach which reconstructs dense range images from sparse range data. We notice certain shortcomings of this approach and propose some improvements, particularly, to address the super-resolution problem. Our method only uses a single colour image in addition to the range observation in the super-resolution process. Using the proposed approach, we demonstrate super-resolution results for large factors (e.g. 4 and 8) with good localization and accuracy.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131371251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526938
Sahil Shaikh, B. Lahiri, G. Bhatt, N. Raja
In this paper, innovative method is proposed for number plate recognition. It uses series of image manipulations to recognize number plates. It uses 4-6 algorithms in order to do the same. For plate localization, several traditional images processing techniques are used. Techniques such as image enhancement, unsharp masking, edge detection, filtering and component analysis each plays a role in the extraction process. For character segmentation, connected components are extracted as individual number plate characters. Template Matching is in charge of the Optical Character Recognition.
{"title":"A novel approach for automatic number plate recognition","authors":"Sahil Shaikh, B. Lahiri, G. Bhatt, N. Raja","doi":"10.1109/ISSP.2013.6526938","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526938","url":null,"abstract":"In this paper, innovative method is proposed for number plate recognition. It uses series of image manipulations to recognize number plates. It uses 4-6 algorithms in order to do the same. For plate localization, several traditional images processing techniques are used. Techniques such as image enhancement, unsharp masking, edge detection, filtering and component analysis each plays a role in the extraction process. For character segmentation, connected components are extracted as individual number plate characters. Template Matching is in charge of the Optical Character Recognition.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116889339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526868
M. Mistry, D. Shah, P. Pathak, Abu Sarwar Zamani
The paper presents a business scenario showing how web services are used as multi agents for communication. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Healthcare domain is one domain where several complex issues need to be addressed. Multi agents can be useful to solve such complex scenario where minimal human interaction is required. In this paper we attempt to test the usefulness of Web Services in health care domain by developing an application. This paper also shows Multiple Agents have been created for different operations. Agent based approach has created new paradigm for developing complex systems by exchanging messages by autonomous mode.
{"title":"Utilization of web services as multi agents in healthcare system","authors":"M. Mistry, D. Shah, P. Pathak, Abu Sarwar Zamani","doi":"10.1109/ISSP.2013.6526868","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526868","url":null,"abstract":"The paper presents a business scenario showing how web services are used as multi agents for communication. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Healthcare domain is one domain where several complex issues need to be addressed. Multi agents can be useful to solve such complex scenario where minimal human interaction is required. In this paper we attempt to test the usefulness of Web Services in health care domain by developing an application. This paper also shows Multiple Agents have been created for different operations. Agent based approach has created new paradigm for developing complex systems by exchanging messages by autonomous mode.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124017507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-03-01DOI: 10.1109/ISSP.2013.6526883
J. Parmar, S. Patil
Removal of noise is an important step in the image restoration process, but denoising of image remains a challenging problem in recent research associate with image processing. Denoising is used to remove the noise from corrupted image, while retaining the edges and other detailed features as much as possible. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. In this paper, to find out denoised image the modified denoising method and the local adaptive wavelet image denoising method can be used. The noisy image is denoised by modified denoising method which is based on wavelet domain and spatial domain and the local adaptive wavelet image denoising method which is based on wavelet domain. In this paper, we have evaluated and compared performances of modified denoising method and the local adaptive wavelet image denoising method. These methods are compared with other based on PSNR (Peak signal to noise ratio) between original image and noisy image and PSNR between original image and denoised image. Simulation and experiment results for an image demonstrate that RMSE of the local adaptive wavelet image denoising method is least as compare to modified denoising method and the PSNR of the local adaptive wavelet image denoising method is high than other method. Therefore, the image after denoising has a better visual effect. In this paper, these two methods are implemented by using MATLAB for denoising of image.
{"title":"Performance evaluation and comparison of modified denoising method and the local adaptive wavelet image denoising method","authors":"J. Parmar, S. Patil","doi":"10.1109/ISSP.2013.6526883","DOIUrl":"https://doi.org/10.1109/ISSP.2013.6526883","url":null,"abstract":"Removal of noise is an important step in the image restoration process, but denoising of image remains a challenging problem in recent research associate with image processing. Denoising is used to remove the noise from corrupted image, while retaining the edges and other detailed features as much as possible. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. In this paper, to find out denoised image the modified denoising method and the local adaptive wavelet image denoising method can be used. The noisy image is denoised by modified denoising method which is based on wavelet domain and spatial domain and the local adaptive wavelet image denoising method which is based on wavelet domain. In this paper, we have evaluated and compared performances of modified denoising method and the local adaptive wavelet image denoising method. These methods are compared with other based on PSNR (Peak signal to noise ratio) between original image and noisy image and PSNR between original image and denoised image. Simulation and experiment results for an image demonstrate that RMSE of the local adaptive wavelet image denoising method is least as compare to modified denoising method and the PSNR of the local adaptive wavelet image denoising method is high than other method. Therefore, the image after denoising has a better visual effect. In this paper, these two methods are implemented by using MATLAB for denoising of image.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"666 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121994541","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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