Pub Date : 2011-11-03DOI: 10.1109/RAICS.2011.6069397
U. Prakash, Yogavardhanaswamy G.N, S. L. Ajit prasad, H. Ravindra, T. Rajan
In recent years, the utilization of metal matrix composites (MMC) materials in many engineering fields has increased predominantly. The need for accurate machining of these composites has also increased enormously. Despite the recent developments in the near net shape manufacture, composite parts often require post-mold machining to meet dimensional tolerances, surface quality and other functional requirements. In general 70% of the components need machining to attain the final shape. In the present work, the tool wear has been studied in this paper by turning the composite bars using HSS and Carbide tools. The paper presents the results of experimental investigation machinability properties of silicon carbide particle (SiC-p) reinforced aluminum metal matrix composite. The effect of machining parameters, e.g. cutting speed, feed rate and depth of cut on tool wear and surface roughness was studied. Machinability properties of the selected material were studied using HSS and Carbide tool material; surface roughness was generally affected by feed rate and cutting speed. Hence the tool wear were measured at different speed and feed conditions. Experimental data collected are tested with Multiple Regression Analysis. On completion of the experimental test, multiple regression analysis is used to predict the wear behavior of the system under any condition within the operating range.
{"title":"Tool wear prediction by Regression Analysis in turning A356 with 10% SiC","authors":"U. Prakash, Yogavardhanaswamy G.N, S. L. Ajit prasad, H. Ravindra, T. Rajan","doi":"10.1109/RAICS.2011.6069397","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069397","url":null,"abstract":"In recent years, the utilization of metal matrix composites (MMC) materials in many engineering fields has increased predominantly. The need for accurate machining of these composites has also increased enormously. Despite the recent developments in the near net shape manufacture, composite parts often require post-mold machining to meet dimensional tolerances, surface quality and other functional requirements. In general 70% of the components need machining to attain the final shape. In the present work, the tool wear has been studied in this paper by turning the composite bars using HSS and Carbide tools. The paper presents the results of experimental investigation machinability properties of silicon carbide particle (SiC-p) reinforced aluminum metal matrix composite. The effect of machining parameters, e.g. cutting speed, feed rate and depth of cut on tool wear and surface roughness was studied. Machinability properties of the selected material were studied using HSS and Carbide tool material; surface roughness was generally affected by feed rate and cutting speed. Hence the tool wear were measured at different speed and feed conditions. Experimental data collected are tested with Multiple Regression Analysis. On completion of the experimental test, multiple regression analysis is used to predict the wear behavior of the system under any condition within the operating range.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115564389","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069441
M. Majumder, B. Kaushik, S. Manhas
Multi-walled carbon nanotubes (MWNT) have provided potentially attractive solution over single-wall carbon nanotube (SWNT) bundles at current very large scale integration (VLSI) technologies. This paper presents a comprehensive analysis of propagation delay for both MWNT and SWNT bundles at different interconnect lengths (global) and shows a comparison of equivalent number of SWNTs in bundle and shells in MWNTs for specified propagation delays and lengths. It has been observed that irrespective of the type of CNTs, propagation delay increases with interconnect lengths. For same propagation delay performance, the number of SWNTs required in a bundle are found to be more than number of shells in MWNT for a given interconnect length.
{"title":"Comparison of propagation delay characteristics for single-walled CNT bundle and multiwalled CNT in global VLSI interconnects","authors":"M. Majumder, B. Kaushik, S. Manhas","doi":"10.1109/RAICS.2011.6069441","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069441","url":null,"abstract":"Multi-walled carbon nanotubes (MWNT) have provided potentially attractive solution over single-wall carbon nanotube (SWNT) bundles at current very large scale integration (VLSI) technologies. This paper presents a comprehensive analysis of propagation delay for both MWNT and SWNT bundles at different interconnect lengths (global) and shows a comparison of equivalent number of SWNTs in bundle and shells in MWNTs for specified propagation delays and lengths. It has been observed that irrespective of the type of CNTs, propagation delay increases with interconnect lengths. For same propagation delay performance, the number of SWNTs required in a bundle are found to be more than number of shells in MWNT for a given interconnect length.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122320212","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069366
Mohd Azman Abdul Latif, N. B. Z. Zain Ali, F. Hussin
Recent submicron process technology scaling leads the urgency to build an efficient methodology of characterizing and modeling the process variation effect, for example, the threshold voltage, Vt. This is one of the key process parameters that must be extensively modeled and validated for accurate circuit performance. Furthermore, this requirement is even much more critical for analog applications which demand an ability to match devices precisely. Analog circuits use larger device dimensions as compared to digital circuits in order to minimize the process variation implication. This has led Negative Bias Temperature Instability (NBTI) to be the most performance limiter compared to the rest of reliability mechanisms. This reliability sensitivity is even more challenging as most of the circuit blocks (digital and analog) are fabricated on the same chip for system-on-chip (SoC) applications. This paper will describe in detail the actions taken to minimize impact to customers and will show how important proper aging simulations to be conducted with the right combination of process, voltage, temperature (PVT) and coupling/timing to occur due to process variation effect beyond specifications on analog differential amplifier (diffamp) circuits in SoC products.
{"title":"A case study of process-variation effect to SoC analog circuits","authors":"Mohd Azman Abdul Latif, N. B. Z. Zain Ali, F. Hussin","doi":"10.1109/RAICS.2011.6069366","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069366","url":null,"abstract":"Recent submicron process technology scaling leads the urgency to build an efficient methodology of characterizing and modeling the process variation effect, for example, the threshold voltage, Vt. This is one of the key process parameters that must be extensively modeled and validated for accurate circuit performance. Furthermore, this requirement is even much more critical for analog applications which demand an ability to match devices precisely. Analog circuits use larger device dimensions as compared to digital circuits in order to minimize the process variation implication. This has led Negative Bias Temperature Instability (NBTI) to be the most performance limiter compared to the rest of reliability mechanisms. This reliability sensitivity is even more challenging as most of the circuit blocks (digital and analog) are fabricated on the same chip for system-on-chip (SoC) applications. This paper will describe in detail the actions taken to minimize impact to customers and will show how important proper aging simulations to be conducted with the right combination of process, voltage, temperature (PVT) and coupling/timing to occur due to process variation effect beyond specifications on analog differential amplifier (diffamp) circuits in SoC products.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128986263","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069445
J. David, A. Sukesh Kumar
Glaucoma, the second leading cause of blindness is a disease characterized by loss of neural tissue over time. The key issue in dealing with this disease is early detection of its presence or progression, with the rapid initiation or advancement of appropriate treatment. Quantitative analysis of Retinal Nerve Fiber Layer (RNFL) via image processing of fundus images plays a major role in its early detection. The disease is characterized by the progressive degeneration of optic nerve fibers showing a distinct image of the optic nerve head. Glaucoma leads to (i) structural changes of the optic nerve head (ONH) and the nerve fiber layer and (ii) a simultaneous functional failure of the visual field. This work aims to develop a system which will recognize the presence of glaucoma by the changes in the fundus image of an eye of a person and automatically quantify the RNFL defect using image processing techniques which aids in the diagnosis of glaucoma disease. Input image of the system will be the fundus image of an eye saved in bitmap or JPEG format or a real time one. Results show that the performance of our system is appreciable with the clinical diagnosis. In the future, the system can provide a first low-priced glaucoma indication in order to possibly reduce the amount of false positives misrouted to the cost-intensive elaborate clinical investigations.
{"title":"Early detection of retinal nerve fiber layer defects using fundus image processing","authors":"J. David, A. Sukesh Kumar","doi":"10.1109/RAICS.2011.6069445","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069445","url":null,"abstract":"Glaucoma, the second leading cause of blindness is a disease characterized by loss of neural tissue over time. The key issue in dealing with this disease is early detection of its presence or progression, with the rapid initiation or advancement of appropriate treatment. Quantitative analysis of Retinal Nerve Fiber Layer (RNFL) via image processing of fundus images plays a major role in its early detection. The disease is characterized by the progressive degeneration of optic nerve fibers showing a distinct image of the optic nerve head. Glaucoma leads to (i) structural changes of the optic nerve head (ONH) and the nerve fiber layer and (ii) a simultaneous functional failure of the visual field. This work aims to develop a system which will recognize the presence of glaucoma by the changes in the fundus image of an eye of a person and automatically quantify the RNFL defect using image processing techniques which aids in the diagnosis of glaucoma disease. Input image of the system will be the fundus image of an eye saved in bitmap or JPEG format or a real time one. Results show that the performance of our system is appreciable with the clinical diagnosis. In the future, the system can provide a first low-priced glaucoma indication in order to possibly reduce the amount of false positives misrouted to the cost-intensive elaborate clinical investigations.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129521781","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069382
R. Archana, A. Unnikrishnan, R. Gopikakumari, M. Rajesh
The identification of nonlinear systems with chaotic behavior using a neural network based computational algorithm is presented.. A neural network is trained on the measured output data of the actual system. The network parameters viz. the neural network weights are estimated using the Elman back propagation algorithm .Further, The Rossler and the Chen chaotic systems are used for simulation. The simulation results show that the ANN trained with back propagation algorithm performs very well and give exact reproduction of the output time series and states, as generated from the dynamical equations. The Kaplan Yorke dimensions and the Lyapunov exponents of the model are calculated.
{"title":"An intelligent computational algorithm based on neural networks for the identification of chaotic systems","authors":"R. Archana, A. Unnikrishnan, R. Gopikakumari, M. Rajesh","doi":"10.1109/RAICS.2011.6069382","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069382","url":null,"abstract":"The identification of nonlinear systems with chaotic behavior using a neural network based computational algorithm is presented.. A neural network is trained on the measured output data of the actual system. The network parameters viz. the neural network weights are estimated using the Elman back propagation algorithm .Further, The Rossler and the Chen chaotic systems are used for simulation. The simulation results show that the ANN trained with back propagation algorithm performs very well and give exact reproduction of the output time series and states, as generated from the dynamical equations. The Kaplan Yorke dimensions and the Lyapunov exponents of the model are calculated.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127774692","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069314
Mahantesh P Mattad, H. Guhilot, R. Kamat
We present an area efficient Time to Digital Converter (TDC) yielding a high resolution of nearly 10ps. The TDC architecture reported in this paper comprises of coarse measurement using system clock and two controllable oscillators for fine resolution measurement. The reported improved resolution is attributed to the difference in their frequencies. One of the main features of the implementation is its prototyping on a low-cost FPGA.
{"title":"Area efficient time to digital converter (TDC) architecture with double ring-oscillator technique on FPGA for fluorescence measurement application","authors":"Mahantesh P Mattad, H. Guhilot, R. Kamat","doi":"10.1109/RAICS.2011.6069314","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069314","url":null,"abstract":"We present an area efficient Time to Digital Converter (TDC) yielding a high resolution of nearly 10ps. The TDC architecture reported in this paper comprises of coarse measurement using system clock and two controllable oscillators for fine resolution measurement. The reported improved resolution is attributed to the difference in their frequencies. One of the main features of the implementation is its prototyping on a low-cost FPGA.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128077306","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069297
R. Hari, M. Wilscy
Video summarization is the main aspect in video content management system, by which users can easily search the video content for a particular data or scene. Video summarization is the process of selecting a set of significant frames called key frames to represent original video in the form of a short video clip. In this work, individual frames of the video represented using Contourlet Transform are analyzed structurally to detect the scene changes, which will result in clustering of frames in the video. Finally Renyi Entropy can be used to extract most relevant frames from clusters to construct full motion summarized video.
{"title":"Video summarization by Contourlet Transform and structural similarity","authors":"R. Hari, M. Wilscy","doi":"10.1109/RAICS.2011.6069297","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069297","url":null,"abstract":"Video summarization is the main aspect in video content management system, by which users can easily search the video content for a particular data or scene. Video summarization is the process of selecting a set of significant frames called key frames to represent original video in the form of a short video clip. In this work, individual frames of the video represented using Contourlet Transform are analyzed structurally to detect the scene changes, which will result in clustering of frames in the video. Finally Renyi Entropy can be used to extract most relevant frames from clusters to construct full motion summarized video.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126391436","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069364
R. Harikumar, T. Vijaykumar, C. Palanisamy
The objective of this paper is to compare the performance of Hierarchical Soft (max-min) Decision Trees and Support Vector Machine (SVM) in optimization of fuzzy outputs for the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical Soft Decision Tree (HDT post classifiers with max-min criteria of four types) and Support Vector Machine (SVM) are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patient's risk level. The efficacy of the above methods is compared based on the bench mark parameters such as Performance Index (PI), and Quality Value (QV).
{"title":"Performance analysis of fuzzy techniques hierarchical aggregation functions decision trees and Support Vector Machine (SVM)for the classification of epilepsy risk levels from EEG signals","authors":"R. Harikumar, T. Vijaykumar, C. Palanisamy","doi":"10.1109/RAICS.2011.6069364","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069364","url":null,"abstract":"The objective of this paper is to compare the performance of Hierarchical Soft (max-min) Decision Trees and Support Vector Machine (SVM) in optimization of fuzzy outputs for the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical Soft Decision Tree (HDT post classifiers with max-min criteria of four types) and Support Vector Machine (SVM) are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patient's risk level. The efficacy of the above methods is compared based on the bench mark parameters such as Performance Index (PI), and Quality Value (QV).","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125893036","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069372
T. Sarma, P. Viswanath, B. Reddy
In unsupervised classification, kernel k-means clustering method has been shown to perform better than conventional k-means clustering method in identifying non-isotropic clusters in a data set. The space and time requirements of this method are O(n2), where n is the data set size. The paper proposes a two stage hybrid approach to speed-up the kernel k-means clustering method. In the first stage, the data set is divided in to a number of group-lets by employing a fast clustering method called leaders clustering method. Each group-let is represented by a prototype called its leader. The set of leaders, which depends on a threshold parameter, can be derived in O(n) time. The paper presents a modification to the leaders clustering method where group-lets are found in the kernel space (not in the input space), but are represented by leaders in the input space. In the second stage, kernel k-means clustering method is applied with the set of leaders to derive a partition of the set of leaders. Finally, each leader is replaced by its group to get a partition of the data set. The proposed method has time complexity of O(n+p2), where p is the leaders set size. Its space complexity is also O(n+p2). The proposed method can be easily implemented. Experimental results shows that, with a small loss of quality, the proposed method can significantly reduce the time taken than the conventional kernel k-means clustering method.
{"title":"A fast approximate kernel k-means clustering method for large data sets","authors":"T. Sarma, P. Viswanath, B. Reddy","doi":"10.1109/RAICS.2011.6069372","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069372","url":null,"abstract":"In unsupervised classification, kernel k-means clustering method has been shown to perform better than conventional k-means clustering method in identifying non-isotropic clusters in a data set. The space and time requirements of this method are O(n2), where n is the data set size. The paper proposes a two stage hybrid approach to speed-up the kernel k-means clustering method. In the first stage, the data set is divided in to a number of group-lets by employing a fast clustering method called leaders clustering method. Each group-let is represented by a prototype called its leader. The set of leaders, which depends on a threshold parameter, can be derived in O(n) time. The paper presents a modification to the leaders clustering method where group-lets are found in the kernel space (not in the input space), but are represented by leaders in the input space. In the second stage, kernel k-means clustering method is applied with the set of leaders to derive a partition of the set of leaders. Finally, each leader is replaced by its group to get a partition of the data set. The proposed method has time complexity of O(n+p2), where p is the leaders set size. Its space complexity is also O(n+p2). The proposed method can be easily implemented. Experimental results shows that, with a small loss of quality, the proposed method can significantly reduce the time taken than the conventional kernel k-means clustering method.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077663","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 : 2011-11-03DOI: 10.1109/RAICS.2011.6069356
M. Karpaka Murthy, S. Seetha, F. Pádua
The problem of classification of continuous general data for content based retrieval and describe the scheme that able to classify the audio segments based on the MPEG-7 audio descriptors and description schemes that consist of tools for indexing audio media using probabilistic sound models. The descriptors provide containers for category labels as well as data structures for quantitative information about sound content. We describe the normative tools as well as informative methods for automatic description extraction.
{"title":"Generating MPEG 7 audio descriptor for content-based retrieval","authors":"M. Karpaka Murthy, S. Seetha, F. Pádua","doi":"10.1109/RAICS.2011.6069356","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069356","url":null,"abstract":"The problem of classification of continuous general data for content based retrieval and describe the scheme that able to classify the audio segments based on the MPEG-7 audio descriptors and description schemes that consist of tools for indexing audio media using probabilistic sound models. The descriptors provide containers for category labels as well as data structures for quantitative information about sound content. We describe the normative tools as well as informative methods for automatic description extraction.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125996224","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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