Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745496
A. Biswas, Goutham Pilla, B. R. Tamma
Onroad distance calculation between two geographical points is an integral part of various Global Positioning System (GPS) based Intelligent Transportation Systems (ITS) applications. We have found that mere calculating the distance between two geographical points without giving importance to geographical information of the road, such as curves can lead to under estimation of the distance calculated, cause of which we refer to as the “ Displacement problem “. In this paper, we propose the methodology of Microsegmenting to overcome the Displacement Problem. To validate the proposed method and to quantify improvement over the existing technique of distance calculation we conduct experiments using real-world GPS traces from cities: Hyderabad, India and Chicago, USA. The experimental results show a significant improvement in distance estimation over existing technique. The significance of the improvement can be visualized by the fact that, theoretically this improvement in distance calculation can improve the travel time prediction, an important ITS applications, by an average of 22 seconds (approx.) between each pair of traces.
{"title":"Microsegmenting: An approach for precise distance calculation for GPS based its applications","authors":"A. Biswas, Goutham Pilla, B. R. Tamma","doi":"10.1109/RAICS.2013.6745496","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745496","url":null,"abstract":"Onroad distance calculation between two geographical points is an integral part of various Global Positioning System (GPS) based Intelligent Transportation Systems (ITS) applications. We have found that mere calculating the distance between two geographical points without giving importance to geographical information of the road, such as curves can lead to under estimation of the distance calculated, cause of which we refer to as the “ Displacement problem “. In this paper, we propose the methodology of Microsegmenting to overcome the Displacement Problem. To validate the proposed method and to quantify improvement over the existing technique of distance calculation we conduct experiments using real-world GPS traces from cities: Hyderabad, India and Chicago, USA. The experimental results show a significant improvement in distance estimation over existing technique. The significance of the improvement can be visualized by the fact that, theoretically this improvement in distance calculation can improve the travel time prediction, an important ITS applications, by an average of 22 seconds (approx.) between each pair of traces.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127919585","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745475
Sukriti Jalali
Within the next decade, the major portion of Internet traffic is forecast to come from devices connected to the Internet. Ericsson™ envisions tens of billions of internet-connected devices, with 50 billion connections by 2020[1]. The volume of traffic, the kind of data and the level of meaningful interactions this will generate is something that the technology universe as well as the business world has never encountered till now. This is also poised to create tremendous challenges for enterprise architects, business analysts, design engineers and enterprise users. This paper provides insights into Machine to Machine (M2M) communication - its growth factors, possible solution areas and high level architecture. The paper delves a bit deeper into various entities involved in M2M design and development. It covers key points that architects and designers should keep in mind for effective deployment.
{"title":"M2M solutions — Design challenges and considerations","authors":"Sukriti Jalali","doi":"10.1109/RAICS.2013.6745475","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745475","url":null,"abstract":"Within the next decade, the major portion of Internet traffic is forecast to come from devices connected to the Internet. Ericsson™ envisions tens of billions of internet-connected devices, with 50 billion connections by 2020[1]. The volume of traffic, the kind of data and the level of meaningful interactions this will generate is something that the technology universe as well as the business world has never encountered till now. This is also poised to create tremendous challenges for enterprise architects, business analysts, design engineers and enterprise users. This paper provides insights into Machine to Machine (M2M) communication - its growth factors, possible solution areas and high level architecture. The paper delves a bit deeper into various entities involved in M2M design and development. It covers key points that architects and designers should keep in mind for effective deployment.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121025892","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745478
M. Saravanan, D. Sundar, V. S. Kumaresh
Probing of data streams in a distributed environment for observation is considered to be one of the prime activities of Big Data Handlers. The notion of big data is efficiently leveraged through popular social networking sites such as Facebook, Twitter, LinkedIn, etc. Twitter is a most popular micro-blogging website enriched with many research issues. The users are allowed to put their ideas and thoughts in the form of messages called “Tweets” in twitter. In this study, the purpose of gathering the location specific tweets is to understand and surface the insights which are related to human dynamics. We have employed the data stream mining approach to process geo-spatial time invariant tweets in a distributed real-time environment to gain more useful information. Topic models were explored for identifying a particular topic of interest or to extract prudent information from the stream data. Our concentration is on the evolution of different topics at different places, a location-topic matrix is formed for the set of topics observed as most predominant for the specific locations. Then a user graph is generated for the volatile topics that help in analyzing the users who have tweeted or has been re-tweeted on a specific topic the most. From the properties of the generated graph, the disorientation of the topics is reported in the given locations by the use of a sentimental analysis that deems the topic discussed as positive or negative. These analyzes have shown that there is a possibility to outwit the useless and most rampant negative issues spread mutely on a specific location which later creates unnecessary panic to the society.
{"title":"Probing of geospatial stream data to report disorientation","authors":"M. Saravanan, D. Sundar, V. S. Kumaresh","doi":"10.1109/RAICS.2013.6745478","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745478","url":null,"abstract":"Probing of data streams in a distributed environment for observation is considered to be one of the prime activities of Big Data Handlers. The notion of big data is efficiently leveraged through popular social networking sites such as Facebook, Twitter, LinkedIn, etc. Twitter is a most popular micro-blogging website enriched with many research issues. The users are allowed to put their ideas and thoughts in the form of messages called “Tweets” in twitter. In this study, the purpose of gathering the location specific tweets is to understand and surface the insights which are related to human dynamics. We have employed the data stream mining approach to process geo-spatial time invariant tweets in a distributed real-time environment to gain more useful information. Topic models were explored for identifying a particular topic of interest or to extract prudent information from the stream data. Our concentration is on the evolution of different topics at different places, a location-topic matrix is formed for the set of topics observed as most predominant for the specific locations. Then a user graph is generated for the volatile topics that help in analyzing the users who have tweeted or has been re-tweeted on a specific topic the most. From the properties of the generated graph, the disorientation of the topics is reported in the given locations by the use of a sentimental analysis that deems the topic discussed as positive or negative. These analyzes have shown that there is a possibility to outwit the useless and most rampant negative issues spread mutely on a specific location which later creates unnecessary panic to the society.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132600943","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745470
R. Sethunadh, T. Thomas
Directionlet Transform (DT) has gained popularity over the last few years as an anisotropic, critically sampled and perfect reconstruction transform with directional vanishing moments along any two directions. The performance of despeckling schemes based on multi-resolution analysis can be improved significantly by taking into account the multi-scale correlation among the transform coefficients. This paper proposes a novel directionally adaptive de-speckling algorithm for SAR images by taking into account the statistical inter scale dependency of Cauchy-Gaussian modeled DT coefficients. The effectiveness of the proposed scheme is illustrated by comparing it with other similar schemes.
{"title":"Directionally adaptive despeckling of SAR image using interscale dependence","authors":"R. Sethunadh, T. Thomas","doi":"10.1109/RAICS.2013.6745470","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745470","url":null,"abstract":"Directionlet Transform (DT) has gained popularity over the last few years as an anisotropic, critically sampled and perfect reconstruction transform with directional vanishing moments along any two directions. The performance of despeckling schemes based on multi-resolution analysis can be improved significantly by taking into account the multi-scale correlation among the transform coefficients. This paper proposes a novel directionally adaptive de-speckling algorithm for SAR images by taking into account the statistical inter scale dependency of Cauchy-Gaussian modeled DT coefficients. The effectiveness of the proposed scheme is illustrated by comparing it with other similar schemes.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131386985","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745440
C. Reddy, V. Sumalatha
The Built in Self Test (BIST) scheme proposed here is a combination of two test pattern generators. One is Low Transition Random Test Pattern Generator (LT-RTPG) and the other is Arithmetic based 3-weighted Random Test pattern Generator (A-3WRTPG). The LT-RTPG aims at detection of easy to detect faults which are prone to pseudo random patterns and reduction of power consumption during BIST activity. The LT-RTPG uses Bit-Swapping Linear Feedback Shift Register (BS-LFSR) for generation of pseudo random sequences. The BS-LFSR focuses on reducing the transitions in generated test pattern and there by reduces the power consumption during BIST activity. The A-3WRTPG aims at detection of pattern resistant faults that are left undetected by LT-RTPG and thereby increases the detection of fault probability. The A-3WRTPG uses flip flops and adders for carrying out arithmetic operations and modified form of weighted algorithm to achieve complete fault coverage. The weighted sets computed by A-3WRTPG comprising three weights, namely 0, 1, and 0.5 have been successfully utilized so far for test pattern generation, as a result in both low testing time and low consumed power. The proposed BIST can significantly reduce switching activity during BIST while achieving 100% fault coverage for all ISCAS'89 benchmark circuits.
{"title":"A new built in self test pattern generator for low power dissipation and high fault coverage","authors":"C. Reddy, V. Sumalatha","doi":"10.1109/RAICS.2013.6745440","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745440","url":null,"abstract":"The Built in Self Test (BIST) scheme proposed here is a combination of two test pattern generators. One is Low Transition Random Test Pattern Generator (LT-RTPG) and the other is Arithmetic based 3-weighted Random Test pattern Generator (A-3WRTPG). The LT-RTPG aims at detection of easy to detect faults which are prone to pseudo random patterns and reduction of power consumption during BIST activity. The LT-RTPG uses Bit-Swapping Linear Feedback Shift Register (BS-LFSR) for generation of pseudo random sequences. The BS-LFSR focuses on reducing the transitions in generated test pattern and there by reduces the power consumption during BIST activity. The A-3WRTPG aims at detection of pattern resistant faults that are left undetected by LT-RTPG and thereby increases the detection of fault probability. The A-3WRTPG uses flip flops and adders for carrying out arithmetic operations and modified form of weighted algorithm to achieve complete fault coverage. The weighted sets computed by A-3WRTPG comprising three weights, namely 0, 1, and 0.5 have been successfully utilized so far for test pattern generation, as a result in both low testing time and low consumed power. The proposed BIST can significantly reduce switching activity during BIST while achieving 100% fault coverage for all ISCAS'89 benchmark circuits.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114874485","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745469
C. Byju, R. Murali, S. Vishnu, Jose Joji
This paper describes the hardware implementation of real time configurable, electronically steered, transducer array for ultrasonic applications. In a transducer array radiation pattern of each of the elements are superimposed to get the resultant radiation pattern of the array. By applying progressive phase delay (time delay) to the driving signal of each of the transducer array elements the radiation beam of the transmitter can be steered to the intended direction. The implementation includes an graphical user interface for configuring the steering angle and other waveform parameters such as amplitude, frequency, modulation scheme etc. in real time. These parameters are communicated to the Digital Signal Processor (DSP) via. Serial Peripheral Interface (SPI). The programmable delay and waveform generation are done by Field Programmable Gate array (FPGA) so that the steering resolution is high. This implementation find application in radar systems where the beam steering angle needs to be dynamically varied on real time without any movement of mechanical masses.
{"title":"Reconfigurable ultrasonic beamformer","authors":"C. Byju, R. Murali, S. Vishnu, Jose Joji","doi":"10.1109/RAICS.2013.6745469","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745469","url":null,"abstract":"This paper describes the hardware implementation of real time configurable, electronically steered, transducer array for ultrasonic applications. In a transducer array radiation pattern of each of the elements are superimposed to get the resultant radiation pattern of the array. By applying progressive phase delay (time delay) to the driving signal of each of the transducer array elements the radiation beam of the transmitter can be steered to the intended direction. The implementation includes an graphical user interface for configuring the steering angle and other waveform parameters such as amplitude, frequency, modulation scheme etc. in real time. These parameters are communicated to the Digital Signal Processor (DSP) via. Serial Peripheral Interface (SPI). The programmable delay and waveform generation are done by Field Programmable Gate array (FPGA) so that the steering resolution is high. This implementation find application in radar systems where the beam steering angle needs to be dynamically varied on real time without any movement of mechanical masses.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114874833","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745486
Subarna Sinha, S. Deb
Image segmentation based on clustering techniques still remains a challenging task. The aim of clustering is to generate homogeneous groups of data. In this paper, we present bio-inspired formulation to perform image segmentation. Specifically, we used the Bird flocking algorithm that uses the concepts of a flock of agents, e.g. birds moving together in a complex manner with simple local rules. Each bird representing one data, move with the aim of creating homogeneous groups of data in a two dimensional environment producing a spatial distribution that can be used to solve a particular computational problem. These characteristics have been used to solve the task of segmentation of images which optimize the partition of image data into homogenous regions.
{"title":"Image segmentation by intelligent clustering technique","authors":"Subarna Sinha, S. Deb","doi":"10.1109/RAICS.2013.6745486","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745486","url":null,"abstract":"Image segmentation based on clustering techniques still remains a challenging task. The aim of clustering is to generate homogeneous groups of data. In this paper, we present bio-inspired formulation to perform image segmentation. Specifically, we used the Bird flocking algorithm that uses the concepts of a flock of agents, e.g. birds moving together in a complex manner with simple local rules. Each bird representing one data, move with the aim of creating homogeneous groups of data in a two dimensional environment producing a spatial distribution that can be used to solve a particular computational problem. These characteristics have been used to solve the task of segmentation of images which optimize the partition of image data into homogenous regions.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124003970","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745472
A. Mamatha, Vipula Singh
Hyperspectral imaging technology plays an important role in the field of remote sensing applications. Hyperspectral images exhibit significant spectral correlation whose exploitation is crucial for compression. In this paper an efficient method for Hyperspectral image compression is presented based on differential prediction with very low complexity. The proposed scheme consists of a difference coder, two predictors and a Huffman codec. The processing of the pixels varies depending on their position in the image. The resulting difference between the predicted and the actual pixel values are encoded into variable-length codewords using the Huffman codebook. The performance of the proposed algorithm has been evaluated on AVIRIS images. The experimental results show that with a Compression Ratio (CR) up to 4.14, the proposed method provides a competitive performance with comparison of JPEG2000, JPEG-LS and the OCC schemes.
{"title":"Lossless hyperspectral image compression based on prediction","authors":"A. Mamatha, Vipula Singh","doi":"10.1109/RAICS.2013.6745472","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745472","url":null,"abstract":"Hyperspectral imaging technology plays an important role in the field of remote sensing applications. Hyperspectral images exhibit significant spectral correlation whose exploitation is crucial for compression. In this paper an efficient method for Hyperspectral image compression is presented based on differential prediction with very low complexity. The proposed scheme consists of a difference coder, two predictors and a Huffman codec. The processing of the pixels varies depending on their position in the image. The resulting difference between the predicted and the actual pixel values are encoded into variable-length codewords using the Huffman codebook. The performance of the proposed algorithm has been evaluated on AVIRIS images. The experimental results show that with a Compression Ratio (CR) up to 4.14, the proposed method provides a competitive performance with comparison of JPEG2000, JPEG-LS and the OCC schemes.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131007162","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 : 2013-12-01DOI: 10.1109/RAICS.2013.6745448
T. P. Shabeera, S. D. Madhu Kumar
We are living in a data rich era. The size of the data is increasing exponentially. Social networking applications, Scientific experiments, etc. are the major contributors of Big Data. The data can be structured, semi-structured or unstructured. Big Data management solutions can be implemented in-house in the organization or it can be stored in cloud. Whether it is stored in-house or in cloud, the placement of data is very important. In general, users demand the availability of data whenever they request for it. There are many parameters that effect the data retrieval time in Hadoop. Among them, this paper pays attention to the available bandwidth. To minimize the data retrieval time, the data must be placed in a DataNode which has the maximum bandwidth. We have proposed a solution for bandwidth-aware data placement in Hadoop by periodically measuring the bandwidth between clients and DataNodes and placing the data blocks in DataNodes that have maximum end-to-end bandwidth.
{"title":"Bandwidth-aware data placement scheme for Hadoop","authors":"T. P. Shabeera, S. D. Madhu Kumar","doi":"10.1109/RAICS.2013.6745448","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745448","url":null,"abstract":"We are living in a data rich era. The size of the data is increasing exponentially. Social networking applications, Scientific experiments, etc. are the major contributors of Big Data. The data can be structured, semi-structured or unstructured. Big Data management solutions can be implemented in-house in the organization or it can be stored in cloud. Whether it is stored in-house or in cloud, the placement of data is very important. In general, users demand the availability of data whenever they request for it. There are many parameters that effect the data retrieval time in Hadoop. Among them, this paper pays attention to the available bandwidth. To minimize the data retrieval time, the data must be placed in a DataNode which has the maximum bandwidth. We have proposed a solution for bandwidth-aware data placement in Hadoop by periodically measuring the bandwidth between clients and DataNodes and placing the data blocks in DataNodes that have maximum end-to-end bandwidth.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"63 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130526004","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 : 2013-12-01DOI: 10.1007/978-81-322-1000-9_6
A. K. Nejiya, M. Wilscy
{"title":"Example based super-resolution using fuzzy clustering and sparse neighbor embedding","authors":"A. K. Nejiya, M. Wilscy","doi":"10.1007/978-81-322-1000-9_6","DOIUrl":"https://doi.org/10.1007/978-81-322-1000-9_6","url":null,"abstract":"","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115669772","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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