Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745446
Lakshmi Boppana, Chandana N. Amanchi, R. Kodali
Various Various wireless technologies have been emerging with ever increasing demand for higher data rates along with low bit error rates (BER's). Adaptive modulation and coding (AMC) schemes, when incorporated into WiMAX helps the system to react dynamically to the channel variations thereby providing higher data rates and improve BER performance. Based on the channel state information, both the modulation and coding rates can be varied so as to achieve higher throughput and improve spectral efficiency. This work proposes an efficient adaptive modulation coding technique, which maximizes the throughput, while maintaining a target BER. It proposes to select a particular modulation coding scheme along with the corresponding coding rates based on the given threshold. The parameter values, such as SNR, BER, CINR, BLER channel attenuation factor, are accepted and then the modulation schemes with an appropriate coding rate are selected for the operation of a OFDM system in GNU Radio.
{"title":"Coding rates and MCS using adaptive modulation for WiMAX in OFDM systems using GNU Radio","authors":"Lakshmi Boppana, Chandana N. Amanchi, R. Kodali","doi":"10.1109/RAICS.2013.6745446","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745446","url":null,"abstract":"Various Various wireless technologies have been emerging with ever increasing demand for higher data rates along with low bit error rates (BER's). Adaptive modulation and coding (AMC) schemes, when incorporated into WiMAX helps the system to react dynamically to the channel variations thereby providing higher data rates and improve BER performance. Based on the channel state information, both the modulation and coding rates can be varied so as to achieve higher throughput and improve spectral efficiency. This work proposes an efficient adaptive modulation coding technique, which maximizes the throughput, while maintaining a target BER. It proposes to select a particular modulation coding scheme along with the corresponding coding rates based on the given threshold. The parameter values, such as SNR, BER, CINR, BLER channel attenuation factor, are accepted and then the modulation schemes with an appropriate coding rate are selected for the operation of a OFDM system in GNU Radio.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"53 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":"123782266","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.2013.6745449
Debasis Das, R. Misra
Geographic Perimeter Stateless Routing (GPSR) use local information to forward packets greedily. Nodes need to keep only this information, hence called as stateless. When not possible the algorithm and Greedy forwarding recovers to this scenario by switching to face routing, which is further based on the right-hand rule in the planarized node graph, in order to route around the void. The Gabriel Graph(GG) and the Relative Neighbourhood Graph (RNG) are the two graphs used for the planarization, but results in graph partitioning. In this work, we propose an improvised RNG-GG algorithm which makes sure to avoid the partitioning of the underlying connected graph and the cross-link, which remain in the node connectivity graph. We have given simulation results for the performance analysis of our proposed protocol compared to the competitive schemes and found improvement in terms of an increased packet delivery success rate, reducing routing protocol overhead and increased the path length.
{"title":"Improvised geographic scheme for greedy perimeter stateless routing","authors":"Debasis Das, R. Misra","doi":"10.1109/RAICS.2013.6745449","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745449","url":null,"abstract":"Geographic Perimeter Stateless Routing (GPSR) use local information to forward packets greedily. Nodes need to keep only this information, hence called as stateless. When not possible the algorithm and Greedy forwarding recovers to this scenario by switching to face routing, which is further based on the right-hand rule in the planarized node graph, in order to route around the void. The Gabriel Graph(GG) and the Relative Neighbourhood Graph (RNG) are the two graphs used for the planarization, but results in graph partitioning. In this work, we propose an improvised RNG-GG algorithm which makes sure to avoid the partitioning of the underlying connected graph and the cross-link, which remain in the node connectivity graph. We have given simulation results for the performance analysis of our proposed protocol compared to the competitive schemes and found improvement in terms of an increased packet delivery success rate, reducing routing protocol overhead and increased the path length.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"5 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":"128796590","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.2013.6745441
K. Selvan, M. Tech, Aju Joseph, Anish Babu
Due to the rapid advances in algorithms, VLSI design and computer technology, security systems based on speaker recognition are on the verge of commercial success. Nowadays, it is obvious that speakers can be identified from their voices. In this paper, an improved strategy for Text Dependent Automatic Speaker Verification (TD-ASV) system based on Malayalam and English language has been proposed and comparison of results are discussed. The system performs on Hidden Markov Model (HMM) technique with cepstral based features. Different speech pre-processing techniques like pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. MFCC, ΔMFCC and Δ ΔMFCC have been used to extract the features. Speaker Identification (SI) is performed using Continuous Hidden Markov Model. The performance is analyzed in terms of Percentage Correctness (PC) and accuracy and result is visualized in a confusion matrix. The system has percentage correctness of 99.71% in English and 99.71% in Malayalam language. An application with Graphical User Interface (GUI) is also developed for security purposes using the system. The system is developed using the framework of Hidden Markov Model Tool Kit (HTK).
{"title":"Speaker recognition system for security applications","authors":"K. Selvan, M. Tech, Aju Joseph, Anish Babu","doi":"10.1109/RAICS.2013.6745441","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745441","url":null,"abstract":"Due to the rapid advances in algorithms, VLSI design and computer technology, security systems based on speaker recognition are on the verge of commercial success. Nowadays, it is obvious that speakers can be identified from their voices. In this paper, an improved strategy for Text Dependent Automatic Speaker Verification (TD-ASV) system based on Malayalam and English language has been proposed and comparison of results are discussed. The system performs on Hidden Markov Model (HMM) technique with cepstral based features. Different speech pre-processing techniques like pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. MFCC, ΔMFCC and Δ ΔMFCC have been used to extract the features. Speaker Identification (SI) is performed using Continuous Hidden Markov Model. The performance is analyzed in terms of Percentage Correctness (PC) and accuracy and result is visualized in a confusion matrix. The system has percentage correctness of 99.71% in English and 99.71% in Malayalam language. An application with Graphical User Interface (GUI) is also developed for security purposes using the system. The system is developed using the framework of Hidden Markov Model Tool Kit (HTK).","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"4 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":"124655832","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.2013.6745437
J. Jayarajan, R. Kumaran, Sandip Paul, R. Parmar, Purvi A. Koringa
Resolution of Time to Digital Convertor (TDC) is a critical parameter in determining the overall performance of Time Of Flight based laser range finder system. This paper focuses on designing a high resolution Laser Range Finder (LRF) using Commercial-Off-The-Shelf (COTS) components. The designed LRF consists of a high resolution Time to Digital Convertor using Virtex-4 FPGA, Parallel to USB converter, High Voltage Power Supply and Data acquisition and display module. TDC generates START pulse at pulse repetition frequency (prf). This pulse is fed as trigger to laser TX. Avalanche Photo-Diode (APD) receiver with high voltage bias (~140V) generates a STOP pulse on receipt of reflected laser beam. This pulse is level translated and fed to TDC as STOP pulse. Digital Clock Manager (DCM) is used to achieve clock interpolation for improving resolution beyond 1 clock period. The output of TDC is parallel 16-bit digital count which is converted to serial USB protocol and interfaced to PC based data acquisition system. The raw data is processed and distance information is derived after calibration with known distance sets. Graphical User Interface (GUI) is developed for display, record and calibration. Full system resolution of about 22 cm is achieved in hardware for a range of 10m. The system has a power consumption of 6.15W.
{"title":"Design of high precision electronics for laser range finder","authors":"J. Jayarajan, R. Kumaran, Sandip Paul, R. Parmar, Purvi A. Koringa","doi":"10.1109/RAICS.2013.6745437","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745437","url":null,"abstract":"Resolution of Time to Digital Convertor (TDC) is a critical parameter in determining the overall performance of Time Of Flight based laser range finder system. This paper focuses on designing a high resolution Laser Range Finder (LRF) using Commercial-Off-The-Shelf (COTS) components. The designed LRF consists of a high resolution Time to Digital Convertor using Virtex-4 FPGA, Parallel to USB converter, High Voltage Power Supply and Data acquisition and display module. TDC generates START pulse at pulse repetition frequency (prf). This pulse is fed as trigger to laser TX. Avalanche Photo-Diode (APD) receiver with high voltage bias (~140V) generates a STOP pulse on receipt of reflected laser beam. This pulse is level translated and fed to TDC as STOP pulse. Digital Clock Manager (DCM) is used to achieve clock interpolation for improving resolution beyond 1 clock period. The output of TDC is parallel 16-bit digital count which is converted to serial USB protocol and interfaced to PC based data acquisition system. The raw data is processed and distance information is derived after calibration with known distance sets. Graphical User Interface (GUI) is developed for display, record and calibration. Full system resolution of about 22 cm is achieved in hardware for a range of 10m. The system has a power consumption of 6.15W.","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":"126507969","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.2013.6745490
Archana Aniyan, J. Deepa
Development of digital watermarking technology has enabled the copyright protection and content authentication of digital multimedia data. Watermarking technique for digital images uses either spatial or frequency domain method. This paper describes a discrete cosine transform (DCT) based blind watermarking method for digital images and its hardware implementation using BeagleBoard. Experimental results show that the developed method is robust against various attacks and potentially compatible with JPEG compression.
{"title":"Hardware implementation of a robust watermarking technique for digital images","authors":"Archana Aniyan, J. Deepa","doi":"10.1109/RAICS.2013.6745490","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745490","url":null,"abstract":"Development of digital watermarking technology has enabled the copyright protection and content authentication of digital multimedia data. Watermarking technique for digital images uses either spatial or frequency domain method. This paper describes a discrete cosine transform (DCT) based blind watermarking method for digital images and its hardware implementation using BeagleBoard. Experimental results show that the developed method is robust against various attacks and potentially compatible with JPEG compression.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"78 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":"125715570","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.2013.6745493
K. Vupparaboina, Kamala Raghavan, S. Jana
With the proliferation of smart environment, smart multi-camera networks assume growing significance. Specifically, non-intrusive calibration of such camera networks becomes imperative in smart applications such as telepresence systems, where multi-view imaging/recording needs to be performed in a dynamic setting with continuously changing intrinsic and extrinsic camera parameters. Unfortunately, popular auto calibration methods are known to introduce ambiguity or require manual intervention. In this backdrop, we propose a three-camera configuration (which can be generalized) with a stereo pair having known baseline distance and an additional (mono) camera positioned arbitrarily, and analytically establish the uniqueness of auto calibration in the proposed configuration.
{"title":"Smart camera networks: An analytical framework for auto calibration without ambiguity","authors":"K. Vupparaboina, Kamala Raghavan, S. Jana","doi":"10.1109/RAICS.2013.6745493","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745493","url":null,"abstract":"With the proliferation of smart environment, smart multi-camera networks assume growing significance. Specifically, non-intrusive calibration of such camera networks becomes imperative in smart applications such as telepresence systems, where multi-view imaging/recording needs to be performed in a dynamic setting with continuously changing intrinsic and extrinsic camera parameters. Unfortunately, popular auto calibration methods are known to introduce ambiguity or require manual intervention. In this backdrop, we propose a three-camera configuration (which can be generalized) with a stereo pair having known baseline distance and an additional (mono) camera positioned arbitrarily, and analytically establish the uniqueness of auto calibration in the proposed configuration.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"38 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":"129996273","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.2013.6745489
Saptaditya Maiti, D. Mandal, Pabitra Mitra
This article discusses about detecting the most influential users in an online social network. We observe that a communication of an influential user is likely to reach many more users than the same made by a user having lesser influence in the network. Based on this observation, We have formulated a method using the spread of communications (i.e., the number of users the communication reaches). We have verified the method on three datasets downloaded from `Twitter' and results are found to be the best among existing methods on the said datasets.
{"title":"Detecting influential users using spread of communications","authors":"Saptaditya Maiti, D. Mandal, Pabitra Mitra","doi":"10.1109/RAICS.2013.6745489","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745489","url":null,"abstract":"This article discusses about detecting the most influential users in an online social network. We observe that a communication of an influential user is likely to reach many more users than the same made by a user having lesser influence in the network. Based on this observation, We have formulated a method using the spread of communications (i.e., the number of users the communication reaches). We have verified the method on three datasets downloaded from `Twitter' and results are found to be the best among existing methods on the said datasets.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"6 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":"134179564","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.2013.6745444
Jubin James Thennattil, Ebin M. Manuel
Radio spectrum is being underutilized. Cognitive Radio acts as a solution to the problem of spectrum under-utilization. Spectrum sensing is the most important feature of Cognitive Radio. Cooperative spectrum sensing improves sensing performance by including a number of cognitive users rather than a single one. In cooperative spectrum sensing, each cognitive radio performs individual spectrum sensing by any of the available methods and individual sensing results are combined according to certain rules. We propose a novel method where signal to noise ratio, credibility and position information of secondary users are used for spectrum sensing. They are much important factors that affect the sensing, but were not considered in previous works. The performance of this scheme is investigated by simulation results and is much better than the traditional ones. Significant improvement in detection probabilities are achieved reducing false alarm rates even in situations including malicious users and hidden primary user.
{"title":"A novel approach in cooperative spectrum sensing for cognitive radio","authors":"Jubin James Thennattil, Ebin M. Manuel","doi":"10.1109/RAICS.2013.6745444","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745444","url":null,"abstract":"Radio spectrum is being underutilized. Cognitive Radio acts as a solution to the problem of spectrum under-utilization. Spectrum sensing is the most important feature of Cognitive Radio. Cooperative spectrum sensing improves sensing performance by including a number of cognitive users rather than a single one. In cooperative spectrum sensing, each cognitive radio performs individual spectrum sensing by any of the available methods and individual sensing results are combined according to certain rules. We propose a novel method where signal to noise ratio, credibility and position information of secondary users are used for spectrum sensing. They are much important factors that affect the sensing, but were not considered in previous works. The performance of this scheme is investigated by simulation results and is much better than the traditional ones. Significant improvement in detection probabilities are achieved reducing false alarm rates even in situations including malicious users and hidden primary user.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"6 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":"131146333","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.2013.6745471
Agrima Srivastava, G. Geethakumari
Privacy is one of the most important concerns in an online social network. Online social network data is big data as millions of users are a part of it. The personal information of every user in an online social network is an asset that may be traded by a third party for its benefits. Individuals should be aware of how much of their personal information could be shared without risk. Different people have different requirements to share a profile item hence measuring privacy of such huge and diverse population is a challenging and complicated task in itself. In this paper we have proposed a framework that ensures privacy of individuals by allowing them to measure their privacy with respect to some specific people of their choice rather than measuring it with the entire population on online social networks. We have suggested a method to choose the best model to fit the real world data and to calculate the sensitivities of various profile items. The framework gives specific labels to users that indicates their profile privacy strength and enable them to customize their privacy settings so as to improve the privacy quotient. The users can also act as advisers to their online friends whose privacy quotients are low and thus spread privacy awareness in social networks.
{"title":"A framework to customize privacy settings of online social network users","authors":"Agrima Srivastava, G. Geethakumari","doi":"10.1109/RAICS.2013.6745471","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745471","url":null,"abstract":"Privacy is one of the most important concerns in an online social network. Online social network data is big data as millions of users are a part of it. The personal information of every user in an online social network is an asset that may be traded by a third party for its benefits. Individuals should be aware of how much of their personal information could be shared without risk. Different people have different requirements to share a profile item hence measuring privacy of such huge and diverse population is a challenging and complicated task in itself. In this paper we have proposed a framework that ensures privacy of individuals by allowing them to measure their privacy with respect to some specific people of their choice rather than measuring it with the entire population on online social networks. We have suggested a method to choose the best model to fit the real world data and to calculate the sensitivities of various profile items. The framework gives specific labels to users that indicates their profile privacy strength and enable them to customize their privacy settings so as to improve the privacy quotient. The users can also act as advisers to their online friends whose privacy quotients are low and thus spread privacy awareness in social networks.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"20 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":"127653066","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.2013.6745497
Radhakrishnan Gopalapillai, J. Vidhya, Deepa Gupta, Sudarshan TSB
As time series data are common in the field of science and commerce, time series data analysis has an important role in these areas for extracting information from available data. This paper presents the application of Artificial Neural Networks (ANN) for analyzing huge amount of time series data collected by sensors mounted on a robot navigating in a simulated environment. The Artificial Neural Network system employing back propagation learning algorithm classified different scenarios encountered by the robot using the data collected by sensors.
{"title":"Classification of robotic data using artificial neural network","authors":"Radhakrishnan Gopalapillai, J. Vidhya, Deepa Gupta, Sudarshan TSB","doi":"10.1109/RAICS.2013.6745497","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745497","url":null,"abstract":"As time series data are common in the field of science and commerce, time series data analysis has an important role in these areas for extracting information from available data. This paper presents the application of Artificial Neural Networks (ANN) for analyzing huge amount of time series data collected by sensors mounted on a robot navigating in a simulated environment. The Artificial Neural Network system employing back propagation learning algorithm classified different scenarios encountered by the robot using the data collected by sensors.","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":"117205100","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：