Pub Date : 2014-12-01DOI: 10.1109/CNT.2014.7062772
M. P. Kumar, P. R. Kumar
The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.
{"title":"A multi sensor monochrome video fusion using Image Quality Assessment","authors":"M. P. Kumar, P. R. Kumar","doi":"10.1109/CNT.2014.7062772","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062772","url":null,"abstract":"The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126903156","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062735
K. Kavitha, P. Nivedha, S. Arivazhagan, P. Palniladevi
This paper aims at the wavelet transform based algorithm for landcover classification of Hyperspectral remote sensing images using Support Vector Machines (SVM). In this paper Feature Extraction and Hyperspectral pixel classification are done based on Discrete Wavelet Transform (DWT) features which includes the Statistical Features and the Gray Level Co-occurrence Features. The experiment is performed on a hyperspectral dataset acquired from ROSIS sensor and the experimental results indicate that it provides an Overall accuracy of about 98.28%. When compared to the other methods, the wavelet transform based method increases the overall classification accuracy.
{"title":"Wavelet transform based land cover classification of hyperspectral images","authors":"K. Kavitha, P. Nivedha, S. Arivazhagan, P. Palniladevi","doi":"10.1109/CNT.2014.7062735","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062735","url":null,"abstract":"This paper aims at the wavelet transform based algorithm for landcover classification of Hyperspectral remote sensing images using Support Vector Machines (SVM). In this paper Feature Extraction and Hyperspectral pixel classification are done based on Discrete Wavelet Transform (DWT) features which includes the Statistical Features and the Gray Level Co-occurrence Features. The experiment is performed on a hyperspectral dataset acquired from ROSIS sensor and the experimental results indicate that it provides an Overall accuracy of about 98.28%. When compared to the other methods, the wavelet transform based method increases the overall classification accuracy.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126116662","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062755
V. Arun Raj, M. Davidson Kamala Dhas, D. Gnanadurai
Modified Discrete Cosine Transform (MDCT) is a upcoming special transform implemented in areas of audio signal processing and compression. As, the name implies it is the modified form of DCT (Discrete Cosine Transform) that allows overlapping of segments (say 50%) and thereby it helps in avoiding artifacts. MDCT in general is a lapped transform that rectifies the problem of TDAC (Time Domain Aliasing Cancellation) and hence widely used in audio codec (.mp3, .wav) applications. The scope of this paper is to use MDCT in a system that overcomes the problem of TDAC and implementation of different windows those are capable with this transform. Finally, we calculate the MSE (Mean Squared Error) for the system with different inputs stating that perfect audio reconstruction is possible.
{"title":"An overview of MDCT for Time Domain Aliasing Cancellation","authors":"V. Arun Raj, M. Davidson Kamala Dhas, D. Gnanadurai","doi":"10.1109/CNT.2014.7062755","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062755","url":null,"abstract":"Modified Discrete Cosine Transform (MDCT) is a upcoming special transform implemented in areas of audio signal processing and compression. As, the name implies it is the modified form of DCT (Discrete Cosine Transform) that allows overlapping of segments (say 50%) and thereby it helps in avoiding artifacts. MDCT in general is a lapped transform that rectifies the problem of TDAC (Time Domain Aliasing Cancellation) and hence widely used in audio codec (.mp3, .wav) applications. The scope of this paper is to use MDCT in a system that overcomes the problem of TDAC and implementation of different windows those are capable with this transform. Finally, we calculate the MSE (Mean Squared Error) for the system with different inputs stating that perfect audio reconstruction is possible.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124133849","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062716
Shubhra Dixit, R. Nema
Low Noise Amplifier is the Front End Block of Radio-Frequency Receiver System. Various characteristics are Gain, Noise Figure, Insertion Losses and Power Dissipation is required in its designing. In this Paper we have surveyed almost all the Possible Work Done in Low Noise Amplifier in Past Decades. Here we will Study about Varying Range of Noise Figure, Gain, Power Consumption and Different Methodologies Used in Different Papers From 1998 to 2013.
{"title":"A review paper on different methodology of Low Noise Amplifier","authors":"Shubhra Dixit, R. Nema","doi":"10.1109/CNT.2014.7062716","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062716","url":null,"abstract":"Low Noise Amplifier is the Front End Block of Radio-Frequency Receiver System. Various characteristics are Gain, Noise Figure, Insertion Losses and Power Dissipation is required in its designing. In this Paper we have surveyed almost all the Possible Work Done in Low Noise Amplifier in Past Decades. Here we will Study about Varying Range of Noise Figure, Gain, Power Consumption and Different Methodologies Used in Different Papers From 1998 to 2013.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"479 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123398400","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062720
Ajni K Ajai, R. Rajesh
For providing efficient data security, sensitive data has to be doubly encrypted in public clouds. Recent approaches to perform the two layer encryption the data owners carry out coarse grained encryption, whereas the cloud implements a fine-grained encryption on top of the owner encrypted data. But in this for searchable encryption points, it was done using Plaintext keyword search or Single keyword search or Boolean keyword search. When large amount of data users and documents in the cloud taken into concern, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. In this paper, for the first time, we define and solve the problem of privacy preserving and data retrieval from encrypted data in public clouds by Double Layer Encryption (DLE) and Hierarchical Multi-Keyword Ranked Search schema (HMRS). Through these two concepts our system assures the confidentiality of the data with ranking and secures the privacy of users from the cloud. On the real-world it shows proposed schemes indeed introduce fast retrieval, more security and less cost in computation and communication in Public Cloud.
{"title":"Hierarchical Multi-Keyword Ranked search for secured document retrieval in public clouds","authors":"Ajni K Ajai, R. Rajesh","doi":"10.1109/CNT.2014.7062720","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062720","url":null,"abstract":"For providing efficient data security, sensitive data has to be doubly encrypted in public clouds. Recent approaches to perform the two layer encryption the data owners carry out coarse grained encryption, whereas the cloud implements a fine-grained encryption on top of the owner encrypted data. But in this for searchable encryption points, it was done using Plaintext keyword search or Single keyword search or Boolean keyword search. When large amount of data users and documents in the cloud taken into concern, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. In this paper, for the first time, we define and solve the problem of privacy preserving and data retrieval from encrypted data in public clouds by Double Layer Encryption (DLE) and Hierarchical Multi-Keyword Ranked Search schema (HMRS). Through these two concepts our system assures the confidentiality of the data with ranking and secures the privacy of users from the cloud. On the real-world it shows proposed schemes indeed introduce fast retrieval, more security and less cost in computation and communication in Public Cloud.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123469178","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062753
J. V. Suman, J. Seventline
The Hyperbolic Frequency Modulated (HFM) and Nonlinear Frequency Modulated (NLFM) signals have been gradually used in new radar systems. These signals excitation when combined with pulse compression provides an increase in SNR at the receiver. These signals are of longer duration as compared to pulse signals of same bandwidth. Separation of echoes becomes impossible in some practical situations when these signals are used for transmission. In this paper a new method is explored to separate the time overlapping HFM and NLFM signals using the fractional fourier transform. The motivation behind using this method is because some of the techniques like time windowing and frequency domain filtering are unable to separate these signals overlapping in time and spectra. Simulation results show that using FrFT desirable outputs are obtained.
{"title":"Separation of HFM and NLFM signals for radar using fractional fourier transform","authors":"J. V. Suman, J. Seventline","doi":"10.1109/CNT.2014.7062753","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062753","url":null,"abstract":"The Hyperbolic Frequency Modulated (HFM) and Nonlinear Frequency Modulated (NLFM) signals have been gradually used in new radar systems. These signals excitation when combined with pulse compression provides an increase in SNR at the receiver. These signals are of longer duration as compared to pulse signals of same bandwidth. Separation of echoes becomes impossible in some practical situations when these signals are used for transmission. In this paper a new method is explored to separate the time overlapping HFM and NLFM signals using the fractional fourier transform. The motivation behind using this method is because some of the techniques like time windowing and frequency domain filtering are unable to separate these signals overlapping in time and spectra. Simulation results show that using FrFT desirable outputs are obtained.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123270141","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062726
S. Arivazhagan, R. Ahila Priyadharshini, S. Sowmiya
In this work, an efficient algorithm for facial expression recognition using a local feature descriptor, Local Binary Pattern (LBP), Local Directional Number Pattern (LDN) and Soft Computing Technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is presented. In the first experiment local binary pattern is computed using the input image.In the second experiment, the face image is subjected to a Kirsch compass mask that gives the directional information of the image and with the help of masked output Local Directional Number Pattern (LDN) code is computed. The obtained LBP and LDN image is divided into several regions and the distribution of the LBP and LDN features are extracted from them. These features are then concatenated into a feature vector, which is used for ANFIS training and classification. The experimental evaluation of the presented method is carried out using Japanese Female Facial Expression Database (JAFFE) and Indian Face Database (IFD). The results obtained from the experiments prove that the presented method successfully recognize the facial expression variations.
{"title":"Facial expression recognition based on local directional number pattern and ANFIS classifier","authors":"S. Arivazhagan, R. Ahila Priyadharshini, S. Sowmiya","doi":"10.1109/CNT.2014.7062726","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062726","url":null,"abstract":"In this work, an efficient algorithm for facial expression recognition using a local feature descriptor, Local Binary Pattern (LBP), Local Directional Number Pattern (LDN) and Soft Computing Technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is presented. In the first experiment local binary pattern is computed using the input image.In the second experiment, the face image is subjected to a Kirsch compass mask that gives the directional information of the image and with the help of masked output Local Directional Number Pattern (LDN) code is computed. The obtained LBP and LDN image is divided into several regions and the distribution of the LBP and LDN features are extracted from them. These features are then concatenated into a feature vector, which is used for ANFIS training and classification. The experimental evaluation of the presented method is carried out using Japanese Female Facial Expression Database (JAFFE) and Indian Face Database (IFD). The results obtained from the experiments prove that the presented method successfully recognize the facial expression variations.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131381718","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062736
M. Mayilvaganan, D. Kalpanadevi
The aim of this study is to compares some classification techniques used to predict the performance of student. It is helps to analyse the slow leaner in the semester exams that are likely study in poor which are used to improve their skill as early to achieve the goal in end semester. The task can be processed based on the several attributes to predict the performance of the student activity respectively. In this research, the paper have been focused the improvement of Prediction/ classification techniques which are used to analyse the skill expertise based on their academic performance by the scope of knowledge. Also the paper shows the comparative performance of C4.5 algorithm, AODE, Naïve Bayesian classifier algorithm, Multi Label K-Nearest Neighbor algorithm to find the well suited accuracy of classification algorithm and decision tree algorithm to analysis the performance of the students which can be experimented in Weka tool.
{"title":"Comparison of classification techniques for predicting the performance of students academic environment","authors":"M. Mayilvaganan, D. Kalpanadevi","doi":"10.1109/CNT.2014.7062736","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062736","url":null,"abstract":"The aim of this study is to compares some classification techniques used to predict the performance of student. It is helps to analyse the slow leaner in the semester exams that are likely study in poor which are used to improve their skill as early to achieve the goal in end semester. The task can be processed based on the several attributes to predict the performance of the student activity respectively. In this research, the paper have been focused the improvement of Prediction/ classification techniques which are used to analyse the skill expertise based on their academic performance by the scope of knowledge. Also the paper shows the comparative performance of C4.5 algorithm, AODE, Naïve Bayesian classifier algorithm, Multi Label K-Nearest Neighbor algorithm to find the well suited accuracy of classification algorithm and decision tree algorithm to analysis the performance of the students which can be experimented in Weka tool.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"22 5-6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125618564","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062758
G. Indumathi, V. Aarthi
The need for low-power design is becoming a major issue in high-performance digital systems such as microprocessors, Digital Signal Processors (DSPs) and other applications. The increasing market of mobile devices and battery powered portable electronic systems is creating demands for chips that consume the smallest possible amount of power. On the one hand, hundreds to millions of transistors can be integrated on the same chip using System on Chip (SoC) design methodologies. On the other hand, the shrinking feature sizes and increasing circuit speed causes higher power consumption, which not only shorten the battery life of handheld devices, but also lead to thermal and reliability problems. Until now various techniques of energy optimization have come forward and effectively contributed to the problem of energy optimization. In this paper, we discuss the various factors for designing the low power SRAM cells by analyzing the power dissipation issues by considering the basic Static Random Access Memory (SRAM) structure and concentrate on supply voltage, parallelism and memory architecture. Regarding the supply voltage, the voltage scaling technique with hybrid parallelism is surveyed and various cache architectures for memory has been addressed to optimize the energy. The energy optimization in memory array could be achieved by an efficient SRAM cell along with sense amplifiers and read write circuitry.
{"title":"Energy optimization techniques on SRAM: A survey","authors":"G. Indumathi, V. Aarthi","doi":"10.1109/CNT.2014.7062758","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062758","url":null,"abstract":"The need for low-power design is becoming a major issue in high-performance digital systems such as microprocessors, Digital Signal Processors (DSPs) and other applications. The increasing market of mobile devices and battery powered portable electronic systems is creating demands for chips that consume the smallest possible amount of power. On the one hand, hundreds to millions of transistors can be integrated on the same chip using System on Chip (SoC) design methodologies. On the other hand, the shrinking feature sizes and increasing circuit speed causes higher power consumption, which not only shorten the battery life of handheld devices, but also lead to thermal and reliability problems. Until now various techniques of energy optimization have come forward and effectively contributed to the problem of energy optimization. In this paper, we discuss the various factors for designing the low power SRAM cells by analyzing the power dissipation issues by considering the basic Static Random Access Memory (SRAM) structure and concentrate on supply voltage, parallelism and memory architecture. Regarding the supply voltage, the voltage scaling technique with hybrid parallelism is surveyed and various cache architectures for memory has been addressed to optimize the energy. The energy optimization in memory array could be achieved by an efficient SRAM cell along with sense amplifiers and read write circuitry.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131245313","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 : 2014-12-01DOI: 10.1109/CNT.2014.7062765
Dr. T. Ananth kumar, R. Rajesh
With the Continuous advancement of technology, enormous amount of heterogeneous devices can be integrated on a single chip in an efficient manner. It implies the need of high performance routers to communicate between the devices. For achieving high speed communication, the interconnection between the multiple cores should be an efficient one. In this paper, we expose a new architecture for an efficient low power wireless network on chip router which can be integrated within the System on Chip. The Interconnect fabric router architecture is designed through VHDL and simulated using Xilinx.
{"title":"Towards power efficient wireless NoC router for SOC","authors":"Dr. T. Ananth kumar, R. Rajesh","doi":"10.1109/CNT.2014.7062765","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062765","url":null,"abstract":"With the Continuous advancement of technology, enormous amount of heterogeneous devices can be integrated on a single chip in an efficient manner. It implies the need of high performance routers to communicate between the devices. For achieving high speed communication, the interconnection between the multiple cores should be an efficient one. In this paper, we expose a new architecture for an efficient low power wireless network on chip router which can be integrated within the System on Chip. The Interconnect fabric router architecture is designed through VHDL and simulated using Xilinx.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132004776","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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