Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208361
J. Saranya, S. Malarkhodi
Image segmentation is important tasks in medical image analysis. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The segmentation of an ultrasound image is a difficult task as it suffers from speckle noise. The main aim of this work is to segment the fibroid in the uterus. Uterine fibroid is the most common benign tumour of the female in the world. Uterine Fibroid segmentation in patient is the challenging task manually. Exactly extracting the fibroid in the uterus is the challenging task because of size, location and low contrast boundaries. Instead of doing the segmentation manually, this work proposes a new method for segmenting the fibroid in the uterus. The performance of this method is also commendable.
{"title":"Filtering and segmentation of a uterine fibroid with an ultrasound images","authors":"J. Saranya, S. Malarkhodi","doi":"10.1109/ICPRIME.2012.6208361","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208361","url":null,"abstract":"Image segmentation is important tasks in medical image analysis. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The segmentation of an ultrasound image is a difficult task as it suffers from speckle noise. The main aim of this work is to segment the fibroid in the uterus. Uterine fibroid is the most common benign tumour of the female in the world. Uterine Fibroid segmentation in patient is the challenging task manually. Exactly extracting the fibroid in the uterus is the challenging task because of size, location and low contrast boundaries. Instead of doing the segmentation manually, this work proposes a new method for segmenting the fibroid in the uterus. The performance of this method is also commendable.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115033657","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208301
K. Vidhya, R. Kumar
In this work we have compared different types of channel estimation algorithm for Orthogonal Frequency Division Multiplexing (OFDM)systems. The result of the Mean Square algorithm(MMSE)was compared with Least Square(LS) algorithm.
{"title":"Channel estimation techniques for OFDM systems","authors":"K. Vidhya, R. Kumar","doi":"10.1109/ICPRIME.2012.6208301","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208301","url":null,"abstract":"In this work we have compared different types of channel estimation algorithm for Orthogonal Frequency Division Multiplexing (OFDM)systems. The result of the Mean Square algorithm(MMSE)was compared with Least Square(LS) algorithm.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"117 5 Pt 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129151064","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208285
D. A. Kumar, T. Ummal, Sariba Begum
Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc. all this condensed into a simple box called ballot unit of the electronic voting machine. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. So the Electronic voting system has to be improved based on the current technologies viz., biometric system. This article discusses complete review about voting devices, Issues and comparison among the voting methods and biometric EVM.
{"title":"Electronic voting machine — A review","authors":"D. A. Kumar, T. Ummal, Sariba Begum","doi":"10.1109/ICPRIME.2012.6208285","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208285","url":null,"abstract":"Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc. all this condensed into a simple box called ballot unit of the electronic voting machine. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. So the Electronic voting system has to be improved based on the current technologies viz., biometric system. This article discusses complete review about voting devices, Issues and comparison among the voting methods and biometric EVM.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132838731","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208347
Gokulnath Thandavarayan, K. Sangeetha, S. Seerangan
Mobile Ad Hoc Network (MANET) is a wireless communication with a collection of devices that communicate with each other without the aid of any centralized administrator. Due to its properties MANET environment is prone to attacks in routes. ORZEF is a self-motivated routing system to provide has less security secure routing. When a node enters into a zone it distributes its secret key upto two hop count nodes and it shares their secret keys by using asymmetric key encryption. For each node routing zone is defined separately using its radius. When there is a malicious activity in the environment the authentication algorithm is initiated to isolate the malicious nodes. As a result of this scheme, the network will be able to effectively isolate the malicious nodes. Through extensive simulation analysis using QualNet simulator it is concluded that this scheme provides an efficient approach towards security and easier detection of the malicious nodes in the mobile ad hoc network and the power also utilized effectively.
{"title":"ORZEF: An optimized routing using zone to establish security in MANET using multipath and friend-based ad hoc routing","authors":"Gokulnath Thandavarayan, K. Sangeetha, S. Seerangan","doi":"10.1109/ICPRIME.2012.6208347","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208347","url":null,"abstract":"Mobile Ad Hoc Network (MANET) is a wireless communication with a collection of devices that communicate with each other without the aid of any centralized administrator. Due to its properties MANET environment is prone to attacks in routes. ORZEF is a self-motivated routing system to provide has less security secure routing. When a node enters into a zone it distributes its secret key upto two hop count nodes and it shares their secret keys by using asymmetric key encryption. For each node routing zone is defined separately using its radius. When there is a malicious activity in the environment the authentication algorithm is initiated to isolate the malicious nodes. As a result of this scheme, the network will be able to effectively isolate the malicious nodes. Through extensive simulation analysis using QualNet simulator it is concluded that this scheme provides an efficient approach towards security and easier detection of the malicious nodes in the mobile ad hoc network and the power also utilized effectively.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134600988","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208382
A. Martin, V. Aswathy, S. Balaji, T. Lakshmi, V. Prasanna Venkatesan
Many Qualitative Bankruptcy Prediction models are available. These models use non-financial information as Qualitative factors to predict Bankruptcy. In the prior researches Genetic Algorithm was applied to generate Qualitative Bankruptcy Prediction Rules. However this Model uses only very less number of Qualitative factors and the generated rules has redundancy and overlapping. To improve the Prediction accuracy we have proposed a model which applies more number of Qualitative factors which can be categorized using Fuzzy ID3 Algorithm and Prediction Rules are generated using Ant Colony Optimization Algorithm (ACO). In Fuzzy ID3 the concept of Entropy and Information Gain helps to rank the qualitative parameters and this can be used to generate prediction rules in qualitative Bankruptcy prediction. The concept of pheromone depositing and updating in Ant Colony Algorithm reduce the false negative rules in the bankruptcy prediction. The heuristic and probabilistic features of Ant Colony Algorithm increase the prediction accuracy of Bankruptcy. By using these two algorithms we provide more accurate prediction.
{"title":"An analysis on Qualitative Bankruptcy Prediction using Fuzzy ID3 and Ant Colony Optimization Algorithm","authors":"A. Martin, V. Aswathy, S. Balaji, T. Lakshmi, V. Prasanna Venkatesan","doi":"10.1109/ICPRIME.2012.6208382","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208382","url":null,"abstract":"Many Qualitative Bankruptcy Prediction models are available. These models use non-financial information as Qualitative factors to predict Bankruptcy. In the prior researches Genetic Algorithm was applied to generate Qualitative Bankruptcy Prediction Rules. However this Model uses only very less number of Qualitative factors and the generated rules has redundancy and overlapping. To improve the Prediction accuracy we have proposed a model which applies more number of Qualitative factors which can be categorized using Fuzzy ID3 Algorithm and Prediction Rules are generated using Ant Colony Optimization Algorithm (ACO). In Fuzzy ID3 the concept of Entropy and Information Gain helps to rank the qualitative parameters and this can be used to generate prediction rules in qualitative Bankruptcy prediction. The concept of pheromone depositing and updating in Ant Colony Algorithm reduce the false negative rules in the bankruptcy prediction. The heuristic and probabilistic features of Ant Colony Algorithm increase the prediction accuracy of Bankruptcy. By using these two algorithms we provide more accurate prediction.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127347313","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208345
S. Soundharya, G. Prakash
For high data rate Multiple Input Multiple Output technology is used in wireless communications. The use of multiple antennas at both transmitter and receiver (MIMO) significantly increases the capacity and spectral efficiency of wireless systems. This paper presents a Field Programmable Gate Array (FPGA) implementation for a 4 × 4 breadth first K-best MIMO decoder using a 64 Quadrature Amplitude Modulation (QAM) scheme. A novel sort free approach to path extension, as well as, quantized metrics result in a high throughput, low power and area. Finally, VLSI architectural tradeoffs are explored for a synthesized using synopsys the power analysis, throughput analysis in 120 nm technology. The power needed is 20.0025 μW.
{"title":"A high throughput sort free VLSI architecture for wireless applications","authors":"S. Soundharya, G. Prakash","doi":"10.1109/ICPRIME.2012.6208345","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208345","url":null,"abstract":"For high data rate Multiple Input Multiple Output technology is used in wireless communications. The use of multiple antennas at both transmitter and receiver (MIMO) significantly increases the capacity and spectral efficiency of wireless systems. This paper presents a Field Programmable Gate Array (FPGA) implementation for a 4 × 4 breadth first K-best MIMO decoder using a 64 Quadrature Amplitude Modulation (QAM) scheme. A novel sort free approach to path extension, as well as, quantized metrics result in a high throughput, low power and area. Finally, VLSI architectural tradeoffs are explored for a synthesized using synopsys the power analysis, throughput analysis in 120 nm technology. The power needed is 20.0025 μW.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121689527","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208362
K. Madhankumar, P. Kumar
Malignant melanoma is the deadliest form among all skin cancers. Fortunately, if detected early, even malignant melanoma may be treated successfully. In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is used. As the first step of the image analysis, preprocessing techniques are used to remove noise and undesired structures from the images using filter such as median filtering. Segmentation is one of the important steps in cancer automatic detection, because it can greatly affect on the results of detection. In the second step, a simple thresholding method is used to segment and localize the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. In the third step, the different features are extracted from a segmented image and classified by using Stolz algorithm.
{"title":"Characterization of skin lesions","authors":"K. Madhankumar, P. Kumar","doi":"10.1109/ICPRIME.2012.6208362","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208362","url":null,"abstract":"Malignant melanoma is the deadliest form among all skin cancers. Fortunately, if detected early, even malignant melanoma may be treated successfully. In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is used. As the first step of the image analysis, preprocessing techniques are used to remove noise and undesired structures from the images using filter such as median filtering. Segmentation is one of the important steps in cancer automatic detection, because it can greatly affect on the results of detection. In the second step, a simple thresholding method is used to segment and localize the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. In the third step, the different features are extracted from a segmented image and classified by using Stolz algorithm.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124010947","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208303
Sagadevan K V Babu, Samson S Arivumani, Asst Pg Scholar, Asst Prof, Prof
Reconfigurability and low complexity are two key requirements of Finite Impulse Response (FIR) filters employed in multi-standard wireless communication systems. In this paper, two new reconfigurable architectures of low complexity FIR filters are proposed, namely Constant Shift Method and Programmable Shift Method. The proposed FIR filter architecture is capable of operating for different wordlength filter coefficients without any overhead in the hardware circuitry. This reconfigurable architecture filters can be efficiently implemented by using common subexpression elimination (CSE) algorithm. Design examples show that the proposed 3 bit Binary Common Subexpression Elimination Constant Shift Method architecture offer speed improvement and Programmable Shift Method architecture offer area and power reduction compared to existing reconfigurable FIR filter.
{"title":"Novel reconfigurable architecture with low complexity FIR filter","authors":"Sagadevan K V Babu, Samson S Arivumani, Asst Pg Scholar, Asst Prof, Prof","doi":"10.1109/ICPRIME.2012.6208303","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208303","url":null,"abstract":"Reconfigurability and low complexity are two key requirements of Finite Impulse Response (FIR) filters employed in multi-standard wireless communication systems. In this paper, two new reconfigurable architectures of low complexity FIR filters are proposed, namely Constant Shift Method and Programmable Shift Method. The proposed FIR filter architecture is capable of operating for different wordlength filter coefficients without any overhead in the hardware circuitry. This reconfigurable architecture filters can be efficiently implemented by using common subexpression elimination (CSE) algorithm. Design examples show that the proposed 3 bit Binary Common Subexpression Elimination Constant Shift Method architecture offer speed improvement and Programmable Shift Method architecture offer area and power reduction compared to existing reconfigurable FIR filter.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116717916","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208373
S. Sekar, K. Prabakaran, E. Paramanathen
In this paper, a new technique known as Single Term Haar Wavelet Series (STHWS) has been presented to determine the solutions for the time varying linear and non-linear singular systems. The exact solutions and the solutions by the classical fourth order Runge-Kutta (RK) method for the problems of time varying linear and non-linear singular systems are compared with the simulated results by STHWS method. This new approach provides a better accuracy in finding discrete solutions of time varying systems for any length of time and it can be easily implemented in a digital computer which is an added advantage of this method.
{"title":"Single-term Haar wavelet series technique for time varying linear and non-linear singular systems","authors":"S. Sekar, K. Prabakaran, E. Paramanathen","doi":"10.1109/ICPRIME.2012.6208373","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208373","url":null,"abstract":"In this paper, a new technique known as Single Term Haar Wavelet Series (STHWS) has been presented to determine the solutions for the time varying linear and non-linear singular systems. The exact solutions and the solutions by the classical fourth order Runge-Kutta (RK) method for the problems of time varying linear and non-linear singular systems are compared with the simulated results by STHWS method. This new approach provides a better accuracy in finding discrete solutions of time varying systems for any length of time and it can be easily implemented in a digital computer which is an added advantage of this method.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127752329","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208294
G. M. Nasira, N. Hemageetha
Each and every sector in this digital world is undergoing a dramatic change due to the influence of IT field. The agricultural sector needs more support for its development in developing countries like India. Price prediction helps the farmers and also Government to make effective decision. Based on the complexity of vegetable price prediction, making use of the characteristics of neural networks such as self-adapt, self-study and high fault tolerance, to build up the model of Back-propagation neural network to predict vegetable price. A prediction model was set up by applying the neural network. Taking tomato as an example, the parameters of the model are analyzed through experiment. At the end of the result of Back-propagation neural network shows absolute error percentage of monthly and weekly vegetable price prediction and analyze the accuracy percentage of the price prediction.
{"title":"Vegetable price prediction using data mining classification technique","authors":"G. M. Nasira, N. Hemageetha","doi":"10.1109/ICPRIME.2012.6208294","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208294","url":null,"abstract":"Each and every sector in this digital world is undergoing a dramatic change due to the influence of IT field. The agricultural sector needs more support for its development in developing countries like India. Price prediction helps the farmers and also Government to make effective decision. Based on the complexity of vegetable price prediction, making use of the characteristics of neural networks such as self-adapt, self-study and high fault tolerance, to build up the model of Back-propagation neural network to predict vegetable price. A prediction model was set up by applying the neural network. Taking tomato as an example, the parameters of the model are analyzed through experiment. At the end of the result of Back-propagation neural network shows absolute error percentage of monthly and weekly vegetable price prediction and analyze the accuracy percentage of the price prediction.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128087383","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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