Lincoln Mohanty, Saikath Bhattacharya, S. S. Singh
One of the most important issues in Wireless Sensor Nodes (WSN) is the proper utilization of the energy and reduction in its consumption. Energy consumption in a node takes place at places: (I) circuit level for processing the data and performing some actions, (II) power consumption during transmission. For our model we have considered both the parameter into a simplified equation. We considered various WSN systems consisting different no of sensor nodes and with different topologies are also selected for our simulation purpose. We found that operating the WSN in a Multi input Multi output (MIMO) manner we can reduce the overall energy of the system. Parameters like first packet send, last packet send, and total bytes send, first packet received, total packet received are compared and analyzed.
{"title":"Efficient Energy Management in Mobile MIMO Cooperative Sensor Networks (M-MCSN)","authors":"Lincoln Mohanty, Saikath Bhattacharya, S. S. Singh","doi":"10.1109/CINE.2016.13","DOIUrl":"https://doi.org/10.1109/CINE.2016.13","url":null,"abstract":"One of the most important issues in Wireless Sensor Nodes (WSN) is the proper utilization of the energy and reduction in its consumption. Energy consumption in a node takes place at places: (I) circuit level for processing the data and performing some actions, (II) power consumption during transmission. For our model we have considered both the parameter into a simplified equation. We considered various WSN systems consisting different no of sensor nodes and with different topologies are also selected for our simulation purpose. We found that operating the WSN in a Multi input Multi output (MIMO) manner we can reduce the overall energy of the system. Parameters like first packet send, last packet send, and total bytes send, first packet received, total packet received are compared and analyzed.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124552962","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}
T. Anandharajan, G. A. Hariharan, K. K. Vignajeth, R. Jijendiran, Kushmita
Weather forecasting is rather a statistical measure than a binary decision. We intend to develop an intelligent weather predicting module since this has become a necessary tool. This tool considers measures such as maximum temperature, minimum temperature and rainfall for a sampled period of days and are analyzed. An intelligent prediction based on the available data is accomplished using machine learning techniques. The analysis and prediction is based on linear regression which predicts the next day's weather with good accuracy. An accuracy of more than 90% is obtained, based on the data set. Recent studies have reflected that machine learning techniques achieved better performance than traditional statistical methods. Machine learning, a branch of artificial intelligence has been proved to be a robust method in predicting and analyzing a given data set. The module plays a vital role in agricultural, industrial and logistical fields where the weather forecast is an important criterion.
{"title":"Weather Monitoring Using Artificial Intelligence","authors":"T. Anandharajan, G. A. Hariharan, K. K. Vignajeth, R. Jijendiran, Kushmita","doi":"10.1109/CINE.2016.26","DOIUrl":"https://doi.org/10.1109/CINE.2016.26","url":null,"abstract":"Weather forecasting is rather a statistical measure than a binary decision. We intend to develop an intelligent weather predicting module since this has become a necessary tool. This tool considers measures such as maximum temperature, minimum temperature and rainfall for a sampled period of days and are analyzed. An intelligent prediction based on the available data is accomplished using machine learning techniques. The analysis and prediction is based on linear regression which predicts the next day's weather with good accuracy. An accuracy of more than 90% is obtained, based on the data set. Recent studies have reflected that machine learning techniques achieved better performance than traditional statistical methods. Machine learning, a branch of artificial intelligence has been proved to be a robust method in predicting and analyzing a given data set. The module plays a vital role in agricultural, industrial and logistical fields where the weather forecast is an important criterion.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115429641","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}
In this paper, an optimization algorithm is proposed for solving combinatorial optimization problems. The designing of the algorithm is based on the Bohr's atomic model. Microcosm of physics and chemistry such as excitation and de-excitation of electrons in atom and atom's bond formation phenomenon are the key mechanism of this algorithm. Atoms form compounds to minimize the energy of their electrons and become more stable, with this quest positively charged atoms attracts negatively charged atoms to form bonds among them. Utilizing these phenomenon to attain more stable state of an atom, a novel strategy is incorporated into the algorithm. This stable state is resembled with global optima in the proposed algorithm. Performance of proposed algorithm is analyzed on real life combinatorial optimization problems.
{"title":"An Atomic Model Based Optimization Algorithm","authors":"A. Biswas, Bhaskar Biswas, K. Mishra","doi":"10.1109/CINE.2016.18","DOIUrl":"https://doi.org/10.1109/CINE.2016.18","url":null,"abstract":"In this paper, an optimization algorithm is proposed for solving combinatorial optimization problems. The designing of the algorithm is based on the Bohr's atomic model. Microcosm of physics and chemistry such as excitation and de-excitation of electrons in atom and atom's bond formation phenomenon are the key mechanism of this algorithm. Atoms form compounds to minimize the energy of their electrons and become more stable, with this quest positively charged atoms attracts negatively charged atoms to form bonds among them. Utilizing these phenomenon to attain more stable state of an atom, a novel strategy is incorporated into the algorithm. This stable state is resembled with global optima in the proposed algorithm. Performance of proposed algorithm is analyzed on real life combinatorial optimization problems.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125485859","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}
The multi-antenna relay cooperation-hybrid (MARC-H) scheme. This paper studied the impact of MARC-H on the performance of moving (line of sight (LOS) between source and destination) multi-antenna relay. The MARC-H opts adaptively either Decode-and-Forward (DF) or Amplify-and-Forward (AF) scheme based on the relay placement. In particular, this paper analyzed the outage performance of MARC-H scheme and compared with multi-antenna relay cooperation-AF (MARC-AF) and multi-antenna relay cooperation-DF (MARC-DF) schemes. Maximal ratio combining (MRC) and selection combining (SC) are performed at destination in order to compare outage probability. The effect of number of antennas installed on the relay node and its placement on the MARC-H have also been studied.
{"title":"Performance Analysis of Moving Multi-antenna Relay Cooperation with Hybrid Relaying Scheme in Cooperative Wireless Networks","authors":"P. Sunil","doi":"10.1109/CINE.2016.36","DOIUrl":"https://doi.org/10.1109/CINE.2016.36","url":null,"abstract":"The multi-antenna relay cooperation-hybrid (MARC-H) scheme. This paper studied the impact of MARC-H on the performance of moving (line of sight (LOS) between source and destination) multi-antenna relay. The MARC-H opts adaptively either Decode-and-Forward (DF) or Amplify-and-Forward (AF) scheme based on the relay placement. In particular, this paper analyzed the outage performance of MARC-H scheme and compared with multi-antenna relay cooperation-AF (MARC-AF) and multi-antenna relay cooperation-DF (MARC-DF) schemes. Maximal ratio combining (MRC) and selection combining (SC) are performed at destination in order to compare outage probability. The effect of number of antennas installed on the relay node and its placement on the MARC-H have also been studied.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122300092","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}
Annapurna Pradhan, Nibedita Pati, Suvendu Rup, Avipsa S. Panda
The paper presents a modified framework for image compression using Burrow Wheeler Transform (BWT). The BWT is widely used in text compression but very few attempts have been made to BWT in image compression. Just like text compression it will not directly apply to an image. After performing some recorder arrangement it has been applied successively in an image compression framework. In the proposed approach it is applied before entropy coding and it has observed that a significant amount of improvement in terms of compression efficiency is achieved as compared to the JPEG and wavelet based JPEG2000 approach. The proposed scheme is simulated along with other standard image coding scheme. Performance comparisons have been made with respect to PSNR in (db), rate distortion performance in terms of bit rate (bpp) vs. PSNR and compression ratio. In general, it is obtained that the proposed scheme has a superior performance as compared to its competent schemes.
{"title":"A Modified Framework for Image Compression Using Burrows-Wheeler Transform","authors":"Annapurna Pradhan, Nibedita Pati, Suvendu Rup, Avipsa S. Panda","doi":"10.1109/CINE.2016.33","DOIUrl":"https://doi.org/10.1109/CINE.2016.33","url":null,"abstract":"The paper presents a modified framework for image compression using Burrow Wheeler Transform (BWT). The BWT is widely used in text compression but very few attempts have been made to BWT in image compression. Just like text compression it will not directly apply to an image. After performing some recorder arrangement it has been applied successively in an image compression framework. In the proposed approach it is applied before entropy coding and it has observed that a significant amount of improvement in terms of compression efficiency is achieved as compared to the JPEG and wavelet based JPEG2000 approach. The proposed scheme is simulated along with other standard image coding scheme. Performance comparisons have been made with respect to PSNR in (db), rate distortion performance in terms of bit rate (bpp) vs. PSNR and compression ratio. In general, it is obtained that the proposed scheme has a superior performance as compared to its competent schemes.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437780","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}
Sunil Kumar, M. Pandey, A. Nath, Karthikeyan Subbiah
In this era of cloud computing, web services based solutions are gaining popularity. The applications running on distributed environment seek new parameters for them to perform efficiently to satisfy end user's requirements. Finding these parameters for increasing efficiency has become a talk of researchers now days. Non functional performance of a web service is described through User dependent QoS properties. These QoS parameters are generally described in WS-Policy in Service Level Agreement (SLA). Usually in web service QoS datasets, web service QoS values are missing, which makes missing value imputations an important job while working with cloud web services. In the current work we compared the prediction accuracy of two groups of supervised machine learning ensembles based Meta learners: bagging and additive regression (boosting) with a fusion of the seven base learners in both. Random forest is found to be better performing in both Meta learners: bagging and boosting than other learning algorithms.
{"title":"Performance Analysis of Ensemble Supervised Machine Learning Algorithms for Missing Value Imputation","authors":"Sunil Kumar, M. Pandey, A. Nath, Karthikeyan Subbiah","doi":"10.1109/CINE.2016.35","DOIUrl":"https://doi.org/10.1109/CINE.2016.35","url":null,"abstract":"In this era of cloud computing, web services based solutions are gaining popularity. The applications running on distributed environment seek new parameters for them to perform efficiently to satisfy end user's requirements. Finding these parameters for increasing efficiency has become a talk of researchers now days. Non functional performance of a web service is described through User dependent QoS properties. These QoS parameters are generally described in WS-Policy in Service Level Agreement (SLA). Usually in web service QoS datasets, web service QoS values are missing, which makes missing value imputations an important job while working with cloud web services. In the current work we compared the prediction accuracy of two groups of supervised machine learning ensembles based Meta learners: bagging and additive regression (boosting) with a fusion of the seven base learners in both. Random forest is found to be better performing in both Meta learners: bagging and boosting than other learning algorithms.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124481057","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}
Alok Kumar, Jai Ram Singh, Dinesh Singh, R. Dewang
Vehicular Ad-hoc Network (VANET) is a promising technology with a great potential for providing enhanced safety and convenience to the drivers and passengers. The majority of application in VANET involves exchange of information amongst vehicles. An adversary may take this as an advantage to disturb the network by disseminating false information about any occurred event on the road. In this paper, we propose a Historical Feedback based Misbehavior Detection Algorithm (HFMDA) to detect the misbehavior vehicles inside from the network. In this algorithm, an observer vehicle sends a notification to the nearest RSU against a crash-event occurred on the road. Here we assume that all vehicles accumulate its past history for event notifications. All the vehicles maintains this history with two parameters: Event Notifications (EN) and True Event Notification (TEN). In proposed HFMD algorithm, a vehicle's historical record is firstly check to know its past misbehavior history and an RSU_Verification algorithm is used to verify the status of current received notification at the RSU. The proposed hybrid algorithm i.e. data centric and event centric, is a RSU side algorithm instead of vehicle side. The RSU overhead is significantly reduced through the proposed algorithm since verification of only highest trusted vehicle is done.
{"title":"A Historical Feedback Based Misbehavior Detection (HFMD) Algorithm in VANET","authors":"Alok Kumar, Jai Ram Singh, Dinesh Singh, R. Dewang","doi":"10.1109/CINE.2016.11","DOIUrl":"https://doi.org/10.1109/CINE.2016.11","url":null,"abstract":"Vehicular Ad-hoc Network (VANET) is a promising technology with a great potential for providing enhanced safety and convenience to the drivers and passengers. The majority of application in VANET involves exchange of information amongst vehicles. An adversary may take this as an advantage to disturb the network by disseminating false information about any occurred event on the road. In this paper, we propose a Historical Feedback based Misbehavior Detection Algorithm (HFMDA) to detect the misbehavior vehicles inside from the network. In this algorithm, an observer vehicle sends a notification to the nearest RSU against a crash-event occurred on the road. Here we assume that all vehicles accumulate its past history for event notifications. All the vehicles maintains this history with two parameters: Event Notifications (EN) and True Event Notification (TEN). In proposed HFMD algorithm, a vehicle's historical record is firstly check to know its past misbehavior history and an RSU_Verification algorithm is used to verify the status of current received notification at the RSU. The proposed hybrid algorithm i.e. data centric and event centric, is a RSU side algorithm instead of vehicle side. The RSU overhead is significantly reduced through the proposed algorithm since verification of only highest trusted vehicle is done.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123228691","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}
A vehicular ad hoc network (VANET) uses vehicles as mobile nodes to create a network. The increasing number of vehicle on road creates alot of problem to the vehicle driver as well as passengers. VANET is network which is developed to face these situations and provide road safety and comfortable journey to the driver. In this network each vehicle can communicate to other vehicle and share the rode condition to each other. By shared information in the network, drivers take its own decision. So each messages hared in the network should be authentic if not, a wrong information leads to dangers situation for the driver. If a vehicle is sharing a wrong information it must be removed from the communicating network by adding its certificates in the Certificate Revocation List (CRL). Here we propose a method, how the certificate of vehicle is revoke when it misbehaves. In our proposed method we use a fully trusted vehicle i.e. RTO Vehicle on the road. There vocation decision is taken by RTO vehicle which observe the behavior of vehicle before revoking it. It also observes the position of malicious vehicle in its range and inform to other vehicle in the proximity of malicious vehicle. This method significantly improves the revocation process speed and distribution of latest CRL in the network very fast.
{"title":"A Single-Hop Based Fast Certificate Revocation Protocol in VANET","authors":"Jaya Singh, Alok Kumar, Dinesh Singh, R. Dewang","doi":"10.1109/CINE.2016.12","DOIUrl":"https://doi.org/10.1109/CINE.2016.12","url":null,"abstract":"A vehicular ad hoc network (VANET) uses vehicles as mobile nodes to create a network. The increasing number of vehicle on road creates alot of problem to the vehicle driver as well as passengers. VANET is network which is developed to face these situations and provide road safety and comfortable journey to the driver. In this network each vehicle can communicate to other vehicle and share the rode condition to each other. By shared information in the network, drivers take its own decision. So each messages hared in the network should be authentic if not, a wrong information leads to dangers situation for the driver. If a vehicle is sharing a wrong information it must be removed from the communicating network by adding its certificates in the Certificate Revocation List (CRL). Here we propose a method, how the certificate of vehicle is revoke when it misbehaves. In our proposed method we use a fully trusted vehicle i.e. RTO Vehicle on the road. There vocation decision is taken by RTO vehicle which observe the behavior of vehicle before revoking it. It also observes the position of malicious vehicle in its range and inform to other vehicle in the proximity of malicious vehicle. This method significantly improves the revocation process speed and distribution of latest CRL in the network very fast.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285856","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}
Recent dynamic advances in Telecom evolution calls for optimization of technologies, something which we continually learn from the nature. Adaptive intelligent machines, inspired from biological evolution, should emerge as cost-controlled, energy-efficient and sustainable alternatives for future generations. In this paper, we review the different evolving intelligent techniques implemented in various dimensions of telecommunication networks.
{"title":"Communication Converging towards Adaptive Intelligence: A Survey","authors":"Avijit Paul, Amrita Mukherjee Paul, Kuntal Ghosh","doi":"10.1109/CINE.2016.10","DOIUrl":"https://doi.org/10.1109/CINE.2016.10","url":null,"abstract":"Recent dynamic advances in Telecom evolution calls for optimization of technologies, something which we continually learn from the nature. Adaptive intelligent machines, inspired from biological evolution, should emerge as cost-controlled, energy-efficient and sustainable alternatives for future generations. In this paper, we review the different evolving intelligent techniques implemented in various dimensions of telecommunication networks.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121086702","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}
Sushil Kumar Mahapatra, Sumant Kumar Mohapatra, Sakuntala Mahapatra, S. K. Tripathy
Recently, Scientists needs to know the behavior of fish populations in underwater. Previously many algorithms are used but they are suffered in complex textures and low detection rate. This paper proposed a multi threading fuzzy c-mean (MFC mean) approach to detect multi-moving fishes in a noisy and dense condition. In this approach, we combines the multi threaded parallel (MTP) approach and kernel based approach for optical flow. A fuzzy c-mean concept provided as a supporting factor. The simulation results show that the proposed method can able to track and detect underwater fishes with high detection rate.
{"title":"A Proposed Multithreading Fuzzy C-Mean Algorithm for Detecting Underwater Fishes","authors":"Sushil Kumar Mahapatra, Sumant Kumar Mohapatra, Sakuntala Mahapatra, S. K. Tripathy","doi":"10.1109/CINE.2016.25","DOIUrl":"https://doi.org/10.1109/CINE.2016.25","url":null,"abstract":"Recently, Scientists needs to know the behavior of fish populations in underwater. Previously many algorithms are used but they are suffered in complex textures and low detection rate. This paper proposed a multi threading fuzzy c-mean (MFC mean) approach to detect multi-moving fishes in a noisy and dense condition. In this approach, we combines the multi threaded parallel (MTP) approach and kernel based approach for optical flow. A fuzzy c-mean concept provided as a supporting factor. The simulation results show that the proposed method can able to track and detect underwater fishes with high detection rate.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127403942","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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