Lubrication is one of the essential parts of various processes and instruments namely rotational devices such as bearings. Artificial intelligence (AI) systems such as artificial neural networks (ANNs) have been applied to solve, predict and optimize in engineering problems in the last decade. Present study assesses the capability of artificial neural networks (ANNs) in estimating viscosity of lubricants used in the lubrication of journal bearings. Using neural networks instead of running various tests to predict lubricant viscosity reduces costs and eliminates the necessity of using various devices and instruments by the researcher. The data of SAE 10, 20, 30, and 40 lubricants were used to train the neural networks. Back propagation (BP) error algorithm employed to networks training. Also, lubricant temperature was used as the input and its viscosity as the output of the simulation. In order to increase the accuracy of network training, a separate network was learned for each grade of lubricant, and the structure of each neural network and the effective parameters were optimized for each lubricant type through trial-and-error so that they would make more accurate predictions. The results of this simulation show that the error of neural networks in estimating lubricant viscosity in SAE 10, 20, 30, and 40 lubricants are in very small range, which indicate the capability of neural networks in the estimation of the desired parameters.
{"title":"Investigation of Artificial Neural Networks Capability to Predict Viscosity of Lubricants Used in Journal Bearings","authors":"E. Maleki, H. Sadrhosseini, A. Ghiami","doi":"10.1145/2832987.2833019","DOIUrl":"https://doi.org/10.1145/2832987.2833019","url":null,"abstract":"Lubrication is one of the essential parts of various processes and instruments namely rotational devices such as bearings. Artificial intelligence (AI) systems such as artificial neural networks (ANNs) have been applied to solve, predict and optimize in engineering problems in the last decade. Present study assesses the capability of artificial neural networks (ANNs) in estimating viscosity of lubricants used in the lubrication of journal bearings. Using neural networks instead of running various tests to predict lubricant viscosity reduces costs and eliminates the necessity of using various devices and instruments by the researcher. The data of SAE 10, 20, 30, and 40 lubricants were used to train the neural networks. Back propagation (BP) error algorithm employed to networks training. Also, lubricant temperature was used as the input and its viscosity as the output of the simulation. In order to increase the accuracy of network training, a separate network was learned for each grade of lubricant, and the structure of each neural network and the effective parameters were optimized for each lubricant type through trial-and-error so that they would make more accurate predictions. The results of this simulation show that the error of neural networks in estimating lubricant viscosity in SAE 10, 20, 30, and 40 lubricants are in very small range, which indicate the capability of neural networks in the estimation of the desired parameters.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131324013","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}
Ibrihich Ouafaa, Laassiri Jalal, Krit Salah-ddine, E. Said
The hierarchical clustering is an efficient way to reduce the overall energy consumption within the cluster by performing aggregation and fusion of data. Clusters create hierarchical WSNs, which facilitate efficient utilization of limited resources of sensor nodes and thus extend network lifetime, reduce energy consumption of the system and provide overall system scalability. The proposed work of this paper is to provide an overview of hierarchical protocols and an overview of the protocol's performance. In this paper, we present the study of different clustering routing protocols of WSN and Ad-Hoc. The main focus of this paper is to give the comparison of different hierarchical routing protocols between WSNs and Ad-Hoc on various parameters.
{"title":"The Comparison Study of Hierarchical Routing Protocols for Ad-Hoc and Wireless Sensor Networks: A Literature Survey","authors":"Ibrihich Ouafaa, Laassiri Jalal, Krit Salah-ddine, E. Said","doi":"10.1145/2832987.2833039","DOIUrl":"https://doi.org/10.1145/2832987.2833039","url":null,"abstract":"The hierarchical clustering is an efficient way to reduce the overall energy consumption within the cluster by performing aggregation and fusion of data. Clusters create hierarchical WSNs, which facilitate efficient utilization of limited resources of sensor nodes and thus extend network lifetime, reduce energy consumption of the system and provide overall system scalability. The proposed work of this paper is to provide an overview of hierarchical protocols and an overview of the protocol's performance. In this paper, we present the study of different clustering routing protocols of WSN and Ad-Hoc. The main focus of this paper is to give the comparison of different hierarchical routing protocols between WSNs and Ad-Hoc on various parameters.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126764861","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}
Mining medical datasets is a challenging problem before data mining researchers as these datasets have several hidden challenges compared to conventional datasets. Starting from the collection of samples through field experiments and clinical trials to performing classification, there are numerous challenges at every stage in the mining process. The preprocessing phase in the mining process itself is a challenging issue when, we work on medical datasets. One of the prime challenges in mining medical datasets is handling missing values which is part of preprocessing phase. In this paper, we address the issue of handling missing values in medical dataset consisting of categorical attribute values. The main contribution of this research is to use the proposed imputation measure to estimate and fix the missing values. We discuss a case study to demonstrate the working of proposed measure.
{"title":"An Approach to Find Missing Values in Medical Datasets","authors":"B. Bai, N.Mangathayaru, B. Rani","doi":"10.1145/2832987.2833083","DOIUrl":"https://doi.org/10.1145/2832987.2833083","url":null,"abstract":"Mining medical datasets is a challenging problem before data mining researchers as these datasets have several hidden challenges compared to conventional datasets. Starting from the collection of samples through field experiments and clinical trials to performing classification, there are numerous challenges at every stage in the mining process. The preprocessing phase in the mining process itself is a challenging issue when, we work on medical datasets. One of the prime challenges in mining medical datasets is handling missing values which is part of preprocessing phase. In this paper, we address the issue of handling missing values in medical dataset consisting of categorical attribute values. The main contribution of this research is to use the proposed imputation measure to estimate and fix the missing values. We discuss a case study to demonstrate the working of proposed measure.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115134103","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}
Mamoun Qasem, A. Al-Dubai, R. Imed, Muneer Bani Yassien
Energy is a precious resource in Internet of Things (IoT) especially with battery operated nodes, the overhead that consumes the battery power of the sensor nodes is a fundamental problem. This overhead is mainly caused by the frequent update messages sent to service directories. Although this problem has been investigated in the literature, it is still in its infancy as existing works do not consider the dynamic adjustments of the update messages. To fill in this gap, this paper presents a new adaptive tuning approach between sensor nodes and the resource directory to adjust the frequency of updates based on the battery level of the sensing node. Our protocol works dynamically in both modes, stateless and stateful service registration mechanisms.
{"title":"ATP: Adaptive Tuning Protocol for Service Discovery in Internet of Things","authors":"Mamoun Qasem, A. Al-Dubai, R. Imed, Muneer Bani Yassien","doi":"10.1145/2832987.2833058","DOIUrl":"https://doi.org/10.1145/2832987.2833058","url":null,"abstract":"Energy is a precious resource in Internet of Things (IoT) especially with battery operated nodes, the overhead that consumes the battery power of the sensor nodes is a fundamental problem. This overhead is mainly caused by the frequent update messages sent to service directories. Although this problem has been investigated in the literature, it is still in its infancy as existing works do not consider the dynamic adjustments of the update messages. To fill in this gap, this paper presents a new adaptive tuning approach between sensor nodes and the resource directory to adjust the frequency of updates based on the battery level of the sensing node. Our protocol works dynamically in both modes, stateless and stateful service registration mechanisms.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124666002","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}
B. Barán, J. Paciello, Vanessa J. Cañete, N. Hernández
The electrical energy distribution subsystem is a component of the power delivery infrastructure that carries electricity from the high voltage transmission circuits to the customers. In order to prevent damage of the electrical energy distribution infrastructure, companies typically use transformers with digital meters that allow monitoring in real time, certain parameters like the amount of transformed energy. In several underdeveloped countries as Paraguay, the meters are installed only on a limited number of key transformers. Therefore, it is necessary to estimate the power consumption for the unmetered transformers using existing measurements. For this aim, this paper proposes the application of Linear Genetic Programming (LGP) to find good estimates of the power consumption of unmetered transformers. The proposal is compared with an analytical consumption estimation model proposed in a previous related work, being 13% better on average and 41% better in the best case. Dimensionality reduction proves to be useful to speed up calculation without losing much precision in the LGP estimations.
{"title":"Estimating electrical energy consumption using Linear Genetic Programming","authors":"B. Barán, J. Paciello, Vanessa J. Cañete, N. Hernández","doi":"10.1145/2832987.2833021","DOIUrl":"https://doi.org/10.1145/2832987.2833021","url":null,"abstract":"The electrical energy distribution subsystem is a component of the power delivery infrastructure that carries electricity from the high voltage transmission circuits to the customers. In order to prevent damage of the electrical energy distribution infrastructure, companies typically use transformers with digital meters that allow monitoring in real time, certain parameters like the amount of transformed energy. In several underdeveloped countries as Paraguay, the meters are installed only on a limited number of key transformers. Therefore, it is necessary to estimate the power consumption for the unmetered transformers using existing measurements. For this aim, this paper proposes the application of Linear Genetic Programming (LGP) to find good estimates of the power consumption of unmetered transformers. The proposal is compared with an analytical consumption estimation model proposed in a previous related work, being 13% better on average and 41% better in the best case. Dimensionality reduction proves to be useful to speed up calculation without losing much precision in the LGP estimations.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131452585","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}
Temporal database is a database which captures and maintains past, present and future data. Conventional databases are not suitable for handling such time varying data. In this context temporal database has gained a significant importance in the field of databases and data mining. The major objective of this research is to perform a detailed survey on temporal databases and the various temporal data mining techniques and explore the various research issues in temporal data mining. We also throw light on the temporal association rules and temporal clustering works carried in literature.
{"title":"A Survey on Temporal Databases and Data mining","authors":"V. Radhakrishna, P. Kumar, V. Janaki","doi":"10.1145/2832987.2833064","DOIUrl":"https://doi.org/10.1145/2832987.2833064","url":null,"abstract":"Temporal database is a database which captures and maintains past, present and future data. Conventional databases are not suitable for handling such time varying data. In this context temporal database has gained a significant importance in the field of databases and data mining. The major objective of this research is to perform a detailed survey on temporal databases and the various temporal data mining techniques and explore the various research issues in temporal data mining. We also throw light on the temporal association rules and temporal clustering works carried in literature.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134371181","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}
As a very well-known non-gradient global optimization method, DIviding RECTangles (DIRECT) algorithm has been proven to be an effective and efficient search method for many global optimization problems. However, computation of the algorithm could be costly and slow in solving problems involving computation intensive, Expensive Black Box (EBB) function due to the high number of objective function evolution required. This work proposes a new strategy which integrates meta-modeling techniques with DIRECT for solving EBB problems. The principal idea of the new approach is to use meta-modeling techniques, such as Kriging, to assist DIRECT to identify the optimum with less number of function evolutions. Specifically, the new approach starts with DIRECT search with a number of iterations and then uses the resulting points in Kriging to construct the meta-model. The best point predicted by Kriging search will then be used by DIRECT as new initial point. As a result, the entire search domain will gradually shrink to the region enclosing the possible optimum. Several runs are carried out to avoid high number of function evaluations to obtain the approximation solution at each stage. The newly proposed method has been tested using ten commonly used benchmark functions. All these tests showed significant improvements over the original DIRECT for EBB design problems.
{"title":"An Extension of DIRECT Algorithm Using Kriging Metamodel for Global Optimization","authors":"Abdulbaset El. Saad, Z. Dong","doi":"10.1145/2832987.2833057","DOIUrl":"https://doi.org/10.1145/2832987.2833057","url":null,"abstract":"As a very well-known non-gradient global optimization method, DIviding RECTangles (DIRECT) algorithm has been proven to be an effective and efficient search method for many global optimization problems. However, computation of the algorithm could be costly and slow in solving problems involving computation intensive, Expensive Black Box (EBB) function due to the high number of objective function evolution required. This work proposes a new strategy which integrates meta-modeling techniques with DIRECT for solving EBB problems. The principal idea of the new approach is to use meta-modeling techniques, such as Kriging, to assist DIRECT to identify the optimum with less number of function evolutions. Specifically, the new approach starts with DIRECT search with a number of iterations and then uses the resulting points in Kriging to construct the meta-model. The best point predicted by Kriging search will then be used by DIRECT as new initial point. As a result, the entire search domain will gradually shrink to the region enclosing the possible optimum. Several runs are carried out to avoid high number of function evaluations to obtain the approximation solution at each stage. The newly proposed method has been tested using ten commonly used benchmark functions. All these tests showed significant improvements over the original DIRECT for EBB design problems.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133975539","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 present study concerns experimental measurements of the salting-out effect on liquid-liquid phase equilibrium (LLE) of partially miscible systems such as water/ ethanol/1- butanol /Potassium chloride at 298.15K. The salt KCl was used at different mass percentages of 5, 10 and 15. The binodal and tie line data results were determined by the cloud point method. The addition of the salt showed to be effective in altering the LLE of water/ ethanol/1- butanol system in favor of the solvent extraction of ethanol from the aqueous solution particularly at high salt concentrations. The experimental data were correlated considering the modified version of the NRTL model for the activity coefficient, with the estimation of new binary interaction parameters corresponding to salt-solvent and solvent-solvent pairs. The deviations between experimental and calculated compositions in both phases for the ternary system using these new interaction parameters showed the ability of NRTL to determine liquid-liquid equilibrium data of the studied system in the presence of the salts.
{"title":"Modeling of Liquid-Liquid Equilibrium Data and Estimation of New Binary Interaction Parameters for NRTL Model for the Quaternary System Water/ Ethanol/1-Butanol / KCL at 298.15K","authors":"E. N. Bourayou, A. Méniai, A. Gouaoura","doi":"10.1145/2832987.2832992","DOIUrl":"https://doi.org/10.1145/2832987.2832992","url":null,"abstract":"The present study concerns experimental measurements of the salting-out effect on liquid-liquid phase equilibrium (LLE) of partially miscible systems such as water/ ethanol/1- butanol /Potassium chloride at 298.15K. The salt KCl was used at different mass percentages of 5, 10 and 15. The binodal and tie line data results were determined by the cloud point method. The addition of the salt showed to be effective in altering the LLE of water/ ethanol/1- butanol system in favor of the solvent extraction of ethanol from the aqueous solution particularly at high salt concentrations. The experimental data were correlated considering the modified version of the NRTL model for the activity coefficient, with the estimation of new binary interaction parameters corresponding to salt-solvent and solvent-solvent pairs. The deviations between experimental and calculated compositions in both phases for the ternary system using these new interaction parameters showed the ability of NRTL to determine liquid-liquid equilibrium data of the studied system in the presence of the salts.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117311838","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}
Finding suitable wind speed distribution is one of the most important tasks for the correct estimation of wind energy potential of the specified region. The Weibull distribution is the well-known and suggested distribution in estimating wind energy potential. However, in order to predict wind energy more correctly, new and flexible statistical distributions have been proposed in the last decade. In this study, we introduce a new modified Weibull distribution (MWD) for modelling wind speed and estimating wind power density and also we test MWD versus the classical Weibull distribution on real wind speed data measured in various regions of Turkey. The results of the analysis indicate that MWD suits well for most of the examined wind data cases. Therefore, MWD can be alternatively used for assessment of wind energy potential.
{"title":"Analysis of the Modified Weibull Distribution for Estimation of Wind Speed Distribution","authors":"Ismail Yenilmez, Y. Kantar, I. Arik, I. Usta","doi":"10.1145/2832987.2833059","DOIUrl":"https://doi.org/10.1145/2832987.2833059","url":null,"abstract":"Finding suitable wind speed distribution is one of the most important tasks for the correct estimation of wind energy potential of the specified region. The Weibull distribution is the well-known and suggested distribution in estimating wind energy potential. However, in order to predict wind energy more correctly, new and flexible statistical distributions have been proposed in the last decade. In this study, we introduce a new modified Weibull distribution (MWD) for modelling wind speed and estimating wind power density and also we test MWD versus the classical Weibull distribution on real wind speed data measured in various regions of Turkey. The results of the analysis indicate that MWD suits well for most of the examined wind data cases. Therefore, MWD can be alternatively used for assessment of wind energy potential.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115705198","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}
Two-parameter Weibull distribution has been widely-used reference distribution in wind energy studies and thus its parameter estimation methods have been well-studied in the literature. However, the literature have generally focused on non-robust methods which produce unreliable results in the cases of wind speed data with outliers. In this study, we deal with robust estimation methods of the Weibull distribution for wind energy applications. The considered robust methods are evaluated for both clear and contaminated real wind data cases. It was found that the considered robust methods provides reliable results when it is taken into account in the case of real wind speed data cases. Also, the certain robust methods for the Weibull distribution yield less mean power density error than classical methods in the case of wind speed data with outliers. As a result, it is deduced from analysis that robust methods can be simultaneously used with efficient estimators to check the estimated reliability of the results on wind power.
{"title":"Evaluation of Robust Estimation Methods in Estimating Weibull Parameters for Wind Energy Application","authors":"I. Arik, Y. Kantar, I. Usta, Ismail Yenilmez","doi":"10.1145/2832987.2833041","DOIUrl":"https://doi.org/10.1145/2832987.2833041","url":null,"abstract":"Two-parameter Weibull distribution has been widely-used reference distribution in wind energy studies and thus its parameter estimation methods have been well-studied in the literature. However, the literature have generally focused on non-robust methods which produce unreliable results in the cases of wind speed data with outliers. In this study, we deal with robust estimation methods of the Weibull distribution for wind energy applications. The considered robust methods are evaluated for both clear and contaminated real wind data cases. It was found that the considered robust methods provides reliable results when it is taken into account in the case of real wind speed data cases. Also, the certain robust methods for the Weibull distribution yield less mean power density error than classical methods in the case of wind speed data with outliers. As a result, it is deduced from analysis that robust methods can be simultaneously used with efficient estimators to check the estimated reliability of the results on wind power.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121378479","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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