V. Mezhuyev, V. Lavrik, R. Samikannu, Y. Gunchenko
Paper discusses a potential of the metamodelling technology to improve computer-based methods of geometrical modelling. The meta-metamodel for the development of the geometrical modelling languages is proposed. It is defined as a formal system, which consists of geometrical metatypes, grammar and operations. The grammar rules are expressed as logical formulas, setting constraints on the geometric structure of a model. Paper proposes an additional system of relations for constructing the grammatical rules of geometrical languages. It is shown that use of the metamodeling makes the process of a geometrical design more effective.
{"title":"Metamodel for The Development of Geometrical Modelling Languages","authors":"V. Mezhuyev, V. Lavrik, R. Samikannu, Y. Gunchenko","doi":"10.1145/3209914.3209926","DOIUrl":"https://doi.org/10.1145/3209914.3209926","url":null,"abstract":"Paper discusses a potential of the metamodelling technology to improve computer-based methods of geometrical modelling. The meta-metamodel for the development of the geometrical modelling languages is proposed. It is defined as a formal system, which consists of geometrical metatypes, grammar and operations. The grammar rules are expressed as logical formulas, setting constraints on the geometric structure of a model. Paper proposes an additional system of relations for constructing the grammatical rules of geometrical languages. It is shown that use of the metamodeling makes the process of a geometrical design more effective.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123665577","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}
Jeonghyo Ha, Jung Eun, Pyunghwan Ahn, Dong-Hoon Shin, Junmo Kim
In this paper, we describe a training methodology of convolutional neural networks(CNNs) using data from a different domain when the number of training data in the test domain is small. Training a CNN for classification without enough data might lead to serious problems of overfitting and thus fail to generalize. In this case, if large data of the same object categories is available in another domain, this problem can be alleviated. We propose a method to train a CNN with small data in the test domain and large data in another. Since training a single network using data from different domains could lead to performance degradation, we consider this problem as cross-domain image similarity learning. In our experiment, we train a Siamese network to compute similarity between a pair of images from different domains, which are natural photos and 3D model projections. We design the network to output the probability that the input image pair belongs to the same category. Thus, the network can calculate similarity between the input pair and also classify a natural photo by comparing it with each images in the 3D model database. Since the network output represents similarity, we can greatly reduce testing time for classification compared to other methods (such as NN classification) in which distances between feature vectors must be calculated for every pair of images.
{"title":"Learning Convolutional Neural Network Using Data from Other Domains in case of Insufficient Data","authors":"Jeonghyo Ha, Jung Eun, Pyunghwan Ahn, Dong-Hoon Shin, Junmo Kim","doi":"10.1145/3209914.3209927","DOIUrl":"https://doi.org/10.1145/3209914.3209927","url":null,"abstract":"In this paper, we describe a training methodology of convolutional neural networks(CNNs) using data from a different domain when the number of training data in the test domain is small. Training a CNN for classification without enough data might lead to serious problems of overfitting and thus fail to generalize. In this case, if large data of the same object categories is available in another domain, this problem can be alleviated. We propose a method to train a CNN with small data in the test domain and large data in another. Since training a single network using data from different domains could lead to performance degradation, we consider this problem as cross-domain image similarity learning. In our experiment, we train a Siamese network to compute similarity between a pair of images from different domains, which are natural photos and 3D model projections. We design the network to output the probability that the input image pair belongs to the same category. Thus, the network can calculate similarity between the input pair and also classify a natural photo by comparing it with each images in the 3D model database. Since the network output represents similarity, we can greatly reduce testing time for classification compared to other methods (such as NN classification) in which distances between feature vectors must be calculated for every pair of images.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126456896","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, we consider network-based VM migration in the Edge Computing environment, which provides minimized downtime and user processing load. The architecture and interfaces for network-based VM migration in an edge computing environment are defined based on 3-tiered network architecture to support various VM migration scenarios depending on network capability and stateful application. We classify the possible migration scenarios in the edge computing architecture and design the functional blocks required for the edge devices to support them.
{"title":"Network-based VM Migration Architecture in Edge Computing","authors":"Kyoungjae Sun, Younghan Kim","doi":"10.1145/3209914.3209930","DOIUrl":"https://doi.org/10.1145/3209914.3209930","url":null,"abstract":"In this paper, we consider network-based VM migration in the Edge Computing environment, which provides minimized downtime and user processing load. The architecture and interfaces for network-based VM migration in an edge computing environment are defined based on 3-tiered network architecture to support various VM migration scenarios depending on network capability and stateful application. We classify the possible migration scenarios in the edge computing architecture and design the functional blocks required for the edge devices to support them.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131037308","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}
Jasmin A. Caliwag, M. C. Aragon, Reynaldo E. Castillo, Ellizer Mikko S. Colantes
Anybody can guess the winners of a basket game. The question is how big the chances are in predicting the real winners. Relying only on the experts' experiences and intuition could not discover all the value and potential of the collected data. Driven by the increasing comprehensive data in sports datasets and data mining technique successfully used in different areas, sports data mining technique emerges and enables us to find hidden knowledge to impact the sports industry. A more scientific approach is needed to use for these data that are collected. Some predictors based only on winning records and some based only on statistical records of both teams. There are also predictors which use both types of data, but the accuracy of applying different individual algorithms is only ranging about 60% - 70%. To achieve better prediction rates and deal with that complexity, a lot of machine learning methods have been implemented over these data. This paper presents an improved technique for predicting basketball game results implementing cascading algorithm. The researchers combined Naive Bayes, Four Factor Analysis, and Fuzzy Logic Algorithms to predict basketball game result in an acceptable level of 69% - 70% accuracy. The researchers tested several times using data sets from NBA game Season 2015-2016, and the cascading algorithm result manages to reach 70% prediction accuracy. The result of this system can be used to assist basketball coaches in making plans for possible team developments. Also, the forecasted results can serve as an aid in building effective gameplay.
{"title":"Predicting Basketball Results Using Cascading Algorithm","authors":"Jasmin A. Caliwag, M. C. Aragon, Reynaldo E. Castillo, Ellizer Mikko S. Colantes","doi":"10.1145/3209914.3209921","DOIUrl":"https://doi.org/10.1145/3209914.3209921","url":null,"abstract":"Anybody can guess the winners of a basket game. The question is how big the chances are in predicting the real winners. Relying only on the experts' experiences and intuition could not discover all the value and potential of the collected data. Driven by the increasing comprehensive data in sports datasets and data mining technique successfully used in different areas, sports data mining technique emerges and enables us to find hidden knowledge to impact the sports industry. A more scientific approach is needed to use for these data that are collected. Some predictors based only on winning records and some based only on statistical records of both teams. There are also predictors which use both types of data, but the accuracy of applying different individual algorithms is only ranging about 60% - 70%. To achieve better prediction rates and deal with that complexity, a lot of machine learning methods have been implemented over these data. This paper presents an improved technique for predicting basketball game results implementing cascading algorithm. The researchers combined Naive Bayes, Four Factor Analysis, and Fuzzy Logic Algorithms to predict basketball game result in an acceptable level of 69% - 70% accuracy. The researchers tested several times using data sets from NBA game Season 2015-2016, and the cascading algorithm result manages to reach 70% prediction accuracy. The result of this system can be used to assist basketball coaches in making plans for possible team developments. Also, the forecasted results can serve as an aid in building effective gameplay.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122393562","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}
Hui Guo, Shuguang Huang, Zulie Pan, Jianliang Hu, Minghong Hu
Buffer overflow vulnerability is one of the most common and harmful vulnerabilities in computer software. This paper analyzed and summarized the general method and process of testing buffer overflow vulnerability in software. And the key data structure localization technology in software buffer overflow vulnerability was also studied in this paper. By constructing special filling data and designing location algorithm, this paper presented a new localization technology based on block localization. The technology can locate key data structure address of buffer overflow vulnerability fleetly and exactly. It can effectively assist testing buffer overflow vulnerabilities in software security.
{"title":"Research on Key Data Structure Localization Technology of Buffer Overflow Vulnerability","authors":"Hui Guo, Shuguang Huang, Zulie Pan, Jianliang Hu, Minghong Hu","doi":"10.1145/3209914.3226150","DOIUrl":"https://doi.org/10.1145/3209914.3226150","url":null,"abstract":"Buffer overflow vulnerability is one of the most common and harmful vulnerabilities in computer software. This paper analyzed and summarized the general method and process of testing buffer overflow vulnerability in software. And the key data structure localization technology in software buffer overflow vulnerability was also studied in this paper. By constructing special filling data and designing location algorithm, this paper presented a new localization technology based on block localization. The technology can locate key data structure address of buffer overflow vulnerability fleetly and exactly. It can effectively assist testing buffer overflow vulnerabilities in software security.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129877774","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}
Zhiqian Weng, J. Yang, Qingnian Zhang, Zhiqiang Guo
Aiming at the problems of multi-target tracking, such as occlusion between target and background, similarity of features and random change of the target number, this paper designs a multi-target tracking system which can be used in complex environment. In this thesis, the constraints of scene is added to the target detection algorithm based on the hybrid multiscale deformable model to improve the efficiency. At the same time, the global motion parameter is obtained by using the dual absolute conic constraint. The obtained parameters are used to modify the motion model of target tracking. Then based on the basic particle filter, MCMC (Markov Chain Monte Carlo) improvement strategy and reversibility-jump mechanism (RJ) are added to reduce the computational complexity and solve the stochastic change of target number. Finally, verify the validity of the tracking algorithm in the thesis.
针对多目标跟踪中存在的目标与背景遮挡、特征相似、目标数量随机变化等问题，设计了一种适用于复杂环境的多目标跟踪系统。本文在基于混合多尺度变形模型的目标检测算法中加入了场景约束，提高了算法的效率。同时，利用对偶绝对二次约束得到了整体运动参数。得到的参数用于修改目标跟踪的运动模型。然后在基本粒子滤波的基础上，加入MCMC (Markov Chain Monte Carlo)改进策略和可逆性跳跃机制(reversible -jump mechanism, RJ)来降低计算复杂度，解决目标数的随机变化问题。最后，验证了本文跟踪算法的有效性。
{"title":"Multi-target Tracking Based on Motion Estimation and RJ-MCMC Particle Filter","authors":"Zhiqian Weng, J. Yang, Qingnian Zhang, Zhiqiang Guo","doi":"10.1145/3209914.3209949","DOIUrl":"https://doi.org/10.1145/3209914.3209949","url":null,"abstract":"Aiming at the problems of multi-target tracking, such as occlusion between target and background, similarity of features and random change of the target number, this paper designs a multi-target tracking system which can be used in complex environment. In this thesis, the constraints of scene is added to the target detection algorithm based on the hybrid multiscale deformable model to improve the efficiency. At the same time, the global motion parameter is obtained by using the dual absolute conic constraint. The obtained parameters are used to modify the motion model of target tracking. Then based on the basic particle filter, MCMC (Markov Chain Monte Carlo) improvement strategy and reversibility-jump mechanism (RJ) are added to reduce the computational complexity and solve the stochastic change of target number. Finally, verify the validity of the tracking algorithm in the thesis.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122701221","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}
With the rapid development of information technology, information and digitalization have entered almost every walk of life, therefore, modern hospital information construction needs to combine various new technologies to improve hospital medical quality, work efficiency and management level. At the same time, the hospital data is becoming more and more intensive and the processing is becoming more and more laborious, so, we need to find new ways to solve those problems. This made the cloud computing which can collect and process large amounts of resources appear in hospital information construction. Based on the author's learning and practical experience, this paper first summarized the related theories of cloud computing, and then analyzed the importance of cloud computing in the process of hospital information, finally put forward some strategies to apply cloud computing technology in hospital information construction.
{"title":"A Study on the Application of Cloud Computing Platform in Hospital Information Construction","authors":"Cheng-Yao Chang, Y. Zhu","doi":"10.1145/3209914.3234642","DOIUrl":"https://doi.org/10.1145/3209914.3234642","url":null,"abstract":"With the rapid development of information technology, information and digitalization have entered almost every walk of life, therefore, modern hospital information construction needs to combine various new technologies to improve hospital medical quality, work efficiency and management level. At the same time, the hospital data is becoming more and more intensive and the processing is becoming more and more laborious, so, we need to find new ways to solve those problems. This made the cloud computing which can collect and process large amounts of resources appear in hospital information construction. Based on the author's learning and practical experience, this paper first summarized the related theories of cloud computing, and then analyzed the importance of cloud computing in the process of hospital information, finally put forward some strategies to apply cloud computing technology in hospital information construction.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123252498","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}
Nowadays, researcher is focus in developing reliable iris recognition systems for non-cooperative situations. The demand for iris recognition is increasing due to its reliability, accuracy and uniqueness. There are major factors involved in unconstrained environment such as obstruction by eyelids, eyelashes, glass frames, hair, off-angle, presence of contact lenses, poor illumination, motion blur, lighting and specular reflections, partially eye image, etc. The performance of the iris will be deteriorated and this results in lower recognition rate. In this paper, an overview of iris recognition for noisy imaging environments is presented included various related databases for iris recognition systems.
{"title":"A Review on Iris Recognition in Non-Cooperative Environment","authors":"Nurul Amirah Mashudi, Md. Jan Nordin","doi":"10.1145/3209914.3209925","DOIUrl":"https://doi.org/10.1145/3209914.3209925","url":null,"abstract":"Nowadays, researcher is focus in developing reliable iris recognition systems for non-cooperative situations. The demand for iris recognition is increasing due to its reliability, accuracy and uniqueness. There are major factors involved in unconstrained environment such as obstruction by eyelids, eyelashes, glass frames, hair, off-angle, presence of contact lenses, poor illumination, motion blur, lighting and specular reflections, partially eye image, etc. The performance of the iris will be deteriorated and this results in lower recognition rate. In this paper, an overview of iris recognition for noisy imaging environments is presented included various related databases for iris recognition systems.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130688928","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}
This paper aims to gradually transform the network public data information into a new social public property and to build a future knowledge society through the development of semantic web. In the context that nowadays the network public data information is being transformed into the common property of the whole society, it is of great significance for to building a technical framework for the generation, publication, aggregation, dissemination and reuse of public data by means of the semantic web and data opening, which lays the digital ecological foundation for the economic development of future knowledge society. The core innovation of this research is building up the framework of public property management through public data reuse with semantic web and data opening as the technical basis by taking the data opening policy and measures in France as an example. Open data services enable collaborative innovation and "win-win" mode for public institutions, private enterprises and individuals, encourage young people to lead innovation management and development, and gradually transform the economic model of France and Europe from "scarcity" to "post-scarcity". Compared with previous researches, the innovative part of the paper is the study of the reuse of public data and information property of France, encouraging the role of "sharing" in promoting the "post-scarcity" economic model, and building the future development model of knowledge society for France and Europe. By studying the relevant policies and measures of public data reuse implemented by France and by analyzing the effect, this paper proves that the reuse of public data and information property plays an important role in the construction of knowledge society.
{"title":"Reuse of Public Data and Information Property and Building of Knowledge Society","authors":"X. Zhang, Deling Yang","doi":"10.1145/3209914.3226156","DOIUrl":"https://doi.org/10.1145/3209914.3226156","url":null,"abstract":"This paper aims to gradually transform the network public data information into a new social public property and to build a future knowledge society through the development of semantic web. In the context that nowadays the network public data information is being transformed into the common property of the whole society, it is of great significance for to building a technical framework for the generation, publication, aggregation, dissemination and reuse of public data by means of the semantic web and data opening, which lays the digital ecological foundation for the economic development of future knowledge society. The core innovation of this research is building up the framework of public property management through public data reuse with semantic web and data opening as the technical basis by taking the data opening policy and measures in France as an example. Open data services enable collaborative innovation and \"win-win\" mode for public institutions, private enterprises and individuals, encourage young people to lead innovation management and development, and gradually transform the economic model of France and Europe from \"scarcity\" to \"post-scarcity\". Compared with previous researches, the innovative part of the paper is the study of the reuse of public data and information property of France, encouraging the role of \"sharing\" in promoting the \"post-scarcity\" economic model, and building the future development model of knowledge society for France and Europe. By studying the relevant policies and measures of public data reuse implemented by France and by analyzing the effect, this paper proves that the reuse of public data and information property plays an important role in the construction of knowledge society.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126765299","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}
Fog computing has emerged due to the problem that it becomes difficult to store every data to the cloud system as the number of Internet of Things increases. In this fog computing, a vast amount of data generated from the Internet of Things is transmitted to the cloud system located at a remote place, and is processed by a fog computer such as a sensor or a router located nearby, so that only the necessary data is transmitted to the cloud system. However, the above-mentioned fog computer has some drawbacks like being shut down due to an attack by a malicious user in advance, and a method of processing when a fog computer is down or restored. In this paper we describe a fog computing with blockchain that enables fog computers to share transaction generated by processing transaction information of a device controlled by a blockchain method to a security and device control method of a fog computer utilizing the technology. Furthemore by using security properties of blockchain such as authentication, non-repudiation and data integrity, fog computing using blockchain has advantage of security comparing to previous Cloud and fog computing system using centralized database or P2P networks.
{"title":"Security and Device Control Method for Fog Computer using Blockchain","authors":"Junhyeon Jeong, Bo Youn Kim, J. Jang","doi":"10.1145/3209914.3209917","DOIUrl":"https://doi.org/10.1145/3209914.3209917","url":null,"abstract":"Fog computing has emerged due to the problem that it becomes difficult to store every data to the cloud system as the number of Internet of Things increases. In this fog computing, a vast amount of data generated from the Internet of Things is transmitted to the cloud system located at a remote place, and is processed by a fog computer such as a sensor or a router located nearby, so that only the necessary data is transmitted to the cloud system. However, the above-mentioned fog computer has some drawbacks like being shut down due to an attack by a malicious user in advance, and a method of processing when a fog computer is down or restored. In this paper we describe a fog computing with blockchain that enables fog computers to share transaction generated by processing transaction information of a device controlled by a blockchain method to a security and device control method of a fog computer utilizing the technology. Furthemore by using security properties of blockchain such as authentication, non-repudiation and data integrity, fog computing using blockchain has advantage of security comparing to previous Cloud and fog computing system using centralized database or P2P networks.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124759550","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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