Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921879
H. Drias
This paper deals with association rules mining using evolutionary algorithms. All previous bio-inspired based association rules mining approaches generate non admissible rules, which cannot be exploited by the end-user. To cope with this issue, we propose two approaches that avoid non admissible rules by developing a new strategy called delete and decomposition strategy. If an item appears in the antecedent and the consequent parts of a given rule, the latter is decomposed in two admissible rules. Then, we delete such item from the antecedent part of the first rule and from the consequent part of the second rule. Afterwards, we design a genetic algorithm called IARMGA and a memetic algorithm called IARMMA for association rules mining. Several experiments were carried out using both synthetic and reals instances. The results reveal a compromise between the execution time and the quality of output rules. IARMGA is faster than IARMMA whereas the latter outperforms the former in terms of rules quality.
{"title":"Genetic algorithm versus memetic algorithm for association rules mining","authors":"H. Drias","doi":"10.1109/NaBIC.2014.6921879","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921879","url":null,"abstract":"This paper deals with association rules mining using evolutionary algorithms. All previous bio-inspired based association rules mining approaches generate non admissible rules, which cannot be exploited by the end-user. To cope with this issue, we propose two approaches that avoid non admissible rules by developing a new strategy called delete and decomposition strategy. If an item appears in the antecedent and the consequent parts of a given rule, the latter is decomposed in two admissible rules. Then, we delete such item from the antecedent part of the first rule and from the consequent part of the second rule. Afterwards, we design a genetic algorithm called IARMGA and a memetic algorithm called IARMMA for association rules mining. Several experiments were carried out using both synthetic and reals instances. The results reveal a compromise between the execution time and the quality of output rules. IARMGA is faster than IARMMA whereas the latter outperforms the former in terms of rules quality.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115791115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921884
Shangling Jui, Chao Lin, Haibing Guan, A. Abraham, A. Hassanien, Kai Xiao
In this paper, we present an image segmentation technique based on fuzzy c-means (FCM) incorporated with wavelet domain noise filtration. With the use of image noise feature estimation composed of preliminary coefficient classification and wavelet domain indicator, a filter for balancing the preservation of relevant details against the degree of noise reduction can be created. The filter is further incorporated with FCM algorithm into the membership function for clustering. This approach allows FCM not only to exploit useful spatial information, but also dynamically minimize clustering errors caused by common noise in medical images. Experimental results suggest its usefulness for reducing FCM clustering noise sensitivity. In MR image segmentation applications, the proposed method outperforms other FCM variations, in terms of quantitative performance measure and visual quality.
{"title":"Fuzzy c-means with wavelet filtration for MR image segmentation","authors":"Shangling Jui, Chao Lin, Haibing Guan, A. Abraham, A. Hassanien, Kai Xiao","doi":"10.1109/NaBIC.2014.6921884","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921884","url":null,"abstract":"In this paper, we present an image segmentation technique based on fuzzy c-means (FCM) incorporated with wavelet domain noise filtration. With the use of image noise feature estimation composed of preliminary coefficient classification and wavelet domain indicator, a filter for balancing the preservation of relevant details against the degree of noise reduction can be created. The filter is further incorporated with FCM algorithm into the membership function for clustering. This approach allows FCM not only to exploit useful spatial information, but also dynamically minimize clustering errors caused by common noise in medical images. Experimental results suggest its usefulness for reducing FCM clustering noise sensitivity. In MR image segmentation applications, the proposed method outperforms other FCM variations, in terms of quantitative performance measure and visual quality.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114947547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921887
Khac Tuan Le, Thi Thanh Binh Huynh
The study of protection and prevention against failures is an important problem in communication networks due to the growth of capacity demands for data transmission, especially in the Internet traffic. In this paper, we consider the Survivable Network Design Problem (SNDP) with Protected Working Capacity Envelope (PWCE) called capacity SNDP (ca-SNDP) in which a network topology is modeled by a weighted and undirected graph. The weight of each edge is maximum capacity bandwidth of this edge. A working network (Wn) and a backup network (Bn) will be constructed from this topology. Design survivable network with maximum total bandwith in Wn is objective of ca-SNDP. This paper proposes Extending Cycle (EC) model and genetic algorithm for solving ca-SNDP. We experimented and evaluated the effectiveness of proposed aprroach for solving survivable network design problem.
{"title":"Genetic algorithm for solving Survivable Network Design Problem with Extending-Cycle-Based Protected Working Capacity Envelope","authors":"Khac Tuan Le, Thi Thanh Binh Huynh","doi":"10.1109/NaBIC.2014.6921887","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921887","url":null,"abstract":"The study of protection and prevention against failures is an important problem in communication networks due to the growth of capacity demands for data transmission, especially in the Internet traffic. In this paper, we consider the Survivable Network Design Problem (SNDP) with Protected Working Capacity Envelope (PWCE) called capacity SNDP (ca-SNDP) in which a network topology is modeled by a weighted and undirected graph. The weight of each edge is maximum capacity bandwidth of this edge. A working network (Wn) and a backup network (Bn) will be constructed from this topology. Design survivable network with maximum total bandwith in Wn is objective of ca-SNDP. This paper proposes Extending Cycle (EC) model and genetic algorithm for solving ca-SNDP. We experimented and evaluated the effectiveness of proposed aprroach for solving survivable network design problem.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133909030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921877
N. Costa, M. Varela, S. Carmo-Silva
Scheduling is one of the most important decisions in production control systems. This paper explores different approaches for scheduling two stage jobs in two configurations of product oriented manufacturing systems, namely an hybrid flow shop (HFS) and a parallel machine flow shop (PMFS). An industrial case is analyzed from the automotive components industry. The HFS problem resolution is compared with PMFS one in terms of makespan and other performance measures. The results allow concluding that the HFS performs considerably better than the PMFS.
{"title":"Scheduling in product oriented manufacturing systems","authors":"N. Costa, M. Varela, S. Carmo-Silva","doi":"10.1109/NaBIC.2014.6921877","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921877","url":null,"abstract":"Scheduling is one of the most important decisions in production control systems. This paper explores different approaches for scheduling two stage jobs in two configurations of product oriented manufacturing systems, namely an hybrid flow shop (HFS) and a parallel machine flow shop (PMFS). An industrial case is analyzed from the automotive components industry. The HFS problem resolution is compared with PMFS one in terms of makespan and other performance measures. The results allow concluding that the HFS performs considerably better than the PMFS.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132483558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921868
Shiyuan Han, Yuehui Chen, Kun Ma, Dong Wang, A. Abraham, Zhong-Guang Liu
This paper studies the vibration rejection problem of active suspension discrete-time systems under in-vehicle networks and designs a controller of feedforward and feedback optimal vibration rejection. Based on the ground displacement power spectral density, an discrete-time exosystem is employed to estimate the random road disturbances. A two degree of freedom discrete-time system is introduced to describe the active suspension under in-vehicle networks. Then, the original vibration control is formulated as the optimal control for a linear discrete-time system affected by external disturbances. The feedforward and feedback optimal vibration rejection law (FFOVRL) is designed by solving the Riccate and Stein equations, in which the feedforward term incorporates the information of the random road disturbances and the feedback loop includes the status of suspension system. The feasibility and effectiveness of the proposed approaches are validated by an active suspension structure.
{"title":"Feedforward and feedback optimal vibration rejection for active suspension discrete-time systems under in-vehicle networks","authors":"Shiyuan Han, Yuehui Chen, Kun Ma, Dong Wang, A. Abraham, Zhong-Guang Liu","doi":"10.1109/NaBIC.2014.6921868","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921868","url":null,"abstract":"This paper studies the vibration rejection problem of active suspension discrete-time systems under in-vehicle networks and designs a controller of feedforward and feedback optimal vibration rejection. Based on the ground displacement power spectral density, an discrete-time exosystem is employed to estimate the random road disturbances. A two degree of freedom discrete-time system is introduced to describe the active suspension under in-vehicle networks. Then, the original vibration control is formulated as the optimal control for a linear discrete-time system affected by external disturbances. The feedforward and feedback optimal vibration rejection law (FFOVRL) is designed by solving the Riccate and Stein equations, in which the feedforward term incorporates the information of the random road disturbances and the feedback loop includes the status of suspension system. The feasibility and effectiveness of the proposed approaches are validated by an active suspension structure.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113955879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921878
R. Tavakkoli-Moghaddam, S. Sedehzadeh
A hub location problem is a main group of the transportation network, which is utilized as a connecting and switching point for demand between origins and destinations. Recently, a tree hub location problem has been introduced as an incomplete hub network with single assignment, in which hubs are connected by means of a tree. This paper presents a new bi-objective, multi-modal tree hub location problem with different capacity levels. Besides the location and allocation decisions in tree hub network, this model decides on transportation modes and capacity levels such that the total transportation cost and time are minimized. Additionally, a multi-objective imperialist competitive algorithm (MOICA) is proposed to solve the presented model and obtain Pareto-optimal solutions of the given problem. Finally, the performance of this algorithm is compared with a non-dominated sorting genetic algorithm (NSGA-II).
{"title":"A multi-objective imperialist competitive algorithm to solve a new multi-modal tree hub location problem","authors":"R. Tavakkoli-Moghaddam, S. Sedehzadeh","doi":"10.1109/NaBIC.2014.6921878","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921878","url":null,"abstract":"A hub location problem is a main group of the transportation network, which is utilized as a connecting and switching point for demand between origins and destinations. Recently, a tree hub location problem has been introduced as an incomplete hub network with single assignment, in which hubs are connected by means of a tree. This paper presents a new bi-objective, multi-modal tree hub location problem with different capacity levels. Besides the location and allocation decisions in tree hub network, this model decides on transportation modes and capacity levels such that the total transportation cost and time are minimized. Additionally, a multi-objective imperialist competitive algorithm (MOICA) is proposed to solve the presented model and obtain Pareto-optimal solutions of the given problem. Finally, the performance of this algorithm is compared with a non-dominated sorting genetic algorithm (NSGA-II).","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134202999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921853
T. Komine, Masaya Nakata, K. Takadama
In dynamic environment, Learning Classifier System (LCS) evolves classifiers to fit the current situation, but may forget classifiers which were useful for previous situations. Our main idea is that, we store the forgotten classifiers as archives and generate new classifiers by recombining them to fit the current situation. Specifically, we propose an archive-based LCS called Arc-XCS, which detects environmental changes and generates classifiers based on the archive. The experimental results on the benchmark problem show that, Arc-XCS successfully stored good classifiers when each environmental changes occurs; compared to the conventional LCS (XCS), Arc-XCS reaches better performances with fewer trainings.
{"title":"Archives-holding XCS Classifier System: A preliminary study","authors":"T. Komine, Masaya Nakata, K. Takadama","doi":"10.1109/NaBIC.2014.6921853","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921853","url":null,"abstract":"In dynamic environment, Learning Classifier System (LCS) evolves classifiers to fit the current situation, but may forget classifiers which were useful for previous situations. Our main idea is that, we store the forgotten classifiers as archives and generate new classifiers by recombining them to fit the current situation. Specifically, we propose an archive-based LCS called Arc-XCS, which detects environmental changes and generates classifiers based on the archive. The experimental results on the benchmark problem show that, Arc-XCS successfully stored good classifiers when each environmental changes occurs; compared to the conventional LCS (XCS), Arc-XCS reaches better performances with fewer trainings.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133787096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921871
Majid Almaraashi, A. Hedar
In this paper, a new method to optimise interval type-2 fuzzy logic systems (IT2FLSs) using two forms of tabu search (TS) is presented. TS algorithms search for the best configuration of the interval type-2 fuzzy logic system (IT2FLS) rule-base membership functions parameters. Directed tabu search (DTS), which uses pattern search to control TS moves, and short-term tabu search (STS) have been applied with IT2FLS to a classification problem of two benchmark datasets. The main objective is to better improve the configuration of (IT2FLSs) using an intelligent directed search rather than a random-based search. The comparison results show that DTS outperformed the default TS by a noticeable difference. This observation reveals the importance of using guided search moves rather than using a randomized search direction especially with complex large intelligent systems as in (IT2FLSs).
{"title":"Optimization of interval type-2 fuzzy logic systems using tabu search algorithms","authors":"Majid Almaraashi, A. Hedar","doi":"10.1109/NaBIC.2014.6921871","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921871","url":null,"abstract":"In this paper, a new method to optimise interval type-2 fuzzy logic systems (IT2FLSs) using two forms of tabu search (TS) is presented. TS algorithms search for the best configuration of the interval type-2 fuzzy logic system (IT2FLS) rule-base membership functions parameters. Directed tabu search (DTS), which uses pattern search to control TS moves, and short-term tabu search (STS) have been applied with IT2FLS to a classification problem of two benchmark datasets. The main objective is to better improve the configuration of (IT2FLSs) using an intelligent directed search rather than a random-based search. The comparison results show that DTS outperformed the default TS by a noticeable difference. This observation reveals the importance of using guided search moves rather than using a randomized search direction especially with complex large intelligent systems as in (IT2FLSs).","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126105949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921854
Hongwei Mo, Mengjiao Geng
Magnetotactic bacteria optimization algorithm (MBOA) is a kind of optimization algorithm inspired by the characteristics of magnetotactic bacteria(MTB). They have chains consisting of micro magnetic particles called magnetosomes inside their bodies. These magnetic chains make MTB have magnetotaxis that make them orient and swim along geomagnetic field lines. The original MBOA mimics the interaction energy between magnetosomes chains to obtain moments for solving problems. But its performance is mainly update to operation of candidate solutions replacement with randomly generated cells. In this paper, an improved MBOA is proposed. It regulates the moments based on the information exchange between best individual's moments and some randomly one. It is called best-rand scheme. The performance of proposed algorithm is tested on twelve standard function problems and compared with some popular optimization algorithms, including variants of DE, ABC. Experiment results show that the improved algorithm is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.
{"title":"Magnetotactic bacteria optimization algorithm based on best-rand scheme","authors":"Hongwei Mo, Mengjiao Geng","doi":"10.1109/NaBIC.2014.6921854","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921854","url":null,"abstract":"Magnetotactic bacteria optimization algorithm (MBOA) is a kind of optimization algorithm inspired by the characteristics of magnetotactic bacteria(MTB). They have chains consisting of micro magnetic particles called magnetosomes inside their bodies. These magnetic chains make MTB have magnetotaxis that make them orient and swim along geomagnetic field lines. The original MBOA mimics the interaction energy between magnetosomes chains to obtain moments for solving problems. But its performance is mainly update to operation of candidate solutions replacement with randomly generated cells. In this paper, an improved MBOA is proposed. It regulates the moments based on the information exchange between best individual's moments and some randomly one. It is called best-rand scheme. The performance of proposed algorithm is tested on twelve standard function problems and compared with some popular optimization algorithms, including variants of DE, ABC. Experiment results show that the improved algorithm is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124845527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921881
G. Bernardo, M. A. R. Loja
Radial basis functions are being used in different scientific areas in order to reproduce the geometrical modeling of an object/structure, as well as to predict its behavior. Due to its characteristics, these functions are well suited for meshfree modeling of physical quantities, which for instances can be associated to the data sets of 3D laser scanning point clouds. In the present work the geometry of a structure is modeled by using multiquadric radial basis functions, and its configuration is further optimized in order to obtain better performances concerning to its static and dynamic behavior. For this purpose the authors consider the particle swarm optimization technique. A set of case studies is presented to illustrate the adequacy of the meshfree model used, as well as its link to particle swarm optimization technique.
{"title":"Optimization of structures modeled with a meshfree approach","authors":"G. Bernardo, M. A. R. Loja","doi":"10.1109/NaBIC.2014.6921881","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921881","url":null,"abstract":"Radial basis functions are being used in different scientific areas in order to reproduce the geometrical modeling of an object/structure, as well as to predict its behavior. Due to its characteristics, these functions are well suited for meshfree modeling of physical quantities, which for instances can be associated to the data sets of 3D laser scanning point clouds. In the present work the geometry of a structure is modeled by using multiquadric radial basis functions, and its configuration is further optimized in order to obtain better performances concerning to its static and dynamic behavior. For this purpose the authors consider the particle swarm optimization technique. A set of case studies is presented to illustrate the adequacy of the meshfree model used, as well as its link to particle swarm optimization technique.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129079110","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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