Pub Date : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804021
Mahbouba Brahmi, C. B. Regaya, Hichem Hamdi, A. Zaafouri
The performance of a photovoltaic system is strongly affected by the environmental conditions which it is subjected such as random atmospheric variations. In order to improve the performance of a photovoltaic system, the work of this paper is devoted to the comparative study between the following MPPT algorithms: the perturbation and observation algorithm (P&O) and the particle swarm optimization algorithm PSO. These two algorithms are tested under various atmospheric conditions and evaluated in terms of efficiency, stability, speed, and robustness. The obtained simulation results show the effectiveness of the PSO than the P&O algorithm.
{"title":"Comparative Study of P&O and PSO Particle Swarm Optimization MPPT Controllers for Photovoltaic Systems","authors":"Mahbouba Brahmi, C. B. Regaya, Hichem Hamdi, A. Zaafouri","doi":"10.1109/CoDIT55151.2022.9804021","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804021","url":null,"abstract":"The performance of a photovoltaic system is strongly affected by the environmental conditions which it is subjected such as random atmospheric variations. In order to improve the performance of a photovoltaic system, the work of this paper is devoted to the comparative study between the following MPPT algorithms: the perturbation and observation algorithm (P&O) and the particle swarm optimization algorithm PSO. These two algorithms are tested under various atmospheric conditions and evaluated in terms of efficiency, stability, speed, and robustness. The obtained simulation results show the effectiveness of the PSO than the P&O algorithm.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124589888","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804031
Marina Ciocîrlan, A. Udrea
Recently, the interest in electrocardiogram (ECG) signal analysis has grown, as it has been seen as a saddle point in diagnosing cardiovascular disease. The ECG is a standard noninvasive method for diagnostic and routine monitoring of the heart. Neural networks were used for automatic disease identification. In this context, the main subject of this article is the classification of ECG signals for the identification of heart functioning problems. Secondarily, we analyze how different acquisition frequencies of the ECG signals lead to variation in neural networks performance. To this end, two data sets containing ECG signals were used: PTB and PTB-XL. Four neural networks architectures were compared in terms of performance: the first and the second are based on convolutional neural networks and the third and fourth are derived from the first two, by adding a new branch containing nonlinear features extracted from the ECG signals. On the PTB database, the best results were obtained with a convolutional neural network with feature injection, with an accuracy of 89.012% for 100 Hz acquired signals. The best results for PTB- XL were obtained with the same network with an accuracy of 85.111% and 100 Hz.
{"title":"Classification and Feature Extraction of Biological Signals Using Machine Learning Techniques","authors":"Marina Ciocîrlan, A. Udrea","doi":"10.1109/CoDIT55151.2022.9804031","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804031","url":null,"abstract":"Recently, the interest in electrocardiogram (ECG) signal analysis has grown, as it has been seen as a saddle point in diagnosing cardiovascular disease. The ECG is a standard noninvasive method for diagnostic and routine monitoring of the heart. Neural networks were used for automatic disease identification. In this context, the main subject of this article is the classification of ECG signals for the identification of heart functioning problems. Secondarily, we analyze how different acquisition frequencies of the ECG signals lead to variation in neural networks performance. To this end, two data sets containing ECG signals were used: PTB and PTB-XL. Four neural networks architectures were compared in terms of performance: the first and the second are based on convolutional neural networks and the third and fourth are derived from the first two, by adding a new branch containing nonlinear features extracted from the ECG signals. On the PTB database, the best results were obtained with a convolutional neural network with feature injection, with an accuracy of 89.012% for 100 Hz acquired signals. The best results for PTB- XL were obtained with the same network with an accuracy of 85.111% and 100 Hz.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128731321","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804002
A. Davydov, Aleksandr Larionov, N. Nagul
The paper describes a new approach to checking the observability of formal regular languages. As well known, the observability is a crucial property for existence of the supervisory control for partially observed discrete event systems. Our checking procedure is based on the automatic theorem proving in the calculus of positively constructed formulas. The presented technique may be successfully used in various control problems including those appearing in robotics.
{"title":"On Checking Observability of Formal Languages in DES Control Problems","authors":"A. Davydov, Aleksandr Larionov, N. Nagul","doi":"10.1109/CoDIT55151.2022.9804002","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804002","url":null,"abstract":"The paper describes a new approach to checking the observability of formal regular languages. As well known, the observability is a crucial property for existence of the supervisory control for partially observed discrete event systems. Our checking procedure is based on the automatic theorem proving in the calculus of positively constructed formulas. The presented technique may be successfully used in various control problems including those appearing in robotics.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116005225","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804066
J. P. Vega, E. Sánchez, Larbi Djilali, A. Loukianov
One of the most used electrical machines in the industry and domestic applications are the Single-Phase Induction Motor (SPIM), due to its low cost and low-price regarding maintenance. In this paper the Neural Inverse Optimal Control (NIOC) based Recurrent High Order Neural Network (RHONN) identifier is developed to control the SPIM flux and mechanical speed. The proposed neural identifier is on-line trained using the Extended Kalman Filter (EKF) based algorithm, which helps to obtain adequate SPIM model even in the presence of disturbances. To synthesize the NIOC, a Control Lyapunov Function (CLF) is selected as a cost function to be optimized. To illustrate the effectiveness of the proposed control scheme, simulations results considering time-varying references tracking and robustness in presence of parameter variations are presented and compared with conventional controllers.
{"title":"Neural Inverse Optimal Control of Single-Phase Induction Motors","authors":"J. P. Vega, E. Sánchez, Larbi Djilali, A. Loukianov","doi":"10.1109/CoDIT55151.2022.9804066","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804066","url":null,"abstract":"One of the most used electrical machines in the industry and domestic applications are the Single-Phase Induction Motor (SPIM), due to its low cost and low-price regarding maintenance. In this paper the Neural Inverse Optimal Control (NIOC) based Recurrent High Order Neural Network (RHONN) identifier is developed to control the SPIM flux and mechanical speed. The proposed neural identifier is on-line trained using the Extended Kalman Filter (EKF) based algorithm, which helps to obtain adequate SPIM model even in the presence of disturbances. To synthesize the NIOC, a Control Lyapunov Function (CLF) is selected as a cost function to be optimized. To illustrate the effectiveness of the proposed control scheme, simulations results considering time-varying references tracking and robustness in presence of parameter variations are presented and compared with conventional controllers.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"18 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120894890","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804065
E. Yumuk, C. Copot, C. Ionescu
In this study, a revisited improved approach of an initial frequency response based autotuner is proposed to enable PID controller design based on S-shaped step response data. In prior autotuner, the critical frequency value is found using relay test whereas process frequency response and its derivative at this frequency are calculated via the sine test. With the proposed approach, these values are estimated using the first order plus time delay models, which are employed to characterize S-shaped step response. Firstly, an identification method is used to find the model parameters, i.e. time constant $T$ and delay time L. Secondly, the required values are estimated using the first order plus time delay model. The remaining tuner design steps are the same as in the prior autotuner. The simulations are performed on four different types of dynamical systems to show effectiveness of the proposed approach. The simulation results suggest that the performance of the control system using the proposed approach improves in terms of achievable performance indicators such as overshoot and settling time.
{"title":"A Robust Auto-Tuning PID Controller Design based on S-Shaped Time Domain Response","authors":"E. Yumuk, C. Copot, C. Ionescu","doi":"10.1109/CoDIT55151.2022.9804065","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804065","url":null,"abstract":"In this study, a revisited improved approach of an initial frequency response based autotuner is proposed to enable PID controller design based on S-shaped step response data. In prior autotuner, the critical frequency value is found using relay test whereas process frequency response and its derivative at this frequency are calculated via the sine test. With the proposed approach, these values are estimated using the first order plus time delay models, which are employed to characterize S-shaped step response. Firstly, an identification method is used to find the model parameters, i.e. time constant $T$ and delay time L. Secondly, the required values are estimated using the first order plus time delay model. The remaining tuner design steps are the same as in the prior autotuner. The simulations are performed on four different types of dynamical systems to show effectiveness of the proposed approach. The simulation results suggest that the performance of the control system using the proposed approach improves in terms of achievable performance indicators such as overshoot and settling time.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122370854","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9804024
Bogdan Popa, D. Selișteanu, A. E. Lörincz, Tudosie Robert
The purpose of this research article is to create an optimized purpose for the Dijkstra algorithm, with a superior degree of efficiency. This research proposes also, in the first instance, an innovative and efficient analysis of the Dijkstra's and Roy-Floyd algorithms. This proposed method is useful in various application cases, such as information grouping systems associated with a graph with a small but high node density. The analysis part explains the strategies chosen for today's parallel solutions and comparisons with the implemented method. It can be stated that the parallelization solution proposed in the article is specific to a configuration. There will be also presented other strategies considering the grouping systems for the tests with many nodes and edges. The algorithm for determining the shortest path is presented and tested at the multi-language level in different contexts and scenarios.
{"title":"Optimization Possibilities for the Shortest-Path Algorithms in the Context of Large Volumes of Information","authors":"Bogdan Popa, D. Selișteanu, A. E. Lörincz, Tudosie Robert","doi":"10.1109/CoDIT55151.2022.9804024","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9804024","url":null,"abstract":"The purpose of this research article is to create an optimized purpose for the Dijkstra algorithm, with a superior degree of efficiency. This research proposes also, in the first instance, an innovative and efficient analysis of the Dijkstra's and Roy-Floyd algorithms. This proposed method is useful in various application cases, such as information grouping systems associated with a graph with a small but high node density. The analysis part explains the strategies chosen for today's parallel solutions and comparisons with the implemented method. It can be stated that the parallelization solution proposed in the article is specific to a configuration. There will be also presented other strategies considering the grouping systems for the tests with many nodes and edges. The algorithm for determining the shortest path is presented and tested at the multi-language level in different contexts and scenarios.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127036541","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9803935
Mariem Belhor, A. E. Amraoui, A. Jemai, F. Delmotte
In this paper, a new bi-objective model is proposed to deal with the Home Health Care Routing and Scheduling Problem. The considered problem combined the Vehicle Routing Problem with the Personnel scheduling Problem. Two well-known multi-objective Evolutionary algorithms are suggested to solved it with test instances taking from the literature. The obtained results show the effectiveness and the suitability of evolutionary algorithms to solve the problem.
{"title":"Multiobjective Evolutionary Algorithm for Home Health Care Routing and Scheduling Problem","authors":"Mariem Belhor, A. E. Amraoui, A. Jemai, F. Delmotte","doi":"10.1109/CoDIT55151.2022.9803935","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9803935","url":null,"abstract":"In this paper, a new bi-objective model is proposed to deal with the Home Health Care Routing and Scheduling Problem. The considered problem combined the Vehicle Routing Problem with the Personnel scheduling Problem. Two well-known multi-objective Evolutionary algorithms are suggested to solved it with test instances taking from the literature. The obtained results show the effectiveness and the suitability of evolutionary algorithms to solve the problem.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127191671","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9803963
Abbas Tariverdi, Kim Mathiassen, V. Søyseth, H. Kalvøy, O. J. Elle, J. Tørresen, Ø. Martinsen, M. Høvin
This paper establishes a physics-based simulation framework for steering a magnetically actuated guidewire based on the linear elasticity and dipoles theories. Interaction wrenches resulting from an external magnetic field and embedded magnets in a continuum rod, i.e., guidewire, serves as actuators for steering. In the presented framework, a simplified integration scheme based on the finite-volume method is employed to model guidewire using the linear elasticity theory and forces resulting from the interference of magnetic fields to provide a rapid model reconstruction. Furthermore, orienting the external magnetic field is employed to steer a guidewire into a constrained environment. Finally, simulations illustrate the approach performance on a soft rod where an external magnetic field is orientated to form the desired shape for a continuum rod and steer it within an environment. The results open up possibilities to construct a rapid model for continuum manipulators in practice.
{"title":"Physics-Based Simulation and Control Framework for Steering a Magnetically-Actuated Guidewire","authors":"Abbas Tariverdi, Kim Mathiassen, V. Søyseth, H. Kalvøy, O. J. Elle, J. Tørresen, Ø. Martinsen, M. Høvin","doi":"10.1109/CoDIT55151.2022.9803963","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9803963","url":null,"abstract":"This paper establishes a physics-based simulation framework for steering a magnetically actuated guidewire based on the linear elasticity and dipoles theories. Interaction wrenches resulting from an external magnetic field and embedded magnets in a continuum rod, i.e., guidewire, serves as actuators for steering. In the presented framework, a simplified integration scheme based on the finite-volume method is employed to model guidewire using the linear elasticity theory and forces resulting from the interference of magnetic fields to provide a rapid model reconstruction. Furthermore, orienting the external magnetic field is employed to steer a guidewire into a constrained environment. Finally, simulations illustrate the approach performance on a soft rod where an external magnetic field is orientated to form the desired shape for a continuum rod and steer it within an environment. The results open up possibilities to construct a rapid model for continuum manipulators in practice.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125978460","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9803958
Zhijia Yang, Byron Mason, Wen Gu, E. Winward, J. Knowles
For nonlinear systems, Nonlinear Model Predictive Control (NMPC) is preferred to linear Model Predictive Control(MPC) since the nonlinear dynamics of the plant and the control performance index can be incorporated directly. In certain applications the computational resources available for calculating the control solution are severely restricted or the solution is required at high frequency. To overcome these computational challenges this paper presents a computationally efficient update scheme for NMPC using the Forward Dif-ference Generalized Minimum RESidual (FDGMRES) method with a neuro-fuzzy nonlinear dynamic model to describe the plant. Following a description of the FDGMRES approach and a simple case study, an evaluation of the algorithms computational performance is presented using the example of a reference tracking controller for control of a nonlinear Continuously Stirred Tank Reactor (CSTR) system. The online execution time of the FDGMRES algorithm based controller is compared in real time with the more conventional approach of the Sequential Quadratic Programming (SQP) algorithm using Rapid Controls Prototyping hardware.
{"title":"Computationally Efficient Nonlinear Model Predictive Control","authors":"Zhijia Yang, Byron Mason, Wen Gu, E. Winward, J. Knowles","doi":"10.1109/CoDIT55151.2022.9803958","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9803958","url":null,"abstract":"For nonlinear systems, Nonlinear Model Predictive Control (NMPC) is preferred to linear Model Predictive Control(MPC) since the nonlinear dynamics of the plant and the control performance index can be incorporated directly. In certain applications the computational resources available for calculating the control solution are severely restricted or the solution is required at high frequency. To overcome these computational challenges this paper presents a computationally efficient update scheme for NMPC using the Forward Dif-ference Generalized Minimum RESidual (FDGMRES) method with a neuro-fuzzy nonlinear dynamic model to describe the plant. Following a description of the FDGMRES approach and a simple case study, an evaluation of the algorithms computational performance is presented using the example of a reference tracking controller for control of a nonlinear Continuously Stirred Tank Reactor (CSTR) system. The online execution time of the FDGMRES algorithm based controller is compared in real time with the more conventional approach of the Sequential Quadratic Programming (SQP) algorithm using Rapid Controls Prototyping hardware.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126739708","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 : 2022-05-17DOI: 10.1109/CoDIT55151.2022.9803930
Denis C. Ilie-Ablachim, Bogdan Dumitrescu
In this paper we present new methods of anomaly detection based on Dictionary Learning (DL) and Kernel Dictionary Learning (KDL). The main contribution consists in the adaption of known DL and KDL algorithms in the form of unsupervised methods, used for outlier detection. We propose a reduced kernel version (RKDL), which is useful for problems with large data sets, due to the large kernel matrix. We also improve the DL and RKDL methods by the use of a random selection of signals, which aims to eliminate the outliers from the training procedure. All our algorithms are introduced in an anomaly detection toolbox and are compared to standard benchmark results.
{"title":"Anomaly Detection with Selective Dictionary Learning","authors":"Denis C. Ilie-Ablachim, Bogdan Dumitrescu","doi":"10.1109/CoDIT55151.2022.9803930","DOIUrl":"https://doi.org/10.1109/CoDIT55151.2022.9803930","url":null,"abstract":"In this paper we present new methods of anomaly detection based on Dictionary Learning (DL) and Kernel Dictionary Learning (KDL). The main contribution consists in the adaption of known DL and KDL algorithms in the form of unsupervised methods, used for outlier detection. We propose a reduced kernel version (RKDL), which is useful for problems with large data sets, due to the large kernel matrix. We also improve the DL and RKDL methods by the use of a random selection of signals, which aims to eliminate the outliers from the training procedure. All our algorithms are introduced in an anomaly detection toolbox and are compared to standard benchmark results.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121524018","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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