This research compares and contrasts the simple regression model's parameter estimation methods, which consisted of a dependent variable and one independent variable. Parameter estimation uses the ordinary least square method, Bayesian method, Markov Chain Monte Carlo (MCMC) method, and local weight Markov Chain Monte Carlo (LWMCMC) method. The standard method is the ordinary least square method, which uses the concept of minimum sum square error to estimate parameters for fitting the linear regression model. However, for a set of the parameter relating to the Bayesian approach, the use of prior and posterior distributions may affect the approximation of the Bayesian, MCMC, LWMCMC methods. This paper considers the ordinal least square method and Bayesian approach by estimating the parameter for outlier data while some data points are far from other observations. The independent variable is simulated from the contaminated normal distribution, and the error is simulated from the normal distribution that made the outlier data on dependent and independent variables for the several sample sizes as 20, 50, 100, and 200. The criterion of the best efficiency is considered by the minimum of the average mean square errors. Through simulation data, the Bayesian method presents the minimum of average mean square errors at the sample sizes 20 and 50. However, when the sample size value increases, the MCMC and LWMCMC method are the best efficiency method at the sample sizes 100 and 200, respectively.
{"title":"Bayesian Approach for Comparing Parameter Estimation of Regression Model for Outlier Data","authors":"Autcha Araveeporn, K. Kumnungkit","doi":"10.1145/3545839.3545841","DOIUrl":"https://doi.org/10.1145/3545839.3545841","url":null,"abstract":"This research compares and contrasts the simple regression model's parameter estimation methods, which consisted of a dependent variable and one independent variable. Parameter estimation uses the ordinary least square method, Bayesian method, Markov Chain Monte Carlo (MCMC) method, and local weight Markov Chain Monte Carlo (LWMCMC) method. The standard method is the ordinary least square method, which uses the concept of minimum sum square error to estimate parameters for fitting the linear regression model. However, for a set of the parameter relating to the Bayesian approach, the use of prior and posterior distributions may affect the approximation of the Bayesian, MCMC, LWMCMC methods. This paper considers the ordinal least square method and Bayesian approach by estimating the parameter for outlier data while some data points are far from other observations. The independent variable is simulated from the contaminated normal distribution, and the error is simulated from the normal distribution that made the outlier data on dependent and independent variables for the several sample sizes as 20, 50, 100, and 200. The criterion of the best efficiency is considered by the minimum of the average mean square errors. Through simulation data, the Bayesian method presents the minimum of average mean square errors at the sample sizes 20 and 50. However, when the sample size value increases, the MCMC and LWMCMC method are the best efficiency method at the sample sizes 100 and 200, respectively.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121120745","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 propose a collaborative strategy for an autonomous PTZ (Pan Tilt Zoom) camera network, for improved target vehicle tracking, in real-world traffic. In addition, we explore ways to improve the target-tracking system to adapt itself to unexpected changes in traffic patterns. In the exploration phase, the camera nodes utilize the target identification information shared among themselves in the network to learn a graph. The vertices represent the camera nodes, while edges represent links to immediate neighbors, and edge weights represent the distance between the nodes in terms of the time taken by the target vehicles. In the exploitation phase, once a target vehicle is identified, the camera broadcasts the information to the neighbors. In turn, the neighbors consult the graph to position themselves better for capturing footage of the target vehicle. We carried out two agent-based simulation experiments to test the strategy. In the first experiment, we compare the proposed strategy, which uses the learned graph, to a baseline where the cameras operate independently for scanning traffic. In the second experiment, we compare the strategy to an improved adaptive version of itself, in which the system learns online continuously by observing live traffic. The results show that our cooperative camera network outperforms the baseline and the adaptive strategy outperforms the static one.
{"title":"A Decentralized Collaborative Strategy for PTZ Camera Network Tracking System using Graph Learning: Assessing strategies for information sharing in a PTZ camera network for improving vehicle tracking, via agent-based simulations","authors":"Shaik Masihullah, Subu Kandaswamy","doi":"10.1145/3545839.3545849","DOIUrl":"https://doi.org/10.1145/3545839.3545849","url":null,"abstract":"In this paper, we propose a collaborative strategy for an autonomous PTZ (Pan Tilt Zoom) camera network, for improved target vehicle tracking, in real-world traffic. In addition, we explore ways to improve the target-tracking system to adapt itself to unexpected changes in traffic patterns. In the exploration phase, the camera nodes utilize the target identification information shared among themselves in the network to learn a graph. The vertices represent the camera nodes, while edges represent links to immediate neighbors, and edge weights represent the distance between the nodes in terms of the time taken by the target vehicles. In the exploitation phase, once a target vehicle is identified, the camera broadcasts the information to the neighbors. In turn, the neighbors consult the graph to position themselves better for capturing footage of the target vehicle. We carried out two agent-based simulation experiments to test the strategy. In the first experiment, we compare the proposed strategy, which uses the learned graph, to a baseline where the cameras operate independently for scanning traffic. In the second experiment, we compare the strategy to an improved adaptive version of itself, in which the system learns online continuously by observing live traffic. The results show that our cooperative camera network outperforms the baseline and the adaptive strategy outperforms the static one.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130857598","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, the sum of a hyper-Erlang and a hyper-exponential distributed random variables is analyzed. Although tedious, the resulting random variable’s probability density function (PDF) can be obtained through convolution of its summands’ PDFs. Alternatively, the resulting distribution can be stated directly in terms of a phase-type distribution. However, computing its PDF can still be very costly and this representation gives little insight on the distribution. It can be shown that the sum of both random variable is again hyper-Erlang distributed of incremented order and can therefore be described without requiring the matrix exponential function. We derive a closed form linear algebra expression for the probability weights of the sum’s hyper-Erlang distribution, which significantly reduces the computational complexity of evaluating its distribution.
{"title":"Convolving Hyper-Erlang with Hyper-Exponential Distributions Using Linear Algebra","authors":"Clemens Neumüller, J. Robert, A. Heuberger","doi":"10.1145/3545839.3545840","DOIUrl":"https://doi.org/10.1145/3545839.3545840","url":null,"abstract":"In this paper, the sum of a hyper-Erlang and a hyper-exponential distributed random variables is analyzed. Although tedious, the resulting random variable’s probability density function (PDF) can be obtained through convolution of its summands’ PDFs. Alternatively, the resulting distribution can be stated directly in terms of a phase-type distribution. However, computing its PDF can still be very costly and this representation gives little insight on the distribution. It can be shown that the sum of both random variable is again hyper-Erlang distributed of incremented order and can therefore be described without requiring the matrix exponential function. We derive a closed form linear algebra expression for the probability weights of the sum’s hyper-Erlang distribution, which significantly reduces the computational complexity of evaluating its distribution.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131114732","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 proposes a pricing model of insurance for persons with autism and further designs a possible insurance product that compensate the insured persons 18 years after purchasing the insurance. Using MATLAB programming, the variation of insurance premium with insurance parameters are plotted to analyze the effect of the insured years, the chance to diagnose a child as autism and the compensation pay-outs for non-autism on the breakeven insurance premium. The analytical results of the pricing model shows that there are a nonlinear relationship between the insurance premium and the insured years, a linear relationship between the insurance premium and the compensation pay-outs, a linear relationship between the insurance premium and the annuity insurance sent back to a non-autism insured, and a linear relationship between the insurance premium and the chance to diagnose a child as autistic. This work also establishes a model to calculate the profit generated from this insurance product.
{"title":"Pricing Model of Insurance Product for Autistic Persons","authors":"Zhiheng Jiang, Jiahao Fan, Qiyi Wang","doi":"10.1145/3545839.3545851","DOIUrl":"https://doi.org/10.1145/3545839.3545851","url":null,"abstract":"This paper proposes a pricing model of insurance for persons with autism and further designs a possible insurance product that compensate the insured persons 18 years after purchasing the insurance. Using MATLAB programming, the variation of insurance premium with insurance parameters are plotted to analyze the effect of the insured years, the chance to diagnose a child as autism and the compensation pay-outs for non-autism on the breakeven insurance premium. The analytical results of the pricing model shows that there are a nonlinear relationship between the insurance premium and the insured years, a linear relationship between the insurance premium and the compensation pay-outs, a linear relationship between the insurance premium and the annuity insurance sent back to a non-autism insured, and a linear relationship between the insurance premium and the chance to diagnose a child as autistic. This work also establishes a model to calculate the profit generated from this insurance product.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126880006","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}
One of the main problems faced by health institutions is the unwarned absenteeism of patients in medical appointments. Patients’ no-shows, without prior notice, can result in loss of revenue for health centres and increasing waiting lines. Hence, there is a need to predict the non-attendance of patients to improve health institutions’ management performance. In this paper, a brief literature review was carried out to understand which factors can be related to patients’ absenteeism, and which forecasting methods are often applied to discover patterns in health datasets. As the logistic binary regression model has been proved to be effective on that matter, it was applied to a real hospital data set comprising information on 98.511 patients, with a corresponding 645.576 appointments, in a period between 2018 and 2020. Results indicate a significant effect on the chance of appointment attendance of patient age, patient gender, patient Marital Status, number of previous appointments, appointment month, precipitation levels, Lead time, and the number of previous no-show appointments.
{"title":"Risk Factors Associated with Hospital Unwarned Appointment Absenteeism: A logistic binary regression approach","authors":"Miguel Maia, A. Borges, Mariana Cavalho","doi":"10.1145/3545839.3545848","DOIUrl":"https://doi.org/10.1145/3545839.3545848","url":null,"abstract":"One of the main problems faced by health institutions is the unwarned absenteeism of patients in medical appointments. Patients’ no-shows, without prior notice, can result in loss of revenue for health centres and increasing waiting lines. Hence, there is a need to predict the non-attendance of patients to improve health institutions’ management performance. In this paper, a brief literature review was carried out to understand which factors can be related to patients’ absenteeism, and which forecasting methods are often applied to discover patterns in health datasets. As the logistic binary regression model has been proved to be effective on that matter, it was applied to a real hospital data set comprising information on 98.511 patients, with a corresponding 645.576 appointments, in a period between 2018 and 2020. Results indicate a significant effect on the chance of appointment attendance of patient age, patient gender, patient Marital Status, number of previous appointments, appointment month, precipitation levels, Lead time, and the number of previous no-show appointments.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114796141","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 proposes a new approach to optimizing cost function for binary logistic regression by the Gauss-Newton method. This method was applied to the backpropagation phase as a part of the training process to update the weighted coefficients. To show the performance of the approach, we used two data sets to train the logistic regression model for binary classification problems. Our experiment demonstrated that the proposed methods could perform better than gradient descent for both examples, as we expected. Furthermore, the performance of our approach is more advanced than the classical method, either in speed or accuracy.
{"title":"Performance Improvement of Logistic Regression for Binary Classification by Gauss-Newton Method","authors":"M. Jamhuri, I. Mukhlash, M. I. Irawan","doi":"10.1145/3545839.3545842","DOIUrl":"https://doi.org/10.1145/3545839.3545842","url":null,"abstract":"This paper proposes a new approach to optimizing cost function for binary logistic regression by the Gauss-Newton method. This method was applied to the backpropagation phase as a part of the training process to update the weighted coefficients. To show the performance of the approach, we used two data sets to train the logistic regression model for binary classification problems. Our experiment demonstrated that the proposed methods could perform better than gradient descent for both examples, as we expected. Furthermore, the performance of our approach is more advanced than the classical method, either in speed or accuracy.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131824158","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 order to improve the prediction accuracy, this study proposes an new PCA-LSTM neural network stock price prediction model that combines principal component analysis(PCA) and long-term and short-term memory neural network (LSTM). We download time series indicators and technical indicators of PingAn insurance (X601318) form Tushare interface and Wind database. PCA method was used to reduce the technical indicators dimension, LSTM model was used to predict the next day stock closing price. The results show that PCA-LSTM model can greatly reduce data redundancy and obtain better prediction accuracy compared with the simple LSTM model. Additional Keywords and Phrases: stock price prediction, PCA, LSTM
{"title":"Stock price prediction based on PCA-LSTM model","authors":"Xinyuan Zheng, Naiping Xiong","doi":"10.1145/3545839.3545852","DOIUrl":"https://doi.org/10.1145/3545839.3545852","url":null,"abstract":"In order to improve the prediction accuracy, this study proposes an new PCA-LSTM neural network stock price prediction model that combines principal component analysis(PCA) and long-term and short-term memory neural network (LSTM). We download time series indicators and technical indicators of PingAn insurance (X601318) form Tushare interface and Wind database. PCA method was used to reduce the technical indicators dimension, LSTM model was used to predict the next day stock closing price. The results show that PCA-LSTM model can greatly reduce data redundancy and obtain better prediction accuracy compared with the simple LSTM model. Additional Keywords and Phrases: stock price prediction, PCA, LSTM","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828335","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, the variational form is used to analyze the existence and uniqueness of the corresponding partial differential equations. In addition, the equation of the magnetic field induced by the magnet is also investigated. By constructing the corresponding Hilbert space and variational formulation, we can deduce that the equation admits a unique solution under some assumptions.
{"title":"Research on the Equation of the Magnetic Field Caused by Magnets","authors":"Jia Su, Qingfei Shu","doi":"10.1145/3545839.3545857","DOIUrl":"https://doi.org/10.1145/3545839.3545857","url":null,"abstract":"In this paper, the variational form is used to analyze the existence and uniqueness of the corresponding partial differential equations. In addition, the equation of the magnetic field induced by the magnet is also investigated. By constructing the corresponding Hilbert space and variational formulation, we can deduce that the equation admits a unique solution under some assumptions.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128035761","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 recent development of Hifi sequencing has greatly improved people's understanding of genomics. Hifi reads provide a more accurate and complete picture than traditional long reads and Illumina short reads. However, both long reads and short reads assemblers are not good fits for Hifi reads in reality. Therefore, in late 2020, HiCanu and Hifiasm have been developed to assemble Hifi reads. Even though they are both phased assemblers, which highly complexed regions will be separated into two different alleles, they show different output formats, algorithms and performance. The topic of this paper will be focused on comparison between HiCanu and Hifiasm on contiguity, completeness, and runtime. In order to compare the two tools, it is necessary to examine HiCanu and Hifiasm results of different genome assemblies from several published papers. Despite some shortcomings of Hifiasm assembler which is associated with increased coverage, Hifiasm is the best assembler for Hifi reads so far because of its high contiguity, completeness and fast runtime.
{"title":"A Comparative Study of HiCanu and Hifiasm","authors":"Yuqiu Wang","doi":"10.1145/3545839.3545855","DOIUrl":"https://doi.org/10.1145/3545839.3545855","url":null,"abstract":"The recent development of Hifi sequencing has greatly improved people's understanding of genomics. Hifi reads provide a more accurate and complete picture than traditional long reads and Illumina short reads. However, both long reads and short reads assemblers are not good fits for Hifi reads in reality. Therefore, in late 2020, HiCanu and Hifiasm have been developed to assemble Hifi reads. Even though they are both phased assemblers, which highly complexed regions will be separated into two different alleles, they show different output formats, algorithms and performance. The topic of this paper will be focused on comparison between HiCanu and Hifiasm on contiguity, completeness, and runtime. In order to compare the two tools, it is necessary to examine HiCanu and Hifiasm results of different genome assemblies from several published papers. Despite some shortcomings of Hifiasm assembler which is associated with increased coverage, Hifiasm is the best assembler for Hifi reads so far because of its high contiguity, completeness and fast runtime.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131171399","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 work we investigate the possibility of expressing the solution of the Navier-Stokes equations as a power series. Although there have been many studies on this subject, it is still much debated. The existence of such a solution and its uniqueness are debated, especially in the general case of a non-stationary fluid in two or three dimensions. The greater the complexity of the fluid dynamical phenomenon under consideration, the more controversial and therefore uncertain are the deductions about the existence and uniqueness of the solution as a power series. Here, we ask some crucial questions on the matter and try to give an answer from the point of view of applied mathematics and numerical analysis. In particular, by way of example, we construct the Navier-Stokes equations for a compressible, multicomponent and non-stationary fluid from elementary principles of conservation of mass, momentum and energy, and we introduce a bump function model for the presence of different components and/or different phases in the fluid. The bump function is a function of space, time and physical characteristics of the components (and/or phases) such as density. We present a method to calculate it and discuss about its uniqueness. We show that under certain conditions on the bump function, and the forces acting on and in the fluid, the power series solution is unique. We finally discuss the advantages and the limitations of a solution in power series, concluding that, although plagued by limitations, it is a viable way forward even in highly complex case studies.
{"title":"A new proposal of power series method to solve the Navier-Stokes equations: application contexts and perspectives","authors":"P. Lecca, Angela Re","doi":"10.1145/3545839.3545844","DOIUrl":"https://doi.org/10.1145/3545839.3545844","url":null,"abstract":"In this work we investigate the possibility of expressing the solution of the Navier-Stokes equations as a power series. Although there have been many studies on this subject, it is still much debated. The existence of such a solution and its uniqueness are debated, especially in the general case of a non-stationary fluid in two or three dimensions. The greater the complexity of the fluid dynamical phenomenon under consideration, the more controversial and therefore uncertain are the deductions about the existence and uniqueness of the solution as a power series. Here, we ask some crucial questions on the matter and try to give an answer from the point of view of applied mathematics and numerical analysis. In particular, by way of example, we construct the Navier-Stokes equations for a compressible, multicomponent and non-stationary fluid from elementary principles of conservation of mass, momentum and energy, and we introduce a bump function model for the presence of different components and/or different phases in the fluid. The bump function is a function of space, time and physical characteristics of the components (and/or phases) such as density. We present a method to calculate it and discuss about its uniqueness. We show that under certain conditions on the bump function, and the forces acting on and in the fluid, the power series solution is unique. We finally discuss the advantages and the limitations of a solution in power series, concluding that, although plagued by limitations, it is a viable way forward even in highly complex case studies.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114455114","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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