Pub Date : 2014-12-08DOI: 10.1109/ICNC.2014.6976000
Kyon-Mo Yang, Sung-Bae Cho
Recently, a lot of the fields such as education, marketing, and design have applied human's emotion stimuli to increase the effectiveness of services as well as user-computer interaction. Predicting the emotion in the field is important to decide relevant stimuli because emotion has the element of uncertainty and is sensitive to sensory stimuli. In this paper, we propose a modular dynamic Bayesian network based on Markov boundary theory to predict current emotion. A relation between emotion and stimuli is identified as four types of structure. The proposed method was verified by several experiments. The computational time is 0.032 second and the average accuracy rate is 80.97%, which are quite promising for a realistic system.
{"title":"Modular dynamic Bayesian network based on Markov boundary for emotion prediction in multi-sensory environment","authors":"Kyon-Mo Yang, Sung-Bae Cho","doi":"10.1109/ICNC.2014.6976000","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6976000","url":null,"abstract":"Recently, a lot of the fields such as education, marketing, and design have applied human's emotion stimuli to increase the effectiveness of services as well as user-computer interaction. Predicting the emotion in the field is important to decide relevant stimuli because emotion has the element of uncertainty and is sensitive to sensory stimuli. In this paper, we propose a modular dynamic Bayesian network based on Markov boundary theory to predict current emotion. A relation between emotion and stimuli is identified as four types of structure. The proposed method was verified by several experiments. The computational time is 0.032 second and the average accuracy rate is 80.97%, which are quite promising for a realistic system.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122055521","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975957
Jinpu Xu, Yeping Zhu, Hailong Liu, J. Zhao
Speech recognition technology was applied to information collection of agricultural prices, with the acoustic models trained for agricultural prices information collection environment so as to minimize the environmental influence. Firstly, we constructed the speech corpus by collecting speech under the operating scene, and then selected tri-phone modeling as the decode unit to train hidden Markov model (HMM) for the recognition of male and female voices. Secondly, decision tree-based clustering of states was used to solve the problem caused by insufficiency in training samples, and then increased mixture of Gaussian components to make the model more accurately described. In the end, we adopted the CMN and CVN methods (often used in conjunction, called CMVN) to reduce the mismatch between testing and the training environment. From the test results of different locations and different speakers, the ultimate recognition rate reached 95.04% for males, and 97.62% for females.
{"title":"An approach of agricultural price information collection based on speech recognition","authors":"Jinpu Xu, Yeping Zhu, Hailong Liu, J. Zhao","doi":"10.1109/ICNC.2014.6975957","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975957","url":null,"abstract":"Speech recognition technology was applied to information collection of agricultural prices, with the acoustic models trained for agricultural prices information collection environment so as to minimize the environmental influence. Firstly, we constructed the speech corpus by collecting speech under the operating scene, and then selected tri-phone modeling as the decode unit to train hidden Markov model (HMM) for the recognition of male and female voices. Secondly, decision tree-based clustering of states was used to solve the problem caused by insufficiency in training samples, and then increased mixture of Gaussian components to make the model more accurately described. In the end, we adopted the CMN and CVN methods (often used in conjunction, called CMVN) to reduce the mismatch between testing and the training environment. From the test results of different locations and different speakers, the ultimate recognition rate reached 95.04% for males, and 97.62% for females.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116793553","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975900
Yingjun Ma, Xueyuan Cui
According to the characteristics of fuel transportation problem, the traditional genetic algorithm model is improved in this paper. The complexity of encoding is simplified by considering the condition of putting the distances of the tanker going halfway back and forth into the objective function. Scanning method is used to generate the initial population improving the quality of chromosomes in the initial population. Adopting the way of "interval crossover, random replacement" ensures the effectiveness and randomness of the crossover. Adding the operation of evolutionary cycle after crossover and mutation operation enhances the local search ability of the algorithm. Finally through MATLAB programming, the traditional genetic algorithm, the scanning genetic algorithm and the evolutionary cycle genetic algorithm and the improved genetic algorithm are compared which further verifies that the improved genetic algorithm is effective.
{"title":"Solving the fuel transportation problem based on the improved genetic algorithm","authors":"Yingjun Ma, Xueyuan Cui","doi":"10.1109/ICNC.2014.6975900","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975900","url":null,"abstract":"According to the characteristics of fuel transportation problem, the traditional genetic algorithm model is improved in this paper. The complexity of encoding is simplified by considering the condition of putting the distances of the tanker going halfway back and forth into the objective function. Scanning method is used to generate the initial population improving the quality of chromosomes in the initial population. Adopting the way of \"interval crossover, random replacement\" ensures the effectiveness and randomness of the crossover. Adding the operation of evolutionary cycle after crossover and mutation operation enhances the local search ability of the algorithm. Finally through MATLAB programming, the traditional genetic algorithm, the scanning genetic algorithm and the evolutionary cycle genetic algorithm and the improved genetic algorithm are compared which further verifies that the improved genetic algorithm is effective.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123978569","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975875
Aijia Ouyang, Libin Liu, Kenli Li, Kuan-Ching Li
Considering the problems of slow convergence and easily getting into local optimum of intelligent optimization algorithms in finding the optimal solution to complex high-dimensional functions, we have proposed an improved invasive weed optimization (IIWO). Concrete adjustments include setting the newborn seeds per plant to a fixed number, changing the initial step and final step to adaptive one, and re-initializing the solution which exceeds the boundary value. Meanwhile, through applying the algorithm to the GPU platform, a parallel IIWO (PIIWO) based on GPU is obtained. The algorithm not only improves the convergence, but also strikes a balance between the global and local search capabilities. The simulation results of solving on the CEC' 2010 1000-dimensional (1000D) functions, have shown that, compared with other algorithms, our designed IIWO can yield better performance, faster convergence, higher accuracy and stronger robustness; whilst the PIIWO has significant speedup than the IIWO.
{"title":"GPU-based variation of parallel invasive weed optimization algorithm for 1000D functions","authors":"Aijia Ouyang, Libin Liu, Kenli Li, Kuan-Ching Li","doi":"10.1109/ICNC.2014.6975875","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975875","url":null,"abstract":"Considering the problems of slow convergence and easily getting into local optimum of intelligent optimization algorithms in finding the optimal solution to complex high-dimensional functions, we have proposed an improved invasive weed optimization (IIWO). Concrete adjustments include setting the newborn seeds per plant to a fixed number, changing the initial step and final step to adaptive one, and re-initializing the solution which exceeds the boundary value. Meanwhile, through applying the algorithm to the GPU platform, a parallel IIWO (PIIWO) based on GPU is obtained. The algorithm not only improves the convergence, but also strikes a balance between the global and local search capabilities. The simulation results of solving on the CEC' 2010 1000-dimensional (1000D) functions, have shown that, compared with other algorithms, our designed IIWO can yield better performance, faster convergence, higher accuracy and stronger robustness; whilst the PIIWO has significant speedup than the IIWO.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124067055","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975988
H. Cheng, Shajia Yu, Li Cheng
In order to detect the fault signal of rolling bearing, the fault diagnosis of rolling bearings is carried out by using discrete wavelet transform. The practical vibration speed signals measured from rolling bearings are decomposed and reconstructed by Mallat algorithm. Then an envelope analysis is made to the signal. The fault of rolling bearing component is diagnosed by extracting fault feature from envelop frequency spectrum figure. The experiments results showed that mutation signal can be easily found from detail signals after N-decomposition of the vibration signal of rolling bearing. The existence of fault points can be judged accurately by detecting the characteristic frequency of fault signals from the power spectrum after Hilbert envelop.
{"title":"Application of wavelet transform in fault diagnosis of rolling bearing","authors":"H. Cheng, Shajia Yu, Li Cheng","doi":"10.1109/ICNC.2014.6975988","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975988","url":null,"abstract":"In order to detect the fault signal of rolling bearing, the fault diagnosis of rolling bearings is carried out by using discrete wavelet transform. The practical vibration speed signals measured from rolling bearings are decomposed and reconstructed by Mallat algorithm. Then an envelope analysis is made to the signal. The fault of rolling bearing component is diagnosed by extracting fault feature from envelop frequency spectrum figure. The experiments results showed that mutation signal can be easily found from detail signals after N-decomposition of the vibration signal of rolling bearing. The existence of fault points can be judged accurately by detecting the characteristic frequency of fault signals from the power spectrum after Hilbert envelop.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"56 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126139217","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975951
Ming-Xiu Lin, Junjie Xian, Di Gao, Shunxiang Wu, Jian-Huai Cai
The digital target image, in a machine vision based automatic scoring system, should be recognized for the subsequent automatic scoring and records analysis. However, target images collected from a camera are bound to be distorted, which would pose some difficulties to recognition. In this paper, according to the automatic closed loop controlling idea, a loop algorithm is proposed after the verification of both the intermediate results and the final ones with the utilization of prior knowledge, which is founded on the basic image processing algorithm and employs the technology of border extraction and segmentation as well as the pixel search. And it is considered that the position of the 10.9 ring and the spacing between each two rings are obtained through the recognition of the chest bitmap at a minimum time with the least memory resource with both accuracy and precision guaranteed. The method put forward by this paper has been tested a lot in android automatic scoring system practically, so the results feature reliability, accuracy and accordance with the requirements of the system.
{"title":"A chest silhouette recognition method based on digital image processing","authors":"Ming-Xiu Lin, Junjie Xian, Di Gao, Shunxiang Wu, Jian-Huai Cai","doi":"10.1109/ICNC.2014.6975951","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975951","url":null,"abstract":"The digital target image, in a machine vision based automatic scoring system, should be recognized for the subsequent automatic scoring and records analysis. However, target images collected from a camera are bound to be distorted, which would pose some difficulties to recognition. In this paper, according to the automatic closed loop controlling idea, a loop algorithm is proposed after the verification of both the intermediate results and the final ones with the utilization of prior knowledge, which is founded on the basic image processing algorithm and employs the technology of border extraction and segmentation as well as the pixel search. And it is considered that the position of the 10.9 ring and the spacing between each two rings are obtained through the recognition of the chest bitmap at a minimum time with the least memory resource with both accuracy and precision guaranteed. The method put forward by this paper has been tested a lot in android automatic scoring system practically, so the results feature reliability, accuracy and accordance with the requirements of the system.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126158871","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975955
Zhang Tao, K. Xie
When steganalysis performed on heterogeneous images made up by different resampled images and raw single-sampled images, the difference of statistical properties between which can caused “mismatch” between training and testing images in steganalytic classifier. Therefore, the detection performance of the classifier decreases. The problem above limits the application of the existing steganalysis algorithms in practical networks. In this study, a multi-classifier based on SVM is constructed to perform multi-classification on the resampled image, and a steganalysis algorithm integrating resampled image multi-classification is proposed. The algorithm prevents the "mismatch" between the training image and the testing image, and improves the detection performance of steganalysis algorithm under the condition of hybrid heterogeneous images. Finally, the effectiveness of the algorithm is proved by experiments.
{"title":"A steganalysis algorithm integrating resampled image multi-classification","authors":"Zhang Tao, K. Xie","doi":"10.1109/ICNC.2014.6975955","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975955","url":null,"abstract":"When steganalysis performed on heterogeneous images made up by different resampled images and raw single-sampled images, the difference of statistical properties between which can caused “mismatch” between training and testing images in steganalytic classifier. Therefore, the detection performance of the classifier decreases. The problem above limits the application of the existing steganalysis algorithms in practical networks. In this study, a multi-classifier based on SVM is constructed to perform multi-classification on the resampled image, and a steganalysis algorithm integrating resampled image multi-classification is proposed. The algorithm prevents the \"mismatch\" between the training image and the testing image, and improves the detection performance of steganalysis algorithm under the condition of hybrid heterogeneous images. Finally, the effectiveness of the algorithm is proved by experiments.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128686732","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975872
A. Narayanan, E. Keedwell
Explaining and controlling the emergence of synchronization between and across biological circuits are becoming increasingly important in systems biology. Computational models of increasing complexity are being proposed for explaining biological cycles with periods ranging from milliseconds to years. Such models have focused on period and amplitude. However, there is an equally important aspect of biological cycles, which is phase, or the ability of circuits and their components to synchronize their activities at the same level and across levels. Phase requires cooperation and feedback so that appropriate dynamical behavior and response result between and across different biological circuits. The purpose of this paper is to demonstrate how evolutionary computing, specifically a genetic algorithm, can help model the development of phased biological circuit cycles so that synchronized and periodic macro-level behavior emerges from micro-level circuit components and complexes.
{"title":"An evolutionary computational approach to phase and synchronization in biological circuits","authors":"A. Narayanan, E. Keedwell","doi":"10.1109/ICNC.2014.6975872","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975872","url":null,"abstract":"Explaining and controlling the emergence of synchronization between and across biological circuits are becoming increasingly important in systems biology. Computational models of increasing complexity are being proposed for explaining biological cycles with periods ranging from milliseconds to years. Such models have focused on period and amplitude. However, there is an equally important aspect of biological cycles, which is phase, or the ability of circuits and their components to synchronize their activities at the same level and across levels. Phase requires cooperation and feedback so that appropriate dynamical behavior and response result between and across different biological circuits. The purpose of this paper is to demonstrate how evolutionary computing, specifically a genetic algorithm, can help model the development of phased biological circuit cycles so that synchronized and periodic macro-level behavior emerges from micro-level circuit components and complexes.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132884979","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975871
Qingzheng Xu, Lemeng Guo, Na Wang, Jin Pan, Lei Wang
In this paper, a novel definition of opposite path is proposed. Its core feature is that the node sequence of candidate paths and the distances between adjacent nodes in the tour are considered simultaneously. In a sense, the path and its corresponding opposite path have the same (or similar, at least) distance from the optimal path in the current population. Based on an accepted framework for employing opposition-based learning, the Oppositional Biogeography-Based Optimization using the Current Optimum, called COOBBO algorithm, is introduced to solve combinatorial problem, such as traveling salesman problems. The performance of COOBBO on 8 benchmark problems is demonstrated and compared with other optimization algorithms. Simulation results illustrate that the excellent performance of our proposed algorithm is attributed to the distinct definition of opposite path.
{"title":"A novel oppositional biogeography-based optimization for combinatorial problems","authors":"Qingzheng Xu, Lemeng Guo, Na Wang, Jin Pan, Lei Wang","doi":"10.1109/ICNC.2014.6975871","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975871","url":null,"abstract":"In this paper, a novel definition of opposite path is proposed. Its core feature is that the node sequence of candidate paths and the distances between adjacent nodes in the tour are considered simultaneously. In a sense, the path and its corresponding opposite path have the same (or similar, at least) distance from the optimal path in the current population. Based on an accepted framework for employing opposition-based learning, the Oppositional Biogeography-Based Optimization using the Current Optimum, called COOBBO algorithm, is introduced to solve combinatorial problem, such as traveling salesman problems. The performance of COOBBO on 8 benchmark problems is demonstrated and compared with other optimization algorithms. Simulation results illustrate that the excellent performance of our proposed algorithm is attributed to the distinct definition of opposite path.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130868567","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975898
Yuxin Tian, Shan Liang
Most of the coal mine monitoring and control systems are the gas alarm device for the gas, this type of monitoring and control system can only monitor downhole gas, but it can't provide the visual condition of downhole to the ground monitoring person. To get the visible light image and infrared image, we research the target feature extraction technology of multi-source image. On the basis, we use the partial differential equations to get the fusion of the visible light image and the infrared image, then use the wavelet analysis method to solve the corresponding partial differential equation. We use compactly supported wavelet representation of differential operator structure the Daubechies wavelet solution of nonlinear partial differential equation. This article focused on using wavelet analysis algorithm to solve the partial differential equationsand used it on the multi-source image fusion. We hope the result of this article is superior to the classic image fusion algorithm in the application of the underground mine multi-source image fusion.
{"title":"Multi-source image fusion technology in the system of coal mine monitoring and control","authors":"Yuxin Tian, Shan Liang","doi":"10.1109/ICNC.2014.6975898","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975898","url":null,"abstract":"Most of the coal mine monitoring and control systems are the gas alarm device for the gas, this type of monitoring and control system can only monitor downhole gas, but it can't provide the visual condition of downhole to the ground monitoring person. To get the visible light image and infrared image, we research the target feature extraction technology of multi-source image. On the basis, we use the partial differential equations to get the fusion of the visible light image and the infrared image, then use the wavelet analysis method to solve the corresponding partial differential equation. We use compactly supported wavelet representation of differential operator structure the Daubechies wavelet solution of nonlinear partial differential equation. This article focused on using wavelet analysis algorithm to solve the partial differential equationsand used it on the multi-source image fusion. We hope the result of this article is superior to the classic image fusion algorithm in the application of the underground mine multi-source image fusion.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126573022","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：