Pub Date : 2016-08-01DOI: 10.1109/FSKD.2016.7603255
Yitong Lu, Mingxin Liang, Chao Gao, Yuxin Liu, Xianghua Li
The community structure as a vital property for complex networks contributes a lot for understanding and detecting inherent functions of real networks. However, existing algorithms which are ranging from the optimization-based to model-based strategies still need to be strengthened further in terms of their robustness and accuracy. In this paper, a kind of multi-headed slime molds, Physarum, is used for optimizing genetic algorithm (GA), due to its intelligence of generating foraging networks based on bioresearches. Thus, a Physarum-based Network Model (PNM) is proposed based on the Physarum-based Model, which shows an ability of recognizing inter-community edges. Combining PNM with a genetic algorithm, a novel genetic algorithm, called PNGACD, is putting forward to enhance the GA's efficiency, in which a priori edge recognition of PNM is integrated into the phase of initialization. Moreover, experiments in six real-world networks are used to evaluate the efficiency of the proposed method. Results show that there is a remarkable improvement in term of the robustness and accuracy, which demonstrates that PNGACD has a better performance, compared with the existing algorithms.
{"title":"A bio-inspired genetic algorithm for community mining","authors":"Yitong Lu, Mingxin Liang, Chao Gao, Yuxin Liu, Xianghua Li","doi":"10.1109/FSKD.2016.7603255","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603255","url":null,"abstract":"The community structure as a vital property for complex networks contributes a lot for understanding and detecting inherent functions of real networks. However, existing algorithms which are ranging from the optimization-based to model-based strategies still need to be strengthened further in terms of their robustness and accuracy. In this paper, a kind of multi-headed slime molds, Physarum, is used for optimizing genetic algorithm (GA), due to its intelligence of generating foraging networks based on bioresearches. Thus, a Physarum-based Network Model (PNM) is proposed based on the Physarum-based Model, which shows an ability of recognizing inter-community edges. Combining PNM with a genetic algorithm, a novel genetic algorithm, called PNGACD, is putting forward to enhance the GA's efficiency, in which a priori edge recognition of PNM is integrated into the phase of initialization. Moreover, experiments in six real-world networks are used to evaluate the efficiency of the proposed method. Results show that there is a remarkable improvement in term of the robustness and accuracy, which demonstrates that PNGACD has a better performance, compared with the existing algorithms.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127934176","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603460
Huayong Liu, Tao Li
An adaptive threshold shot detection algorithm based on improved block color features is proposed in this paper. This paper adopts an improved block color feature extraction method based on equal area of rectangular ring. Sub-block accumulative color histogram is extracted as color features and different weight for different rectangle rings is set in order to highlight the central part of frame. Then, adaptive threshold of detecting abrupt shot and gradual shot is calculated, and different detection modules is used according to the distance of the characteristics between frames. In the abrupt shots detection, several frames' frame difference and the edge shape features between adjacent frames are calculated to detect the flash. In the gradual shots detection, the discontinuous frame differences between the current frame and back frames are used to detect the boundary of the gradual shot. The experimental results show that this method has better effect to different types of video.
{"title":"An adaptive threshold shot detection algorithm based on improved block color features","authors":"Huayong Liu, Tao Li","doi":"10.1109/FSKD.2016.7603460","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603460","url":null,"abstract":"An adaptive threshold shot detection algorithm based on improved block color features is proposed in this paper. This paper adopts an improved block color feature extraction method based on equal area of rectangular ring. Sub-block accumulative color histogram is extracted as color features and different weight for different rectangle rings is set in order to highlight the central part of frame. Then, adaptive threshold of detecting abrupt shot and gradual shot is calculated, and different detection modules is used according to the distance of the characteristics between frames. In the abrupt shots detection, several frames' frame difference and the edge shape features between adjacent frames are calculated to detect the flash. In the gradual shots detection, the discontinuous frame differences between the current frame and back frames are used to detect the boundary of the gradual shot. The experimental results show that this method has better effect to different types of video.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134137784","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603302
Wei Mei
An axiomatic definition for possibility measure without “maxitivity” operator is proposed in this work. It has a psychology foundation of human cognition of possibility, is consistent with the conditional probability interpretation of possibility. Possibility measure defined this way obeys to a disjunctive operator of arithmetic mean and a conjunctive operator of product, which offers a different perspective on the understanding of possibility and should promote the cross prosperity of probability and possibility.
{"title":"The concept of possibility based on human cognition","authors":"Wei Mei","doi":"10.1109/FSKD.2016.7603302","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603302","url":null,"abstract":"An axiomatic definition for possibility measure without “maxitivity” operator is proposed in this work. It has a psychology foundation of human cognition of possibility, is consistent with the conditional probability interpretation of possibility. Possibility measure defined this way obeys to a disjunctive operator of arithmetic mean and a conjunctive operator of product, which offers a different perspective on the understanding of possibility and should promote the cross prosperity of probability and possibility.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133057271","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603331
Dan Li, W. Yao
In order to ensure the normal operation of water supply projects, especially long-distance water transmission pipeline (LDWTP), it is necessary to recognize and avoid potential risk events during its operation process. As the vagueness and correlation of risk indices usually have a significant impact on the risk assessment result, those indices with high similarity are found out and eliminated based on the fuzzy similarity theory and triangular fuzzy number. Then the quantitative risk assessment using the fuzzy comprehensive evaluation method by combining analytic hierarchy process (AHP) approach is conducted based on the newly established risk index system. The case study shows that there are five groups of indices with high similarity and the risk index system can be screened from 27 indices to 22 indices. The risk assessment result illustrates that risk grades of the four categories from high to low are technology risk, management risk, third-party risk and nature risk. The comprehensive risk of LDWTP is high, which can help the decision makers to identify the most contributing risk events and allow them to take necessary measures for the risk reduction and risk control.
{"title":"Risk assessment of long-distance water transmission pipeline based on fuzzy similarity evaluation approach","authors":"Dan Li, W. Yao","doi":"10.1109/FSKD.2016.7603331","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603331","url":null,"abstract":"In order to ensure the normal operation of water supply projects, especially long-distance water transmission pipeline (LDWTP), it is necessary to recognize and avoid potential risk events during its operation process. As the vagueness and correlation of risk indices usually have a significant impact on the risk assessment result, those indices with high similarity are found out and eliminated based on the fuzzy similarity theory and triangular fuzzy number. Then the quantitative risk assessment using the fuzzy comprehensive evaluation method by combining analytic hierarchy process (AHP) approach is conducted based on the newly established risk index system. The case study shows that there are five groups of indices with high similarity and the risk index system can be screened from 27 indices to 22 indices. The risk assessment result illustrates that risk grades of the four categories from high to low are technology risk, management risk, third-party risk and nature risk. The comprehensive risk of LDWTP is high, which can help the decision makers to identify the most contributing risk events and allow them to take necessary measures for the risk reduction and risk control.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413916","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603246
Ying Lin, Suoping Li, Haiyan Chen, Duo Peng
Cooperative networking is used widely because it has advantages in terms of network capacity and transmission reliability upgrade. This paper presents an analytical study on channel capacity of amplify-and-forward (AF) relay system with multi-relays in multiple input multiple output (MIMO) system. The problem of resource allocation is studied in this paper and an algorithm of amplification matrix for each antenna of multi-relays is presented. Then we solved above problem using a global optimization method. Results of simulation show that proposed algorithm could greatly improve the channel capacity at little cost.
{"title":"Capacity maximization on multi-relay MIMO cooperative system","authors":"Ying Lin, Suoping Li, Haiyan Chen, Duo Peng","doi":"10.1109/FSKD.2016.7603246","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603246","url":null,"abstract":"Cooperative networking is used widely because it has advantages in terms of network capacity and transmission reliability upgrade. This paper presents an analytical study on channel capacity of amplify-and-forward (AF) relay system with multi-relays in multiple input multiple output (MIMO) system. The problem of resource allocation is studied in this paper and an algorithm of amplification matrix for each antenna of multi-relays is presented. Then we solved above problem using a global optimization method. Results of simulation show that proposed algorithm could greatly improve the channel capacity at little cost.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123062866","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603222
Weiwei Pan, Guolong Chen
Signature verification is an important part of digital forensics. In order to solve the shortcomings of manual identification in technical accuracy and subjectivity, this paper proposed an off-line signature identification method based on Support Vector Machine (SVM). A powerful feature set is collected by extracting grid features and global features of a signature picture. The method is applied for identifying different writing systems and the highest correct probability of identification arrives at 100%. The results indicated that the method is workable and can be an effectively technical support for digital forensics.
{"title":"A method of off-line signature verification for digital forensics","authors":"Weiwei Pan, Guolong Chen","doi":"10.1109/FSKD.2016.7603222","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603222","url":null,"abstract":"Signature verification is an important part of digital forensics. In order to solve the shortcomings of manual identification in technical accuracy and subjectivity, this paper proposed an off-line signature identification method based on Support Vector Machine (SVM). A powerful feature set is collected by extracting grid features and global features of a signature picture. The method is applied for identifying different writing systems and the highest correct probability of identification arrives at 100%. The results indicated that the method is workable and can be an effectively technical support for digital forensics.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122199073","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}
Accurate demand forecasting could reduce the uncertainty of inventory and provide theoretical basis for strategic decisions. Without the accurate prediction of actual market demand, there will be a supply shortage or surplus, which influences the enterprise's inventory level and costs of operation. Product substitution is an important factor which affects the precision of demand forecasting. It could reduce the retailer's out-of-stock losses and raise the quality of services. However, it can also distort the genuine demand of the product by exaggerating the demand of substitute products. Product substitution presents a new challenge in demand forecasting. In this paper, an Estimation of Adjacent Substitution Rate based on Clustering Algorithm (EASR-CA) method is proposed according to a cornucopia of categories situation. First, all categories are divided into different clusters by weighted Clustering Algorithm. Then, in each cluster, the product adjacent substitution is calculated. According to the concept mentioned above, a Support Vector Machine (SVM) demand forecasting model, based on adjacent substitution rate estimation, is applied to PC product demand forecasting, which results in higher precision. The experiments identify that the precision is improved and the prediction obtains proper objectivity by considering clustering analysis method.
{"title":"Estimation of adjacent substitution rate based on clustering algorithm and its application","authors":"Yue Liu, Pengfei Ren, Tianlu Zhao, Zhengkai Yang, Junjun Gao","doi":"10.1109/FSKD.2016.7603277","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603277","url":null,"abstract":"Accurate demand forecasting could reduce the uncertainty of inventory and provide theoretical basis for strategic decisions. Without the accurate prediction of actual market demand, there will be a supply shortage or surplus, which influences the enterprise's inventory level and costs of operation. Product substitution is an important factor which affects the precision of demand forecasting. It could reduce the retailer's out-of-stock losses and raise the quality of services. However, it can also distort the genuine demand of the product by exaggerating the demand of substitute products. Product substitution presents a new challenge in demand forecasting. In this paper, an Estimation of Adjacent Substitution Rate based on Clustering Algorithm (EASR-CA) method is proposed according to a cornucopia of categories situation. First, all categories are divided into different clusters by weighted Clustering Algorithm. Then, in each cluster, the product adjacent substitution is calculated. According to the concept mentioned above, a Support Vector Machine (SVM) demand forecasting model, based on adjacent substitution rate estimation, is applied to PC product demand forecasting, which results in higher precision. The experiments identify that the precision is improved and the prediction obtains proper objectivity by considering clustering analysis method.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131706731","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603325
X. Xia, Wenhuan Zhu
In order to ensure the product quality and save manufacturing costs, growing attention has been paid to the problem of the stability of the manufacturing process with unknown probability distribution and trend. Considering that the stability of the manufacturing process is uncertain and its variation trend is unknown in the practical production, the evaluation for the stability variation of the manufacturing process can be performed by the measured data regarding to the product performance parameter based on the fuzzy norm method in this paper. The experimental investigation on the stability variation of the manufacturing process shows that if the relative error of the measurement uncertainty between the intrinsic sequence and the evaluated sequence is that dU≤15%, the manufacturing process is fairly stable; if 15%<;dU≤30%, the manufacturing process is general stable; if dU>30%, the manufacturing process is unstable under the confidence level P=95.44%. The fuzzy norm method can be applied to enforce the real-time evaluation for the stability variation of the manufacturing process without considering the probability distribution, and the evaluation results can be expected to be of great interest for mass production.
{"title":"Evaluation for the stability variation of the manufacturing process based on fuzzy norm method","authors":"X. Xia, Wenhuan Zhu","doi":"10.1109/FSKD.2016.7603325","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603325","url":null,"abstract":"In order to ensure the product quality and save manufacturing costs, growing attention has been paid to the problem of the stability of the manufacturing process with unknown probability distribution and trend. Considering that the stability of the manufacturing process is uncertain and its variation trend is unknown in the practical production, the evaluation for the stability variation of the manufacturing process can be performed by the measured data regarding to the product performance parameter based on the fuzzy norm method in this paper. The experimental investigation on the stability variation of the manufacturing process shows that if the relative error of the measurement uncertainty between the intrinsic sequence and the evaluated sequence is that dU≤15%, the manufacturing process is fairly stable; if 15%<;dU≤30%, the manufacturing process is general stable; if dU>30%, the manufacturing process is unstable under the confidence level P=95.44%. The fuzzy norm method can be applied to enforce the real-time evaluation for the stability variation of the manufacturing process without considering the probability distribution, and the evaluation results can be expected to be of great interest for mass production.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"342 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132418447","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603204
Ning Wang, Jinyan Liu, Ting-quan Deng
A supervised class-preserving Laplacian eigenmaps (SCPLE) algorithm is proposed. In this algorithm, two neighbor graphs, intra-class graph and inter-class graph, are constructed, whose edge weights determined by class label information and adaptive thresholds. By maximizing the weighted neighbor distances between heterogeneous samples and minimizing the weighted neighbor distances between homogeneous samples, this algorithm maps homogeneous samples closer and heterogeneous samples farther in the low dimensional space. Experiments demonstrate the superiority of the proposed algorithm against the classical LE, DVE and S-LE algorithms.
{"title":"A supervised class-preserving Laplacian eigenmaps for dimensionality reduction","authors":"Ning Wang, Jinyan Liu, Ting-quan Deng","doi":"10.1109/FSKD.2016.7603204","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603204","url":null,"abstract":"A supervised class-preserving Laplacian eigenmaps (SCPLE) algorithm is proposed. In this algorithm, two neighbor graphs, intra-class graph and inter-class graph, are constructed, whose edge weights determined by class label information and adaptive thresholds. By maximizing the weighted neighbor distances between heterogeneous samples and minimizing the weighted neighbor distances between homogeneous samples, this algorithm maps homogeneous samples closer and heterogeneous samples farther in the low dimensional space. Experiments demonstrate the superiority of the proposed algorithm against the classical LE, DVE and S-LE algorithms.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"94 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133821808","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603220
Bingfen Li, Yu-an Zhang
A difference hybrid genetic algorithm to solve 3-SAT problem has been developed in this paper. It is an hybrid genetic algorithm with combination of GSAT, the three-route quick sort algorithm and the cloud theory. In this algorithm, basic cloud generator is used to generate the mutation rate and cross rate. Numerical experiments have been carried out for the analytical investigation of this algorithm. Comparing to the similar algorithms, it is proven that the time of finding optimal solution has been reduced and the success probability has raised. Finally, the validity and feasibility of the algorithms have been verified.
{"title":"A hybrid genetic algorithm to solve 3-SAT problem","authors":"Bingfen Li, Yu-an Zhang","doi":"10.1109/FSKD.2016.7603220","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603220","url":null,"abstract":"A difference hybrid genetic algorithm to solve 3-SAT problem has been developed in this paper. It is an hybrid genetic algorithm with combination of GSAT, the three-route quick sort algorithm and the cloud theory. In this algorithm, basic cloud generator is used to generate the mutation rate and cross rate. Numerical experiments have been carried out for the analytical investigation of this algorithm. Comparing to the similar algorithms, it is proven that the time of finding optimal solution has been reduced and the success probability has raised. Finally, the validity and feasibility of the algorithms have been verified.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122220522","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：