Complex & Intelligent Systems最新文献_第6页

Fall detection method based on spatio-temporal coordinate attention for high-resolution networks 基于高分辨率网络时空坐标注意力的跌倒检测方法

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-11-01 DOI: 10.1007/s40747-024-01660-4

Xiaorui Zhang, Qijian Xie, Wei Sun, Ting Wang

{"title":"Fall detection method based on spatio-temporal coordinate attention for high-resolution networks","authors":"Xiaorui Zhang, Qijian Xie, Wei Sun, Ting Wang","doi":"10.1007/s40747-024-01660-4","DOIUrl":"https://doi.org/10.1007/s40747-024-01660-4","url":null,"abstract":"Fall behavior is closely related to the high mortality rate of the elderly, so fall detection has become an important and urgent research area in human behavior recognition. However, the existing fall detection methods, suffer from the loss of detailed action information during feature extraction due to the downsampling operation, resulting in subpar performance when detecting falls with similar behaviors such as lying and sitting. To solve the challenges, this study proposes a high-resolution spatio-temporal feature extraction method based on a spatio-temporal coordinate attention mechanism. The method employs 3D convolutions to extract spatio-temporal features and utilizes gradual down-sampling to generate a multi-resolution sub-network, thus realizing multi-scale fusion and perception enhancement of details. In particular, this study designs a pseudo-3D basic block, which simulates the ability of 3D convolution, to ensure the running speed of the network while controlling the number of parameters. Further, a spatio-temporal coordinate attention mechanism is designed to accurately extract the spatio-temporal positional changes of key skeletal points and the interrelationships among them. Long-term dependencies in horizontal, vertical, temporal directions are captured through three one-dimensional global pooling operations. Then the long-range relationships and channel correlations among features are captured by cascading and slicing operations. Finally, the key information is effectively highlighted by performing dot-multiplication operations between the feature maps from the horizontal, vertical and temporal directions and the input feature maps. Experimental results on three typical public datasets show that the proposed method can better extract motion features and improve the accuracy of fall detection.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"4 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A spherical Z-number multi-attribute group decision making model based on the prospect theory and GLDS method 基于前景理论和 GLDS 方法的球形 Z 数多属性群体决策模型

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-09-13 DOI: 10.1007/s40747-024-01552-7

Meiqin Wu, Sining Ma, Jianping Fan

{"title":"A spherical Z-number multi-attribute group decision making model based on the prospect theory and GLDS method","authors":"Meiqin Wu, Sining Ma, Jianping Fan","doi":"10.1007/s40747-024-01552-7","DOIUrl":"https://doi.org/10.1007/s40747-024-01552-7","url":null,"abstract":"Multi-attribute group decision-making is an important research field in decision science, and its theories and methods have been widely applied to engineering, economics and management. However, as the information embedded volume and complexity of decision-making expand, the diversity and heterogeneity of decision-making groups present significant challenges to the decision-making process. In order to effectively address these challenges, this paper defines the concept of spherical Z-number, which is a fuzzy number that takes into account a wide range of evaluation and its reliability. Additionally, a group decision-making model in a spherical Z-number environment is proposed. First, an objective phased tracking method is used to determine expert weights, maintain the consistency in decision-making group evaluations. The gained and lost dominance score method is combined with prospect theory to integrate expert psychological behavior when facing risks. The proposed method considers both group utility and individual regret, and balances the gains and losses of various options in the decision-making process. Finally, in response to the 3R principle, the model is employed to address the shared e-bike recycling supplier selection problem and to assess the viability of the decision-making outcomes. The results demonstrate that the model is robust in the context of varying parameter configurations. Moreover, the correlation coefficients between its ranking outcomes and those of alternative methodologies are all above 0.77, and its average superiority degree is 1.121, which is considerably higher than that of other methods. Consequently, the model's effectiveness and superiority are substantiated.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"34 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A collision-free transition path planning method for placement robots in complex environments 复杂环境中放置机器人的无碰撞过渡路径规划方法

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-09-09 DOI: 10.1007/s40747-024-01585-y

Yanzhe Wang, Qian Yang, Weiwei Qu

{"title":"A collision-free transition path planning method for placement robots in complex environments","authors":"Yanzhe Wang, Qian Yang, Weiwei Qu","doi":"10.1007/s40747-024-01585-y","DOIUrl":"https://doi.org/10.1007/s40747-024-01585-y","url":null,"abstract":"In Automated Fiber Placement (AFP), the substantial structure of the placement robot, the variable mold shapes, and the limited free space pose significant challenges for planning collision-free robot transitions. The task involves planning a collision-free path within the robot's high-dimensional configuration space. Informed RRT* is a common approach for such problems but often struggles with efficiency and path quality in environments with large informed sampling spaces influenced by obstacles. To address these issues, this paper proposes an improved Informed RRT* algorithm with a Local Knowledge Acceleration sampling strategy (LKA-Informed RRT*), aimed at enhancing planning efficiency and adaptability in complex obstacle settings. An Adaptive Sampling Control (ASC) rate is introduced, measuring the algorithm’s convergence speed, guides the algorithm to switch between informed and local sampling adaptively. The proposed local sampling method uses failure nodes from the exploration process to estimate obstacle distributions, steering sampling toward regions that expedite path convergence. Experimental results show that LKA-Informed RRT* significantly outperforms state-of-the-art algorithms in convergence efficiency and path cost. Compared to the original Informed RRT*, the proposed method reduces planning time by about 60%, substantially boosting efficiency for collision-free transitions in complex environments.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"22 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SAGB: self-attention with gate and BiGRU network for intrusion detection SAGB：利用门和 BiGRU 网络进行自注意入侵检测

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-09-09 DOI: 10.1007/s40747-024-01577-y

Zhanhui Hu, Guangzhong Liu, Yanping Li, Siqing Zhuang

{"title":"SAGB: self-attention with gate and BiGRU network for intrusion detection","authors":"Zhanhui Hu, Guangzhong Liu, Yanping Li, Siqing Zhuang","doi":"10.1007/s40747-024-01577-y","DOIUrl":"https://doi.org/10.1007/s40747-024-01577-y","url":null,"abstract":"Network traffic intrusion detection technology plays an important role in host and platform security. At present, machine learning and deep learning methods are often used for network traffic intrusion detection. However, the imbalance of relevant data sets will cause the model algorithm to learn the features of the majority categories and ignore the features of the minority categories, which will seriously affect the precision of network intrusion detection models. The number of samples of the attacks is much less than the number of normal samples. The classification performance on unbalanced data sets is poor and can not identify the minority attack samples well. To solve these problems, this paper proposed the resampling mechanism, which used random undersampling for the majority categories samples and K-Smote oversampling for the minority categories samples, so as to generate a more balanced data set and improve the model's detection rate for the minority categories. This paper proposed the Self-Attention with Gate (SAG) and BiGRU network model for intrusion detection on the CICIDS2017 data set, which can fully extract high-dimensional information from data samples and improve the detection rate of network attacks. The Self-Attention with Gate mechanism (SAG) based on the Transformer performed the feature extraction, filtered the irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. Compared to the experimental results of other algorithms, such as Random Forest (RF) and BiGRU, it can be found that the overall classification precision for the SAG-BiGRU model in this paper is much higher and also has a good effect on the NSL-KDD data set.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"15 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integration of a novel 3D chaotic map with ELSS and novel cross-border pixel exchange strategy for secure image communication 将新型 3D 混沌地图与 ELSS 和新型跨境像素交换策略相结合，实现安全图像通信

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-09-09 DOI: 10.1007/s40747-024-01568-z

Sajid Khan, Hao Peng, Zhaoquan Gu, Sardar Usman, Namra Mukhtar

{"title":"Integration of a novel 3D chaotic map with ELSS and novel cross-border pixel exchange strategy for secure image communication","authors":"Sajid Khan, Hao Peng, Zhaoquan Gu, Sardar Usman, Namra Mukhtar","doi":"10.1007/s40747-024-01568-z","DOIUrl":"https://doi.org/10.1007/s40747-024-01568-z","url":null,"abstract":"This paper proposes a robust image encryption algorithm that utilizes a Novel three-dimensional (3D) Chaotic map and an Enhanced Logistic Sine System (ELSS). We leverage the unpredictability of 3D chaotic dynamics alongside the complexity of ELSS and DNA Sequence to forge a formidable image encryption scheme. Firstly, the image pixels are converted from decimal to hexadecimal notation and sorted in a 1D pixel array carrying a unique sequence of three channels of the RGB image. Secondly, the secret key is appended to XOR, the values with that 1-D pixels array. Thirdly, values are sorted by performing the binary right shift operation and encoded into DNA. Fourthly, a novel chaotic map is used to perform scrambling operations. Lastly, a novel enormous keyspace ELSS is used to perform efficient Border and Cross-Border (B &CB) pixel exchange, further enhancing the encryption quality of the proposed algorithm. Comprehensive security analysis proved that the proposed algorithm exhibits remarkable resilience against powerful known and chosen plaintext attacks and other prevalent cryptanalysis attacks, including differential attacks and exhaustive key search attacks. Henceforth, the proposed algorithm’s superior security and low computational cost make it an ideal choice for real-time secure image communication across various platforms, including satellite, multimedia, and military communications.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"10 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced EDAS methodology for multiple-criteria group decision analysis utilizing linguistic q-rung orthopair fuzzy hamacher aggregation operators 利用语言q-rung正交模糊哈马赫聚合算子的增强型EDAS方法进行多标准群体决策分析

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-09-06 DOI: 10.1007/s40747-024-01586-x

Jawad Ali, Waqas Ali, Haifa Alqahtani, Muhammad I. Syam

{"title":"Enhanced EDAS methodology for multiple-criteria group decision analysis utilizing linguistic q-rung orthopair fuzzy hamacher aggregation operators","authors":"Jawad Ali, Waqas Ali, Haifa Alqahtani, Muhammad I. Syam","doi":"10.1007/s40747-024-01586-x","DOIUrl":"https://doi.org/10.1007/s40747-024-01586-x","url":null,"abstract":"The linguistic q-rung orthopair fuzzy ((L^{q}ROF)) set serves as a useful way of presenting uncertain information by offering more space for decision experts. In the present research, we first link the concepts of Hamacher t-norm and t-conorm with the frame of (L^{q}ROF) numbers to develop and analyze the innovative (L^{q}ROF) Hamacher operations. Then, following the proposed Hamacher’s norm operations, a series of aggregation operators including (L^{q}ROF) weighted averaging, (L^{q}ROF) ordered weighted averaging, (L^{q}ROF) hybrid averaging, (L^{q}ROF) weighted geometric, (L^{q}ROF) ordered weighted geometric, (L^{q}ROF) hybrid geometric operators are investigated. Some interesting aspects of these AOs are also presented. We further develop evaluation based on distance from average solution (EDAS) approach in light of the newly outlined concepts to cope with (L^{q}ROF) decision-making problems where the weight information of criteria is fully unknown, ultimately, the practicality of the framed approach is demonstrated through an empirical case, and a detailed analysis is carried out to showcase the methodology dominance.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"48 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph convolutional networks with the self-attention mechanism for adaptive influence maximization in social networks 具有自我关注机制的图卷积网络在社交网络中实现自适应影响力最大化

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-08-28 DOI: 10.1007/s40747-024-01604-y

Jianxin Tang, Shihui Song, Qian Du, Yabing Yao, Jitao Qu

{"title":"Graph convolutional networks with the self-attention mechanism for adaptive influence maximization in social networks","authors":"Jianxin Tang, Shihui Song, Qian Du, Yabing Yao, Jitao Qu","doi":"10.1007/s40747-024-01604-y","DOIUrl":"https://doi.org/10.1007/s40747-024-01604-y","url":null,"abstract":"The influence maximization problem that has drawn a great deal of attention from researchers aims to identify a subset of influential spreaders that can maximize the expected influence spread in social networks. Existing works on the problem primarily concentrate on developing non-adaptive policies, where all seeds will be ignited at the very beginning of the diffusion after the identification. However, in non-adaptive policies, budget redundancy could occur as a result of some seeds being naturally infected by other active seeds during the diffusion process. In this paper, the adaptive seeding policies are investigated for the intractable adaptive influence maximization problem. Based on deep learning model, a novel approach named graph convolutional networks with self-attention mechanism (ATGCN) is proposed to address the adaptive influence maximization as a regression task. A controlling parameter is introduced for the adaptive seeding model to make a tradeoff between the spreading delay and influence coverage. The proposed approach leverages the self-attention mechanism to dynamically assign importance weight to node representations efficiently to capture the node influence feature information relevant to the adaptive influence maximization problem. Finally, intensive experimental findings on six real-world social networks demonstrate the superiorities of the adaptive seeding policy over the state-of-the-art baseline methods to the conventional influence maximization problem. Meanwhile, the proposed adaptive seeding policy ATGCN improves the influence spread rate by up to 7% in comparison to the existing state-of-the-art greedy-based adaptive seeding policy.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"7 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142085525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack 仅有准确性是不够的：异质集合模型与 FGSM 攻击的比较

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-08-28 DOI: 10.1007/s40747-024-01603-z

Reham A. Elsheikh, M. A. Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata

{"title":"Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack","authors":"Reham A. Elsheikh, M. A. Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata","doi":"10.1007/s40747-024-01603-z","DOIUrl":"https://doi.org/10.1007/s40747-024-01603-z","url":null,"abstract":"In this paper, based on facial landmark approaches, the possible vulnerability of ensemble algorithms to the FGSM attack has been assessed using three commonly used models: convolutional neural network-based antialiasing (A_CNN), Xc_Deep2-based DeepLab v2, and SqueezeNet (Squ_Net)-based Fire modules. Firstly, the three individual deep learning classifier-based Facial Emotion Recognition (FER) classifications have been developed; the predictions from all three classifiers are then merged using majority voting to develop the HEM_Net-based ensemble model. Following that, an in-depth investigation of their performance in the case of attack-free has been carried out in terms of the Jaccard coefficient, accuracy, precision, recall, F1 score, and specificity. When applied to three benchmark datasets, the ensemble-based method (HEM_Net) significantly outperforms in terms of precision and reliability while also decreasing the dimensionality of the input data, with an accuracy of 99.3%, 87%, and 99% for the Extended Cohn-Kanade (CK+), Real-world Affective Face (RafD), and Japanese female facial expressions (Jaffee) data, respectively. Further, a comprehensive analysis of the drop in performance of every model affected by the FGSM attack is carried out over a range of epsilon values (the perturbation parameter). The results from the experiments show that the advised HEM_Net model accuracy declined drastically by 59.72% for CK + data, 42.53% for RafD images, and 48.49% for the Jaffee dataset when the perturbation increased from A to E (attack levels). This demonstrated that a successful Fast Gradient Sign Method (FGSM) can significantly reduce the prediction performance of all individual classifiers with an increase in attack levels. However, due to the majority voting, the proposed HEM_Net model could improve its robustness against FGSM attacks, indicating that the ensemble can lessen deception by FGSM adversarial instances. This generally holds even as the perturbation level of the FGSM attack increases.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"6 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142085549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive dynamic programming-based multi-fault tolerant control of reconfigurable manipulator with input constraint 基于自适应动态编程的带输入约束的可重构机械手多故障容错控制

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-08-28 DOI: 10.1007/s40747-024-01550-9

Zhenguo Zhang, Tianhao Ma, Yadan Zhao, Shuai Yu, Fan Zhou

引用次数: 0

A DQN based approach for large-scale EVs charging scheduling 基于 DQN 的大规模电动汽车充电调度方法

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2024-08-21 DOI: 10.1007/s40747-024-01587-w

Yingnan Han, Tianyang Li, Qingzhu Wang

{"title":"A DQN based approach for large-scale EVs charging scheduling","authors":"Yingnan Han, Tianyang Li, Qingzhu Wang","doi":"10.1007/s40747-024-01587-w","DOIUrl":"https://doi.org/10.1007/s40747-024-01587-w","url":null,"abstract":"This paper addresses the challenge of large-scale electric vehicle (EV) charging scheduling during peak demand periods, such as holidays or rush hours. The growing EV industry has highlighted the shortcomings of current scheduling plans, which struggle to manage surge large-scale charging demands effectively, thus posing challenges to the EV charging management system. Deep reinforcement learning, known for its effectiveness in solving complex decision-making problems, holds promise for addressing this issue. To this end, we formulate the problem as a Markov decision process (MDP). We propose a deep Q-learning (DQN) based algorithm to improve EV charging service quality as well as minimizing average queueing times for EVs and average idling times for charging devices (CDs). In our proposed methodology, we design two types of states to encompass global scheduling information, and two types of rewards to reflect scheduling performance. Based on this designing, we developed three modules: a fine-grained feature extraction module for effectively extracting state features, an improved noise-based exploration module for thorough exploration of the solution space, and a dueling block for enhancing Q value evaluation. To assess the effectiveness of our proposal, we conduct three case studies within a complex urban scenario featuring 34 charging stations and 899 scheduled EVs. The results of these experiments demonstrate the advantages of our proposal, showcasing its superiority in effectively locating superior solutions compared to current methods in the literature, as well as its efficiency in generating feasible charging scheduling plans for large-scale EVs. The code and data are available by accessing the hyperlink: https://github.com/paperscodeyouneed/A-Noisy-Dueling-Architecture-for-Large-Scale-EV-ChargingScheduling/tree/main/EV%20Charging%20Scheduling.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"8 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0