Concurrency and Computation-Practice & Experience最新文献

Entropy-Aware VM Selection and Placement in Cloud Data Centers 云数据中心中熵感知虚拟机的选择和放置

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-30 DOI: 10.1002/cpe.70117

Somayeh Rahmani, Vahid Khajehvand, Mohsen Torabian

{"title":"Entropy-Aware VM Selection and Placement in Cloud Data Centers","authors":"Somayeh Rahmani, Vahid Khajehvand, Mohsen Torabian","doi":"10.1002/cpe.70117","DOIUrl":"https://doi.org/10.1002/cpe.70117","url":null,"abstract":"<div>\u0000 \u0000 <p>The increase in popularity and demand for cloud services has caused a huge growth of cloud data centers, and this has caused the challenge of energy management in data centers. Virtual Machine (VM) consolidation is a critical process aimed at optimizing resource utilization and minimizing energy usage. VM consolidation with the turnoff of underloaded hosts and reducing the load of overloaded hosts establishes a balance between energy consumption and SLA violations. In fact, the consolidation process includes three sub-problems: determining overloaded and underloaded hosts, VM selection in overloaded hosts, and finding a new destination for VMs that will be migrated (VM placement). This paper introduces an entropy-based approach to VM selection and placement to improve efficiency in cloud data centers. Entropy is a quantifiable characteristic often linked to disorder, randomness, or unpredictability. By leveraging entropy as a measure of workload distribution and uncertainty, the proposed method effectively predicts future resource demands, enabling informed decisions that enhance energy efficiency and reduce SLA violations. A key advantage of this approach is the significant reduction in the number of VM migrations, which decreases overhead and minimizes potential service disruptions. Experimental results demonstrate that our entropy-based method outperforms the VM consolidation process in terms of energy consumption, SLA compliance, and system stability. The findings suggest that this approach offers a more sustainable and cost-effective solution for managing cloud resources, contributing to the development of efficient and reliable cloud computing environments.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 15-17","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Dual-Weighted Multiview Clustering Based on Anchor 基于锚点的双加权多视图聚类

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-30 DOI: 10.1002/cpe.70134

Yan Zhang, Yali Peng, Shengnan Wu, Shigang Liu

{"title":"Dual-Weighted Multiview Clustering Based on Anchor","authors":"Yan Zhang, Yali Peng, Shengnan Wu, Shigang Liu","doi":"10.1002/cpe.70134","DOIUrl":"https://doi.org/10.1002/cpe.70134","url":null,"abstract":"<div>\u0000 \u0000 <p>In the field of multiview clustering, how to make full use of information from multiple data sources to improve the clustering performance has become a hot research topic. However, the rapid growth of high-dimensional multiview data brings great challenges to the research of multiview clustering algorithms, especially the time and space complexity of the algorithms. As an effective solution, anchor-based technique has gained wide attention in large-scale multiview clustering tasks. Nevertheless, the current anchor-based methods fail to fully take into account the importance of different views and the difference and diversity of anchors at the same time, which limits the clustering performance to some extent. To address these problems, we propose a dual-weighted multiview clustering based on anchor (DwMVCA). First, we effectively distinguish the different impacts of high-quality and low-quality views on clustering by adaptively learning the weights of different views. Second, by introducing the adaptive weighting matrix of anchors and self-correlation matrix regularization term, the difference and diversity of anchors are fully considered to effectively reduce the effect of redundant information on clustering. Furthermore, we design a three-step alternating optimization algorithm to solve the resultant optimization problem and prove its convergence. Extensive experimental results show that the proposed DwMVCA has obvious advantages in clustering performance on large-scale datasets, especially on datasets with more than 100,000 samples that still maintain linear time complexity.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 15-17","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

RIES Low-Carbon Economic Dispatch With Improved WSO Algorithm Considering Integrated Demand Response 考虑综合需求响应的改进WSO算法的低碳经济调度

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-30 DOI: 10.1002/cpe.70139

Jiaqi Li

{"title":"RIES Low-Carbon Economic Dispatch With Improved WSO Algorithm Considering Integrated Demand Response","authors":"Jiaqi Li","doi":"10.1002/cpe.70139","DOIUrl":"https://doi.org/10.1002/cpe.70139","url":null,"abstract":"<div>\u0000 \u0000 <p>Aiming at the low carbon economic dispatch problem of the regional integrated energy system, a low carbon economic dispatch model combining integrated demand response and carbon capture and storage technology is proposed, and an improved great white shark optimization algorithm is used for solving. Experimental results show that this method can significantly reduce the system dispatch cost. Compared with traditional methods, the total dispatch cost is reduced by 22.81% and 17.77%, respectively. Meanwhile, the utilization rates of wind energy and solar energy are improved, and the curtailment rates of wind power and solar power are reduced to 0% respectively. In addition, the improved great white shark optimization algorithm exhibits a faster convergence speed and higher solution accuracy during the solving process. Its solution time cost is reduced by 66.45% and 45.74% compared with the traditional great white shark optimization algorithm and the whale optimization algorithm respectively. This research provides a new strategy for achieving the low-carbon economic operation of the regional integrated energy system and makes an important contribution to promoting the transformation of the energy structure and sustainable development.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 15-17","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Knowledge Graph and CNN-GRU in College Students' Mental Health Education and Psychological Crisis Intervention 知识图谱与CNN-GRU在大学生心理健康教育与心理危机干预中的整合

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-30 DOI: 10.1002/cpe.70138

Biao Gan, Xiaoxia Jin

{"title":"Integration of Knowledge Graph and CNN-GRU in College Students' Mental Health Education and Psychological Crisis Intervention","authors":"Biao Gan, Xiaoxia Jin","doi":"10.1002/cpe.70138","DOIUrl":"https://doi.org/10.1002/cpe.70138","url":null,"abstract":"<div>\u0000 \u0000 <p>To improve the predictive ability of depression behavior among college students and improve the mental health warning system for college students, this study proposes a support vector machine prediction model with a depression knowledge graph and a depression prediction model with a convolutional neural network gated loop unit, according to the Weibo platform and language, gender, behavior, and emotional characteristics, to predict depression behavior among college students. The model constructed by the research institute outperformed the comparison model in all indicators, with an average improvement of 9.95%, 12.2%, 14.55%, and 11.55% in accuracy, recall, F1 score, and precision. In addition, the area value under the operating characteristic curve of the subjects in the final prediction model tended to 0.872, which was an average improvement of 0.059. The accuracy, recall, F1 score, and precision of the proposed prediction model had been improved by an average of 0.216, 0.140, 0.169, and 0.081. Thus, the model constructed by the research institute exhibits superior predictive ability for depressive behavior, providing theoretical reference for optimizing the mental health warning system for college students.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 15-17","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Construction and Application of a Digital Platform for Charitable Cultural Resources Integrating VR Technology and BiGRU VR技术与BiGRU相结合的慈善文化资源数字平台的构建与应用

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70123

Huifang Liu, Huilin Ye, Yunfeng Ye

{"title":"Construction and Application of a Digital Platform for Charitable Cultural Resources Integrating VR Technology and BiGRU","authors":"Huifang Liu, Huilin Ye, Yunfeng Ye","doi":"10.1002/cpe.70123","DOIUrl":"https://doi.org/10.1002/cpe.70123","url":null,"abstract":"<div>\u0000 \u0000 <p>As an important spiritual driving force to promote the development of public welfare undertakings, charity culture is currently facing challenges such as lack of professional talents and inefficient resource management. The purpose of this research is to build a digital platform of charity cultural resources that integrates virtual reality technology and bidirectional gated circulation unit network, so as to solve the problems of low efficiency of charity cultural information processing, insufficient interaction, and weak public cognition. By introducing a sentence-level attention mechanism and a relationship perception enhancement module, the bidirectional gated cyclic unit network model is improved, and the entity extraction and relationship mining capabilities of the charity culture knowledge map are optimized. Combine virtual reality technology to realize dynamic visual display of cultural resources to improve platform performance. In the initial stage of the pattern, the growth rate of <i>F</i>1 was very fast; then the growth rate slowed down, and finally stabilized, with good generalization performance. At 80% CPU occupancy, the response time of the system did not change by more than 0.18 s. With 500 and 1000 parallel users respectively, the communication efficiency of the platform reached 98.37%, demonstrating good signal transmission and communication performance. However, the hardware environment of the digital platform constructed in this study may limit its popularity, and the real-time update and maintenance of the knowledge graph are faced with challenges.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 12-14","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 S-Threshold Method to Perform Horizontal Auto-Scaling in a Cloud Computing Environment 云计算环境下水平自动伸缩的s -阈值方法

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70135

Archana Archana, Narander Kumar

{"title":"A S-Threshold Method to Perform Horizontal Auto-Scaling in a Cloud Computing Environment","authors":"Archana Archana, Narander Kumar","doi":"10.1002/cpe.70135","DOIUrl":"https://doi.org/10.1002/cpe.70135","url":null,"abstract":"<div>\u0000 \u0000 <p>Cloud computing provides numerous benefits to individuals and any organization, making it a vital technology today. Users can communicate with the cloud computing systems and access the resources through the network. The need for resources can be increased, or at some time, it can be minimized according to the necessity of the resources. However, dynamic scaling is the pivotal property of cloud computing systems to dynamically devote the resources and manage the load while maintaining the quality of service requirement. This paper aims to provide a horizontal auto-scaling method that makes the system fault-tolerant, meets processing demand, optimizes the overall performance, meets user satisfaction, and ensures the quality of service requirement. The proposed S-Threshold method combines the State–action–reward–state–action (SARSA) method with the threshold model. It overcomes the drawbacks of the threshold method, automatically allocates the resources by adding or removing the machine according to the requisite basis, and ensures the aforementioned objectives. In this paper, the system initially relies on threshold-based rules for quick decisions. Over time, SARSA learns from experience and improves decisions, making scaling more adaptive and optimized. The proposed method juxtaposed with some existing methods and evaluated the five performance metrics to state the effectiveness of the proposed method. CloudSimPlus simulator simulates the proposed method into three significant categories: with various numbers of cloudlets, processing speeds, and VMs. While considering the increasing number of cloudlets, increasing processing speed, and increase in VMs, it noted that evaluated results of the proposed method give 50%, 80%, 85%, 60%, and 62% better results with respect to makespan, response time, waiting duration, average turnaround time, and throughput respectively.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 12-14","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies 在AMD和Nvidia图形处理器上的模板计算：性能和调优策略

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70129

Johannes Pekkilä, Oskar Lappi, Fredrik Robertsén, Maarit J. Korpi-Lagg

引用次数: 0

Where High-Performance Computing Meets Radiotherapy for Enhanced Intensity-Modulated Radiation Therapy Planning 增强调强放疗计划中高性能计算与放疗的结合

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70133

Juan José Moreno, Savíns Puertas-Martín, Juana L. Redondo, Pilar M. Ortigosa, Ester M. Garzón

{"title":"Where High-Performance Computing Meets Radiotherapy for Enhanced Intensity-Modulated Radiation Therapy Planning","authors":"Juan José Moreno, Savíns Puertas-Martín, Juana L. Redondo, Pilar M. Ortigosa, Ester M. Garzón","doi":"10.1002/cpe.70133","DOIUrl":"https://doi.org/10.1002/cpe.70133","url":null,"abstract":"<p>Intensity Modulated Radiotherapy (IMRT) employs radiation beams with varying angles and intensities to precisely target cancerous tissues while sparing healthy organs. Planning methods based on the generalized Equivalent Uniform Dose (gEUD) metric achieve excellent Planning Target Volume coverage. However, computing these plans requires extensive parameter adjustments and multiple model evaluations, making the process resource-intensive and time-consuming. This study aims to enhance the computational efficiency of radiotherapy plans by automating the adjustment of gEUD parameters, reducing solution times, and facilitating clinical integration. We introduced a novel approach that combines Gradient Descent algorithms with evolutionary optimization to explore the gEUD parameter space. This hybrid methodology generates radiation plans that meet clinical constraints. To address the high computational costs, we implemented parallelization and batching strategies, leveraging multicore servers to accelerate the optimization process and enable real-time clinical applications. Benchmarking was conducted on three multicore platforms with distinct micro-architectures, testing various batch sizes and thread configurations. Using a dataset of three Head and Neck IMRT patients treated with nine beams, our approach demonstrated substantial computational speed-ups. Results confirmed the ability of the method to consistently produce high-quality radiation therapy plans that meet clinical constraints. By effectively exploiting multicore servers, this approach overcomes the computational challenges of gEUD parameter tuning, enabling its integration into clinical practice. This advancement reduces planning times, supports medical physicists, and ultimately enhances patient care in radiotherapy.</p>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 12-14","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cpe.70133","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of a Configurable Acoustic Sensor Network for Privacy-Compliant Urban Soundscape Recordings 一个可配置的声学传感器网络的设计，用于隐私兼容的城市声景记录

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70137

Paraskevi Kritopoulou, Loupas Georgios, Eleftheria Lagiokapa, Nefeli Georgakopoulou, Sotiris Diplaris, Stefanos Vrochidis

{"title":"Design of a Configurable Acoustic Sensor Network for Privacy-Compliant Urban Soundscape Recordings","authors":"Paraskevi Kritopoulou, Loupas Georgios, Eleftheria Lagiokapa, Nefeli Georgakopoulou, Sotiris Diplaris, Stefanos Vrochidis","doi":"10.1002/cpe.70137","DOIUrl":"https://doi.org/10.1002/cpe.70137","url":null,"abstract":"<p>Environmental acoustics, particularly urban soundscape monitoring, has gained increasing consideration since the United Nations established the Sustainable Development Goals in 2015, and to an even greater extent with the rise of privacy concerns following the introduction of global regulations such as GDPR. As a result, privacy-compliant devices have become essential for soundscape monitoring in urban environments. In this paper, we present the design and implementation of a portable AI-driven, privacy-compliant urban sound recording device that locally captures and processes acoustic data on the edge. In more detail, this device operates as a sensor that captures soundscapes and processes them through a pipeline, which employs a pre-trained open-source AI model to anonymize human voices, ensuring privacy without compromising the integrity of the acoustic environment. The anonymization process alters human speech in a way that protects identity while maintaining environmental audio quality. The device can function as a standalone sensor or as part of a synchronized network of distributed sensors. Privacy-focused evaluation of the device's recordings indicates that, while the anonymization process impacts speech intelligibility, it preserves the overall soundscape with a recall rate of 96%. The system was deployed in a real-world setting with four temporally synchronized sensors. While network synchronization was achieved, a 1 to 2-s deviation was occasionally observed in the first duty cycle interval, reflecting timing variability inherent to Cron-based script triggering. This limitation has been identified for future refinement. This work demonstrates the feasibility of deploying privacy-compliant, edge-based soundscape sensors in urban environments, contributing to privacy preservation, and enhanced public safety.</p>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 12-14","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cpe.70137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effective Cluster Head and Routing Scheme Estimation Using Mixed Attention-Based Drift Enabled Federated Deep Reinforcement Learning in Wireless Sensor Networks 基于混合注意漂移的无线传感器网络联合深度强化学习簇头和路由方案估计

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2025-05-26 DOI: 10.1002/cpe.70132

Mahesh P. Wankhade, Dharmendra G. Ganage, Megha M. Wankhade, Yugendra Chincholkar

{"title":"Effective Cluster Head and Routing Scheme Estimation Using Mixed Attention-Based Drift Enabled Federated Deep Reinforcement Learning in Wireless Sensor Networks","authors":"Mahesh P. Wankhade, Dharmendra G. Ganage, Megha M. Wankhade, Yugendra Chincholkar","doi":"10.1002/cpe.70132","DOIUrl":"https://doi.org/10.1002/cpe.70132","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless Sensor Networks (WSN) serve as an efficient network for gathering and transmitting data in different application domains with the deployment of Internet of Things (IoT) devices. In the WSN, the selection of optimal cluster heads (CHs) and routing is an NP-hard problem. Nevertheless, the traditional routing protocols encounter challenges in handling frequent node relocations, scalability, long communication delays, energy constraints, security vulnerabilities, and dynamic network environments. Hence, this research proposes the Multi-objective Mixed Attention-based Drift applied Federated deep Reinforcement Learning (M2A-DFR) for selecting the best CH and optimal path for effective data transmission with minimum energy consumption and improved network lifetime. In addition, the M2A-DFR model offers adaptive and energy-efficient routing, taking into account message overhead, packet transfer, communication delay, and scalability. More specifically, the M2A-DFR model facilitates efficient data transmission by promptly detecting the drift occurrences and adapting the model to the dynamic changes in network behavior, thereby improving the overall network efficiency. Further, the federated learning-based global learning method periodically aggregates and updates the explorations of the local models. The simulation results reveal the effectiveness of the proposed approach in terms of energy efficiency, packet transfer ratio, latency, and scalability. Further, the proposed model outperforms other existing techniques, achieving the precision of 95.86%, sensitivity of 95.81%, and accuracy of 95.99%. In addition, the achieved mean square error value for the M2A-DFR model is reduced up to 0.827 when compared with the existing methods.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 12-14","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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