Pervasive and Mobile Computing最新文献_第8页

Federated learning with empirical insights: Leveraging gradient historical experiences for performance fairness 具有经验见解的联合学习：利用梯度历史经验来实现性能公平性

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-05-01 Epub Date: 2025-05-06 DOI: 10.1016/j.pmcj.2025.102061

Tongzhijun Zhu , Ying Lin , Yanzhen Qu , Zediao Liu , Yayu Luo , Tenglong Mao , Ziyi Chen

{"title":"Federated learning with empirical insights: Leveraging gradient historical experiences for performance fairness","authors":"Tongzhijun Zhu , Ying Lin , Yanzhen Qu , Zediao Liu , Yayu Luo , Tenglong Mao , Ziyi Chen","doi":"10.1016/j.pmcj.2025.102061","DOIUrl":"10.1016/j.pmcj.2025.102061","url":null,"abstract":"<div><div>Performance fairness has always been a key issue in federated learning (FL), however, the pursuit of performance consistency can lead to a trade-off where the accuracy of well-performing clients is compromised to enhance the accuracy of poor-performing clients. To ensure equitable treatment and unbiased outcomes for all participants in the FL process, we propose FedMH, a fair and fast multi-gradient descent federated learning algorithm with reinforced gradient historical empirical information. We have conducted a theoretical analysis of FedMH from the perspectives of fairness and convergence. Extensive experiments are performed on four federated datasets, revealing significant improvements achieved by FedMH compared to state-of-the-art baselines. Moreover, the experimental findings highlight FedMH’s superior performance in fine-grained classification problems when compared to existing advanced baselines. In brief, the proper utilization of gradient historical empirical information helps improve the effectiveness and fairness of FL, making it more suitable for large-scale and heterogeneous distributed environments.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"110 ","pages":"Article 102061"},"PeriodicalIF":3.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Contrastive-representation IMU-based fitness activity recognition enhanced by bio-impedance sensing 生物阻抗感知增强基于对比表示imu的健身活动识别

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-05-01 Epub Date: 2025-04-12 DOI: 10.1016/j.pmcj.2025.102047

Mengxi Liu, Vitor Fortes Rey, Lala Shakti Swarup Ray, Bo Zhou, Paul Lukowicz

{"title":"Contrastive-representation IMU-based fitness activity recognition enhanced by bio-impedance sensing","authors":"Mengxi Liu, Vitor Fortes Rey, Lala Shakti Swarup Ray, Bo Zhou, Paul Lukowicz","doi":"10.1016/j.pmcj.2025.102047","DOIUrl":"10.1016/j.pmcj.2025.102047","url":null,"abstract":"<div><div>While IMU-based Human Activity Recognition (HAR) has achieved significant success in wearable and pervasive computing areas over the past decade, the potential for further improvement of IMU-based HAR performance through the contrastive representation method enhanced by other sensing modalities remains underexplored. In this work, we propose a contrastive representation learning framework to demonstrate that bio-impedance can enhance IMU-based fitness activity recognition beyond the common sensor fusion method, which requires all sensing modalities to be available during both training and inference phases. Instead, in our proposed framework, only the target sensing modality (IMU) is required at inference time. To evaluate our method, we collected both IMU and bio-impedance sensing data through an experiment involving ten subjects performing six types of upper-body and four kinds of lower-body exercises over five days. The bio-impedance-alone classification model achieved an average Macro F1 score of 75.49% and 71.57% for upper-body and lower-body fitness activities, respectively, which was lower than that of the IMU-alone model (83.10% and 78.61%). However, with our proposed method, significant performance improvement (2.66% for upper-body activities and 3.2% for lower-body activities) was achieved by the IMU-only classification model. This improvement leverages the contrastive representation learning framework, where the information from bio-impedance sensing guides the training procedure of the IMU-only model. The results highlight the potential of contrastive representation learning as a valuable tool for advancing fitness activity recognition, with bio-impedance playing a pivotal role in augmenting the capabilities of IMU-based systems.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"110 ","pages":"Article 102047"},"PeriodicalIF":3.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Trajectory prediction-based migration target selection method for vehicular network services 基于轨迹预测的车辆网络服务迁移目标选择方法

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-05-01 Epub Date: 2025-04-29 DOI: 10.1016/j.pmcj.2025.102062

Chuan Ying Peng , Wu Jun Yang , Zhi Xian Chang , Jin Ming Lv , Juan Guo

{"title":"Trajectory prediction-based migration target selection method for vehicular network services","authors":"Chuan Ying Peng , Wu Jun Yang , Zhi Xian Chang , Jin Ming Lv , Juan Guo","doi":"10.1016/j.pmcj.2025.102062","DOIUrl":"10.1016/j.pmcj.2025.102062","url":null,"abstract":"<div><div>In mobile vehicular networks, when edge servers (ES) provide services to high-speed moving vehicles, the problem of service interruption is particularly prominent due to the limitation of service coverage, which seriously affects the continuity and quality of services. To solve this problem, this paper proposes a service migration target selection method based on trajectory prediction. The method first predicts the future movement trajectories of vehicles by the TS-LSTM trajectory prediction model to identify potential activity areas and their associated edge servers; then, the target server selection is optimized using Deep Q-Network (DQN), which jointly incorporate delay and load fairness into the optimization objective function. In addition, pre-replication technology is introduced during the service migration process to ensure that the original servers can continue to provide services during the service switchover, allowing the target servers to seamlessly receive tasks, effectively ensuring service continuity. The experimental results show that, compared with the current state-of-the-art, the proposed method has significant advantages in terms of convergence speed, service delay and service stability: the average end-to-end service delay is reduced by 32% and the service rejection rate is reduced by 28%.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"110 ","pages":"Article 102062"},"PeriodicalIF":3.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

In-bed gesture recognition to support the communication of people with Aphasia 床上手势识别，以支持失语症患者的交流

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-02-26 DOI: 10.1016/j.pmcj.2025.102029

Ana Patrícia Rocha, Afonso Guimarães, Ilídio C. Oliveira, José Maria Fernandes, Miguel Oliveira e Silva, Samuel Silva, António Teixeira

{"title":"In-bed gesture recognition to support the communication of people with Aphasia","authors":"Ana Patrícia Rocha, Afonso Guimarães, Ilídio C. Oliveira, José Maria Fernandes, Miguel Oliveira e Silva, Samuel Silva, António Teixeira","doi":"10.1016/j.pmcj.2025.102029","DOIUrl":"10.1016/j.pmcj.2025.102029","url":null,"abstract":"<div><div>People with language impairments can have difficulties expressing themselves to others, leading to major limitations to their safety, independence, and quality of life in general. Aphasia is an example of an acquired language impairment that affects many people (around 2 million in the United States), being commonly caused by stroke, but also by other brain injuries. Several augmentative and alternative communication solutions are available to help people with communication difficulties, but they are generally not suitable for all contexts of use (e.g., lying in bed). In the scope of the “APH-ALARM” project, which aimed at developing solutions to support people with Aphasia, we envision a system for the bedroom that enables conveying messages to be sent to a caregiver or relative, for example. Focusing on gesture input, in this contribution, we investigated if smartwatch sensors and machine learning (ML) can be used to recognise arm gestures executed while lying. We explored different factors, namely the feature set, size of the sliding window used for feature extraction, and ML classifier. The results obtained with data gathered from ten subjects are promising, with the best factor combinations for the user-independent solution leading to a mean macro F1 score of 94% or 95%. They demonstrate the potential of using wearables to develop a gesture input modality for the in-bed scenario, which can also potentially be extended to other contexts (e.g., sitting in a bed, chair, or sofa, or standing). This research also provides useful insights that inform future work, including the development and deployment of communication support systems that can benefit not only people with communication difficulties (e.g., more independence), but also those caring for them (e.g., more peace of mind).</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102029"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Investment-driven budget allocation and dynamic pricing strategies in edge cache network 边缘缓存网络中投资驱动的预算分配与动态定价策略

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-22 DOI: 10.1016/j.pmcj.2025.102040

Quyuan Wang , Pengyang Chen , Jiadi Liu , Ying Wang , Zhiwei Guo

{"title":"Investment-driven budget allocation and dynamic pricing strategies in edge cache network","authors":"Quyuan Wang , Pengyang Chen , Jiadi Liu , Ying Wang , Zhiwei Guo","doi":"10.1016/j.pmcj.2025.102040","DOIUrl":"10.1016/j.pmcj.2025.102040","url":null,"abstract":"<div><div>Edge Caching is an application with great commercial potential in accelerating content acquisition by near-client content caching. To provide high-quality services for customers, it is indispensable for content providers to purchase or rent sufficient wireless channels and cache storage resources from edge suppliers. However, few work has investigated how to allocate limited budget to the appropriate resources in an economically way for caching at a network edge. In this paper, we construct a Fisher cache market to tackle the budget allocation problem and the price adjustment problem in edge caching by using the portfolio approach. In the budget allocation problem, we utilize the Iso-cost line and threshold settings to narrow search space and propose an algorithm termed as Gradient descent based Portfolio Search (GBPS) to acquire an optimal portfolio within a limited search field. With the aid of market supply and demand in micro economic theory, we put forward K-popular Suppliers Price Adjustment algorithm (KSPA) and Elastic Supply and Demand Price Adjustment algorithm (ESDPA) price adjustment algorithms to achieve market equilibrium within a limited budget. Finally, numerical results demonstrate that the proposed algorithms perform better in terms of trading success rate and total payoff by the comparisons of different algorithms.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102040"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Load-balancing model using game theory in edge-based IoT network 基于博弈论的边缘物联网负载均衡模型

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-16 DOI: 10.1016/j.pmcj.2025.102041

Zaineb Naaz , Gamini Joshi , Vidushi Sharma

引用次数: 0

EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles EPCM：基于数据完整性的电动汽车高效隐私保护充电匹配方案

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-22 DOI: 10.1016/j.pmcj.2025.102042

Tingting Jin, Peng Hu, Kaizhong Zuo, Tianjiao Ni, Dong Xie, Zhangyi Shen, Fulong Chen

{"title":"EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles","authors":"Tingting Jin, Peng Hu, Kaizhong Zuo, Tianjiao Ni, Dong Xie, Zhangyi Shen, Fulong Chen","doi":"10.1016/j.pmcj.2025.102042","DOIUrl":"10.1016/j.pmcj.2025.102042","url":null,"abstract":"<div><div>Compared to traditional charging stations, the Vehicle-to-Vehicle (V2V) charging mode can expand the coverage of the charging network and is expected to become an important supplementary method for future electric vehicle charging. However, the leakage of location privacy in charging matching has become one of the main concerns of users. To tackle this problem, we propose an efficient privacy preserving charging matching scheme, named EPCM, which ensures data integrity without compromising the location privacy of vehicles. Firstly, we utilize the modified Paillier cryptosystem and identity based batch signature to achieve location privacy and data integrity. Secondly, our scheme operates in a round-by-round manner, ensuring immediate task completion and allowing vehicles to dynamically join or leave. The security proof and analysis indicates that EPCM can achieve security features including confidentiality, location privacy, authentication, and data integrity. Furthermore, by carrying out extensive experiments, the experimental results demonstrate that our scheme performs excellently in terms of computational and communication overhead, as well as total transmission delay.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102042"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Navigating transient content: PFC caching approach for NDN-based IoT networks 导航瞬时内容：基于 NDN 的物联网网络的 PFC 缓存方法

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-24 DOI: 10.1016/j.pmcj.2025.102031

Sumit Kumar , Rajeev Tiwari

{"title":"Navigating transient content: PFC caching approach for NDN-based IoT networks","authors":"Sumit Kumar , Rajeev Tiwari","doi":"10.1016/j.pmcj.2025.102031","DOIUrl":"10.1016/j.pmcj.2025.102031","url":null,"abstract":"<div><div>The emergence of Internet-of-Things (IoT) has revolutionized communication among devices. IoT devices autonomously collect and disseminate contents to end-users via network routers. There is growing interest in integrating IoT communications with Named Data Networking (NDN) architecture to retrieve and distribute content efficiently. The content caching characteristics of NDN are pivotal in improving Quality-of-Service (QoS) for IoT. However, unlike multimedia content traffic, which tends to remain static, IoT-generated content is inherently transient in nature, and each content has a finite lifespan. As a result, without efficient caching solutions for IoT contents, the network efficiency and user experience would be degraded. Existing caching approaches often overlook the importance of IoT content freshness, its access pattern and the position of routers during content placement decisions in the IoT networks. In this paper, a novel Popularity and Freshness-based Caching (PFC) scheme has been proposed that aims to strategically cache popular and fresh IoT contents on routers located close to the end-user devices. In the proposed solution, the popularity of content is determined using the request history queue deployed on all network routers. For efficient caching decisions, the hop count metric favors routers in close proximity to end-users. Rigorous simulations with realistic network parameters are performed on the realistic IoT network topologies. The simulation results demonstrate that the PFC approach outperforms existing state-of-the-art caching approaches (LCE, LCC, Consumer-Driven, Consumer-Cache, etc.) on several performance parameters: cache hit ratio, network delay, hop count, network traffic, and energy consumption. This makes the PFC caching approach well-suited for NDN-based IoT networks by enabling efficient content caching decisions.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102031"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

MicroFallNet: A lightweight model for real-time fall detection on smart wristbands MicroFallNet：用于智能手环上的实时跌倒检测的轻量级模型

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-30 DOI: 10.1016/j.pmcj.2025.102046

Jun Hu , Feiyan Cheng , Meng Liu , Xuanle Xu , Xiaojing Li

{"title":"MicroFallNet: A lightweight model for real-time fall detection on smart wristbands","authors":"Jun Hu , Feiyan Cheng , Meng Liu , Xuanle Xu , Xiaojing Li","doi":"10.1016/j.pmcj.2025.102046","DOIUrl":"10.1016/j.pmcj.2025.102046","url":null,"abstract":"<div><div>Falls are a major public health concern for the aging population, leading to significant injuries, loss of independence, and increased healthcare costs. While wearable devices present promising solutions, existing algorithms are often hindered by the limitations of microcontroller units (MCU) in terms of computational power, memory, and energy consumption. To overcome these challenges, we introduce MicroFallNet, a lightweight convolutional neural network designed for accurate and efficient fall detection. MicroFallNet features a novel FireModel architecture, incorporating Squeeze and Expand layers to optimize computational efficiency and enhance feature extraction. The proposed algorithm demonstrates superior performance on the UMAFALL and FallAllD datasets, achieving geometric mean accuracies of 97.91 % and 97.86 %, respectively, significantly surpassing traditional methods. Additionally, MicroFallNet showcases excellent deployment efficiency across various microcontrollers, particularly excelling on the ESP32 smart wristband platform, where it achieves an inference time of just 30.3 milliseconds. This capability makes MicroFallNet ideally suited for real-time fall detection applications, advancing the development of wearable devices for the elderly and contributing substantially to the field of smart health monitoring. Our code will be publicly available at <span><span>https://github.com/qwer12330/MicroFallNet-A-Lightweight-Model-for-Real-Time-Fall-Detection-on-Smart-Wristbands-Using-Sm</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102046"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Bio-inspired recruiting strategies for on-demand connectivity over a multi-layer hybrid CubeSat-UAV networks in emergency scenarios 紧急情况下多层立方体卫星-无人机混合网络按需连接的仿生招聘策略

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-04-01 Epub Date: 2025-03-10 DOI: 10.1016/j.pmcj.2025.102030

Mauro Tropea , Alex Ramiro Masaquiza Caiza , Floriano De Rango

{"title":"Bio-inspired recruiting strategies for on-demand connectivity over a multi-layer hybrid CubeSat-UAV networks in emergency scenarios","authors":"Mauro Tropea , Alex Ramiro Masaquiza Caiza , Floriano De Rango","doi":"10.1016/j.pmcj.2025.102030","DOIUrl":"10.1016/j.pmcj.2025.102030","url":null,"abstract":"<div><div>In emergency scenarios, the network infrastructure must remain reliable and continuously available to ensure connectivity to people and optimal performance in supporting different types of applications, including real-time services. When terrestrial infrastructure is compromised during emergencies, Flying Ad Hoc Networks (FANETs) can offer a quick and effective solution for re-establishing connectivity in affected areas. The dynamic coverage provided by a swarm of UAVs (Unmanned Aerial Vehicles) during a disaster could be crucial for people inside the affected areas. In high-demand and critical situations, the performance of FANETs may deteriorate due to several factors, including simultaneous user connections, high traffic volumes, limited energy resources of network devices, and interference arising within the same geographic region. To address these challenges, this paper proposes a novel, bio-inspired recruitment algorithm that aims to guarantee good performance of FANETs in energy constrained scenarios by efficiently recruiting UAVs to cover the demand of end users connected to the network. In such a scenario, when additional UAVs cannot be reachable using the on-earth network infrastructure and multi-hop routing, the recruiting can be supported through a multi-layer hybrid architecture that integrates CubeSats to forward recruiting requests to potential UAVs located far from the network. This approach not only enhances the connectivity of end users but also ensures that the network can efficiently be adapted to the demands of users in emergency situations.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102030"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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