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Multi-Agent Reinforcement Learning Based Context-Aware Heterogeneous Decision Support System 认领 引用 被引量：1
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作者 Taimoor Hassan Ibrar Hussain +4 位作者 Hafiz Mahfooz Ul Haque Hamid Turab Mirza Muhammad Nadeem Ali Byung-Seo Kim Changheun Oh 《Computers, Materials & Continua》 SCIE EI 2026年第6期1764-1780,共17页
The expeditious proliferation of the smart computing paradigm has a remarkable upsurge towards Artificial Intelligence(AI)assistive reasoning with the incorporation of context-awareness.Context-awareness plays a signi... The expeditious proliferation of the smart computing paradigm has a remarkable upsurge towards Artificial Intelligence(AI)assistive reasoning with the incorporation of context-awareness.Context-awareness plays a significant role in fulfilling users’needs whenever and wherever needed.Context-aware systems acquire contextual information from sensors/embedded sensors using smart gadgets and/or systems,perform reasoning using reinforcement learning(RL)or other reasoning techniques,and then adapt behavior.The core intention of using an RL-based reasoning strategy is to train agents to take the right actions at the right time and in the right place.Generally,agents are rewarded for the correct actions and punished for incorrect actions.In an RL deployment setting,agents intend to get cumulative maximal rewards through the continuous learning process.These systems often operate in a highly decentralized environment and exhibit complex adaptive behavior.However,the agent’s actions on the imperfect nature of context may cause inconsistent reasoning behavior in terms of the agent’s reward policies.In this paper,we present a semantic knowledge-based Multi-agent Reinforcement Learning(MARL)formalism for a context-aware heterogeneous decision support system.This is a four-layered architecture to schedule user’s routine tasks where user’s data is acquired with limited or no human intervention and perform operations autonomously based on agent’s reward/punishment policies.For this,we develop a comprehensive case study considering three different domains’ontologies;namely,Smart Home,Smart Shopping,and Smart Fridge Systems,with the prototypal implementation of the system and show the valid execution dynamics,correctness behavior,and verify the agent’s optimal reward policies. 展开更多
关键词 Multi-agent reinforcement learning Markov decision process heterogeneous systems ontologies reinforcement learning context-awareness
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Explainable Context-Aware Fusion Network for Non-Small Cell Lung Cancer Analysis with Application to Smart Healthcare Systems 认领 引用
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作者 Muhammad Waqar Zeshan Aslam Khan +3 位作者 Arthur Chang Zhishan Guo Chun-Liang Lai Chuan-Yu Chang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期1208-1235,共28页
Lung cancer(LC)is among the dangerous cancers spreading progressively,and a timely LC diagnosis becomes a dire need of the time.Various imaging-based studies have been conducted for accurate LC examination through com... Lung cancer(LC)is among the dangerous cancers spreading progressively,and a timely LC diagnosis becomes a dire need of the time.Various imaging-based studies have been conducted for accurate LC examination through computed tomography(CT),X-ray,and histopathology.Worldwide,the proportion of LC-affected patients in hospitals is growing,thereby increasing imaging data for fast processing and early examination.To facilitate histopathological imaging-based automated and timely decision making for accurate LC prediction,a Context Aware Fusion Network(CAFNet)for holistic feature learning and spatially localized feature learning is proposed in this study for the efficient extraction and processing of global as well as local features,respectively.CAFNet exploits histopathological tissues to ensure local and global attributes uniformity for extracting contextual information.The conducted research achieves histopathological image enhancement using median filtering(MF)and contrast-limited-adaptive-HistogramEqualization(CLAHE).Moreover,the classifying power of the proposed CAFNet is enhanced through superior attributes extraction strategies,such as Mobile Inverted Bottleneck Convolution(MIBConv)employed with Spatial Attention with Residual Learning(SARL)and Channel Attention with Residual Learning(CARL).An innovative,partially adaptive optimization approach is utilized to fine-tune the degree of adaptivity in the learning process of the network.The descriptive behavior of CAFNet is explored through explainable artificial intelligence(XAI)strategies like Gradient-Weighted Class Activation Mapping(GradCAM)and Local Interpretable Model-Agnostic Explanation(LIME).The proposed network achieved an improved average classification accuracy of 7.36%while reducing models’complexity by 85%to 99%as compared to the existing benchmark models.The study also addresses users’accessibility challenges by providing a web-based interface using Gradio for users’real-time interaction. 展开更多
关键词 Lung cancer histopathology context-aware network explainable AI web-based Interface
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Context-Aware Identity Validation for UAV-Assisted Urban Mobility and Traffic Monitoring Environments 认领 引用
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作者 Kuldashbay Avazov Kudratjon Zohirov +6 位作者 Alpamis Kutlimuratov Charos Khidirova Jasur Sevinov Urishev Omadjon Adilbek Dauletov Akmalbek Abdusalomov Young Im Cho 《Computers, Materials & Continua》 SCIE EI 2026年第9期1616-1632,共17页
Unmanned aerial vehicles(UAVs)are becoming a common solution to urban mobility,and traffic monitoring as well,owing to their ability to be deployed flexibly,ability to see a broader area and real-time sensing.However,... Unmanned aerial vehicles(UAVs)are becoming a common solution to urban mobility,and traffic monitoring as well,owing to their ability to be deployed flexibly,ability to see a broader area and real-time sensing.However,the reliability of UAV-assisted traffic systems can be compromised through identity spoofing,Sybil attacks,false data injection,and trajectory manipulation.Current authentication techniques primarily verify cryptographic identities but often cannot detect when a claimed identity is inconsistent with physical movement patterns and settings.To overcome this drawback,this paper presents a context-aware identity validation system,CIV-UAV,for UAV-based urban traffic surveillance.The paradigm combines a model of cryptographic validation,model mobility,on-the-fly visual,road-network,temporal continuity,anomaly scoring,and multi-UAV consensus into a cohesive trust-based validation model.The risk-adaptive policy also adjusts the validation strictness based on the seriousness of the situation and the level of uncertainty.The outcomes of simulations indicate that CIV-UAV enhances identity validation,lowers the false detection and false acceptance rates,and reinforces the detection of spoofing,Sybil behaviour,path forgery,injection of fake events,and vision-communication mismatch attacks.The suggested architecture provides an identity validation system that is easy to implement and can be upgraded to a next-generation UAV-intelligent transportation network. 展开更多
关键词 Context-aware identity validation UAV-assisted traffic monitoring urban mobility security multi-UAV cooperation trust management intelligent transportation systems
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Global context-aware multi-scale feature iterative refinement for aviation-road traffic semantic segmentation 认领 引用
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作者 Mengyue ZHANG Shichun YANG +1 位作者 Xinjie FENG Yaoguang CAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第2期429-441,共13页
Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made re... Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made remarkable achievements in both fine-grained segmentation and real-time performance.However,when faced with the huge differences in scale and semantic categories brought about by the mixed scenes of aerial remote sensing and road traffic,they still face great challenges and there is little related research.Addressing the above issue,this paper proposes a semantic segmentation model specifically for mixed datasets of aerial remote sensing and road traffic scenes.First,a novel decoding-recoding multi-scale feature iterative refinement structure is proposed,which utilizes the re-integration and continuous enhancement of multi-scale information to effectively deal with the huge scale differences between cross-domain scenes,while using a fully convolutional structure to ensure the lightweight and real-time requirements.Second,a welldesigned cross-window attention mechanism combined with a global information integration decoding block forms an enhanced global context perception,which can effectively capture the long-range dependencies and multi-scale global context information of different scenes,thereby achieving fine-grained semantic segmentation.The proposed method is tested on a large-scale mixed dataset of aerial remote sensing and road traffic scenes.The results confirm that it can effectively deal with the problem of large-scale differences in cross-domain scenes.Its segmentation accuracy surpasses that of the SOTA methods,which meets the real-time requirements. 展开更多
关键词 Aviation-road traffic Flying cars Global context-aware Multi-scale feature iterative refinement Semantic segmentation
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Distributed context-aware Transformer-enabled dynamic energy consumption prediction for smart building networks 认领 引用
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作者 Rui Dai Ge Bai 《Digital Communications and Networks》 SCIE EI CSCD 2026年第4期640-648,共9页
The integration of communication networks and artificial intelligence enables the effective collection of data over smart building networks,facilitating more accurate predictions of Building Energy Consumption(BEC).Ho... The integration of communication networks and artificial intelligence enables the effective collection of data over smart building networks,facilitating more accurate predictions of Building Energy Consumption(BEC).However,existing schemes for BEC prediction suffer from limited dynamic adaptability,risks of privacy leakage,and the inability to accurately capture actual energy consumption patterns.To improve prediction accuracy while ensuring privacy and dynamic adaptability,we propose a novel BEC prediction design that incorporates dynamic threshold participation and privacy-preserving mechanisms.Specifically,we design a three-tier network architecture integrated with threshold participation tokens to support dynamic access and dropout of building entities during the BEC model construction process.Furthermore,we develop a Context-Aware Transformer(CAT)network integrated into Federated Learning(FL)to enhance feature sensitivity and facilitate the sharing of knowledge derived from Internet of Things(IoT)data and BEC features.Finally,we evaluate the performance of our design using real-world data,and the results demonstrate that our design achieves superior performance in distributed BEC prediction. 展开更多
关键词 Smart building Dynamic BEC prediction Context-aware Transformer Privacy preservation Federated learning
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Context-Aware Relational Learning for Cooperative UAV Formation 认领 引用
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作者 Zhuxun Li Haoxian Jiang Rui Zhou 《Journal of Beijing Institute of Technology》 EI CAS 2026年第1期44-52,共9页
Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL... Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability. 展开更多
关键词 multi-agent reinforcement learning UAV swarm cooperative formation control path planning context-aware exploration relational learning
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BIG-ABAC:Leveraging Big Data for Adaptive,Scalable,and Context-Aware Access Control 认领 引用 被引量：1
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作者 Sondes Baccouri Takoua Abdellatif 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第4期1071-1093,共23页
Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a trans... Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a transformative approach to Attribute-Based Access Control(ABAC)by integrating real-time policy evaluation and contextual adaptation.Unlike traditional ABAC systems that rely on static policies,BIG-ABAC dynamically updates policies in response to evolving rules and real-time contextual attributes,ensuring precise and efficient access control.Leveraging decision trees evaluated in real-time,BIG-ABAC overcomes the limitations of conventional access control models,enabling seamless adaptation to complex,high-demand scenarios.The framework adheres to the NIST ABAC standard while incorporating modern distributed streaming technologies to enhance scalability and traceability.Its flexible policy enforcement mechanisms facilitate the implementation of regulatory requirements such as HIPAA and GDPR,allowing organizations to align access control policies with compliance needs dynamically.Performance evaluations demonstrate that BIG-ABAC processes 95% of access requests within 50 ms and updates policies dynamically with a latency of 30 ms,significantly outperforming traditional ABAC models.These results establish BIG-ABAC as a benchmark for adaptive,scalable,and context-aware access control,making it an ideal solution for dynamic,high-risk domains such as healthcare,smart cities,and Industrial IoT(IIoT). 展开更多
关键词 ABAC big data context-aware decision trees adaptive policy scalability
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Biologically Inspired Design of Context-Aware Smart Products 认领 引用 被引量：6
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作者 Ang Liu Ivan Teo +4 位作者 Diandi Chen Stephen Lu Thorsten Wuest Zhinan Zhang Fei Tao 《Engineering》 SCIE EI CAS 2019年第4期637-645,共9页
The rapid development of information and communication technologies(ICTs)and cyber-physical systems(CPSs)has paved the way for the increasing popularity of smart products.Context-awareness is an important facet of pro... The rapid development of information and communication technologies(ICTs)and cyber-physical systems(CPSs)has paved the way for the increasing popularity of smart products.Context-awareness is an important facet of product smartness.Unlike artifacts,various bio-systems are naturally characterized by their extraordinary context-awareness.Biologically inspired design(BID)is one of the most commonly employed design strategies.However,few studies have examined the BID of context-aware smart products to date.This paper presents a structured design framework to support the BID of context-aware smart products.The meaning of context-awareness is defined from the perspective of product design.The framework is developed based on the theoretical foundations of the situated function-behavior-structure ontology.A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities,such as problem formulation,structure reformulation,behavior reformulation,and function reformulation.Some existing design methods and emerging design tools are incorporated into the framework.A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware. 展开更多
关键词 Design method Biologically inspired design Context-awareness Intelligent design
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Context-Aware Service IVlodes in the Cloud Computing Environment 认领 引用 被引量：3
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作者 Pan Yu Luo Lijuan +1 位作者 Gao Li Lv Tingjie 《China Communications》 SCIE CSCD 2012年第2期86-95,共10页
This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of conte... This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes. 展开更多
关键词 cloud computing context-aware service service mode
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Trust-Based Context-Aware Mobile Social Network Service Recommendation 认领 引用 被引量：4
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作者 XU Jun ZHONG Yuansheng +1 位作者 ZHU Wenqiang SUN Feifei 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第2期149-156,共8页
The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, M... The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, MSN is susceptible to various types of anonymous information or hacker actions. Trust can reduce the risk of interaction with unknown entities and prevent malicious attacks. In our paper, we present a trust-based service recommendation algorithm in MSN that considers users＇ similarity and friends＇ familiarity when computing trustworthy neighbors of target users. Firstly, we use the context information and the number of co-rated items to define users＇ similarity. Then, motivated by the theory of six degrees of space, the friend familiarity is derived by graph-based method. Thus the proposed methods are further enhanced by considering users＇ context in the recommendation phase. Finally, a set of simulations are conducted to evaluate the accuracy of the algorithm. The results show that the friend familiarity and user similarity can effectively improve the recommendation performance, and the friend familiarity contributes more than the user similarity. 展开更多
关键词 trust context-aware mobile social network recommendation
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A Novel Packet Marking Algorithm in Context-aware Autonomic QoS Framework 认领 引用 被引量：2
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作者 Gong Xiangyang Wang Wendong Li Yan 《China Communications》 SCIE 2009年第4期98-107,共10页
Autonomic networking is one of the hot research topics in the research area of future network architectures.In this paper,we introduce context-aware and autonomic attributes into DiffServ QoS framework,and propose a n... Autonomic networking is one of the hot research topics in the research area of future network architectures.In this paper,we introduce context-aware and autonomic attributes into DiffServ QoS framework,and propose a novel autonomic packet marking(APM)algorithm.In the proposed autonomic QoS framework,APM is capable of collecting various QoS related contexts,and adaptively adjusting its behavior to provide better QoS guarantee according to users'requirements and network conditions.Simulation results show that APM provides better performance than traditional packet marker,and significantly improves user's quality of experience. 展开更多
关键词 autonomic QoS framework DiffServ context-aware packet marking
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Context-Aware Tour Planning System Based on Satisfaction Model 认领 引用 被引量：1
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作者 胥正川 潘煜 +1 位作者 梁军 吕廷杰 《China Communications》 SCIE CSCD 2013年第6期156-163,共8页
With the development of communication and ubiquitous computing technologies, context-aware services, which acquire contextual information of users and environment, have become critical applications providing customiza... With the development of communication and ubiquitous computing technologies, context-aware services, which acquire contextual information of users and environment, have become critical applications providing customization in mobile commerce. Meanwhile, tourism has attracted increasing attention as a high value-added service and a hot academic topic. However, the research on how to provide tour services based on context-aware services is in fact still at an early stage, limited to concept elaboration, service framework discussion, prototype system development etc. In this paper, we summarized the previous researches on context-aware services to establish the research foundation, put forward a way of analyzing a tour planning problem with a modified model of Traveling Salesman Problem （TSP） and Vehicle Routing Problem （VRP）, and we applied an innovated Resource Constrain Project Scheduling Problem （RCPSP） mathematical model to solve the tour planning problem based on context information. The simulation under branch and bound algoritban evaluated the validity of our solution. 展开更多
关键词 context-aware service tour planning RCPSP constrained optimization mathematics modelling
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Comprehensively Context-Aware Approach to Guaranteeing Multimedia Conferencing Services 认领 引用 被引量：1
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作者 吴冀衍 田岳 +1 位作者 程渤 商彦磊 《China Communications》 SCIE CSCD 2013年第9期53-64,共12页
Service-Oriented Communication(SOC)is a key research issue to enable media communications using the Service-Oriented Architecture(SOA).Motivated by the necessity to guarantee the service quality of our webbased multim... Service-Oriented Communication(SOC)is a key research issue to enable media communications using the Service-Oriented Architecture(SOA).Motivated by the necessity to guarantee the service quality of our webbased multimedia conferencing system,we present a Comprehensively Context-Aware(CoCA)approach in this paper.One major problem in the existing end-to-end Quality of Service(QoS)management solutions is that they analyse and exploit the relationships between the QoS metrics and corresponding contexts in an isolated manner.In this paper,we propose a novel approach to leveraging such relationships in a comprehensive manner based on Bayesian networks and the fuzzy set theory.This approach includes three phases:1)information feedback and training,2)QoS-to-context mapping,and3)optimal context adaption.We implement the proposed CoCA in the real multimedia conferencing system and compare its performance with the existing bandwidth aware and playback buffer aware schemes.Experimental results show that the proposed CoCA outperforms the competing approaches in improving the average video Peak Signal-to-Noise Ratio(PSNR).It also exhibits good performance in preventing the playback buffer starvation. 展开更多
关键词 SOC multimedia conferencing context-aware
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Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network 认领 引用 被引量：1
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作者 R.Sujatha T.Abirami 《Computer Systems Science & Engineering》 SCIE EI 2023年第8期1775-1787,共13页
The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in ... The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in personalizing the needs of individual users.Therefore,it is essential to improve the user experience.The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites.In Context-Aware Recommender Systems(CARS),several influential and contextual variables are identified to provide an effective recommendation.A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative recommendation.The CARS will generate more recommendations utilizing adapting them to a certain contextual situation of users.However,the key issue is how contextual information is used to create good and intelligent recommender systems.This paper proposes an Artificial Neural Network(ANN)to achieve contextual recommendations based on usergenerated reviews.The ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in CARS.Thus,the most appropriate contexts in which a user should choose an item or service are achieved.This work converts every label set into a Multi-Label Classification(MLC)problem to enhance recommendations.Experimental results show that the proposed ANN performs better in the Binary Relevance(BR)Instance-Based Classifier,the BR Decision Tree,and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa Dataset.Furthermore,the accuracy of the proposed ANN achieves better results by 1.1%to 6.1%compared to other existing methods. 展开更多
关键词 Recommendation agents context-aware recommender systems collaborative recommendation personalization systems optimized neural network-based contextual recommendation algorithm
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Context-Aware技术在智能网络课程设计中的应用 认领 引用 被引量：1
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作者 肖伟 史滋福 《吉首大学学报（自然科学版）》 CAS 2007年第1期44-47,共4页
Context-aware具有自组织性、自适应性和自反馈性,智能网络课程的设计与开发要求教育学、心理学理论和先进的计算机算法的融合.从分析Context-aware技术及其特点入手,将Context-aware应用于网络课程来改变课程教学模式和学生学习方式,... Context-aware具有自组织性、自适应性和自反馈性,智能网络课程的设计与开发要求教育学、心理学理论和先进的计算机算法的融合.从分析Context-aware技术及其特点入手,将Context-aware应用于网络课程来改变课程教学模式和学生学习方式,提高网络课程的智能化程度及学生的学习效率. 展开更多
关键词 Context-aware技术 智能化 网络课程
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CAPT:Context-Aware Provenance Tracing for Attack Investigation 认领 引用
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作者 Cheng Tan Lei Zhao +2 位作者 Weijie Liu Lai Xu Lina Wang 《China Communications》 SCIE CSCD 2018年第2期153-169,共17页
APT attacks are prolonged and have multiple stages, and they usually utilize zero-day or one-day exploits to be penetrating and stealthy. Among all kinds of security tech- niques, provenance tracing is regarded as an ... APT attacks are prolonged and have multiple stages, and they usually utilize zero-day or one-day exploits to be penetrating and stealthy. Among all kinds of security tech- niques, provenance tracing is regarded as an important approach to attack investigation, as it discloses the root cause, the attacking path, and the results of attacks. However, existing techniques either suffer from the limitation of only focusing on the log type, or are high- ly susceptible to attacks, which hinder their applications in investigating APT attacks. We present CAPT, a context-aware provenance tracing system that leverages the advantages of virtualization technologies to transparently collect system events and network events out of the target machine, and processes them in the specific host which introduces no space cost to the target. CAPT utilizes the contexts of collected events to bridge the gap between them, and provides a panoramic view to the attack investigation. Our evaluation results show that CAPT achieves the efi＇ective prov- enance tracing to the attack cases, and it only produces 0.21 MB overhead in 8 hours. With our newly-developed technology, we keep the run-time overhead averages less than 4%. 展开更多
关键词 attack investigation provenance tracing context-aware virtualization technol-ogies APT attacks panoramic view
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Context-Aware Usage-Based Grid Authorization Framework 认领 引用
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作者 CUI Yongquan HONG Fan FU Cai 《Wuhan University Journal of Natural Sciences》 EI CAS 2006年第6期1736-1740,共5页
Due to inherent heterogeneity, multi-domain characteristic and highly dynamic nature, authorization is a critical concern in grid computing. This paper proposes a general authorization and access control architecture,... Due to inherent heterogeneity, multi-domain characteristic and highly dynamic nature, authorization is a critical concern in grid computing. This paper proposes a general authorization and access control architecture, grid usage control （GUCON）, for grid computing. It＇s based on the next generation access control mechanism usage control （UCON） model. The GUCON Framework dynamic grants and adapts permission to the subject based on a set of contextual information collected from the system environments; while retaining the authorization by evaluating access requests based on subject attributes, object attributes and requests. In general, GUCON model provides very flexible approaches to adapt the dynamically security request. GUCON model is being implemented in our experiment prototype. 展开更多
关键词 context-aware access control usage control （UCON）
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Fuzzy Privacy Decision for Context-Aware Access Personal Information 认领 引用
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作者 ZHANG Qingsheng QI Yong ZHAO Jizhong HOU Di NIU Yujie 《Wuhan University Journal of Natural Sciences》 CAS 2007年第5期941-945,共5页
A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, ... A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, it can produce fuzzy privacy decision as the change of personal information sensitivity and personal information receiver trust. The uncertain privacy decision model was proposed about personal information disclosure based on the change of personal information receiver trust and personal information sensitivity. A fuzzy privacy decision information system was designed according to this model. Personal privacy control policies can be extracted from this information system by using rough set theory. It also solves the problem about learning privacy control policies of personal information disclosure. 展开更多
关键词 context-aware privacy decision fuzzy objective information system rough set theory
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Context-Aware Feature Extraction Network for High-Precision UAV-Based Vehicle Detection in Urban Environments 认领 引用 被引量：4
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作者 Yahia Said Yahya Alassaf +3 位作者 Taoufik Saidani Refka Ghodhbani Olfa Ben Rhaiem Ali Ahmad Alalawi 《Computers, Materials & Continua》 SCIE EI 2024年第12期4349-4370,共22页
The integration of Unmanned Aerial Vehicles(UAVs)into Intelligent Transportation Systems(ITS)holds trans-formative potential for real-time traffic monitoring,a critical component of emerging smart city infrastructure.... The integration of Unmanned Aerial Vehicles(UAVs)into Intelligent Transportation Systems(ITS)holds trans-formative potential for real-time traffic monitoring,a critical component of emerging smart city infrastructure.UAVs offer unique advantages over stationary traffic cameras,including greater flexibility in monitoring large and dynamic urban areas.However,detecting small,densely packed vehicles in UAV imagery remains a significant challenge due to occlusion,variations in lighting,and the complexity of urban landscapes.Conventional models often struggle with these issues,leading to inaccurate detections and reduced performance in practical applications.To address these challenges,this paper introduces CFEMNet,an advanced deep learning model specifically designed for high-precision vehicle detection in complex urban environments.CFEMNet is built on the High-Resolution Network(HRNet)architecture and integrates a Context-aware Feature Extraction Module(CFEM),which combines multi-scale feature learning with a novel Self-Attention and Convolution layer setup within a Multi-scale Feature Block(MFB).This combination allows CFEMNet to accurately capture fine-grained details across varying scales,crucial for detecting small or partially occluded vehicles.Furthermore,the model incorporates an Equivalent Feed-Forward Network(EFFN)Block to ensure robust extraction of both spatial and semantic features,enhancing its ability to distinguish vehicles from similar objects.To optimize computational efficiency,CFEMNet employs a local window adaptation of Multi-head Self-Attention(MSA),which reduces memory overhead without sacrificing detection accuracy.Extensive experimental evaluations on the UAVDT and VisDrone-DET2018 datasets confirm CFEMNet’s superior performance in vehicle detection compared to existing models.This new architecture establishes CFEMNet as a benchmark for UAV-enabled traffic management,offering enhanced precision,reduced computational demands,and scalability for deployment in smart city applications.The advancements presented in CFEMNet contribute significantly to the evolution of smart city technologies,providing a foundation for intelligent and responsive traffic management systems that can adapt to the dynamic demands of urban environments. 展开更多
关键词 Smart cities UAVs vehicle detection trafficmanagement intelligent transportation systems anchor-free detection high-resolution network context-aware feature extraction multi-head self-attention
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Context-aware smart car: from model to prototype 认领 引用 被引量：4
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作者 Jie SUN Zhao-hui WU Gang PAN 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2009年第7期1049-1059,共11页
Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have ... Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have been made, we find a lack of fully context-aware smart cars. This study presents a general architecture of smart cars from the viewpoint of context- awareness. A hierarchical context model is proposed for description of the complex driving environment. A smart car prototype including software platform and hardware infrastructures is built to provide the running environment for the context model and applications. Two performance metrics were evaluated: accuracy of the context situation recognition and efficiency of the smart car. The whole response time of context situation recognition is nearly 1.4 s for one person, which is acceptable for non-time critical applications in a smart car. 展开更多
关键词 Smart car Intelligent vehicle Context-aware Ubiquitous computing
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