Intelligent robots in ubiquitous computing environment should be able to receive a variety of surrounding informa tion and provide users with appropriate services. A developer can describe the robot services that are ...Intelligent robots in ubiquitous computing environment should be able to receive a variety of surrounding informa tion and provide users with appropriate services. A developer can describe the robot services that are proper to users＇ envir onments by using his or her various environments, and process them through the execution engine. However, it is difficult for a developer to describe and develop robot services, who knows all surrounding information which is called context infor mation. If there is a method for describing and documenting robot services in intuitive expressions, that is to use graphical user interfaces（GUls）, it would be very helpful. This paper suggests that robot service developers describe robot services us ing intuitive GUls with contextawareness. And the services can be automatically generated into workflow documents. Robot services that robot service developers have made with intuitive GUIs can be automatically generated into workflow docu ments by using the object modeling technique（OMT）. Developers can describe robot services based on contextaware work flow language（CAWL ）. For testing, scenariobased robot services are described using CAWLbased development tool, and their workflow documents are automatically generated.展开更多
In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workf...In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workflows in order to get mare large-scale or complicated workflow. They only provide a simple workflow model, not a composite workflow model. In this paper, the autorhs propose a context-aware workflow model to support composite workflows by expanding the patterns of the existing context-aware wrY：flows, which support the basic woddlow patterns. The suggested workflow model of. fers composite workflow patterns for a context-aware workflow, which consists of various flow patterns, such as simple, split, parallel flows, and subflow. With the suggested model, the model can easily reuse few of existing workflows to make a new workflow. As a result, it can save the development efforts and time of context-aware workflows and increase the workflow reusability. Therefore, the suggested model is expected to make it easy to develop applications related to context-aware workflow services on ubiquitous computing environments.展开更多
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
In distributed computing environment,workflow technologies have been continuously developed.Recently,there is an attempt to apply these technologies to context-aware services in ubiquitous computing environment.The mi...In distributed computing environment,workflow technologies have been continuously developed.Recently,there is an attempt to apply these technologies to context-aware services in ubiquitous computing environment.The middleware,which offers services in such environments,should support the automation services suited for the user using various types of situational information around the user.In this paper,based on context-aware workflow language(CAWL),we propose a CAWL based composite workflow handler for supporting composite workflow services,which can integrate more than two service flows and handle them.The test results shows that the proposed CAWL handler can provide the user with the composite workflow services to cope with various demands on a basis of a scenario document founded on CAWL.展开更多
Business process execution language(BPEL)is a most recognized standard workflow language.However,it is difficult to be used in the ubiquitous system computing environment because it is difficult to describe the contex...Business process execution language(BPEL)is a most recognized standard workflow language.However,it is difficult to be used in the ubiquitous system computing environment because it is difficult to describe the context information in the selection of the flow through the branch.To solve this problem,we propose a new BPEL workflow system with context-awareness by using aspect-oriented programming(AOP).This system is composed of a BPEL system module and a weaving module using AOP for context-aware.The BPEL system module generates a BPEL workflow program.And the weaving module converts a context-aware mark-up language(CAML)document to the aspect-oriented program that is applied to context-aware code without modification of the existing BPEL document.We also define a new document form that is called CAML,which provides a context-aware that is not available in BPEL.The system can generate a context-aware workflow program.It is developed in a way that inserts context information using AOP to provide context-aware services.展开更多
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
The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tas...The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.展开更多
BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces im...BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces image acquisition time of CMR compared to conventional CINE(C-CINE).METHODS Cardio-oncology patients(n=60)and healthy volunteers(n=29)underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner.Acquisition time,visual image quality assessment,and biventricular metrics(end-diastolic volume,endsystolic volume,stroke volume,ejection fraction,left ventricular mass,and wall thickness)were analyzed and compared between C-CINE and AI-CS-CINE with Bland–Altman analysis,and calculation of intraclass coefficient(ICC).RESULTS In 89 participants(58.5±16.8 years,42 males,47 females),total AI-CS-CINE acquisition and reconstruction time(37 seconds)was 84%faster than C-CINE(238 seconds).C-CINE required repeats in 23%(20/89)of cases(approximately 8 minutes lost),while AI-CS-CINE only needed one repeat(1%;2 seconds lost).AICS-CINE had slightly lower contrast but preserved structural clarity.Bland-Altman plots and ICC(0.73≤r≤0.98)showed strong agreement for left ventricle(LV)and right ventricle(RV)metrics,including those in the cardiac amyloidosis subgroup(n=31).AI-CS-CINE enabled faster,easier imaging in patients with claustrophobia,dyspnea,arrhythmias,or restlessness.Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.CONCLUSION AI-CS-CINE accelerated CMR image acquisition and reconstruction,preserved anatomical detail,and diminished impact of patient-related motion.Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients,including the cardiac amyloidosis cohort,as well as healthy volunteers regardless of left and right ventricular size and function.AI-CS-CINE significantly enhanced CMR workflow,particularly in challenging cases.The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.展开更多
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
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
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
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
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...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
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
Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the c...Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.展开更多
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
Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwardin...Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.展开更多
In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger....In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger.Many traditional solutions have been proposed based on the creation of random routes,such as random walk and fake sources approach,which will lead to serious packet delay and high energy consumption.Instead of applying the routing in a blind way,this article proposes a novel solution for source location privacy in WSNs by utilizing sensor ability of perceiving the presence a mobile attacker nearby,for patient attackers in particular to increase the safety period and decrease the data delivery delay.The proposed strategy forms an intelligent silent zone(ISZ)by sacrificing only a minority of sensor nodes to entice patient attackers away from real packet routing path.The analysis and simulation results show that the proposed scheme,besides providing source location privacy energy efficiently,can significantly reduce real event reporting latency compared with the existing approaches.展开更多
In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to an...In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.展开更多
基金The MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support programsupervised by the NIPA(National ITIndustry Promotion Agency)(NIPA-2012-H0301-12-2006)
文摘Intelligent robots in ubiquitous computing environment should be able to receive a variety of surrounding informa tion and provide users with appropriate services. A developer can describe the robot services that are proper to users＇ envir onments by using his or her various environments, and process them through the execution engine. However, it is difficult for a developer to describe and develop robot services, who knows all surrounding information which is called context infor mation. If there is a method for describing and documenting robot services in intuitive expressions, that is to use graphical user interfaces（GUls）, it would be very helpful. This paper suggests that robot service developers describe robot services us ing intuitive GUls with contextawareness. And the services can be automatically generated into workflow documents. Robot services that robot service developers have made with intuitive GUIs can be automatically generated into workflow docu ments by using the object modeling technique（OMT）. Developers can describe robot services based on contextaware work flow language（CAWL ）. For testing, scenariobased robot services are described using CAWLbased development tool, and their workflow documents are automatically generated.
基金supported by the The Ministry of Knowledge Economy,Korea,the ITRC(Information Technology Research Center)support program(ⅡTA-2009-(C1090-0902-0007))
文摘In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workflows in order to get mare large-scale or complicated workflow. They only provide a simple workflow model, not a composite workflow model. In this paper, the autorhs propose a context-aware workflow model to support composite workflows by expanding the patterns of the existing context-aware wrY：flows, which support the basic woddlow patterns. The suggested workflow model of. fers composite workflow patterns for a context-aware workflow, which consists of various flow patterns, such as simple, split, parallel flows, and subflow. With the suggested model, the model can easily reuse few of existing workflows to make a new workflow. As a result, it can save the development efforts and time of context-aware workflows and increase the workflow reusability. Therefore, the suggested model is expected to make it easy to develop applications related to context-aware workflow services on ubiquitous computing environments.
文摘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).
基金The MSIP(Ministry of Science,ICT&Future Planning),Korea,under the ITRC(Information Technology Research Center)support program(NIPA-2013-H0301-13-2006)supervised by the NIPA(National IT Industry Promotion Agency)
文摘In distributed computing environment,workflow technologies have been continuously developed.Recently,there is an attempt to apply these technologies to context-aware services in ubiquitous computing environment.The middleware,which offers services in such environments,should support the automation services suited for the user using various types of situational information around the user.In this paper,based on context-aware workflow language(CAWL),we propose a CAWL based composite workflow handler for supporting composite workflow services,which can integrate more than two service flows and handle them.The test results shows that the proposed CAWL handler can provide the user with the composite workflow services to cope with various demands on a basis of a scenario document founded on CAWL.
基金Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(No.2010-0025831)
文摘Business process execution language(BPEL)is a most recognized standard workflow language.However,it is difficult to be used in the ubiquitous system computing environment because it is difficult to describe the context information in the selection of the flow through the branch.To solve this problem,we propose a new BPEL workflow system with context-awareness by using aspect-oriented programming(AOP).This system is composed of a BPEL system module and a weaving module using AOP for context-aware.The BPEL system module generates a BPEL workflow program.And the weaving module converts a context-aware mark-up language(CAML)document to the aspect-oriented program that is applied to context-aware code without modification of the existing BPEL document.We also define a new document form that is called CAML,which provides a context-aware that is not available in BPEL.The system can generate a context-aware workflow program.It is developed in a way that inserts context information using AOP to provide context-aware services.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia through research group No.(RG-NBU-2022-1234).
文摘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.
文摘The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.
基金Supported by James Russell Hornsby and Jun Xiong Fund and United Imaging Healthcare.
文摘BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces image acquisition time of CMR compared to conventional CINE(C-CINE).METHODS Cardio-oncology patients(n=60)and healthy volunteers(n=29)underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner.Acquisition time,visual image quality assessment,and biventricular metrics(end-diastolic volume,endsystolic volume,stroke volume,ejection fraction,left ventricular mass,and wall thickness)were analyzed and compared between C-CINE and AI-CS-CINE with Bland–Altman analysis,and calculation of intraclass coefficient(ICC).RESULTS In 89 participants(58.5±16.8 years,42 males,47 females),total AI-CS-CINE acquisition and reconstruction time(37 seconds)was 84%faster than C-CINE(238 seconds).C-CINE required repeats in 23%(20/89)of cases(approximately 8 minutes lost),while AI-CS-CINE only needed one repeat(1%;2 seconds lost).AICS-CINE had slightly lower contrast but preserved structural clarity.Bland-Altman plots and ICC(0.73≤r≤0.98)showed strong agreement for left ventricle(LV)and right ventricle(RV)metrics,including those in the cardiac amyloidosis subgroup(n=31).AI-CS-CINE enabled faster,easier imaging in patients with claustrophobia,dyspnea,arrhythmias,or restlessness.Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.CONCLUSION AI-CS-CINE accelerated CMR image acquisition and reconstruction,preserved anatomical detail,and diminished impact of patient-related motion.Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients,including the cardiac amyloidosis cohort,as well as healthy volunteers regardless of left and right ventricular size and function.AI-CS-CINE significantly enhanced CMR workflow,particularly in challenging cases.The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.
基金Project supported by the National Hi-Tech Research and Develop-ment Program (863) of China (Nos. 2006AA01Z198, and2008AA01Z132)the National Natural Science Foundation of China(No. 60533040)the National Science Fund for Distinguished Young Scholars of China (No. 60525202)
文摘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.
基金Supported by the National Natural Science Foundation of China(71662014 and 61602219)the Natural Science Foundation of Jiangxi Province of China(20132BAB201050)the Science and Technology Project of Jiangxi Province Educational Department(GJJ151601)
文摘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.
基金This work was supported in part by the project of the National Natural Science Foundation of China(51875030).
文摘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.
基金the National Key Basic Research Program of China，the National Natural Science Foundation of China，the Ministry of Education of the People's Republic of China，the Fundamental Research Funds for the Central Universities of China
文摘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.
基金Supported by the National Grand Fundamental Research 973 Program of China under Grant No. 2009CB320504the National High Technology Development 863 Program of China under Grant No.2007AA01Z206 and No.2009AA01Z210the EU FP7 Project EFIPSANS (INFSO-ICT-215549)
文摘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.
基金supported in partby the National Natural Science Foundation of China under Grants No. 70972048,No. 71071140,No. 71272076,No. 71201011,No. 51108209,No. 60903014Shanghai Philosophy,Social Science Funds for Youth under Grant No. 2008EZH002
文摘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.
文摘Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.
文摘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.
基金Supported by the National Natural Science Foundation of China(61373040,61173137)the Ph.D.Programs Foundation of Ministry of Education of China(20120141110002)the Key Project of Natural Science Foundation of Hubei Province(2010CDA004)
文摘Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.
基金supported by the National Natural Science Foundation of China (Nos.61373015,61300052, 41301047)the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Important National Science and Technology Specific Project(No. BA2013049)
文摘In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger.Many traditional solutions have been proposed based on the creation of random routes,such as random walk and fake sources approach,which will lead to serious packet delay and high energy consumption.Instead of applying the routing in a blind way,this article proposes a novel solution for source location privacy in WSNs by utilizing sensor ability of perceiving the presence a mobile attacker nearby,for patient attackers in particular to increase the safety period and decrease the data delivery delay.The proposed strategy forms an intelligent silent zone(ISZ)by sacrificing only a minority of sensor nodes to entice patient attackers away from real packet routing path.The analysis and simulation results show that the proposed scheme,besides providing source location privacy energy efficiently,can significantly reduce real event reporting latency compared with the existing approaches.
基金Supported by the National Key Research and Development Plan(2016YFB1001200)the National Natural Science Foundation of China(U1435220,61232013)
文摘In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.
