Model of a Context-Aware Middleware for Mobile Workers

With the development of Internet of things and Web of things, computing becomes more pervasive, invisible and present everywhere. In fact, in our environment, we are surrounded by multiple devices that deliver (web) services which meet the needs of the users. However, the mobility of these devices as the users has important repercussions that challenge software design of these applications because the variability of the environment cannot be anticipated at the design time. Thus, it will be interesting to dynamically discover the environment and adapt the application during its execution to the new contextual conditions. We therefore, propose a model of a context-aware middleware that can address this issue through a monitoring service which is capable of reasoning and observation channels capable of calculating the context during the runtime. The monitoring service evaluates the pre-defined X-Query predicates in the context manager and uses Prolog to deduce the services needed to respond back. An independent observation channel for each different predicate is then dynamically generated by the monitoring service depending on the current state of the environment. Each channel sends its result directly to the context manager which consequently calculates the context based on all the predicates’ results while preserving the reactivity of the self-adaptive system.

Ontology-Based Context-Aware Middleware for Smart Spaces

Context-awareness enhances human-centric, intelligent behavior in a smart environment; however context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to applications. The middleware uses a formal context model, which combines first order probabilistic logic （FOPL） and web ontology language （OWL） ontologies, to provide a common understanding of contextual information to facilitate context modeling and reasoning about imperfect and ambiguous contextual information and to enable context knowledge sharing and reuse. A context inference mechanism based on an extended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensitive to the size of the context dataset.

Mobile Web Middleware of NFC Context-Awareness Applications

With the development of wireless networks and mobile computing, more advanced applications with context-awareness and adaptability to their changing context are needed. However, building context-aware applications is difficult due to the lack of adequate infrastructure support. In this paper, a web middleware architecture for the development of context-awareness applications using near field communication （NFC） is proposed. Based on it, the efficient support for acquiring, interpreting, and accessing context is provided, and the user＇s quality of experience is improved. Moreover, a mobile web middleware for the testing and full realization of NFC context-awareness applications has been developed together with two application examples.

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

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.

A Deep Learning Based Approach for Context-Aware Multi-Criteria Recommender Systems

Recommender systems are similar to an informationfiltering system that helps identify items that best satisfy the users’demands based on their pre-ference profiles.Context-aware recommender systems(CARSs)and multi-criteria recommender systems(MCRSs)are extensions of traditional recommender sys-tems.CARSs have integrated additional contextual information such as time,place,and so on for providing better recommendations.However,the majority of CARSs use ratings as a unique criterion for building communities.Meanwhile,MCRSs utilize user preferences in multiple criteria to better generate recommen-dations.Up to now,how to exploit context in MCRSs is still an open issue.This paper proposes a novel approach,which relies on deep learning for context-aware multi-criteria recommender systems.We apply deep neural network(DNN)mod-els to predict the context-aware multi-criteria ratings and learn the aggregation function.We conduct experiments to evaluate the effect of this approach on the real-world dataset.A significant result is that our method outperforms other state-of-the-art methods for recommendation effectiveness.

Relevant Visual Semantic Context-Aware Attention-Based Dialog

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents.However,it faces challenges in overcoming visual semantic limitations,particularly in obtaining sufficient context from visual and textual aspects of images.This paper proposes a new visual dialog dataset called Diverse History-Dialog(DS-Dialog)to address the visual semantic limitations faced by the existing dataset.DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context(MSCOCO)image categories and consolidates them for each image.Specifically,each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical context.These relevant histories are consolidated for each image,and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each image.The new dataset is generated through several stages,including image semantic feature extraction,keyphrase extraction,relevant question extraction,and relevant history dialog generation.The DS-Dialog dataset contains about 2.6 million question-answer pairs,where 1.3 million pairs correspond to existing VisDial’s question-answer pairs,and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image,with each image comprising 10-round relevant question-answer pairs.Moreover,a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each image.DS-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous models.Specifically,the proposed DSDialog model achieves an 8% higher mean reciprocal rank(MRR),11% higher R@1%,6% higher R@5%,5% higher R@10%,and 8% higher normalized discounted cumulative gain(NDCG)compared to LF.DS-Dialog also achieves approximately 1 point improvement on R@k,mean,MRR,and NDCG compared to the original RVA,and 2 points improvement compared to LF andDualVD.These results demonstrates the importance of the relevant semantic historical context in enhancing the visual semantic relationship between textual and visual representations of the images and questions.

Context-Aware技术在智能网络课程设计中的应用

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.

Data Processing Middleware in a High-Powered Neutral Beam Injection Control System

A set of data-processing middleware for a high-powered neutral beam injection（NBI） control system is presented in this paper.The middleware,based on TCP/IP and multi-threading technologies,focuses mainly on data processing and transmission.It separates the data processing and compression from data acquisition and storage.It provides universal transmitting interfaces for different software circumstances,such as WinCC,LabView and other measurement systems. The experimental data acquired on Windows,QNX and Linux platforms are processed by the middleware and sent to the monitoring applications.There are three middleware deployment models：serial processing,parallel processing and alternate serial processing.By using these models,the middleware solves real-time data-processing problems on heterogeneous environmental acquisition hardware with different operating systems and data applications.

Biologically Inspired Design of Context-Aware Smart Products

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.

Interactive Middleware Services for Heterogeneous Systems

Computing has become more invisible, widespread and ubiquitoussince the inception of the Internet of Things (IoT) and Web of Things. Multipledevices that surround us meet user’s requirements everywhere. Multiple Middleware Framework (MF) designs have come into existence because of the rapiddevelopment of interactive services in Heterogeneous Systems. This resulted inthe delivery of interactive services throughout Heterogeneous Environments(HE). Users are given free navigation between devices in a widespread environment and continuously interact with each other from any chosen device. Numerous interactive devices with recent interactive platforms (for example, SmartPhones, Mobile Phones, Personal Computer (PC) and Personal Digital Assistant(PDA)) are available in the market. For easy access to information and servicesirrespective of the device used for working and even at the drastic change ofthe environment, the execution of applications on a broad spectrum of computingdevices is propelled by the availability of the above-mentioned platforms. Different applications that need interoperability to coordinate and correspond with eachother should be facilitated. Using a standard interface and data format, HE mustlink various devices from various platforms together to communicate with eachother. To aid the interactive services performed by a middleware framework thatoperates on Application Programming Interface (API) over HEs, this issue aims toendorse an Adaptable Service Application Programming Interface (ASAPI).

Context-Aware Rate-Adaptive Beaconing for Efficient and Scalable Vehicular Safety Communication

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.

A Glance at the Middleware Technology

After describing the concept of middleware,this paper discusses the position and value of middleware among modern software technologies,summarizes some kinds of common middleware.This paper also gives some proposals for developing middleware in China.

Patterns and Frameworks for E&P Middleware—Introduction to Architecture of PetroCOVERY

This paper presents a domain-specific middleware definition for petroleum exploration and production (E&P) domain on personal view.With detailed introduction of PetroCOVERY architecture,we examine some key features about E&P middleware and evaluate its architecture.E&P middleware should tier different encapsulation layers,which in higher level support interoperability among

Development and Application of WebGIS Middleware in Oil Production Engineering

WebGIS is the result of combining the technology of Internet with that of Geographic Information Systems (GIS). This paper aims at some problems in the development of GIS, such as the system of development is instable, and presents the method of adopting component technology to accomplish WebGIS middleware which has been successfully applied to the Oil Production Engineering information visible system. It showed in practice that the WebGIS middleware can be casily embedded in the web pages to accomplish GIS application system in a network environment. On the one hand, its application can reduce complexity of system and speed up the pace of development. On the other hand, it is certain to reduce the development costs and improve the maintainability. Key words WebGIS - middleware - oil production engineering CLC number TP 31 Biography: LIU Quan (1969-), male, Ph. D. candidate, research direction: include automated resoning, WebGIS.

High Efficiency and Light Mobile Electronic Business System Based on Mobile Agent Middleware

Mobile Network technology has been being the research focus during the 1990’s. The middleware technology is imported for the sake of running distributed transaction smoothly. In this paper, a mobile agent based middleware high efficiency mobile electronic business oriented middleware (HEMEBOM) is designed and implemented based on the requirement and background of collaborative electronic business. Its architecture, elements and excellent properties are mainly focused. Then high efficiency mobile electronic business system μMcommerce is built using HEMEBOM.

A Framework of Web Data Integrated LBS Middleware

In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including positioning, location modeling, location-dependent query processing, privacy and secure management.

An Application of Context Middleware Based on Fuzzy Logic for Wireless Sensor Networks

The research of context-aware computing based on wireless sensor network (WSN) aims at intelligently connecting computers, users, and environment. So its application system should be flexibly adaptable to dynamic changes of context and application requirements and proactively provides the information satisfied with current context for users. The middleware can be very effective to provide the support runtime services for context-aware computing. In this paper we propose middleware architecture for context processing. This architecture is based on fuzzy logic control (FLC) system for context reasoning and sensor fusion. We propose a formal context representation model in which a user’s context is described by a set of roles and relations correspond to a context space. A middleware prototype has been developed, which detect tourist’ physical context and provide reminding. The experiments prove that the model and approach proposed are feasible.

A Communication Middleware with Unified Data Transmission Interface

In a Modern communication network, data exchange become a complex problem because there usually exists a various data formats due to the diversity and complexity of communication devices. In this paper, a communication middleware with unified data transmission interface is introduced, which acts as the abstract communication layer in the heterogeneous distributed private communication network. Devices within the network only need to interact with the middleware, instead of directly communicate with each other by various protocols and interfaces, which can reduce the complexity and diversity of the heterogeneous network. This article describes the structure and features of the middleware, and analyses the use of “buffer pool” in message sending and receiving process. The applications of this middleware can reduce the complexity of heterogeneous network interoperation, and improve communication efficiency.

Intelligent Silent Zone for Source-Location Privacy Based on Context-Awareness in WSNs

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.