Context Awareness and Word-rendering in the Teaching of Chinese-English Translation

In the teaching of Chinese-English（C-E） translation, the cultivation of students＇ awareness of context is very important. As far as word-rendering in C-E translation is concerned, contextual analysis can help student solve such problems as the precise comprehension of the SL（source language） words, the translation of vague words and polysemous words, the conveyance of implicature and non-correspondence of word meaning.

Age-Constrained Dynamic Content Replacing and Delivering for UAV-Assisted Context Awareness

In this work,we employ the cache-enabled UAV to provide context information delivery to end devices that make timely and intelligent decisions.Different from the traditional network traffic,context information varies with time and brings in the ageconstrained requirement.The cached content items should be refreshed timely based on the age status to guarantee the freshness of user-received contents,which however consumes additional transmission resources.The traditional cache methods separate the caching and the transmitting,which are not suitable for the dynamic context information.We jointly design the cache replacing and content delivery based on both the user requests and the content dynamics to maximize the offloaded traffic from the ground network.The problem is formulated based on the Markov Decision Process(MDP).A sufficient condition of cache replacing is found in closed form,whereby a dynamic cache replacing and content delivery scheme is proposed based on the Deep Q-Network(DQN).Extensive simulations have been conducted.Compared with the conventional popularity-based and the modified Least Frequently Used(i.e.,LFU-dynamic)schemes,the UAV can offload around 30%traffic from the ground network by utilizing the proposed scheme in the urban scenario,according to the simulation results.

Context Awareness by Noise-Pattern Analysis of a Smart Factory

Recently,to build a smart factory,research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology,a field of artificial intelligence.Most of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training dataset.However,compared to numerical raw data,learning based on image data has the disadvantage that creating a training dataset is very time-consuming.Therefore,we devised a two-step data preprocessing method that efficiently detects machine anomalies in numerical raw data.In the first preprocessing process,sound signal information is analyzed to extract features,and in the second preprocessing process,data filtering is performed by applying the proposed algorithm.An efficient dataset was built formodel learning through a total of two steps of data preprocessing.In addition,both showed excellent performance in the training accuracy of the model that entered each dataset,but it can be seen that the time required to build the dataset was 203 s compared to 39 s,which is about 5.2 times than when building the image dataset.

A New Aware-Context Collaborative Filtering Approach by Applying Multivariate Logistic Regression Model into General User Pattern

Traditional collaborative filtering (CF) does not take into account contextual factors such as time, place, companion, environment, etc. which are useful information around users or relevant to recommender application. So, recent aware-context CF takes advantages of such information in order to improve the quality of recommendation. There are three main aware-context approaches: contextual pre-filtering, contextual post-filtering and contextual modeling. Each approach has individual strong points and drawbacks but there is a requirement of steady and fast inference model which supports the aware-context recommendation process. This paper proposes a new approach which discovers multivariate logistic regression model by mining both traditional rating data and contextual data. Logistic model is optimal inference model in response to the binary question “whether or not a user prefers a list of recommendations with regard to contextual condition”. Consequently, such regression model is used as a filter to remove irrelevant items from recommendations. The final list is the best recommendations to be given to users under contextual information. Moreover the searching items space of logistic model is reduced to smaller set of items so-called general user pattern (GUP). GUP supports logistic model to be faster in real-time response.

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.

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.

Context-Aware信息检索技术与模型

Context-aware信息检索技术是一种具有自适应性和自组织性的智能信息检索技术,而且是富有挑战性的研究方向。文章首先叙述了与Context-aware相关的基本概念及实现的基本原理,接着介绍了基于不同Context信息的检索模型,并且讨论了各种模型的实现技术及适用范围。

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.

基于网络的Context Aware智能控制系统

提出一种基于网络的Context Aware智能控制系统的体系结构、Context任务控制管理模型。系统将机器人作为Context Aware智能系统的智能接口。通过对Java JINI的服务查找机制进行修改,增强了JINI的服务查找、分发机制,使得系统可以通过综合分析服务提供者当前状态、服务申请者的状态、系统当前的性能以及Context感知信息,经模糊决策,通过”Pull”方式,或“Push”方式给服务申请者(或第三方用户)提供所需的服务。最后对系统性能进行分析。一个应用实例说明Context Aware智能控制系统的应用。

Context-Oriented Multi-RAT User Association and Resource Allocation with Triple Decision in 5G Heterogeneous Networks

In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.

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.

A Survey on Context-Aware Sensing for Body Sensor Networks

Context awareness in Body Sensor Networks (BSNs) has the significance of associating physiological user activity and the environment to the sensed signals of the user. The context information derived from a BSN can be used in pervasive healthcare monitoring for relating importance to events and specifically for accurate episode detection. In this paper, we address the issue of context-aware sensing in BSNs, and survey different techniques for deducing context awareness.

Context Aware Wireless Sensor Network Suitable for Precision Agriculture

Using the Wireless Sensor Networks WSNs in a wide variety of applications is currently considered one of the most challenging solutions. For instance, this technology has evolved the agriculture field, with the precision agriculture challenge. In fact, the cost of sensors and communication infrastructure continuously trend down as long as the technological advances. So, more growers dare to implement WSN for their crops. This technology has drawn substantial interests by improving agriculture productivity. The idea consists of deploying a number of sensors in a given agricultural parcel in order to monitor the land and crop conditions. These readings help the farmer to make the right inputs at the right moment. In this paper, we propose a complete solution for gathering different type of data from variable fields of a large agricultural parcel. In fact, with the in-field variability, adopting a unique data gathering solution for all kinds of fields reveals an inconvenient approach. Besides, as a fault-tolerant application, precision agriculture does not require a high precision value of sensed data. So, our approach deals with a context aware data gathering strategy. In other words, depending on a defined context for the monitored field, the data collector will decide the data gathering strategy to follow. We prove that this approach improves considerably the lifetime of the application.

Context-Based Mobile User Interface

Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.

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.

Smart phone-based context-aware augmentative and alternative communications system

A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

With the popularity of 5G and the rapid development of mobile terminals,an endless stream of short video software exists.Browsing short-form mobile video in fragmented time has become the mainstream of user’s life.Hence,designing an efficient short video recommendation method has become important for major network platforms to attract users and satisfy their requirements.Nevertheless,the explosive growth of data leads to the low efficiency of the algorithm,which fails to distill users’points of interest on one hand effectively.On the other hand,integrating user preferences and the content of items urgently intensify the requirements for platform recommendation.In this paper,we propose a collaborative filtering algorithm,integrating time context information and user context,which pours attention into expanding and discovering user interest.In the first place,we introduce the temporal context information into the typical collaborative filtering algorithm,and leverage the popularity penalty function to weight the similarity between recommended short videos and the historical short videos.There remains one more point.We also introduce the user situation into the traditional collaborative filtering recommendation algorithm,considering the context information of users in the generation recommendation stage,and weight the recommended short-formvideos of candidates.At last,a diverse approach is used to generate a Top-K recommendation list for users.And through a case study,we illustrate the accuracy and diversity of the proposed method.

Non-Intrusive Context Aware Transactional Framework to Derive Business Insights on Big Data

To convert invisible, unstructured and time-sensitive machine data into information for decision making is a challenge. Tools available today handle only structured data. All the transaction data are getting captured without understanding its future relevance and usage. It leads to other big data analytics related issue in storing, archiving, processing, not bringing in relevant business insights to the business user. In this paper, we are proposing a context aware pattern methodology to filter relevant transaction data based on the preference of business.

Generic Framework for Context-Aware Communication Services in Visitor’s Guides

Ubiquitous computing plays an increasing role in our lives. Typically, applications in ubiquitous computing environ-ments are context aware, namely, they react to the situations of their users at a given moment in time. One example for such environment is visitor’s guides in cultural heritage sites, supporting visits of individuals or small groups, such as families or friends. In such environments, it is well known that interaction among visitors enhances the overall visit experience. Recently, some research prototypes of visitor’s guides have started supporting such interaction through textual communication services embedded in them. However, these applications have so far been developed separately in an ad-hoc manner, despite common features and infrastructures they share. The research described here generalizes communication services offered by different visitor’s guides and suggests a systematic and generic framework for developing context-aware communication services for visitor’s guides. The specific communication services are abstracted into a domain model, later used in practice for adapting and tailoring the different concepts to the specific requirements of the applications. The framework is demonstrated in the specific setting of a multi-agent museum visitor’s guide system. We also show that the suggested framework is not limited to the specific museum visitor’s guide system but may facilitate the development of context-aware communication applications in general.