• Journal of Information Technology Services
• /
• v.11 no.sup
• /
• pp.165-176
• /
• 2012

Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.7B
• /
• pp.619-631
• /
• 2006

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of context information, such as the user's location, to offer greater services to the user without any explicit request. In this paper, we propose context-aware active services on the basis of CAMUS (Context-Aware Middleware for URC Systems). CAMUS is a middleware for providing context-aware applications with development and execution methodology. Accordingly, the applications developed by CAMUS respond in a timely fashion to contexts. To evaluate, we apply proposed active services to TV application domain. Therefore, we implement and experiment the TV contents recommendation service agent, control service agent and TV task based on CAMUS. The context-aware TV task is to recommend programs and control of TV according to user preference, location and voice commands.

• ETRI Journal
• /
• v.42 no.2
• /
• pp.230-238
• /
• 2020

Human-object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters can capture local spatial features with a few parameters, they fail to capture larger context information relevant for recognizing interactions between humans and distant objects owing to their small receptive regions. Hence, we herein propose a three-stream HOI detection network that employs a context convolution module (CCM) in each stream branch. The CCM can capture larger contexts from input feature maps by adopting combinations of large separable convolution layers and residual-based convolution layers without increasing the number of parameters by using fewer large separable filters. We evaluate our HOI detection method using two benchmark datasets, V-COCO and HICO-DET, and demonstrate its state-of-the-art performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.2
• /
• pp.383-403
• /
• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

• Journal of Intelligence and Information Systems
• /
• v.14 no.1
• /
• pp.35-45
• /
• 2008

In order to constructan ubiquitous computing environment, it is necessary to develop a technology that can recognize users and circumstances. In this regard, the question of recognizing and expressing user Context regardless of computer and language types has emerged as an important task under the heterogeneous distributed processing system. As a means to solve this task of representing user Context in the ubiquitous environment, this paper proposes to describe user Context as the most similar form of human thinking by using semantic web and fuzzy concept independentof language and computer types. Because the conventional method of representing Context using an usual collection has some limitations in expressing the environment of the real world, this paper has chosen to use Fuzzy OWL language, a fusion of fuzzy concept and standard web ontology language OWL. Accordingly, this paper suggests the following method. First we represent user contacted environmental information with a numerical value and states, and describe it with OWL. After that we transform the converted OWL Context into Fuzzy OWL. As a last step, we prove whether the automatic circumstances are possible in this procedure when we use fuzzy inference engine FiRE. With use the suggested method in this paper, we can describe Context which can be used in the ubiquitous computing environment. This method is more effective in expressing degree and status of the Context due to using fuzzy concept. Moreover, on the basis of the stated Context we can also infer the user contacted status of the environment. It is also possible to enable this system to function automatically in compliance with the inferred state.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.4
• /
• pp.248-254
• /
• 2014

Among acoustic signal analysis tasks, acoustic context awareness is one of the most formidable tasks in terms of complexity since it requires sophisticated understanding of individual acoustic events. In conventional context awareness methods, individual acoustic event detection or recognition is employed to generate a relevant decision on the impending context. However this approach may produce poorly performing decision results in practical situations due to the possibility of events occurring simultaneously or the acoustically similar events that are difficult to distinguish with each other. Particularly, the babble noise acoustic event occurring at a bus or subway environment may create confusion to context awareness task since babbling is similar in any environment. Therefore in this paper, a frequency-cepstral feature vector is proposed to mitigate the confusion problem during the situation awareness task of binary decisions: bus or metro. By employing the Support Vector Machine (SVM) as the classifier, the proposed feature vector scheme is shown to produce better performance than the conventional scheme.

• Journal of Information Processing Systems
• /
• v.11 no.2
• /
• pp.184-204
• /
• 2015

Fuzzy Formal Concept Analysis (FCA) is a mathematical tool for the effective representation of imprecise and vague knowledge. However, with a large number of formal concepts from a fuzzy context, the task of knowledge representation becomes complex. Hence, knowledge reduction is an important issue in FCA with a fuzzy setting. The purpose of this current study is to address this issue by proposing a method that computes the corresponding crisp order for the fuzzy relation in a given fuzzy formal context. The obtained formal context using the proposed method provides a fewer number of concepts when compared to original fuzzy context. The resultant lattice structure is a reduced form of its corresponding fuzzy concept lattice and preserves the specialized and generalized concepts, as well as stability. This study also shows a step-by-step demonstration of the proposed method and its application.

• The Journal of the Korea Contents Association
• /
• v.15 no.10
• /
• pp.658-668
• /
• 2015

The purpose of present study tested the effects of context, transparency, familiarity and related variables on comprehension of 32 idioms in 87 Chinese learners of Korean who were attending the S university in Jeonnam providence. In the first assessment, idiomatic phrases were presented out of context. In another assessment, idiomatic phrases were embedded in supportive story contexts. To examine the difference based on task types, paired t-test or one-way ANOVA was used to test differences on related variables such as TOPIK, years of residence in Korea, major and etc. on idiom comprehension. The results of this study are summarized as follows. First, task type, familiarity and transparency were found to have no significant effect on idiom comprehension for Chinese learners of Korean. Second, the related variables such as TOPIK, and major had a significant effect on idiom comprehension. Third, percentage of context related interpretation error in context task was the highest. Literal interpretation errors were followed by it. It means they have a tendency to use contextual cues and semantic analysis of the phrase to comprehend Korean idioms. The results of study will be used to make a plan for teaching Chinese learners of Korean.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.20 no.5
• /
• pp.59-67
• /
• 2010

In the paper, we proposed an IM-ACM(Insider Misuse-Access Control Model) for preventing illegal information leakage by insider who exploits his legal rights in the ubiquitous computing environment. The IM-ACM can monitor whether insider uses data rightly using misuse monitor add to CA-TRBAC(Context Aware-Task Role Based Access Control) which permits access authorization according to user role, context role, task and entity's security attributes. It is difficult to prevent information leakage by insider because of access to legal rights, a wealth of knowledge about the system. The IM-ACM can prevent the information flow between objects which have the different security levels using context role and security attributes and prevent an insider misuse by misuse monitor which comparing an insider actual processing behavior to an insider possible work process pattern drawing on the current defined profile of insider's process.

• Journal of Information Technology Applications and Management
• /
• v.14 no.2
• /
• pp.11-26
• /
• 2007

In this paper we suggest a context-driven configuration model of virtual businesses to form a business network model consisting of role-based, interaction-centered business partners. The model makes use of the subcontext concept which explicitly represents actors and interactions in virtual business (VB) context. We separate actors who have capacities on tasks in a specific kind of role and actor subcontext which models requirements in specific interaction subcontext. Three kinds of actors are defined in virtual service chains, service user, service provider, and external service supporter. Interaction subcontext models a service exchange process between two actor subcontexts with consideration of context dependencies like task and quality dependencies. Each subcontext may be modeled in the form of a situation network which consists of a finite set of situation nodes and transitions. A specific situation is given in a corresponding context network of actors and interactions. It is illustrated with a simple example.