• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.53-63
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• 2014

Moving context determination is an important issue to be resolved in a mobile computing environment. This paper presents a method for recognizing and classifying a mobile user's moving context by Euclidean distance similarity. In the proposed method, basic data are gathered using Global Positioning System (GPS) and accelerometer sensors, and by using the data, the system decides which moving situation the user is in. The decided situation is one of the four categories: stop, walking, run, and moved by a car. In order to evaluate the effectiveness and feasibility of the proposed scheme, we have implemented applications using several variations of Euclidean distance similarity on the Android system, and measured the accuracies. Experimental results show that the proposed system achieves more than 90% accuracy.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.653-662
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• 2006

In ubiquitous computing that is to build computing environments to provide proper services according to user's context, human being's emotion recognition based on facial expression is used as essential means of HCI in order to make man-machine interaction more efficient and to do user's context-awareness. This paper addresses a problem of rigidly basic emotion recognition in context-sensitive facial expressions through a new Bayesian classifier. The task for emotion recognition of facial expressions consists of two steps, where the extraction step of facial feature is based on a color-histogram method and the classification step employs a new Bayesian teaming algorithm in performing efficient training and test. New context-sensitive Bayesian learning algorithm of EADF(Extended Assumed-Density Filtering) is proposed to recognize more exact emotions as it utilizes different classifier complexities for different contexts. Experimental results show an expression classification accuracy of over 91% on the test database and achieve the error rate of 10.6% by modeling facial expression as hidden context.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.643-648
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• 2005

In order to supply services necessary for users intelligently in the ubiquitous computing, effective filtering of context information is necessary. But studies of context information filtering have not been made much yet. In order for filtering of context information, we can use collaborative filtering being used much at electric commerce, etc. In order to use such collaborative filtering method in the filtering of ubiquitous computing environment, we must solve such problems as first rater problem, sparsity problem, stored data problem and etc. In this study, in order to solve such problems, the researcher proposes the collaborative filtering method using types of context information. And as the result of applying this filtering method to MAUCA, the P2P mobile agent system, the researcher could confirm the average result of 7.7% in the aspect of service supporting function.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.167-172
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• 2006

As ubiquitous devices are fast spreading, the communication problem between humans and these devices is on the rise. The use of context is important in interactive application such as handhold and ubiquitous computing. Context is not crisp data, so it is necessary to introduce the fuzzy concept. The proxity relation is represented by the degree of closeness or similarity between data objects of a scalar domain. A context manager of context-awareness system evaluates imprecise queries with the proximity relations. in this paper, a systematic proximity elicitation method are proposed. The proposed generation method is simple and systematic. It is based on the well-known fuzzy set theory and applicable to the real world applications because it has tuning parameter and weighting factor. The proposed representations of proximity relation is more efficient than the ordinary matrix representation since it reflects some properties of a proximity relation to save space. We show an experiments of quantitative calculate for the proximity relation. And we analyze the time complexity and the space occupancy of the proposed representation method.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.291-299
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• 2012

Ubiquitous computing is a technique to provide users with appropriate services, collecting the context information in somewhere by attached sensor. An intelligent system needs to automatically update services according to the user's various circumstances. To do this, in this paper, we propose a design of context ontology, trigger rule for mining service pattern related to users activity and an active mining architecture integrating trigger system. The proposed system is a framework for active mining user activity and service pattern by considering the relation between user context and object based on trigger system.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.538-544
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• 2005

The service supporting structure for users in ubiquitous computing environment requires technology that divides efficiently resources shared around users according to users context. So, needs research that analyze service items and resources that is offered according to users context information and divide adaptively necessary service and resources. Therefore, in this paper we proposes an intelligent P2P mobile agent that recognizes users context using portable mobile devices and is available for intelligent service by sharing serviced item according to users' context. The proposed structure removes monopoly for specific resources, and supports effective users context-awareness and service.

• Electronics and Telecommunications Trends
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• v.20 no.2 s.92
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• pp.33-42
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• 2005

URC는 기존 로봇에 네트워크 및 정보 기술을 접목한 지능형 서비스 로봇의 새로운 개념으로서, 언제, 어디서나 나와 함께 하며, 나에게 필요한 서비스를 제공하는 네트워크기반 로봇이다. URC 개념이 구현되기 위해서는 유비쿼터스 네트워크 또는 센서 네트워크, 고성능 로봇용 서버 등과 같은 하드웨어 인프라가 구축되어 있어야 하며, 이러한 인프라 상에서 구동되는 소프트웨어 인프라가 필요하다. 본 고에서는 URC의 소프트웨어 인프라의 구현에 요구되는 많은 기술 중 특히 상황인식 컴퓨팅 기술에 대해 논의하고 ETRI에서 개발중인 상황인식 미들웨어인 CAMUS에 대해 소개하고자 한다.

• Korea Information Processing Society Review
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• v.10 no.4
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• pp.97-121
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• 2003

No Abstract, See Full Text

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.172-175
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• 2012

스마트 컴퓨팅은 지능형 정보서비스로서 스마트폰, 스마트패드, 스마트TV 등의 다양한 스마트 기기를 비롯한 스마트 워크, 스마트 자동차 등의 새로운 정보화시스템 개념으로 대두되고 있다. 본 논문은 스마트 컴퓨팅의 컴퓨팅 환경과 최적의 정보 상호작용을 정립하기 위해서 정보 상호작용에 대한 상황 인식 기반 구조적, 기능적, 인터페이스 접근에 대해서 논의한다. 이러한 정보 상호작용을 통해서 사용자 컴퓨팅 환경에 최적화된 스마트 정보시스템의 효율적 구성과 사용자 정보서비스의 편의성을 구축한다.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.