Kwang-Rok Han

Implementation of Ubiquitous Health Care System for Active Measure of Emergencies

The present study discusses the construction of a ubiquitous health care system that can cope actively with urgent situations of chronic disease patients who can lead everyday life despite their chronic diseases. If a patients emergency is detected by personal health care host (PHCH), which is composed of USN, electronic stethoscope, GPS, CDMA and RFID, a text message containing position information is sent immediately to the hospital and the guardians mobile terminal so that they can take an action immediately. In particular, data from accelerometers and vibration sensors, which are composed of ubiquitous sensors, are learned using the back-propagation network algorithm, therefore emergencies such as syncope and convulsion are determined actively. The experiments show that this system is very effective to find emergencies promptly for chronic disease patients who cannot take care of themselves and it is expected to save many lives.

Development of u-Health Care System for Prompt Perception of Emergencies

This study discusses the development of a u-Health care system that can detect quickly and cope actively with emergent situations of chronic disease patients who lead everyday life. If a patient`s emergent situation is detected by personal health care host(PHCH), which is composed of acceleration and vibration sensors, GPS, and CDMA communication module, a text message on the patient`s current location is transmitted to the hospital and the guardian`s mobile terminal so that they can cope with the situation immediately. Especially, the system analyzes data from sensors by using neural network and determines emergent situations such as syncope and convulsion promptly. The exact location of patients can also be found in the electronic map by using GPS information. The experiments show that this system is very effective to find emergencies promptly for chronic disease patients who cannot take care of themselves and it is expected to save many lives.

A Study on Context Aware Middleware Design and Application

This paper describes a design and application of middleware that is essential to the context-aware system. We define a transducer interface protocol in order to deal with a variety of context data. For the purpose of systematic process of data between middleware modules, a message oriented middleware is designed and implemented. Memory improves the performance of high-performance computing system compared to previous strategies. Context aware middleware adopts service oriented architecture so that functions in modules may be independent and scalability can be remarkable. Using messages across modules decreases the complexity of the application development. In order to justify the usefulness of the proposed context aware middleware, we carried out our experiments in bridge health monitoring system and verified the efficacy.

An Ontology-based Context Aware Model for the Implementation of Integrated Security Control System

Abstract In this paper, we describe an ontology-based context aware model that collects context information from USN sensor and CCTV image and reasons about context in order to development an integrated security control system in the industrial environments. The context model represents autonomous and heterogeneous data as ontologies and recognizes the context through DL(description logic) inference in the smart computing environment. We expect that the integrated security control system can automatically detects the risk in the industrial field and reduces the safety and security incidents by applying this context model to the system. Key Words : Ontology, Context aware, Security control system, Inference, Description logic 이 논문은 2009년도 산학협동재단의 학술연구비 지원을 받아 수행된 연구임 * 교신저자 : 손석원(sohn@hoseo.edu)접수일 10년 03월 24일 수정일 (1차 10년 05월 05일, 2차 10년 05월 18일, 3차 10년 06월 09일) 게재확정일 10년 06월 18일 1. 서론 산업현장에서 관제시스템은 단순히 보안측면의 관제 보다는 시설 및 설비, 소방 등 다수의 설비나 시설물을 관제대상으로 하고 있다. 예를 들어 냉난방, 조명과 같은 시설 및 설비의 실시간 감시제어, 소방 설비의 실시간 감시제어 및 CCTV를 이용한 영상 감시등 다양한 종류의 관제시스템이 설치, 운영되고 있으며 이를 조작하는 작업자는 각각의 시스템을 별도로 운영, 조작하고 있다. 이로 인한 보안관제의 효율성의 저하로 개인, 기업 및 사회적인 손실은 매우 커지고 있는 실정이다. 이에 대한 대응책으로 RFID (Radio Frequency IDentification)와 USN (Ubiquitous Sensor Network) 센서 등과 같은 IT 기술을 이용한 통합보안관제 시스템의 구축이 요구되고 있다. 특히 CCTV 기반의 영상감시는 감시 인력이 단순히 모니터를 통하여 감시해야 하기 때문에 위험이 증가하고 인력활용의 효율성이 낮다. 다수의 카메라가 있음에도 감시자들이 전부 모니터링 할 수 없기 때문이다. 미국 Sandia National Lab의 연구결과에 의하면 사람이 20분만 모니터를 보고 있어도 집중력과 판단력이 떨어진다고 한다.

ISO14001-based u-LCA System Development for Operation of Environmental Facilities

This paper describes an information system of operation adequacy in environmental facilities such as environmental contamination prevention and processing equipments, which is namely, an integrated management system for environmental facilities. By developing this system, we can improve environmental characteristics and maximize the efficiency throughout the life cycle from generation of contaminant source to contamination prevention processing, and to contaminant disappearance. In order to meet these objects, we have developed ubiquitous life cycle assessment(u-LCA) for environmental facilities, which is an ISO14001-based incineration facility information system. The developed system is currently operating for test at an incinerator in Koyang city. Due to this system, the managers can confirm the operation condition of the incinerator with real-time and they will be able to improve the problems immediately.

Development of Analysis Software for Railway Vehicle Event Recorder

Recently, to analyze the cause of the railway accident objectively and quickly and prevent the accident, many countries are legislating for the installation of the black box what we call an event recorder, which records information about the operation of railway vehicle. Thus, the study of the event recorder has been in progress. Moreover, the analysis software that can analyze and express the stored data in the event recorder is required for the correct decision on the accident. Therefore, in this paper, we presented a design of analysis software which analyzes the data, plays the audio and video in the event recorder system. This software can quickly and accurately identify the cause of the accident and recognize the driving patterns and habits of the driver according to the operating section. In addition, by analyzing the audio and video data simultaneously in the previous accident, we expect that it is possible to prevent accidents in advance.

Minimizing Energy Consumption of Sensor Networks with Energy Balance Ratio and Relay Node Placement

Abstract The Relay node placement problem is one of the most important requirements for many wireless sensor networks because the lifetime of sensor networks is closely related with the placement of relay nodes which receive sensed data from sensor nodes and forward them to the base station. Relay node placement problem has focused at minimization of dissipated total energy of the sensor nodes in whole networks. However, minimum total energy causes the unbalance of consumed energy in sensor nodes due to different distances between relay nodes and sensor nodes. This paper proposes the concept of energy balance ratio and finds the locations of relay nodes using objective functions which maximize the energy balance ratio. Maximizing this ratio results in maximizing the network lifetime by minimizing the energy consumption of large-scale sensor networks. However, finding a solution to relay node placement problem is NP-hard and it is very difficult to get exact solutions. Therefore, we get approximate solutions to EBR-RNP problem which considers both energy balance ratio and relay node placement using constraint programming.

Korean Document Summarization Using Topic Phrases Extraction and Locality-Based Similarity

We describe a hybrid approach to summarize the document content using the topic phrases extraction and the query-based summary. The topic phrases are extracted using machine learning algorithm. We use these topic phrases as the query terms with locality-based similarity calculation in order to extract highly ranked sentences or paragraph. We experiment with three machine learning methods, Naive Bayesian, decision tree and supported vector machine, for extracting the topic phrases effectively and discuss the results. The overall summaries have been evaluated for the extraction accuracy compared with the human-selected summaries.