• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.379-385
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• 2012

This paper suggests U-healthcare system for individual health management realizing the gateway, client, and Java-based network server by using the vital signal measuring system and android-based mobile platform. This study realized the vital signal measuring system based on the technology to measure the ECG, oxygen saturation, blood pressure, and respiration, etc. And all the information of measurement was transmitted to the mobile gateway using the 3-bite transmission protocol consisting of headers and data. The data transmitted to the mobile gateway was used to examine the mobile client's personal health indexes through the network server. This paper realized and tested the android-based gateway, client, and the broadcasting network server and verified their validity with simulations and actual humans. As a result, the U-healthcare system suggested was proved to be effective in managing each individual's health from short distance and long distance. And it could examine each individual's health conditions in real-time and was found to be advantageous in that it could secure the guardian's mobility.

• Health Policy and Management
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• v.16 no.4
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• pp.68-85
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• 2006

With the competitive environment accelerating in healthcare industry, the hospital network system is considered as one of the strategies for clinical and managerial efficiency. This study was intended to offer a theoretical view on the hospital network system and to analyze the current network status of hospitals in Korea. Specifically, network types were classified based on the criteria modified from previous studies, and were used to describe and compare the scope and intensity of associated activities. The questionnaire survey was conducted with 237 hospitals during the period of December 27 2005 to January 25 2006. Above 90% of tertiary and secondary care hospitals were under the network system, while only 20% of primary care clinics were affiliated. In general, the scope and intensity of network activities was limited. Vertical and/or clinical integration was more common than horizontal and/or managerial integration. Three most frequent types of hospital network systems were clinical-vertical integration (Type A), clinical/managerial-vertical integration(Type B), and clinical/managerial-horizontal /vertical integration (Type C). Such network types differentiated significantly different features of affiliated hospitals and network systems. The affiliation duration to the network system was the only significant factor influencing on the network type. The strategic approach to the network system was emphasized for hospitals to increase the potential advantage of hospital network systems.

• Convergence Security Journal
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• v.13 no.4
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• pp.11-17
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• 2013

All u-Health system has security vulnerabilities. This vulnerability locally(local) or network(network) is on the potential risk. Smart environment of health information technology, Ad-hoc networking, wireless communication environments, u-health are major factor to increase the security vulnerability. u-health care information systems user terminal domain interval, interval public network infrastructure, networking section, the intranet are divided into sections. Health information systems by separating domain specific reason to assess vulnerability vulnerability countermeasure for each domain are different. u-Healthcare System 5 layers of security risk assessment system for domain-specific security vulnerability diagnosis system designed to take the security measures are needed. If you use this proposed model that has been conducted so far vaguely USN-based health information network security vulnerabilities diagnostic measures can be done more systematically provide a model.

• Journal of Sensor Science and Technology
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• v.15 no.5
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• pp.362-370
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• 2006

The wireless sensor network (WSN) based ECG and body temperature measuring system for ubiquitous health-care were designed and developed. The system was composed of a wireless sensor network node, base station and server computer for the continuous monitoring of ECG signals and body temperatures of patients at home or hospital. ECG signal and body temperature data, important vital signals which are commonly used in clinical and trauma care, were displayed on a graphical user interface (GUI). The data transfer from sensor nodes on patients' body to server computer was accomplished through a base-station connected to a server computer using Zigbee compatible IEEE802.15.4 standard wireless communication. Real-time as well as historical, ECG data of elderly persons or patients, can also be retrieved and played back to assist the diagnosis. The ubiquitous health care system presented in this study can effectively reduce social medical expenses, which will be increased greatly in the coming aging society.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.412-417
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• 2009

With ubiquitous computing aid, it can improve human being's life quality if all people have more convenient medical service under pervasive computing environment. In this paper, for a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee-based sensor network. And as a backend, medical information server accumulates sensing data and performs back-end processing. To simply transfer these sensing values to a medical team may be a low level's medical service. So, we've designed a model with context awareness for more improved medical service which is based on ART(adaptive resonance theory) neural network. Our experiments show that a proposed healthcare system can provide improved medical service because it can recognize current context of patient more concretely.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.117-129
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• 2009

This paper studied the safety management network system of infrastructure which constructed smart sensors, closed-circuit television(CCTV) and monitoring system. This safety management of infrastructure applied to bridge, cut slop and tunnel, embankment etc. The system applied to technologies of standardization guidelines, data acquirement technologies, data analysis and judgment technologies, system integration setup technology, and IT technologies. It was constructed safety management network system of various infrastructure to improve efficient management and operation for many infrastructure. Integrated safety management network system of infrastructure consisted of the real-time structural health monitoring system of each infrastructure, integrated control center, measured data transmission using i of tet web-based, collecting data using sf ver, early alarm system which the dangerous event of infrastructure occurred. Integrated control center consisted of conference room, control room to manage and analysis the data, server room to present the measured data and to collect the raw data. Early alarm system proposed realization of warning and response within 5 minute or less through development of sensor-based progress report and propagation automation system using the media such as MMS, VMS, EMS, FMS, SMS and web services of report and propagation. Based on this, the most effective u-Infrastructure Safety Management System is expected to be stably established at a less cost, thus making people's life more comfortable. Information obtained from such systems could be useful for maintenance or structural safety evaluation of existing structures, rapid evaluation of conditions of damaged structures after an earthquake, estimation of residual life of structures, repair and retrofitting of structures, maintenance, management or rehabilitation of historical structures.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.149-156
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• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.

• Convergence Security Journal
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• v.11 no.3
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• pp.39-46
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• 2011

Smart environment of health information technology, u-Healthcare architecture, ad-hoc networking and wireless communications environment are major factors that increase vulnerability of u-healthcare information systems. Traffic domain is the concept of network route that identifies the u-Healthcare information systems area as the traffic passing and security technologies application. The criterion of division is an area requiring the application of security technology. u-Healthcare information system domains are derived from the intranet section. the public switched network infrastructure, and networking sectors. Domains of health information systems are separated by domain vulnerability reason. In this study, domain-specific security vulnerability assessment system based on the USN in u-Healthcare system is derived. The model used in this study suggests how to establish more effective measurement USN-based health information network security vulnerability which has been vague until now.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.91-109
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• 1995

This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).