• Journal of Environmental Health Sciences
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• v.40 no.1
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• pp.1-9
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• 2014

Objectives: The purpose of this review is to suggest future directions for the Korean Environmental Health Survey (KoNEHS) in terms of an environmental health monitoring system and recent environmental health issues in Korea. Methods: The national scale biomonitoring program and environmental health researches which conducted by Ministry of Environment was reviewed for this study. The scope, contents and utilization of results of KoNEHS as a biomonitoring program and other basic function for environmental health monitoring was analyzed. Results: Biomonitoring survey was conducted for basic functions, such as evaluating exposure levels of environmental chemicals and analyzing exposure factors. In order to expand the basic purposes of KoNEHS, the biomonitoring function should be strengthened by enlarging the range of chemicals analyzed and including all age groups in the biomonitoring and health status monitoring functions by using official health-care and mortality data. Exposure factors such as time-activity patterns and micro-environmental pollution levels were studied. The data from the environmental health study were established into a standardized database system for supporting environmental health policy. A definition and concept of environmental health services should be established. Conclusion: To achieve the aims of environmental health, changes in environmental health status and related factors must be observed and predicted reflecting real conditions. In this regard, improving the methodology and system through diverse approaches is necessary for KoNEHS.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.

• Aerospace Engineering and Technology
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• v.11 no.1
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• pp.178-184
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• 2012

In this study, implementation process of sensor-embedded main wing model for structural health monitoring is described. Fiber Bragg Grating (FBG) Sensor, Plumbum-Zirconate-Titanate (PZT) Sensor, and strain gauge are installed in the main wing of Jabiru UL airplane as a test-bed of Health and Usage Monitoring System (HUMS).

• Smart Structures and Systems
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• v.1 no.4
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• pp.325-338
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• 2005

Utilizing robotic based reconfigurable nodal structural health monitoring systems has many advantages over static or human positioned sensor systems. However, creating a robot capable of traversing a variety of civil infrastructures is a difficult task, as these structures each have unique features and characteristics posing a variety of challenges to the robot design. This paper outlines the design and implementation of a novel robotic platform for deployment on ferromagnetic structures as an enabling structural health monitoring technology. The key feature of this design is the utilization of an attachment device which is an advancement of the common magnetic base found in the machine tool industry. By mechanizing this switchable magnetic circuit and redesigning it for light weight and compactness, it becomes an extremely efficient and robust means of attachment for use in various robotic and structural health monitoring applications. The ability to engage and disengage the magnet as needed, the very low power required to do so, the variety of applicable geometric configurations, and the ability to hold indefinitely once engaged make this device ideally suited for numerous robotic and distributed sensor network applications. Presented here are examples of the mechanized variable force magnets, as well as a prototype robot which has been successfully deployed on a large construction site. Also presented are other applications and future directions of this technology.

• Journal of the Korean Society for Railway
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• v.5 no.3
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• pp.148-157
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• 2002

A health monitoring system becomes a useful tool to obtain information on long term behavior of the important railway structures such as very long span and special type bridges. The health monitoring system not only gives the direct measurement data of the railway bridges but also provides the basic data on the maintenance of the structures. Therefore, periodic calibrations of the health monitoring system will be a necessary step toward precise and accurate assessment of the railway bridges. In this study, the calibration and gauge factor readjustment process made for the health monitoring system installed in the railroad bridges is reviewed and some findings are explained in detail: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in full length. Based on the regression results, it was found that the gauge factors need to be readjusted according to the regression equation but, since the deviation or shift is not serious so far, long-term observation on each sensor is also recommended. Future work will be concentrated on the long-term analysis of each sensor and on the database creation so that the assessment of the structures is possible.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Korean Journal of Health Education and Promotion
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• v.32 no.1
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• pp.67-76
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• 2015

Objectives: This study performed to verify Korea National Health and Examination Survey(KNHAES) to monitor recommended physical activity(PA) and to propose an monitoring tools for evidence-based PA projects. Methods: The characteristics of the Global Physical Activity Questionnaire(GPAQ) and its reliability and validity were overviewed based on the current scientific evidence in the field of PA. Relevant articles were identified through multiple sources including PubMed, Science Direct, Scopus, CINAHL, ASP, RISS4U, and KISS. Results: The GPAQ has strong points over the Short Form of International Physical Activity Questionnaire(IPAQ-SF) as a monitoring tool to meet recommended PA levels for three domains separately and reflecting a better understanding about walking. Its reliability and validity also were reported as acceptable in existing studies overall. Some limitations of this questionnaire, however, need to be addressed to improve its quality. Conclusions: For monitoring of evidenced-based physical activity projects, we considered that it is able to be provided an opportunity for in-depth discussion among academic experts and policy-makers about the necessity of complements for KNHAES and applying new tools, and it could be the basis for development of physical activity monitoring tool in the future.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2066-2072
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• 2008

The time reversal was investigated for direct root between PZT and PZT, but in case of a circular PZT, lamb wave moves not only along the direct root but also another roots. The center frequency of lamb wave is kept when the lamb waves are reflected from damage. This paper presents experimental and theoretical results for the new structural health monitoring method by above features of lamb wave, and we can increase accuracy of the new structural health monitoring method by using STFT(Short Time Fourier Transform).

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.481-484
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• 2008

The research was carried out to suggest the bridge health monitoring systems that have been composed damage detection algorithm and a system for evaluation load carrying capacity of bridge by traffic loads for the purpose of safety management of bridge structure in efficient and economic.