• Journal of Preventive Medicine and Public Health
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• v.48 no.6
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• pp.277-279
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• 2015

Contact monitoring is an essential component of the public health response to a Middle East respiratory syndrome coronavirus outbreak, and is required for an effective quarantine to contain the epidemic. The timeliness of a quarantine is associated with its effectiveness. This paper provides a conceptual framework to describe the process of contact monitoring, and proposes a new measure called the "timely quarantined proportion" as a tool to assess the adequacy of a public health response.

• Smart Structures and Systems
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• v.10 no.3
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.

• Journal of Environmental Health Sciences
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• v.41 no.5
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• pp.277-288
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• 2015

Objectives: There are many hazardous agents at livestock farms. In particular, gases can be detrimental to both workers and animals. This study evaluated ammonia and hydrogen sulfide concentrations in broiler hen barns and beef cattle barns according to sampling location and height. Methods: Three broiler hen barns and three beef cattle barns were selected for gas monitoring in this study. Ammonia and hydrogen sulfide concentrations were measured using a direct-reading instrument which could measure the target gases simultaneously. Gas monitoring was conducted at human breathing height and animal breathing height at three points in each livestock farm. Results: Ammonia concentrations at the broiler hen barns ranged from 3.3 to 12.5 ppm by sampling location and height, but hydrogen sulfide was not detected. In the beef cattle barns, ammonia ranged from 3.1 to 16.3 ppm and low concentrations of hydrogen sulfide were detected at some animal breathing heights. The gas concentrations detected at each livestock farm were significantly higher in the animal breathing zones than in human breathing zones (p<0.0001). Conclusions: We found a difference in gas concentrations between human breathing zones and animal breathing zones. Gas monitoring should be conducted to improve the related environment considering both workers' and animals' health and safety.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.2
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• pp.147-155
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• 2021

Objective: The purpose of this study was to find ways for strengthening occupational health services through monitoring exposure to health hazards. Methods: About 70,000 workplaces that have conducted the work environment measurement(WEM) over the last three years(2017~2019) were classified according to the Korean Standard Industry Classification(KSIC), and the current status of WEM by industry was analyzed. The authors considered ways to monitor exposure to health hazards in order to strengthen occupational health services and protect workers' health. Results: Based on the KSIC, 934 of the 1,196 total sub-classified industries have conducted WEM in at least one workplace over the last three year(2017~2019). In the case of manufacturing, out of a total of 477 sub-classified industries, 474 have conducted WEM at more than one workplace. However, in some industries, WEM was not conducted or the implementation rate was low, so it was necessary to examine whether WEM should be expanded based on a detailed analysis of the WEM database. To this end, it is necessary to form an exposure monitoring committee in which various experts from different fields can participate. The committee needs to discuss the overall matters necessary for selecting industries that require detailed investigation or research, review the results, and prepare a final recommendation. Conclusion: In conclusion, the government needs to come up with a plan to strengthen occupational health services through surveys and research on the current status of WEM and work environment management models by industry.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.46-53
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• 2009

This study aims to develop a mobile-based portable u-Health Monitoring System which provides a personal medical service on demand by processing patients' data intellectually achieved through sensing technique of non-restriction/non-consciousness oriented and deciding. To do this, we composed a USN-based portable monitoring unit. It is the one, that contains a somatometry sensor which is attached to patient's body and detects bio information, a portable wireless terminal which receives information from the sensor and transmits it to monitor server, and a monitor server which interprets received data through wireless network and processes. Also, it tries to develop a non-restriction /non-consciousness oriented sensing technique which is related to glycosuria and cardiovascular diseases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1219-1223
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• 2006

Tongue is one of the most important parts in patient diagnosis in traditional Korean(Chinese) medicine. This paper presents health monitoring method using tongue images of a person. The method uses not absolute tongue features but relative ones which are differences from reference health condition(RHC), diagnosed in hospital, for a person. A user can give tongue images to a health monitoring system everyday, which extracts regions of interest (ROI's) of the tongue, and compares their features with reference health condition. In the experiments, tongue image analysis for a person by our computerized method encouraged us that the method using tongue images can be contributed for health monitoring.

• Steel and Composite Structures
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• v.29 no.6
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• pp.703-716
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• 2018

Rapid detection of damages in civil engineering structures, in order to assess their possible disorders and as a result produce competent decision making, are crucial to ensure their health and ultimately enhance the level of public safety. In traditional intelligent health monitoring methods, the features are manually extracted depending on prior knowledge and diagnostic expertise. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed here for intelligent health monitoring of civil engineering structures. In the first stage, $Nystr{\ddot{o}}m$ method is used for automatic feature extraction from structural vibration signals. In the second stage, Moving Kernel Principal Component Analysis (MKPCA) is employed to classify the health conditions based on the extracted features. In this paper, KPCA has been implemented in a new form as Moving KPCA for effectively segmenting large data and for determining the changes, as data are continuously collected. Numerical results revealed that the proposed health monitoring system has a satisfactory performance for detecting the damage scenarios of a three-story frame aluminum structure. Furthermore, the enhanced version of KPCA methods exhibited a significant improvement in sensitivity, accuracy, and effectiveness over conventional methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.387-395
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• 2013

It is important to collect reliable measured data for proper bridge health monitoring. However, in reality incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In case of sensor malfunction, parts of measured data are missing and thus health monitoring cannot be carried out reliably. Due to environmental effects such as temperature variation, dynamic characteristics of natural frequencies may change as if the structure is damaged. The paper proposes a systematic procedure of data processing and data analysis for reliable structural health monitoring. Also, it applies the Mahalanobis distance as a health index computed statistically using revised data. The proposed procedure has been examined using numerically simulated data from a truss structure and then applied to a set of field data measured from Seohae cable-stayed bridge.

• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.129-150
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• 2018

This paper presents the structural performance monitoring of an urban footbridge located in Hangzhou, China. The structural health monitoring (SHM) system is designed and implemented for the footbridge to monitor the structural responses of the footbridge and to ensure the structural safety during the period of operation. The monitoring data of stress and displacement measured by the fiber Bragg grating (FBG)-based sensors installed at the critical locations are used to analyze and assess the operation performance of the footbridge. A linear regression method is applied to separate the temperature effect from the stress monitoring data measured by the FBG-based strain sensors. In addition, the static vertical displacement of the footbridge measured by the FBG-based hydrostatic level gauges are presented and compared with the dynamic displacement remotely measured by a machine vision-based measurement system. Based on the examination of the monitored stress and displacement data, the structural safety evaluation is executed in combination with the defined condition index.