• 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.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.205-208
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• 2008

This article presents a methodology for the monitoring of air pollution. All over the world, the interest in the environment has been continuously increasing. Unfortunately, much of this interest is due to emerging problems, such as the greenhouse effect and climate change. For this reason, research into carbon dioxide, which causes the greenhouse effect, is progressing rapidly. This article presents a method of measuring the level of carbon dioxide and other substances in the air through the utilization of mobile-networking base stations and measured data. First of all, sensors are attached at the appropriate position of the mobile-networking base stations. These sensors will measure the air quality in their respective positions, and send sensor data to an urban management center via network gateways and data-collecting systems. The measured data can be used for various purposes. In general, it can be used to measure the air quality, which can then be used as a basis for urban planning. The method described herein utilizes airpollution sensors that are attached to the base stations in different locations and at varying heights. The data obtained hereby will be applicable in many fields. At this time this is simply a methodology, however we hope that it will lead to a practical application.

• Structural Monitoring and Maintenance
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• v.6 no.2
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• pp.125-145
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• 2019

Bridge scour is one of the predominant causes of bridge failure. Current climate deterioration leads to increase of flooding frequency and severity and thus poses a higher risk of bridge scour failure than before. Recent studies have explored extensively the vibration-based scour monitoring technique by analyzing the structural modal properties before and after damage. However, the state-of-art of this area lacks a systematic approach with sufficient robustness and credibility for practical decision making. This paper attempts to develop a data-driven methodology for bridge scour monitoring using support vector machines. This study extracts features from the bridge dynamic responses based on a generic sensitivity study on the bridge's modal properties and selects the features that are significantly contributive to bridge scour detection. Results indicate that the proposed data-driven method can quantify the bridge scour damage with satisfactory accuracy for most cases. This paper provides an alternative methodology for bridge scour evaluation using the machine learning method. It has the potential to be practically applied for bridge safety assessment in case that scour happens.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.

• Proceedings of the Korean Nuclear Society Conference
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• 2002.05a
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• pp.100-100
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• 2002

• Proceedings of the Korean Nuclear Society Conference
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• 2002.10a
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• pp.62.1-62
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• 2002

• Proceedings of the Korean Nuclear Society Conference
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• 2002.10a
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• pp.102-102
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• 2002

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.161-162
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• 2019

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.53-61
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• 2024

Global Navigation Satellite Systems are expected to meet system-defined integrity requirements when users utilize the system for safety critical applications. While the guaranteed integrity performance of GPS and Galileo is publicly available, their integrity assurance procedure and related methodology have not been released to the public in an official document format. This paper summarizes the integrity assurance procedures of Global Positioning System (GPS) and Galileo, which were utilized during their system development, through a literature survey of their integrity assurance methodology. GPS Block II assures system integrity using the following methods: continuous performance monitoring and maintenance on Space Segment (SS) and Control Segment (CS), through a cause and effect analysis of anomalies and a failure analysis. In GPS Block III, to achieve more stringent integrity performance, safety requirements are integrated into the system design and development from its starting phase to the final phase. Galileo's integrity performance is provided in the Integrity Support Message (ISM) format, as Galileo utilizes a Dual Frequency Multi Constellation (DFMC) Satellite Based Augmentation System (SBAS) and Advanced Receiver Autonomous Integrity Monitoring (ARAIM) to serve safety critical applications. The integrity performance of Galileo is ensured by using a methodology similar to GPS Block II (i.e. continuous performance monitoring and maintenance on the system). The integrity assurance procedures reviewed in this paper can be utilized for a new satellite navigation system that will be developed in the near future.

• Architectural research
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• v.26 no.1
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• pp.1-12
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• 2024

This study introduces a deep reinforcement learning (DRL)-based methodology for optimizing apartment space arrangements, addressing the limitations of human capability in evaluating all potential spatial configurations. Leveraging computational power, the methodology facilitates the autonomous exploration and evaluation of innovative layout options, considering architectural principles, legal standards, and client re-quirements. Through comprehensive simulation tests across various apartment types, the research demonstrates the DRL approach's effec-tiveness in generating efficient spatial arrangements that align with current design trends and meet predefined performance objectives. The comparative analysis of AI-generated layouts with those designed by professionals validates the methodology's applicability and potential in enhancing architectural design practices by offering novel, optimized spatial configuration solutions.