• Journal of the Korean Institute of Gas
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• v.23 no.2
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• pp.17-27
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• 2019

In recent years, dangerous materials and gas leak accidents have been frequently occurred. The hazardous materials storage facility accidents are not rapidly controlled when a leak is detected, unlike other chemical plants can be controled. Externally, the human has to approach and respond to the source of leaking directly. As a result, the human and material damage are likely to larger result in the process. The current approach has been passive response after ringing the alarm. In this study, the suggested tracking system of the leak resource is designed system to track the resource actively by utilizing the mobile sensor robot platform, which can be made easily through recent rapid development technology, is verified through prototype system. Thus, a suggested system should pave the way for minimizing the spread and damage of the accident based on the exact site situation of the initial leak and quick and early measures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.101-112
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• 2019

This study developed selection criteria of small-scales reservoirs, having under $300,000m^3$ storage capacity, for the Emergency Action Plan(EAP) establishment in order to reduce the disaster risks of the reservoir's failures. Those reservoirs are out of ranges of Korean EAP establishment standard, but have potential risk of disasters as they have often failed by the recent extreme rainfall events and earthquakes, causing economical and life losses. The problem of reservoir aging is also one of the reasons of them. In this study, the developed selection criteria of small reservoirs for EAP establishment are storage capacity, embankment height, reservoir age, heavy rain factor and earthquake factor. These criteria were selected based on the review of the existing EAP establishment guidelines, analysis of the past dam failure cases, and the previous related studies. The quantification of these criteria were conducted for the practical applications in the fields, and applied to 67 previous failures in order to investigate the relation of each criteria with these failures. The earthquake factor found to be the highest relations followed by heavy rain factors, combination of earthquake and heavy rain factors, and reservoir age. The classification was made as observation and review groups for EAP establishments based on overlapping numbers of each criteria. This classifications applied to 354 reservoirs designated as having the potential disaster risk by MOIS, and showed 38.4% of observation and 11.9% of review groups. Anticipatory monitoring and regular inspection should be made by professional facility managers for the observation group, and necessity of EAP establishment should be assessed for the review group based on the downstream status and financial budget.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.87-96
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• 2022

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.71-92
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• 2023

Globally, under the leadership of advanced ICT countries, the private sector is promoting various policies to promote the digital transformation of public services. Looking at the research trend, design of public service indicators, development of evaluation system, and empirical research are being carried out steadily, but there are insufficient research cases on models in which the private sector participates in the planning, development, and operation of public services. In this study, Private-centric digital public service suitability evaluation indicators were discovered through interviews with experts in various fields, and weights for each indicator were analyzed through AHP evaluation. In addition, by applying the analysis results to 18 digital public services on a trial basis, the importance and priority of evaluation indicators for each service were derived, and at the same time, the evaluation framework was designed and applied to diagnose implications. As a result of the study, 'social utility', 'corporate acceptability', and 'public acceptability' were selected as the top three indicators of suitability evaluation. At this time, it was analyzed that the weight of the 'company acceptability' index, which includes sub-indices such as 'service profitability', 'service scalability', and 'private initiative possibility', was the highest among the three top indicators. As a result of the demonstration for public services, "IoT facility unmanned remote monitoring service", "blockchain real estate transaction service", and "digital twin disaster prediction service" were evaluated as the most suitable public services for the transition to the private sector.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1332-1341
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• 2023

Beam position measurement system can not only provide the beam position monitoring, but also be used for global orbit correction to reduce beam loss risk and maximize acceptance. The Beam Position Monitors (BPM) are installed along the synchrotron to acquire beam position with the front-end electronics and data acquisition system (DAQ). To realize high precision orbit measurement in the main heavy ion synchrotron and cooling storage ring of heavy-ion research facility in Lanzhou (HIRFL-CSRm), a series of alignment and calibration work has been implemented on the BPM and its DAQ system. This paper analyzed the tests performed in the laboratory as well as with beam based on the developed algorithms and hardware. Several filtering algorithms were designed and implemented on the acquired BPM raw data, then the beam position and resolution were calculated and analyzed. The results show that the position precision was significantly improved from more than 100 ㎛ to about 50 ㎛ by implementing the new designed filtering algorithm. According to the analyzation of the measurement results and upcoming physical requirements, further upgrade scheme for the BPM DAQ system of CSRm based on field programmable gate array (FPGA) technology was proposed and discussed.

• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.25-42
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• 2023

Despite the significance of ports as critical economic infrastructure, the berth facilities usually deteriorate due to heavy loading, unloading, aging, environmental weather conditions, marine growths, and lack of efficient maintenance management. Marine berths require proactive maintenance management to limit deterioration and defects as no berth facility is maintenance-free. Thus, delay in carrying out maintenance work for the marine berths can be devastating to the operational process involving ship entry, loading, and unloading operations. The aim of this research is to coordinate both operations work, and maintenance works that take place inside the berth of a local industrial port in Saudi Arabia, by developing a novel framework that integrates both works without affecting the efficiency and functionality of the berth. The study focused on defining the operational process of the port and identifying the elements with direct and indirect effects. In addition to determining the priority for the entry of ships inside the berth, it also identified the factors involved in designing a framework that included maintenance work as a component of the monthly berth occupancy schedule. By applying a mathematical model, a framework was established, which includes all the important elements of the process. As a result of the mathematical method formulation process, a database was designed that organizes and coordinates the operations of all berths within the port. This creates time to carry out the required maintenance work monthly as well as ease of coordination with the contractors responsible for the implementation of those works.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.

• Research in Plant Disease
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• v.28 no.4
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• pp.221-230
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• 2022

The fire blight caused by Erwinia amylovora (Ea) was first reported in 2015 in Korea, and the disease has rapidly spread to 22 regions until 2021. In Korea, all host plants in the apple and pear orchards where fire blight occurred should be eliminated and buried by the Plant Protection Act. To prevent the spread of the disease, all burial sites were prohibited from planting the new host plants for the next three years. To confirm the eradication efficiency of Ea and the reoccurrence of fire blight, the surveillance facilities were established on three burial sites from 2019 to 2020 in Anseong-si, Gyeonggi-do, and Chungju-si, Chungcheongbuk-do. As host plants, five apple trees of fire blight-susceptible cultivar 'Fuji', were planted in each facility. All facilities were enclosed with fences and nets and equipped with two CCTVs, motion sensors, and several other sensors for recording weather conditions to monitor the environment of the sentinel plants in real-time. The sentinel plants were checked for the reoccurrence of fire blight routinely. Suspicious plant parts were collected and analyzed for Ea detection by loop-mediated isothermal amplification polymerase chain reaction and conventional polymerase chain reaction. Until November 2022, Ea has not been detected in all sentinel plants. These results might support that the burial control of infected plants in soil works efficiently to remove Ea and support the possibility to shorten the prohibition period of host plant establishment in the burial sites.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.275-281
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• 2016

This study was conducted to analyze the runoff characteristics of the highway depending on the number of vehicles and to provide the installation proposal of an NPS pollution reduction facility. There were a total of 5 monitoring sites used for the study namely, Gyeongbu, Seohaean, Honam and Tongyeoung Dageon highway. Monitoring events started from 2006 until 2015 having a total of 44 storm events. According to monitoring statistics, the average antecedent dry days (ADD) and rainfall was 6.2 days and 19.2 mm, respectively. The Gyeongbu Highway (H-4) was recorded having the highest Average Daily Traffic and Catchment Area (ADT/CA) with $49.4car/day{\cdot}m^2$ while other site were less than $10car/day{\cdot}m^2$. The average concentration of the NPS pollutants generated from monitoring sites were 63.5 mg/L(TSS), 24.9 mg/L(BOD), 3.35 mg/L(TN), 0.63 mg/L(TP) and 298 ug/L(Total Zn). This exhibited lower values in comparison to the remarks of highway related runoff EMC values published in Korea. Moreover, through the results of the correlation analysis between the contaminant concentration and ADT/CA, $R^2$ value of SS showed the highest correlation with 585. Through the correlation equation between ADT/CA and EMC of TSS, when there is 73.7 mg/L of TSS EMC found from a domestic highway, ADT/CA ratio is normally $13car/day{\cdot}m^2$. Therefore, in a case of more than 13 cars passing through a certain area, the area can be considered and present as the point of generation of nonpoint source pollutants. Also, in this study, since it considered a unit area ADT indicated in previous studies, it was determined that it has a high applicability and utilization in generalized units than conventional study which were conventionally done.