• Journal of the Korean Professional Engineers Association
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• v.43 no.2
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• pp.53-59
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• 2010

This research is about the inspection system which is for maintenance of laterals of local RBF(River bed Filtration). Inspection system is designed for local use in order to endure water resistance up to 50m and it also can examine the internal condition and colgging of laterals by moving inside of the laterals about 100m back and forward. We will conduct performance test of inspection system at the lacal RBF site and present its result.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.188-189
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• 2015

This study was conducted a survey for suggesting direction of improvement of on­site inspections in Korean construction industry. The survey is limited perspective of owners, contractors and construction managers (including supervisors) about existing 'construction field inspection manual' with field inspections (eg. central inspection, central quality safety unit inspection etc.): focusing on stakeholder's perception and actual state of inspections.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.116-117
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• 2018

The government and the Korea Occupational safety & Health Agency have continuously carried out safety activities such as supervision, inspection, technical guidance and financial support in order to reduce safety accidents at the construction site. However, the number of disasters at construction sites is increasing every year. So analyze the results of the supervision and inspection of the Ministry of Employment and Labor, the projects related to the small-scale construction work of the Safety and Health Corporation, and the technical guidance project of the disaster prevention technology guidance organization. It is also necessary to establish an improvement plan for the disaster reduction of the small-scale construction work site for this project.

• Journal of the Korea institute for structural maintenance and inspection
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• v.4 no.2
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• pp.185-191
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• 2000

The safety problem of aged tunnels has been emphasized. For the effective maintenance, site inspection of tunnel structures and surrounding grounds are required periodically. Also, the determination of safety of tunnels is not a simple problem. So the role experienced engineer in the maintenance is very important and development of an expert system that can perform as the engineers, has been needed. In this study, from the results of numerical analysis in several case, new precision inspection rules which can substitute actual numerical analysis are determined by a commercial program FLAC and regression analysis under various parameters such as material property, lining thickness, overburden and laterial coefficients. They are added to the knowledge base to determine safety of tunnel lining. To verify the expert system, the results are compared with an existing tunnel diagnosis report. It can be concluded that the new rule are well represented the actual numerical analysis under various site conditions. Therefore it is expected that the systematic management for effective maintenance of tunnel structure will be possible.

• Nuclear industry
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• v.5 no.3 s.25
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• pp.28-33
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• 1985

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.104-105
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• 2014

Construction safety inspections come in a wide variety of types. The types of inspection are, 1) a self-checking and a periodical-checking by contractors, 2) a site inspection by Ministry of Land, Infrastructure and Transprt (MOLIT) or licensing organizations and 3) others. In this situation, there are needs to determine fuction of the safty inspection and roll of stakeholders for the inspection to avoid unnecessary duplication and serious omission. The result of this study indicates a guide line for improving of consturcion safety inspection systems as a fundamental research.

• Fire Science and Engineering
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• v.30 no.5
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• pp.124-129
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• 2016

According to the current law, on-site flame resistant-treated interior decorations should pass the flame resistant performance test through a 45 degree combustion test from the district fire department. Although a 45 degree combustion test is the most accurate method for determining the flame resistant performance, it can be unreliable when tested on unauthorized samples. To avoid unauthorized sampling, this study suggests on-site flame resistant inspection by X-ray fluorescence spectrometer. Ten types of flame resistant paint were spread on plywoods and MDFs and the components were analyzed by X-ray fluorescence spectrometer. As a result, due to a difference amounts of substances in each paint, each flame resistant paints showed its own characteristic spectrum and the contents of each substance could be determined. On-site flame resistant inspections can be used efficiently when institutional procedures are created.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.251-254
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• 2003

For improving the flow capacity of pipeline system the hydraulic inspection method was developed conducting on-site with survey of pipeline facility such as diversion work, air vent, etc. and pipe network analysis. The pipe network analysis method determine pipe diameter with trial and error. The validity of the hydraulic inspection method proved adapting on S-district pipeline system.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.717-734
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• 2022

Purpose: The purpose of this study is to effectively detect violations that occur simultaneously against Good Manufacturing Practice, which were concealed by drug manufacturers. Methods: In this study, we present an analysis framework for analyzing regulatory violation patterns using Association Rule Mining (ARM), Text Mining, and t-distributed Stochastic Neighbor Embedding (t-SNE) to increase the effectiveness of on-site inspection. Results: A number of simultaneous violation patterns was discovered by applying Association Rule Mining to FDA's inspection data collected from October 2008 to February 2022. Among them there were 'concurrent violation patterns' derived from similar regulatory ranges of two or more regulations. These patterns do not help to predict violations that simultaneously appear but belong to different regulations. Those unnecessary patterns were excluded by applying t-SNE based on text-mining. Conclusion: Our proposed approach enables the recognition of simultaneous violation patterns during the on-site inspection. It is expected to decrease the detection time by increasing the likelihood of finding intentionally concealed violations.