• Title/Summary/Keyword: Inspection Cost

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Image-Based Automatic Bridge Component Classification Using Deep Learning (딥러닝을 활용한 이미지 기반 교량 구성요소 자동분류 네트워크 개발)

  • Cho, Munwon;Lee, Jae Hyuk;Ryu, Young-Moo;Park, Jeongjun;Yoon, Hyungchul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.6
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    • pp.751-760
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    • 2021
  • Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

Research Trends on External Event Identification and Screening Methods for Safety Assessment of Nuclear Power Plant (원자력발전소 안전성 평가를 위한 외부사건 식별 및 선별 방법 연구동향)

  • Kim, Dongchang;Kwag, Shinyoung;Kim, Jitae;Eem, Seunghyun
    • Journal of the Society of Disaster Information
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    • v.18 no.2
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    • pp.252-260
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    • 2022
  • Purpose: As the intensity and frequency of natural hazards are increasing due to climate change, external events that affecting nuclear power plants(NPPs) may increase. NPPs must be protected from external events such as natural hazards and human-induced hazards. External events that may occur in NPPs should be identified, and external events that may affect NPPs should be identified. This study introduces the methodology of identification and screening methods for external events by literature review. Method: The literature survey was conducted on the identification and screening methods of external events for probabilistic safety assessment of NPPs. In addition, the regulations on the identification and screening of external events were investigated. Result: In order to minimize the cost of external event impact analysis of nuclear power plants, research on identifying and screening external events is being conducted. In general, in the identification process, all events that can occur at the NPPs are identified. In the screening process, external events are selected based on qualitative and quantitative criteria in most studies. Conclusions: The process of identifying and screening external events affecting NPPs is becoming important. This paper, summarize on how to identify and screen external events for a probabilistic safety assessment of NPPs. It is judged that research on bounding analysis and conservative analysis methods performed in the quantitative screening process of external events is necessary.

An Experimental Study to Establish a System for Vertifying the Insulation Performance of Buildings (건축물의 단열성능 검증 시스템 구축을 위한 실험적 연구)

  • Kim, Hyun-Jin;Choi, Se-Jin
    • Journal of the Korea Institute of Building Construction
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    • v.21 no.3
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    • pp.203-211
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    • 2021
  • Recently, the insulaton design standards for reducing the energy use of buildings have been strengthened. Althoug insulation work is the most cost-effective method for reducing the primary energy consumption per unit area of a building, there are no evaluation criteria for insulation performance at the time of construction and completion inspection. The purpose of this study is to provide objective data by establishing a standard for an analysis method and a method for easily experimenting with the exterior wall thermal transmittance of an apartment house using a thermal transmittance measuring device(TESTO 435). For the exterior wall of the test subject, the specific heat per unit area exceeded 20kJ/(m2·K), and the data at the end point suitable for ISO 9869-1 were analyzed by the average method. The measured values of the thermal transmittance for 3 consecutive days converged within +5% of the desing value, and the standard deviation of the thermal transmittance by day decreased in the order of 1-Day > 3-Day > 2-Day. The standard deviation of the thermal transmittance by time period decreased in the order of 00:00~24:00 < 19:00~07:00 < 00:00~07:00. The measured value of the thermal transmittance for the time perion of 00:00 to 07:00 per day almost coincided with an error of -3% to + 2% compare to the desing value.

Grain Aging and Sensory Changes influenced by Milling and Packaging in Rice Storage (저장미 도정과 포장에 따른 고미화 및 식미 변화)

  • Lee, Ho-Jin;Kim, Tae-Hoon;Jeon, Woo-Bang
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.36 no.3
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    • pp.266-270
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    • 1991
  • Storage in the form of brown or milled rice saves space and cut cost rather than storage of rough rice, the common way of grain storage in Korea. But, brown or milled rice may be more susceptable to grain aging and sensory change than rough rice. Rice stored in government warehouse for 20 months after harvest was hulled into brown or milled rice and packaged with kraft paper bag (paper package), polyprophylen (PP package), and polyethylene (PE package). Then, after those rice packages were stored under room condition for one year, we investigated germinability, fat acidity, and sensory change to determine milling and packaging effects. Germinability of rough and brown rice was decreased significantly after long-term storge. In germination rate, Chucheong cultivar was lower than Milyang #23, brown rice was lower than rough rice, but there was no differences within packaging materials. TTC test which had a significant correlation with germinability can be used as a handy procedure for predicting grain germination. Fat acidity was increased as the order of rough < milled < brown rice in terms of milling, and PP < paper < PE package in terms of packaging materials. Especially, storage of brown rice increased fat acidity above 30 mg KOH, indicating one of characteristics of grain aging. To prevent from high fat acidity it was necessary to store in forms of rough grain with paper or PP packaging and milled rice with paper, or PP, or PE packaging. In sensory test of stored grain, eating quality in brown rice was the worst because of acidification of fatty acid. Also, eating quality of stored grain became worse as fat acidity increased.

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A Study on the Prediction Models of Used Car Prices for Domestic Brands Using Machine Learning (머신러닝을 활용한 브랜드별 국내 중고차 가격 예측 모델에 관한 연구)

  • Seungjun Yim;Joungho Lee;Choonho Ryu
    • Journal of Service Research and Studies
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    • v.13 no.3
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    • pp.105-126
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    • 2023
  • The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

Relative Importance Analysis of Management Level Diagnosis for Consignee's Personal Information Protection (수탁사 개인정보 관리 수준 점검 항목의 상대적 중요도 분석)

  • Im, DongSung;Lee, Sang-Joon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.2
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    • pp.1-11
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    • 2018
  • Recently ICT, new technologies such as IoT, Cloud, and Artificial Intelligence are changing the information society explosively. But personal information leakage incidents of consignee's company are increasing more and more because of the expansion of consignment business and the latest threats such as Ransomware and APT. Therefore, in order to strengthen the security of consignee's company, this study derived the checklists through the analysis of the status such as the feature of consignment and the security standard management system and precedent research. It also analyzed laws related to consignment. Finally we found out the relative importance of checklists after it was applied to proposed AHP(Analytic Hierarchy Process) Model. Relative importance was ranked as establishment of an internal administration plan, privacy cryptography, life cycle, access authority management and so on. The purpose of this study is to reduce the risk of leakage of customer information and improve the level of personal information protection management of the consignee by deriving the check items required in handling personal information of consignee and demonstrating the model. If the inspection activities are performed considering the relative importance of the checklist items, the effectiveness of the input time and cost will be enhanced.

Development of Analysis Method for Cholesterol in Infant Formula by Direct Saponification (직접 검화법을 이용한 조제분유의 콜레스테롤 분석법 개발)

  • Kim, Jin-Man;Park, Jung-Min;Yoon, Tae-Hyung;Leem, Dong-Gil;Yoon, Chang-Yong;Jeong, Ja-Young;Jeong, In-Seek;Kwak, Byung-Man;Ahn, Jang-Hyuk
    • Food Science of Animal Resources
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    • v.31 no.6
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    • pp.944-951
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    • 2011
  • An improved cholesterol analysis method was developed for powdered infant formula by gas chromatographic separation after liquid-liquid extraction and partition. In the official Korea Food Standard method for cholesterol analysis, the water phase and solvent phase were not well separated in the case of emulsified foods such as powdered infant formulas and baby foods. For the rapid and simple sample preparation method, an optimized direct saponification condition was established for heating temperature, heating time, and KOH concentration. From the results, the optimum conditions were as follows: heating temperature $90^{\circ}C$, heating time 60 min, and 16 M KOH 10 mL for a 2 g infant formula sample; improved separation condition for gas chromatography was as follows: the initial oven condition was $250^{\circ}C$ for 25 min, the oven temperature was increased to $290^{\circ}C$ by $10^{\circ}C$/min ratio, and finally the oven temperature remained at $290^{\circ}C$for 9 min. The developed method could be implemented for the study of cholesterol, providing the advantages of reduced inspection time and cost in emulsified foods such as infant formula.

A Study on the Improvement of Capital Gains Tax Act through the Analysis of the Precedents of the cases of the lawsuit - Focusing on the transfer of inherited and donated property - (행정소송판례 검토를 통한 양도소득세법 개선방안 - 상속·증여받은 자산의 양도를 중심으로 -)

  • Yu, Soon-Mi;Kim, Hye-Ri
    • Management & Information Systems Review
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    • v.38 no.4
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    • pp.61-78
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    • 2019
  • When calculating gains from transfers of assets inherited or donated, the value recognized at the market price as of the date of inheritance or acquisition is recognized as the actual transaction value at the time of acquisition. However, Precedents for the appeal for review by the NTS, the request for adjudgment by the Tax Tribunal(TT) and the request of examination by the Board of Audit and Inspection of Korea(BAI) and the cases of the lawsuit have not shown a consistent results on how much such a the actual transaction value will be measured. This study investigates the operating state of the current tax appeal system using the statistical data of the TT, NTS, and BAI and cases of the lawsuit from 2008 to 2017, and suggests the Improvement of Capital Gains Tax Act on the transfer of inherited and donated property. As a result, total number of requested cases has diminished because cases of the pre-assessment review and the reconsideration appeal by the NTS have decreased steadily over the past decade, while the cases of the lawsuit and the administrative trials(the request for adjudgment by the TT, the appeal for review by the NTS, and the request of examination by the BAI) have been steadily increasing. Also This study found that more than 40% of the complainants proceeded with the cases of the lawsuit proceedings in disagreement with the disposition of tax dissatisfaction under the administrative trials. In addition, Even though the retrospective appraisal price is not recognized as the market price due to the strict interpretation of the tax regulations, it can be seen that it is interpreted as a more expanded concept in the application of the market price than the government office or the tax judge. Therefore, according to the precedents of the cases lawsuit, it is necessary to establish a regulation on the recognition of retroactive appraisal value.

Applying Meta-model Formalization of Part-Whole Relationship to UML: Experiment on Classification of Aggregation and Composition (UML의 부분-전체 관계에 대한 메타모델 형식화 이론의 적용: 집합연관 및 복합연관 판별 실험)

  • Kim, Taekyung
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.99-118
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    • 2015
  • Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

Steel Plate Faults Diagnosis with S-MTS (S-MTS를 이용한 강판의 표면 결함 진단)

  • Kim, Joon-Young;Cha, Jae-Min;Shin, Junguk;Yeom, Choongsub
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.47-67
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    • 2017
  • Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.