• Title/Summary/Keyword: Industry classification

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Comparison of Fatigue Provisions in Various Codes and Standards -Part 1: Basic Design S-N Curves of Non-Tubular Steel Members

  • Im, Sungwoo;Choung, Joonmo
    • Journal of Ocean Engineering and Technology
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    • v.35 no.2
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    • pp.161-171
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    • 2021
  • For the fatigue design of offshore structures, it is essential to understand and use the S-N curves specified in various industry standards and codes. This study compared the characteristics of the S-N curves for five major codes. The codes reviewed in this paper were DNV Classification Rules (DNV GL, 2016), ABS Classification Rules (ABS, 2003), British Standards (BSI, 2015), International Welding Association Standards (IIW, 2008), and European Standards (BSI, 2005). Types of stress, such as nominal stress, hot-spot stress, and effective notch stress, were analyzed according to the code. The basic shape of the S-N curve for each code was analyzed. A review of the survival probability of the basic design S-N curve for each code was performed. Finally, the impact on the conservatism of the design was analyzed by comparing the S-N curves of three grades D, E, and F by the five codes. The results presented in this paper are considered to be a good guideline for the fatigue design of offshore structures because the S-N curves of the five most-used codes were analyzed in depth.

Character Classification with Triangular Distribution

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.7 no.2
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    • pp.209-217
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    • 2019
  • Due to the development of artificial intelligence and image recognition technology that play important roles in the field of 4th industry, office automation systems and unmanned automation systems are rapidly spreading in human society. The proposed algorithm first finds the variances of the differences between the tile values constituting the learning characters and the experimental character and then recognizes the experimental character according to the distribution of the three learning characters with the smallest variances. In more detail, for 100 learning data characters and 10 experimental data characters, each character is defined as the number of black pixels belonging to 15 tile areas. For each character constituting the experimental data, the variance of the differences of the tile values of 100 learning data characters is obtained and then arranged in the ascending order. After that, three learning data characters with the minimum variance values are selected, and the final recognition result for the given experimental character is selected according to the distribution of these character types. Moreover, we compare the recognition result with the result made by a neural network of basic structure. It is confirmed that satisfactory recognition results are obtained through the processes that subdivide the learning characters and experiment characters into tile sizes and then select the recognition result using variances.

Numerical Range Criteria for Classification of Value Engineering Proposals based on Value Improvement Types (VE제안의 가치향상 유형별 수치적 범위기준 제시)

  • Nam, Keong-Woo;Jang, Myunghoun
    • Journal of Advanced Engineering and Technology
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    • v.11 no.4
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    • pp.287-294
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    • 2018
  • Since its introduction in Korea, design VE has widely been used as a means to enhance values in the construction industry. However, a greater emphasis is still placed on cost reduction in approach attitudes and performance evaluations on the implementation of design VE. In this regard, this study presented a performance evaluation method for cost, function, and value of VE proposals. Numerical criteria on the increase and decrease of cost and function that can classify the value enhancement type of VE proposals were proposed based on the performance evaluation method. It is expected that the use of numerical criteria for the type classification of VE proposal, and cost and performance evaluation method proposed in this study will make it possible to conduct a clear and more intuitive evaluation of VE proposal. However, it is appropriate to use the numerical criteria as a guideline to apply the new performance evaluation method for VE proposals. Therefore, it is necessary to conduct a statistical analysis with a wider range of users after the repeated application of the findings of this study, and thus to carry out research for presenting the numerical criteria for various types of users.

A Proposal of a Smart Work Environmental Management Service Model for Small Business (소규모 사업장 대상 스마트 작업환경관리 서비스 모델 제안)

  • An, Woo-Ju;Kim, Ki-Youn
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.31 no.2
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    • pp.128-137
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    • 2021
  • Objectives: The purpose of this study is to propose a smart work environment management service model that can measure and maintain work environments in real time. Methods: How existing private consignment business is being carried out was identified and a simpler method was applied to the model. Results: Common support was provided according to the Korea Standard Industrial Classification. Hazards suitable for the relevant industry classification were selected and information on safety and health education, etc. was provided. Theme-specific support provides services focusing on hazards that can be measured through applications. Hazards are evaluated by applying new standards divided into 'Good', 'Average', 'Inadequate', and 'Faulty'. Conclusions: This model is designed to help employers identify health and safety conditions in small businesses where it is difficult to hire health and safety professionals. Using the app proposed in this study, anyone can easily measure their work environment at any time.

Cat Monitoring and Disease Diagnosis System based on Deep Learning (딥러닝 기반의 반려묘 모니터링 및 질병 진단 시스템)

  • Choi, Yoona;Chae, Heechan;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.233-244
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    • 2021
  • Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).

Credit Risk Evaluations of Online Retail Enterprises Using Support Vector Machines Ensemble: An Empirical Study from China

  • LI, Xin;XIA, Han
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.8
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    • pp.89-97
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    • 2022
  • The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.

Advanced Approach for Performance Improvement of Deep Learningbased BIM Elements Classification Model Using Ensemble Model (딥러닝 기반 BIM 부재 자동분류 학습모델의 성능 향상을 위한 Ensemble 모델 구축에 관한 연구)

  • Kim, Si-Hyun;Lee, Won-Bok;Yu, Young-Su;Koo, Bon-Sang
    • Journal of KIBIM
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    • v.12 no.2
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    • pp.12-25
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    • 2022
  • To increase the usability of Building Information Modeling (BIM) in construction projects, it is critical to ensure the interoperability of data between heterogeneous BIM software. The Industry Foundation Classes (IFC), an international ISO format, has been established for this purpose, but due to its structural complexity, geometric information and properties are not always transmitted correctly. Recently, deep learning approaches have been used to learn the shapes of the BIM elements and thereby verify the mapping between BIM elements and IFC entities. These models performed well for elements with distinct shapes but were limited when their shapes were highly similar. This study proposed a method to improve the performance of the element type classification by using an Ensemble model that leverages not only shapes characteristics but also the relational information between individual BIM elements. The accuracy of the Ensemble model, which merges MVCNN and MLP, was improved 0.03 compared to the existing deep learning model that only learned shape information.

A Study on Classification Method for Web Service Attacks Information (웹서비스 공격정보 분류 방법 연구)

  • Seo, Jin-Won;Seo, Hee-Suk;Kwak, Jin
    • Journal of the Korea Society for Simulation
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    • v.19 no.3
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    • pp.99-108
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    • 2010
  • The main contents of this paper is to develope effective measures for Internet Web service attack, classifying vulnerability of Web Service by network layer and host unit and researching classification method by attack range of type of services. Using this paper, we can accumulate analyzed Web service attack information which is key information of promote Web security strengthening business, and basis of relevant security research for detect and response Web site attack which can contribute to activation information security industry.

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.493-505
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    • 2023
  • Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

Exploring the Nature of Volunteer and Leadership and Its Implications for Sport Management

  • Nam-Su KIM;Won Jae SEO
    • Journal of Sport and Applied Science
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    • v.7 no.2
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    • pp.53-60
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    • 2023
  • Purpose: This study examines the role of leaders of sport organizations from the perspectives of rank-and-file volunteers. Specifically, the study explores which factors are important in leading volunteers and how rank-and-filers interact with their leaders. Research design, data, and methodology: This study reviews a comprehensive literature on volunteer and leadership theories which are trait theory, behavior theory, and contingency theory. Given the comprehension of prior structure of knowledge on leadership, the study provides a structure of knowledge on volunteer and leadership in sport context and discusses managerial implications for leaders in sport organization. Results: With an exploration of sport leadership, this study proposes a volunteer classification model which presents four-volunteer types: professional volunteer, company volunteer, general volunteer, and school volunteer. Furthermore, this study discussed managerial implications for sport organization leaders. Conclusions: Paid employees may be prepared to accept a job and its requirements mainly due to economic benefits. Volunteers, however, do not pursue economic benefits through their activity. Different types of motivation between paid employees and volunteers bring to surface how a leader influences volunteer effectively. A conceptual volunteer clarification model could be examined in real world situations. Insights for future studies were discussed.