• Title/Summary/Keyword: Industry classification

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Identification and Analysis of the Legal Status of International Maritime Organization Instruments

  • Nam, Dong
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.3
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    • pp.421-428
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    • 2021
  • Identifying which international maritime legal instruments are mandatory or recommendatory is complicated task even for maritime regulatory bodies. Although International Maritime Organization (IMO) had tried to ease the complexity by adopting guidelines on uniform wordings for making reference to other instruments in IMO parent conventions, there has still been some confusion identifying the mandatory status of IMO instruments. The aim of this study was to map out a step-based guideline to resolve the complexity of the mandatory status of IMO instruments to the maximum extent possible. This study reviewed the history of IMO rule-making process to find the root cause of the problem, then analyzed the approaches of regulatory enforcement bodies to check the practices. In conclusion, readers are directed to find such information as to legal status of IMO instruments and an improvement is proposed to enhance the transparency of information sharing for maritime industry to make better informed decisions.

Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification (혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석)

  • Jeong, Jae-Seung;Ju, Hyunsu;Cho, Chi-Hyun
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1512-1523
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    • 2022
  • Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

A study of creative human judgment through the application of machine learning algorithms and feature selection algorithms

  • Kim, Yong Jun;Park, Jung Min
    • International journal of advanced smart convergence
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    • v.11 no.2
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    • pp.38-43
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    • 2022
  • In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

Development of Deep Learning based waste Detection vision system (Deep Learning 기반의 폐기물 선별 Vision 시스템 개발)

  • Bong-Seok Han;Hyeok-Won Kwon;Bong-Cheol Shin
    • Design & Manufacturing
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    • v.16 no.4
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    • pp.60-66
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    • 2022
  • Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

IMPLEMENTATION OF PRODUCT DATA MANAGEMENT SYSTEM FOR DESIGN OF BRIDGE STRUCTURES

  • Jin-Suk Kang;Seung-Ho Jung;Yoon-Bum Lee;Kwang-Myong Lee
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.1318-1323
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    • 2009
  • In recent years, dramatic advances in information technology have motivated the construction industry to improve its productivity. Computer-based information technology includes Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), Computer-Aided Manufacturing (CAM), Enterprise Resource Planning (ERP), Digital Mock-Up (DMU) and Product Data Management (PDM). Most construction industries are trying to apply these technologies for quality improvement, reduction of construction time and cost. PDM is very useful for managing data and process related to product design and manufacturing. PDM system has various functions such as drawing and engineering document management, product structure and structure modification management, part classification management, workflow management, and project management. In this paper, PDM system was applied to the design of steel-concrete composite girder bridge. To make a practical guidance for PDM implementation to bridge design, the procedure for its implementation was presented. Consequently, this paper could be useful to enhance the efficiency of bridge design.

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A Ensemble Classification Method of Korean Standard Industry Code for Corporate Business Analysis (기업 비지니스 분석을 위한 한국표준산업코드 앙상블 분류)

  • Kyo-Joong Oh;Ho-Jin Choi;Jinwon Kim;Wonseok Cha;Ilgu Kim
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.477-479
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    • 2022
  • 본 논문에서는 기업 비즈니스 분석을 위해 한국표준산업분류에 근거하여 국내 사업체의 산업군을 분류하는 앙상블 분류 모델 구축 방법론을 제시한다. 기업 평가 및 보고서 자동화 시스템 구축을 위해 기업의 재무제표 정보, 기업등록부와 같은 신고 정보, 사업체 조사 정보에 포함된 텍스트 정보를 이용하여, 각 기업이 속해 있는 산업군 정보를 분석해야 하며, 이를 통해 동일한 산업군에 속해 있는 다른 기업에 대한 현황 파악 및 비교 등 비즈니스 정보를 분석할 수 있다.

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BETTER INPUTS FOR KNOWLEDGE MANAGEMENT INFORMATION SYSTEMS: KNOWLEDGE SHARING MODELING AND THE INCENTIVES SYSTEM DESIGN

  • S. Ping Ho;Yaowen Hsu;Szu-Wei Lo
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.564-568
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    • 2005
  • Recently, Knowledge Management (KM) has been applied to construction industry. Surprising, there is few studies that address the most fundamental problem in KM: people may prefer not to share their knowledge so as to preserve their intellectual or unique values in the organization. Without the premise of each individual's willingness to share knowledge, there will be no valuable input for the IT system and, thus, no knowledge management at all. This paper aims to model the behavioral dynamics of knowledge sharing and to design an incentive system that may facilitate knowledge sharing for construction companies. In this paper, a game-theory based model will be developed, and the framework for designing an incentive system will be proposed according to the model.

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Development of Framework for Digital Map Time Series Analysis of Earthwork Sites (토공현장 디지털맵 시계열 변화분석 프레임워크 기술개발)

  • Kim, Yong-Gun;Park, Su-Yeul;Kim, Seok
    • Journal of KIBIM
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    • v.13 no.1
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    • pp.22-32
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    • 2023
  • Due to the increased use of digital maps in the construction industry, there is a growing demand for high-quality digital map analysis. With the large amounts of data found in digital maps at earthwork sites, there is a particular need to enhance the accuracy and speed of digital map analysis. To address this issue, our study aims to develop new technology and verify its performance to address non-ground and range mismatch issues that commonly arise. Additionally, our study presents a new digital map analysis framework for earthwork sites that utilizes three newly developed technologies to improve the performance of digital map analysis. Through this, it achieved about 95% improvement in analysis performance compared to the existing framework. This study is expected to contribute to the improvement of the quality of digital map analysis data of earthworks.

Productivity Analysis for Asphalt Paving by Means of Simulation Technique for Site Conditions (조건별 세부공종 시뮬레이션을 통한 아스팔트 포장공사의 생산성 분석)

  • Kim, Yujin;Lee, Sumin;Noh, Jaeyun;Han, Seungwoo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2021.05a
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    • pp.34-35
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    • 2021
  • Currently, the Korean Smart Construction Corporation aims to stimulate overseas expansion of smart construction technology centered on Expressway development. In addition, the integrated classification system of construction information with Work Breakdown Structure(WBS) is currently being established in Korea, but its application to the construction industry is limited. In this study, data generation using simulation is carried out at the lowest level of WBS presented by the Korea Expressway Corporation, and detailed process productivity is predicted by site conditions.

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Automated Methodology for Linking BIM Objects with Cost and Schedule Information by utilizing Geometry Breakdown Structure (GBS)

  • Lee, Kwangjin;Jung, Youngsoo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.637-638
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    • 2015
  • There has been growing interests in life-cycle project management in the construction industry. A lot of attention is given to Building Information Modeling (BIM) which stores and uses a variety of construction information for the life cycle of project management. However, due to the additional workload arising from BIM, its expected effects versus its input costs are still under discussion in practice. As an attempt to address this issue, one of previous studies suggested an automated linking process by developing Standard Classification Numbering System (SCNS) and Geometry Breakdown Structure (GBS) to enhance the efficiency of integration process of BIM objects, cost, and schedule. Though SCNS and GBS facilitates identifying all different dataset, making object sets and linking schedule activities still needs to be manually done without having an automated tool. In this context, the purpose of this paper is to develop and validate a fully automated integration system for 3D-objects, cost, and schedule. A prototype system for single family homes (Hanok) was developed and tested in order to verify its efficiency.

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