• Title/Summary/Keyword: Data Process SW

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Preliminary Investigation for Apply of e-Government Framework at the Construction CALS System (건설CALS시스템에 전자정부 표준프레임워크 적용을 위한 사전 고찰)

  • Yang, Sung-Hoon;Kim, Nam-Gon
    • The Journal of the Korea Contents Association
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    • v.13 no.11
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    • pp.433-440
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    • 2013
  • The Ministry of Land, Infrastructure and Transport was developed the Construction CALS system for improvement of the construction economy. Construction CALS system is consist by Construction Portal System, Construction Management System, Construction Authorization and Permission System, Compensation Management System, Facility Maintenance Management System and has utilized at construction site of more than 900. Ministry of Land, Infrastructure and Transport and related researcher was proposed method of various function improvements for usability of the system. However, the proposed method was expanded the problems like increase of system management cost and development cost with decrease of data process rate. The problem was increases because has added of only service function without modify of software structure to the system on each different platform base. One of the methods for solving problems is to apply the e-Government framework and then integrated the different platform. The purpose of this paper is analyse of the applicability and efficiency of e-Government framework to the construction CALS system. For that was analyzed the e-Government standard framework and the developments case. And then was verified about the adaption possibility and efficiency by use the Function Point tool.

Performance Modeling of an EPC Information Service System

  • Kim, So-Jung;Kang, Yong-Shin;Son, Kyung-Won;Lee, Yong-Han;Rhee, Jong-Tae;Hong, Sung-Jo
    • Industrial Engineering and Management Systems
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    • v.9 no.3
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    • pp.285-293
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    • 2010
  • To obtain visible and traceable information from the supply chain, HW/SW standards for the EPC global network, which process electronic product code (EPC) data read from Radio frequency identification (RFID) tags, are regarded as the de facto industry standard. Supply chain participants install information service systems and provide logistics information to partners by following the EPCglobal architecture framework. Although quality of service (QoS) is essential for providing dependable and scalable services as pointed out by Auto-ID Lab, only a few models for the performance analysis of QoS-related work have been developed in the context of EPC information service systems. Specifically, doing so allows alternative design choices to be tested in an easy and cost-effective manner and can highlight potential performance problems in designs long before any construction costs are incurred. Thus, in this study we construct a model of an EPC information service system for the purposes of performance analysis and designing a dependable system. We also develop a set of building blocks for analytical performance models. To illustrate how the model works, we determine the characteristics of an EPC information service system and then select a combination of these proven modeling concepts. We construct a performance model that considers the response time and shows how to derive meaningful performance values. Finally, we compare the analytical results to measurements of the EPC information service system.

Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises (제조업 특성을 반영한 스마트공장 진단모델 개발 및 중소기업 맞춤형 적용사례)

  • Kim, Hyun-Deuk;Kim, Dong-Min;Lee, Kyung-Geun;Yoon, Je-Whan;Youm, Sekyoung
    • 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.

An Efficient Graph Algorithm Processing Scheme using GPUs with Limited Memory (제한된 메모리를 가진 GPU를 이용한 효율적인 그래프 알고리즘 처리 기법)

  • Song, Sang-ho;Lee, Hyeon-byeong;Choi, Do-jin;Lim, Jong-tae;Bok, Kyoung-soo;Yoo, Jae-soo
    • The Journal of the Korea Contents Association
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    • v.22 no.8
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    • pp.81-93
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    • 2022
  • Recently, research on processing a large-capacity graph using GPUs has been conducting. In order to process a large-capacity graph in a GPU with limited memory, the graph must be divided into subgraphs and then processed by scheduling subgraphs. In this paper, we propose an efficient graph algorithm processing scheme in GPU environments with limited memory and performance evaluation. The proposed scheme consists of a graph differential subgraph scheduling method and a graph segmentation method. The bulk graph segmentation method determines how a large-capacity graph can be segmented into subgraphs so that it can be processed efficiently by the GPU. The differential subgraph scheduling method schedule subgraphs processed by GPUs to reduce redundant transmission of the repeatedly used data between HOST-GPUs. It shows the superiority of the proposed scheme by performing various performance evaluations.

Models of Database Assets Valuation and their Life-cycle Determination (데이터베이스 자산 가치평가 모형과 수명주기 결정)

  • Sung, Tae-Eung;Byun, Jeongeun;Park, Hyun-Woo
    • The Journal of the Korea Contents Association
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    • v.16 no.3
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    • pp.676-693
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    • 2016
  • Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.

Analyzing the effects of artificial intelligence (AI) education program based on design thinking process (디자인씽킹 프로세스 기반의 인공지능(AI) 교육 프로그램 적용 효과분석)

  • Lee, Sunghye
    • The Journal of Korean Association of Computer Education
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    • v.23 no.4
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    • pp.49-59
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    • 2020
  • At the beginning of the discussion of AI education in K-12 education, the study was conducted to develop and apply an AI education program based on Design Thinking and analyze the effects of the AI education programs. In the AI education program, students explored and defined the AI problems they were interested in, gathered the necessary data to build an AI model, and then developed a project using scratch. In order to analyze the effectiveness of the AI education program, the change of learner's perception of the value of AI and the change of AI efficacy were analyzed. The overall perception of the AI project was also analyzed. As a result, AI efficacy was significantly increased through the experience of carrying out the project according to the Design Thinking process. In addition, the efficacy of solving problems with AI was influenced by the level of use of programming languages. The learner's overall perception of the AI project was positive, and the perceptions of each stage of the AI project (AI problem understanding and problem exploration, practice, problem definition, problem solving idea implementation, evaluation and presentation) was also positive. This positive perception was higher among students with high level of programming language use. Based on these results, the implications for AI education were suggested.

The Development of Software Teaching-Learning Model based on Machine Learning Platform (머신러닝 플랫폼을 활용한 소프트웨어 교수-학습 모형 개발)

  • Park, Daeryoon;Ahn, Joongmin;Jang, Junhyeok;Yu, Wonjin;Kim, Wooyeol;Bae, Youngkwon;Yoo, Inhwan
    • Journal of The Korean Association of Information Education
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    • v.24 no.1
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    • pp.49-57
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    • 2020
  • The society we are living in has being changed to the age of the intelligent information society after passing through the knowledge-based information society in the early 21st century. In this study, we have developed the instructional model for software education based on the machine learning which is a field of artificial intelligence(AI) to enhance the core competencies of learners required in the intelligent information society. This model is focusing on enhancing the core competencies through the process of problem-solving as well as reducing the burden of learning about AI itself. The specific stages of the developed model are consisted of seven levels which are 'Problem Recognition and Analysis', 'Data Collection', 'Data Processing and Feature Extraction', 'ML Model Training and Evaluation', 'ML Programming', 'Application and Problem Solving', and 'Share and Feedback'. As a result of applying the developed model in this study, we were able to observe the positive response about learning from the students and parents. We hope that this research could suggest the future direction of not only the instructional design but also operation of software education program based on machine learning.

A Study on Tire Surface Defect Detection Method Using Depth Image (깊이 이미지를 이용한 타이어 표면 결함 검출 방법에 관한 연구)

  • Kim, Hyun Suk;Ko, Dong Beom;Lee, Won Gok;Bae, You Suk
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.5
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    • pp.211-220
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    • 2022
  • Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

Analysis of Competency-Based In-service Training Programs for Informatics Teachers (정보교사의 역량에 기반한 소프트웨어교육 교원 직무 연수과정 분석)

  • Ock, Jihyun;Ahn, Seongjin
    • The Journal of Korean Association of Computer Education
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    • v.21 no.1
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    • pp.43-50
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    • 2018
  • The 2015 Revised National Curriculum emphasizes software education to develop creative and convergent talents in preparation of the Fourth Industrial Revolution. Accordingly, it is necessary to develop competency-based training programs for informatics teachers in a rapidly changing educational environment. In this background, this study selects a framework to analyze the content of in-service training for informatics teachers through review of previous studies. By analyzing the current training programs to strengthen competencies required for informatics teachers in secondary schools, the study aims to develop implications for future in-service training programs. To this end, the study conducted a questionnaire survey of experts who participated in the development of in-service training textbooks and consulted them, then analyzed the elements of competency-based training program content and the relative importance of each competency element using the analytical hierarchy process (AHP). According to the results of the analysis, the content was relatively concentrated on the competency of "Understanding and Reconstructing the National Curriculum" required for general and informatics teachers as well, which accounted for 47% of all, or 7 hours out of the total 15 hours. In contrast, the content structure lacked the competency of highly relative importance by competency element "Establishing and Using Teaching-Learning Strategies for Informatics," which took up the highest portion of 27%. These findings will be used as basic data for understanding and reflecting the areas that fall short of the development of in-service training programs for informatics teachers.

A Proposal for Mobile Gallery Auction Method Using NFC-based FIDO and 2 Factor Technology and Permission-type Distributed Director Block-chain (NFC 기반 FIDO(Fast IDentity Online) 및 2 Factor 기술과 허가형 분산원장 블록체인을 이용한 모바일 갤러리 경매 방안 제안)

  • Noh, Sun-Kuk
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.129-135
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    • 2019
  • Recently, studies have been conducted to improve the m-commerce process in the NFC-based mobile environment and the increase of the number of smart phones built in NFC. Since authentication is important in mobile electronic payment, FIDO(Fast IDentity Online) and 2 Factor electronic payment system are applied. In addition, block-chains using distributed raw materials have emerged as a representative technology of the fourth industry. In this study, for the mobile gallery auction of the traders using NFC embedded terminal (smartphone) in a small gallery auction in which an unspecified minority participates, password-based authentication and biometric authentication technology (fingerprint) were applied to record transaction details and ownership transfer of the auction participants in electronic payment. And, for the cost reduction and data integrity related to gallery auction, the private distributed director block chain was constructed and used. In addition, domestic and foreign cases applying block chain in the auction field were investigated and compared. In the future, the study will also study the implementation of block chain networks and smart contract and the integration of block chain and artificial intelligence to apply the proposed method.