• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.21-35
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• 2020

Due to the coronavirus pandemic and diplomatic disputes, governments are actively developing a policy to revitalize·reshore manufacturing and to diversify international cooperations. In order to develop such a policy, it is very important to compare and analyze domestic·international geospatial information. Over the decade, the US·EC governments have conducted a series of national researches to build data-based tools that can monitor·analyze regional geospatial information driven by government R&D investments. In the case of the EC system, it can compare geospatial information in domestic and international(including Korea) regions. Compared to US·EC cases, Korean examples of national researches with available data analplatform need future improvements. Current study is investigating an automated analysis methodologies using "National Institute of Science and Technology Information (NTIS)" DB, which was national security data until recently. Research on data-mining regional geospatial information can contribute to support policy fields that need to discover new issues in response to unexpected social problems such as recently faced corona and trade disputes.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.10-10
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• 2023

본질적으로 복잡하고 다양한 특성을 가지는 우리나라(도시, 농어촌, 도서산간, 섬 등)의 물 공급 시스템은 생활수준의 향상, 기후변화 및 가뭄위기, 소비환경 중심의 요구와 한정된 수자원을 잘 활용하기 위한 운영 및 관리가 매우 복잡하다. 이로 인한 수자원 고갈과 가뭄위기 등에 관련한 대책 및 방안으로 대체수자원인 지하수 활용방안들이 제시되고 있다. 따라서, 물 관리 시스템과 관련한 디지털 기술은 오늘날 플랫폼과 디지털 트윈의 도입을 통해 네트워크와 가상현실 세계의 연결이 통합되어진 4차 산업혁명 사업이 현실화되고 있다. 물 관리 시스템에 사용된 새로운 디지털 기술 "BDA(Big Data Analytics), CPS(Cyber Physical System), IoT(Internet of Things), CC(Cloud Computing), AI(Artificial Intelligence)" 등의 성장이 증가함에 따라 가뭄대응 위기와 도시 지하수 물 순환 시스템 운영이 증가하는 소비자 중심의 수요를 충족시키기 위해서는 지속가능한 지하수 공급을 효과적으로 관리되어야 한다. 4차 산업혁명과 관련한 기술성장이 증가함으로 인한 물 부문은 시스템의 지속가능성을 향상시키기 위해 전체 디지털화 단계로 이동하고 있다. 이러한 디지털 전환의 핵심은 데이터에 관한 것이며, 이를 활용하여 가치 창출을 위해서 "Digital Groundwater Technology/Twin(DGT)"를 극대화하는 방식으로 제고해야 한다. 현재 당면하고 있는 기후위기에 따른 가뭄, 홍수, 녹조, 탁수, 대체수자원 등의 수자원 재해에 대한 다양한 대응 방안과 수자원 확보 기술이 논의되고 있다. 이에 따른 "물 순환 시스템"의 이해와 함께 문제해결 방안도출을 위하여 이번 "기획 세션"에서는 지하수 수량 및 수질, 정수, 모니터링, 모델링, 운영/관리 등의 수자원 데이터의 플랫폼 동시성 구축으로부터 역동적인 "DGT"을 통한 디지털 트윈화하여, 지표수-토양-지하수 분야의 특화된 연직 프로파일링 관측기술을 다각도로 모색하고자 한다. "Digital Groundwater(DG)"는 지하수의 물 순환, 수량 및 수질 관리, 지표수-지하수 순환 및 모니터링, 지하수 예측 모델링 통합연계를 위해 지하수 플랫폼 동시성, ChatGPT, CPS 및 DT 등의 복합 디지털화 단계로 나가고 있다. 복잡한 지하환경의 이해와 관리 및 보존을 위한 지하수 네트워크에서 수량과 수질 데이터를 수집하기 위한 스마트 지하수 관측기술 개발은 큰 도전이다. 스마트 지하수 관측기술은 BD분석, AI 및 클라우드 컴퓨팅 등의 디지털 기술에 필요한 획득된 데이터 분석에 사용되는 알고리즘의 복잡성과 데이터 품질에 따라 영향을 미칠 수 있기 때문이다. "DG"는 지하수의 정보화 및 네트워크 운영관리 자동화, 지능화 등을 위한 디지털 도구를 활용함으로써 지표수-토양층-지하수 네트워크 통합관리에 대한 비전을 만들 수 있다. 또한, DGT는 지하수 관측센서의 1차원 데이터 융합을 이용한 지하수 플랫폼 동시성과 디지털 트윈을 연계할 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• Smart Media Journal
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• v.9 no.1
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• pp.75-83
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• 2020

Compensation services that are indispensable during large-scale public utilities projects have been gradually increasing with the recent increase in construction, but there are no systematic compensation services due to the complicated procedures and manual work. For this reason, various problems such as construction period delays due to various complaints, corruption in compensation work, and impossible to trace the history of compensation data in the past are emerging. In this paper, in order to solve this problem, in-depth interviews and questionnaires were conducted to find out the problems of each compensation status. Based on this, 3 core technologies and 10 technical needs based on ICT were selected to improve the compensation work by deriving STEEP analysis and Issue Tree. The three core technologies are big data-based decision-making and prediction technology, advanced measurement technology, and open cloud-based compensation platform technology. In order to introduce the derived technologies to the institutions in charge of compensation, the possibility of technology diffusion by project operators was suggested based on the results of the current status of informatization by institution. Based on the core technology derived from this paper, it is necessary to make a prototype that can be advanced in compensation work and apply it to each institution and analyze the effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.578-584
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• 2015

In this study a moving platform for a mobile robot that can be traveling with a full automatic standing arm was developed. Conventional mobile robots generally may equip 4 wheels or 3 wheels with a caster wheel or independent driven wheels and have good statistic stability. When a mobile robot travels on a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it is sometimes physically impossible for the robot to go through the crossroad because of the size limit. The upright running mobile robot changes its posture to the upright posture which has a small planar area and is able to go through the crossroad. The upright control which was manually performed step by step before such as sequences of uprighting (returning), checking, and balancing, is now automated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.331-337
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• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.229-236
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• 2019

IOT middleware is required to play a pivotal role in interpreting, managing, and controlling data information of Internet devices (sensors, etc.). In particular, the root industry has different process flows for different industries, and there are various data processing requirements for each company. Therefore, a general purpose IOT middleware is needed to accommodate this. The IOT middleware structure proposed by this paper is a plug-in that can be used as an engine part for middleware basic processes such as communication, data collection, processing and service linkage, We propose a flexible and effective smart process for root industry. In addition, we propose a method to strengthen prevention and security against tampering, deodorization, etc. through encryption of network data between middleware plug - in and related service layer. We propose a system that will be developed as an IOT middleware platform that is specialized in the root industry so that it can be extended in various network protocols such as MQTT, COAP, XAMP.

• Korea Trade Review
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• v.48 no.3
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• pp.243-262
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• 2023

This study provides a systematic review of smart trade contracts, examining the research trends and theoretical background of utilizing smart contracts and blockchain technology for the digitalization and automation of trade contracts. Smart trade contracts are a concept that applies the automated contract system based on blockchain to trade-related transactions. The study analyzes the technical and legal challenges and proposes solutions. The technical aspect covers the development of smart contract platforms, scalability and performance improvements of blockchain networks, and security and privacy concerns. The legal aspect addresses the legal enforceability of smart contracts, automatic execution of contract conditions, and the responsibilities and obligations of contract parties. Smart trade contracts have been found to have applications in various industries such as international trade, supply chain management, finance, insurance, and energy, contributing to the ease of trade finance, efficiency of supply chains, and business model innovation. However, challenges remain in terms of legal regulations, interaction with existing legal frameworks, and technological aspects. Further research is needed, including empirical studies, business model innovation, resolution of legal issues, security and privacy considerations, standardization and collaboration, and user experience studies to address these challenges and explore additional aspects of smart trade contracts.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.1-9
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• 2024

The introduction of smart factory digital twins is a concept that has already been proposed to increase productivity in the manufacturing industry through CPS(Cyber Physics System), and has been applied to specific industrial process stages or partially introduced in stages where simulation is required. However, with the recent development of the 4th Industrial Revolution technology, it is receiving attention again along with XR (Extended Reality) technology. However, because there are not many effective cases, this study analyzed the devices, equipment, and technology of the manufacturing process to build a digital twin applying digital threads and synchronized signals and information to control, remote control, and produce intelligent process automation equipment. A platform capable of analyzing information was proposed and developed. Through this, we designed and built an XR content service platform that can support artificial intelligence and developed it to enable control, remote control, and analysis of production information. A possible platform was proposed and developed. We hope that this study will be helpful in conducting research on many cases, and in the future, expanded research on increasing productivity in each part of the process and production is needed through intelligent models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.650-661
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• 2020

The digital transformation of the 4th industrial revolution is leading to changes and innovations in the global economy. Various countries are focusing on reviving their manufacturing industries and economic recovery through smart factories. The purpose of this study is to empirically identify technological determinants for the successful implementation of the smart factory and to verify teose effects on manufacturing operations and the firms' operational/environmental performances. Five factors, including sensor network, platform technology, information system, intelligent automation, and safety, were defined as core technologies. The SEM analysis results of 157 small and medium-sized manufacturing firms that have implemented smart factories are as follows. First, sensor network, platform technology, and information system had significant effects on smart manufacturing operations. Second, smart manufacturing operations have improved firm performance. This study is valuable in that it has confirmed the effectiveness of government-funded projects and systemized key technologies for implementing smart factories. Meanwhile, it is helpful for practitioners to support an efficient and effective decision-making for the new adoption.