• Korea Petroleum Association Journal
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• no.10 s.20
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• pp.6-12
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• 1982

1.문제의 제기2.석유류가격의 구조분석 1)단계별 사격형성과정2)공장도가격의 결정요인 3.석규류가격의 국제비교 1)가격정책비교2)국별가격비교3)국내가격수준의 평가4.석유류가격정책의 전환방향 1)유가자율화실시의 타당성 2)유가자율화 실시에 따른 난제 3)합리적인 가격정책방향

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.261-269
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• 2020

This paper introduces a facility simulation system for efficient error detection of smart factories. The facility simulation system, which can infer and solve errors autonomously when analyzing the relationship between plant facilities, is one of the important technologies for constructing a smart factory with high productivity. In order to implement this autonomic control system, it is necessary to be able to identify the status of facilities and analyze the relationship between facilities through the data of factory facilities. Therefore, in this paper, we design and develop a simulation program that can detect the equipment that causes the process error when an error occurs based on the process scenario using the defined equipment status. The simulation shows that the error inference process based on the process map and facility status is more efficient than the general error inference process. This simulation program provides an intuitive view of the reasoning and resolution of facility failures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.377-383
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• 2021

Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.163-170
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• 2023

This paper introduces the semantic modeling technology for autonomous control of manufacturing facilities and status definition algorithm. With the development of digital twin technology and various ICT technologies of the smart factory, a new production management model is being built in the manufacturing industry. Based on the advanced smart manufacturing technology, the status determination algorithm was presented as a methodology to quickly identify and respond to problems with autonomous control and facilities in the factory. But the existing status determination algorithm informs the user or administrator of error information through the grid map and is presented as a model for coping with it. However, the advancement and direction of smart manufacturing technology is diversifying into flexible production and production tailored to consumer needs. Accordingly, in this paper, a technology that can design and build a factory using a semantic-based Linked List data structure and provide only necessary information to users or managers through graph-based information is introduced to improve management efficiency. This methodology can be used as a structure suitable for flexible production and small-volume production of various types.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.340-347
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• 1999

Recently, the progress of industrialization has been taken concern of material handling automation. So far, the conveyor belt has been popular for material handling. However, this system has many disadvantages such as the space, cost, In this paper, a new navigation algorithm using fuzzy is introduced. The mobile robot follows a line installed on the roads. These informations are inputted with three approximate sensors. These obtained informations are analyzed with fuzzy technique for autonomous steering. Therefore, unlike existing systems, high reliability is guaranteed under bad environment conditions. The installation and maintenance of a line is easily made at lower cost. The use of the mobile robot can be extended to materials handing purposes in manufacturing, hospital, inter-of fire documents deliveries.

• Korean journal of communication and information
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• v.79
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• pp.226-259
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• 2016

Drawing on the autonomist Marxist concepts of 'social factory', 'immaterial labour', and 'precarity', this paper discusses the changed nature of labour, life and social relations in contemporary informational capitalism. More specifically, it first traces back to the early autonomist (operasimo) theories of 'social factory' and 'class composition' and then discusses how these earlier theories were developed into the concept of 'immaterial labour' by a group of later autonomist theorists such as Paolo Virno, Maurizio Lazzarato, Micheal Hardt, and Antonio Negri. Then, it reviews how the concept of immaterial labour was taken up to understand the nature of labour in digital economy within the tradition of Cultural Studies, closely intersecting with the critiques of 'creative labour'. Finally, it discusses how the changed nature of labour is interrelated with the neoliberal labour forces transformations such as casualization of employment and increasing insecurity in employment and life, which the autonomist explores with the concept of 'precarity', the material condition of immaterial labour.

• Smart Media Journal
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• v.9 no.4
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• pp.9-16
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• 2020

Recently, various studies are being conducted to integrate Image Segmentation into smart factory industries and autonomous driving fields. In particular, Image Segmentation systems using deep learning algorithms have been researched and developed enough to learn from large volumes of data with higher accuracy. In order to use image segmentation in the autonomous driving sector, sufficient amount of learning is needed with large amounts of data and the streaming environment that processes drivers' data in real time is important for the accuracy of safe operation through highways and child protection zones. Therefore, we proposed a novel DFCN algorithm that enhanced existing FCN algorithms that could be applied to various road environments, demonstrated that the performance of the DFCN algorithm improved 1.3% in terms of "loss" value compared to the previous FCN algorithms. Moreover, the proposed DFCN algorithm was applied to the existing U-Net algorithm to maintain the information of frequencies in the image to produce better results, resulting in a better performance than the classical FCN algorithm in the autonomous environment.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.543-546
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• 2008

국내 50인 이상, 매출 100억이상 규모의 중소제조업을 위한 생산정보화는 그간 정부의 정보화 지원사업의 지원으로 중소제조업에서 평균 생산성 22%이상의 성과를 달성하였다. 그러나, 50인이하, 매출 100억 미만의 국내제조업은 약 20만개 이상이 되고 있으나, 정부에서 지원하고 있는 정보화지원사업의 혜택을 받지 못하고 있다. 그간 ERP, SCM 등과 같은 기업정보화의 경우 ASP (Application Service Provider)모델을 개발하여 적용을 시도하여 보았으나 활성화되지 못했고 생산자원 4M (Man, Machine Material & Method)정보를 실시간 처리가 요구되는 생산정보화의 경우에는 기술적 문제로 인하여 적용 시도조차 할 수 없었다. 최근 RFID/USN, 개방형 임베디드, 모바일, 차세대 인터넷 및 SOA (Service Oriented Architecture)기술의 급속한 발전으로 전세계 산재되어 있는 복수 공장의 생산자원을 중앙에서 서비스기반으로 중앙관리가 가능하게 되었다. 본 논문에서는 50인 이하, 매출 100억 미만의 군소제조업의 생산자원 4M을 유무선 센서 기술을 통하여 자율 재구성 능력 (Autonomous Reconfigurable) 기반의 원격관리가 가능한 핵심기능의 소개와 복수 공장의 다양한 생산정보화 애플리케이션을 단일 표준 플랫폼으로 구현할 수 있는 적용 모델에 대하여 설명한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.237-244
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• 2018

The Smart Factory level of manufacturing factories of SMEs now lacks a system for grasping the accurate inventory amount associated with inventory movements in managing warehouses at the basic level. Also, it is difficult to manage accurate materials for loss of data due to worker manual work and production method due to experience. In order to solve this problem, in this paper, automatic acquisition of inventory to minimize manual work to grasp workers' Inventory and improve automation is done. In the smart warehouse management system using the IoT-based autonomous mobile module, the autonomous mobile module acquires the data of the inventory storage while moving through the line. In order to grasp the material of the Inventory storage, The Camera module recognizes the name of the inventory storage. And Then, If output matches, the data measured by the sensor is transferred to the server. This data can be processed, saved in a database, and real-time inventory quantity and location can be grasped in a web-based monitoring environment for administrators. The Real-time Automatic Inventory (RAIC) systems is reduce manual tasks and expect the effects of automated inventory management systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.603-605
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• 2021

With the expansion of the indoor service-providing robot market and the electrification of automobiles, research on autonomous driving is being actively conducted. In general, in the case of outside, the location is mainly recognized through GPS, and location positioning is performed indoors using technologies such as WiFi, UWB (Ultra-Wide Band), VLP, LiDAR, and Vision. In this paper, we introduce a system for location-positioning using LED lights with different color temperatures in an indoor environment. After installing LED lights in a simulated environment such as a tunnel, it was shown that information about the current location can be obtained through the analysis of chromaticity values according to location. Through this, it is expected to be able to obtain information about the location of the vehicle in the tunnel and the movement of the device in a room such as a warehouse or a factory.