• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.709-714
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• 2005

The purpose of this research is to verify the strategic fitness and relevance of the hub port strategy by SCM in Northeast Asia and to find a method to be a hub-port with a competitive edge. The fitness of the hub port development strategy is analysed by the structural equation model. The essential results of the research show that minimizing lead time from arrival of ship to inland transport and maximizing logistic services of each stage are important to provide optimal logistic service. And value-added port supply chain strategy is highly co-related with all the parts of port operation system, port transport system, distribution park and port information system. It shows that: various value added logistic service activity is more important than lowing cost; inland multimodal system should be rightly connected; distribution park should be connected to industry park to be a port cluster; and port information system should be developed.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.166-172
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• 1999

Weapon system is defined as a combination of primary system and logistics support system which are evaluated by capability and operational availability respectively. Weapon system developer thought that primary system was weapon system and also only primary system was important. Recent comparison of total life cycle cost showed that logistics support system was proved to be more important than primary system. However, until now no systematic approach to logistics support system development have applied in the area of developing support system and much money was exhausted by wrong logistics support system. We need to construct a universal metric for effectiveness of logistics support system and to cut out whatever activities or support elements which do not contribute to the metrics. This study describes a new approach under the name function approach to logistics support system development and also classifies five factors of failure frequency, stock out of frequency, administrative delay time, active repair time and logistic delay time that have influence on operational availability of logistics support system.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.56-63
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• 2008

Many advanced nations have been developing the next generation logistic systems to effectively deal with gradually increased logistic flows over the world. Particularly, dual mode trailer(DMT) systems are significantly focused as a new alternative transportation which basically provides integrating of the land and railroad services. This paper presents new driving mechanism for DMT systems using the hydraulic pressure cylinder systems. Such is mechanically composed of supporting and rotating parts independently, which are mostly important for whole system performance. We analyze feasible operational problem occurred in driving mechanism from the conventional DMT systems and compare our proposed deign specification with the Modalohr DMT system to demonstrate its reliability and practicability.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.397-406
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• 2022

This paper presents an autonomous mobile robot (AMR) system and operation algorithms for logistic and factory facilities without magnet-lines installation. Unlike widely used AMR systems, we propose an EKF-based loosely coupled fusion of LiDAR measurements and visual markers. Our method first constructs occupancy grid and visual marker map in the mapping process and utilizes prebuilt maps for precise localization. Also, we developed a waypoint-based navigation pipeline for robust autonomous operation in unconstrained environments. The proposed system estimates the robot pose using by updating the state with the fusion of visual marker and LiDAR measurements. Finally, we tested the proposed method in indoor environments and existing factory facilities for evaluation. In experimental results, this paper represents the performance of our system compared to the well-known LiDAR-based localization and navigation system.

• 대한상한금궤의학회지
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• v.14 no.1
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• pp.41-50
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• 2022

Objective : The purpose of this study is to explore the most suitable machine learning model algorithm for Shanghanlun diagnostic system classification using natural language processing (NLP). Methods : A total of 201 data items were collected from 『Shanghanlun』 and 『Clinical Shanghanlun』, 'Taeyangbyeong-gyeolhyung' and 'Eumyangyeokchahunobokbyeong' were excluded to prevent oversampling or undersampling. Data were pretreated using a twitter Korean tokenizer and trained by logistic regression, ridge regression, lasso regression, naive bayes classifier, decision tree, and random forest algorithms. The accuracy of the models were compared. Results : As a result of machine learning, ridge regression and naive Bayes classifier showed an accuracy of 0.843, logistic regression and random forest showed an accuracy of 0.804, and decision tree showed an accuracy of 0.745, while lasso regression showed an accuracy of 0.608. Conclusions : Ridge regression and naive Bayes classifier are suitable NLP machine learning models for the Shanghanlun diagnostic system classification.

• International Commerce and Information Review
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• v.18 no.1
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• pp.29-54
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• 2016

The purpose of this study is to future research directions for the e-logistics area in Korea. To this end this study collected journal papers published in the five Korean academic journals for the last 15 years. The contents analysis of the collected papers includes research topic, research strategies and methods used in the studies. The analysis suggests the four trends: First, management of E-logistics has been more actively studied than other topics; second, "E-commerce research journal" has published E-logistics related studies more than other journals; third, empirical research paradigm is dominant in this research area; last, questionnaire survey is a method most frequently used in this area. E-logistics research is attracting researchers' attention but more efforts are needed to diversify research topics and methods.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.46-50
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• 1998

본 연구는 최근에 국내기업의 물류비용절감을 위한 노력의 일환으로 추진되고 있는 적정 물류장비의 선정을 위한 시뮬레이션 모델의 개발이다. 본 연구에서는 제조공장에서 소비자들에게 공급되는 2단계 물류시스템에서 물류재고와 운송수단을 고려하여 최소 물류비용의 운송대안선정을 위한 의사결정을 할 수 있도록 개발하였다. 이를 위하여 2가지의 시뮬레이션모델의 전산프로그램을 개발하고 응용사례를 통하여 출력을 예시하였다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.179-187
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• 2009

The national boundary's meanings turn to weak according to advent of Global enterprises. The place for design a product and marketing are separated to actual market. R&D is to the area where the knowledge activity is well, and low skilful product assembling is to the place the low wage is acceptable. It shows that the importance of net work structure. From early 90's, production system is diversified to markets where with the consumer as the central as multifarious items and creation new demands through consumer's participation into manufacturing process. This phenomenon show that logistics structures adapt to demand of technical variation, and the development of e-business with VAN(:value added network) and EDI(:Electronic data interchange) prove it. This study tried to analyze utilitarian assay about systems those land, sea, air logistics through documents research, and this study also present the direction of logistics system of airline company and goal of development on the based to the model of domestic airline company accordingly.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.624-632
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• 2015

A self-diagnostic monitoring system is a system that has the ability to measure various physical quantities such as temperature, pressure, or acceleration from sensors scattered over a mechanical system such as a power plant, in order to monitor its various states, and to make a decision about its health status. We have developed a self-diagnostic monitoring system for an air-operated valve system to be used in a nuclear power plant. In this study, we have tried to improve the self-diagnostic monitoring system to increase its reliability. We have implemented three different machine learning algorithms, i.e., logistic regression, an artificial neural network, and a support vector machine. After each algorithm performs the decision process independently, the decision-making module collects these individual decisions and makes a final decision using a majority vote scheme. With this, we performed some simulations and presented some of its results. The contribution of this study is that, by employing more robust and stable algorithms, each of the algorithms performs the recognition task more accurately. Moreover, by integrating these results and employing the majority vote scheme, we can make a definite decision, which makes the self-diagnostic monitoring system more reliable.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.55-62
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• 2008

This is to prevent accidents that can be caused during the process of hospital logistics and accidents in relation to the traceability of medical wastes. And this is also to set up the logistic management system of medical wastes is hospital where the safety of patients shall to regard as the first priority. through these case studies effective operating plans shall be provided.