• Spatial Information Research
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• v.13 no.4 s.35
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• pp.355-364
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• 2005

Vector data sets (e.g. maps) are currently major sources of displaying, querying, and identifying locations of spatial features in a variety of applications. Especially in mobile environment, the needs for using spatial data is increasing, and the relative large size of vector maps need to be smaller. Recently, there have been several studies about vector map compression. There was clustering-based compression method with novel encoding/decoding scheme. However, precedent studies did not consider that spatial data have to be updated periodically. This paper explores the problem of existing clustering-based compression method. We propose an adaptive approximation method that is capable of handling data updates as well as reducing error levels. Experimental evaluation showed that when an updated event occurred the proposed adaptive approximation method showed enhanced positional accuracy compared with simple cluster based compression method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.14-23
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• 1996

Scheduling jobs effectively under consideration of actual loads on machines is one of the most complicated tasks in production control. The complexity of the finite capacity scheduling often makes the conventional methods of industrial engineering fail. As an alternative, Knowledge-based approaches to job-shop scheduling have been evolved recently. This paper presents a blackboard- based scheduling expert system which combines knowledge-based scheduling with interactive scheduling. It is shown to be possible to generate the feasible schedule within a reasonable time. Flexible reaction management is also possible while keeping the changes in the generated schedule to the minimal and adjusting the schedule to tardy operations or working environmental changes. The system is equipped with a rule base with heuristics for handling conflicted event. A case study applying the implemented system is described.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.619-622
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• 2004

For recent years, hacking is in the trends of making excessive traffic unnecessarily to obstruct the service by getting a system's performance down. And we can also see systems paralyzed in service ability due to the flash crowds of normal traffic to a popular website. This is an important problem certainly solved in the point of QoS guarantee for the clients. It is known that the former is DDoS(Distributed Denial of Service) attack and the latter is FE(Flash Event). These two are samely anomalous traffic because these make excessive congestion on the network or system and downgrade the system's service ability. In this paper, we propose a scheme for protecting the system against anomalous traffic and for guaranteeing the QoS. For this, a server records and maintains the information of clients accessed more than one time before when it is in normal condition. When it falls into the congestion, the records are used for filtering the spoofed IP. We send and receive the ICMP request/reply packet to know whether the IP is spoofed. And we also propose for applying the object spliting of CDN to guarantee the QoS in the initial FE situation.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.354-364
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• 2017

This study tries to evaluate the effect of ITT introduction in Busan New Port. The study used the estimation model of the number of vehicles required in accordance with the backhaul rate. The model used big data, COPINO e-document for one year in 2015. COPINO recorded the event such as truck ID, container ID, ATA, damage etc when truck arrived at gate. The study finds important information to estimate the required number of trucks for handling current ITT containers in Busan New Port: Daily throughput in Busan New Port is 1650 vans, especially night throughput recorded peak level in 1800 hours to 2400 hours, the throughput between adjacent terminals recorded high, i.e PNIT to HPNT. The transportation capability for 6 hours between terminals is from 4 vans to 7 vans. The required trucks are estimated 89 currently without considering peak level. If we change the back haul rate from current 20% to 40%, 60% and 80%, how much would the cost drop? It was discovered that, if it is raised to 40%, 60% and 80%, the number of vehicle required will be reduced from 89 (current) to 76, 65 and 59. It was also discovered that the total savings will reduce down to 12%, 25% and 34%.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1298-1305
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• 2018

The use of System-on-Chip (SoC) solutions in the design of on-board data handling systems is an important step towards further miniaturization in space. However, the Total Ionizing Dose (TID) and Single Event Effects (SEE) characterization of these complex devices present new challenges that are either not fully addressed by current testing guidelines or may result in expensive, cumbersome test configurations. In this paper we report the test setups, procedures and results for TID testing of a SoC microcontroller both using standard $^{60}Co$ and low-energy protons beams. This paper specifically points out the differences in the test methodology and in the challenges between TID testing with proton beam and with the conventional gamma ray irradiation. New test setup and procedures are proposed which are capable of emulating typical mission conditions (clock, bias, software, reprogramming, etc.) while keeping the test setup as simple as possible at the same time.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.72-81
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• 2023

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.368-371
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• 2020

반도체 제조시설의 효율성을 위해 대부분의 현장에서는 물류 자동화 시스템 (AMHS, Automated Material Handling System)을 도입하여 운영하고 있다. OHT(Overhead Hoist Transfer)는 반도체 공정에서 주로 활용되는 Monorail 컨베이어 형태의 자동 반송 시스템의 일종으로 작업물을 들고 제조라인 위에 설치된 레일을 따라 자율적으로 이동하는 방식으로 운영된다. 도체 물류 시스템의 계층적인 구조적 특징과 고가의 재료를 다루고, 외부유출이 어려운 실제 공정 현장, 실험 환경의 시간, 공간적 구축 등의 현실적 특징 때문에 반도체 제조 공정의 자동화 물류시스템에 대한 모델링 및 시뮬레이션을 통한 연구의 필요성이 대두되고 있다. 본 논문에서는 OHT를 효율적으로 제어하기 위해 DEVS(Discrete Event System Specifications) 형식론을 기반으로 OHT 시스템 모델링 및 시뮬레이션 설계 방법을 제안한다. 이를 위해 반도체 제조 시스템의 전반적인 물류 과정에 대해 분석하고, DEVS 형식론에 대해 연구하며, 이를 바탕으로 반도체 물류 시스템을 위한 모델링 및 시뮬레이션을 설계하였으면, 실험을 통해 제안된 모델리 반도체 물류 시스템 시뮬레이션을 수행할 수 있음을 보인다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.68-75
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• 2023

In an automotive plant, an automated storage and retrieval system (ASRS) synchronizes material handling flows from a part production line to an auto-assembly line. The part production line transfers parts on small-/large-sized pallets. The products on pallets are temporarily stored on the ASRS, and the ASRS retrieves the products upon request from the auto-assembly line. Each ASRS aisle is equipped with narrow-/wide-width racks for two pallet sizes. An ASRS aisle with narrow-/wide-width racks improves both storage space utilization and crane utilization while requiring delicate ASRS aisle design, i.e., the locations of the narrow-/wide-width racks in an ASRS aisle, and proper operation policies affect the ASRS performance over demand fluctuations. We focus on operation policies involving a common storage zone using wide-width racks for two pallet sizes and a storage-retrieval job-change for a crane based on assembly-line batch size. We model a discrete-event simulation model and conduct extensive experiments to evaluate operation policies. The simulation results address the best ASRS aisle design and suggest the most effective operation policies for the aisle design.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.63-70
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• 2002

The main subject to become a hub pen is automation The automated container terminal has already operated in advanced pons and it bas been planned for the basic planning and operation design in domestic case. The key of automated container terminal is effective operation of both ATC(automated transfer crane) and AGV(automated guided vehicle) which is automated handling equipments. This is essential to productivity of automated container terminal. This study suggests the moat optimal method of equipment operation in order to minimize loading time using each three types of effective AT operation methods and AGV dispatching rules in automated container terminals. As the automated equipment operation causes unexpected deadlocks or interferences, it should be proceeded on event-based real tine. Therefore we propose the most effective ATC operation methods and AGV dispatching rules in this paper. The various states occurred in real automated container terminals are simulated to evaluate these methods. This experiment will show the most robust automated equipment operation method on various parameters(the degree of yard re-marshaling, the number of containers and the number of AGVs).