• Applied Chemistry for Engineering
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• v.30 no.3
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• pp.384-388
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• 2019

In winter season, the snow and ice accretion on the bottom of the high speed railway rolling stock and boogie part has fallen at a high speed from the ballast section (gravel section for the transmission of the rolling stock load received by sleepers and fixing sleepers), causing the gravel to be scattered, thereby damaging the railway rolling stock structures and facilities. In order to solve these problems, the gravel scattering prevention net, manual de-icing, and movable hot air machine were used, but their efficiency was low. For the more efficient de-icing than ever before, an optimum material for de-icing fluid for high speed railway rolling stock was developed by evaluating the ice melting capacity, kinematic viscosity, evaporation of the material used as a chemical de-icing fluid. Four kinds of organic acid salts (sodium formate, sodium acetate, potassium formate and potassium acetate) and two different alcohols (propylene glycol, glycerol) were used as evaluation materials. Potassium formate, potassium acetate, and propylene glycol had similar ice melting capacities in the indoor test, but the propylene glycol showed the best ice melting capacity in spraying the system simulation test. This is because the kinematic viscosity of propylene glycol was 2.989029 St, which is higher than those of other materials therefore, it could stay longer on the ice and de-icing. In addition, potassium formate and potassium acetate were difficult to be used since the crystals precipitated and adversely affected the appearance of the rolling stock. The propylene glycol is the most optimum as an de-icing fluid for the high speed railway rolling stock.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.555-556
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• 2023

본 논문에서는 제조/물류 기업 등 제품(물품) 이동 작업 시 효율적인 경로 제공을 위한 경로 최적화 기법을 제안한다. 이 기법은 업무지원 시스템(MES, ERP, WMS 등)이 구축되어있는 기업을 대상으로 공간정보와 업무지원 시스템에 저장되는 제품 데이터를 기준 정보로 하며, 다익스트라(Dijkstra), 개미 집단 알고리즘(Ant Colony Algorithm, ACO)등 경로 탐색 알고리즘을 적용하여 문제를 해결하고자 한다. 공간정보는 공장(현장)의 레이아웃(Layout)과 제품이 적재/출하되는 렉(Rack) 등의 위치 정보가 포함되고, 업무지원 시스템에서 제품의 현재 위치, 공정 상태, 등록 시간, 제품 크기 등을 사용한다. 제안하는 기법은 상기 기준 정보를 경로 탐색 알고리즘에 적용하여 적재/출하, 공정 이동, 보관 장소 변경 등 제품의 위치가 변경되는 경우에 경로를 최적화할 수 있는 기법을 제안한다. 제품 이동 작업은 대부분 노동력에 의존하는 작업으로 경로 최적화 기법을 제안함으로써, 인력 비용 감소와 향후 로봇 기반의 제품 이동 작업에도 적용하여 자동화된 작업효과를 가져다 줄 것으로 기대한다.

• Korean Chemical Engineering Research
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• v.44 no.3
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• pp.314-318
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• 2006

Direct formic acid fuel cells (DFAFCs) are potential alternative power sources for portable devices such as cellular phone, personal digital assistants (PDA) and laptop computers. In this study, we developed the catalysts for great performance of fuel cell, and investigated their characteristics by using EDS and SEM. Pt-Pd catalysts showed uniform size and homogeneous distribution. As the content of palladium increased, the performance of DFAFC increased. Pd black showed the greatest performance among the five catalysts tested. Also, Pt-Pd (1:1) catalyst had an excellent maximum power density of $120mW/cm^2$. As the operating temperature increased, fuel cell performance was increased due to a reaction activity increases of catalyst. But, temperature had only a slight effect on the performance of fuel cell in the best activity range of membrane.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.51-58
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• 2011

One of the objectives of research on routing methods in wireless sensor networks is maximizing the energy life of sensor nodes that have limited energy. In this study, we tried to even energy use in a wireless sensor network by giving a weight to the transition probability of ACS(Ant Colony System), which is commonly used to find the optimal path, based on the amount of energy in a sensor and the distance of the sensor from the sink. The proposed method showed improvement by 46.80% on the average in energy utility in comparison with representative routing method GPSR (Greedy Perimeter Stateless Routing), and its residual energy after operation for a specific length of time was 6.7% more on the average than that in ACS.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.4
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• pp.413-428
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• 2013

In this study, Ant Colony Algorithm(ACO) was used for optimal model. ACO which are metaheuristic algorithm for combinatorial optimization problem are inspired by the fact that ants are able to find the shortest route between their nest and food source. For applying the model to water distribution systems, pipes, tanks(reservoirs), pump construction and pump operation cost were considered as object function and pressure at each node and reservoir level were considered as constraints. Modified model from Ostfeld and Tubaltzev(2008) was verified by applying 2-Looped, Hanoi and Ostfeld's networks. And sensitivity analysis about ant number, number of ants in a best group and pheromone decrease rate was accomplished. After the verification, it was applied to real water network from S water treatment plant. As a result of the analysis, in the Two-looped network, the best design cost was found to $419,000 and in the Hanoi network, the best design cost was calculated to $6,164,384, and in the Ostfeld's network, the best design cost was found to $3,525,096. These are almost equal or better result compared with previous researches. Last, the cost of optimal design for real network, was found for 66 billion dollar that is 8.8 % lower than before. In addition, optimal diameter for aged pipes was found in this study and the 5 of 8 aged pipes were changed the diameter. Through this result, pipe construction cost reduction was found to 11 percent lower than before. And to conclusion, The least cost design model on water distribution system was developed and verified successfully in this study and it will be very useful not only optimal pipe change plan but optimization plan for whole water distribution system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.704-710
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• 2017

Our research team is developing a 6-DOF manipulator that is adequate for the narrow workspace of press forming processes. This paper addresses the task sequence optimization methods for the manipulator to minimize the task-finishing time. First, a kinematic model of the manipulator is presented, and the anticipated times for moving among the task locations are computed. Then, a mathematical model of the task sequence optimization problem is presented, followed by a comparison of three meta-heuristic methods to solve the optimization problem: an ant colony system, simulated annealing, and a genetic algorithm. The simulation shows that the genetic algorithm is robust to the parameter settings and has the best performance in both minimizing the task-finishing time and the computing time compared to the other methods. Finally, the algorithms were implemented and validated through a simulation using Mathworks' Matlab and Coppelia Robotics' V-REP (virtual robot experimentation platform).

• Knowledge Management Research
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• v.23 no.1
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• pp.89-109
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• 2022

Due to COVID-19 and soaring participation of individual investors, large-scale transactions exceeding system capacity limits have been reported frequently in the capital market. The capital market IT systems, which the impact of system failure is very critical, have encountered unexpectedly tremendous transactions in 2020, resulting in a sharp increase in system failures. Despite the fact that many companies maintained large-scale system capacity planning policies, recent transaction influx suggests that a new approach to capacity planning is required. Therefore, this study developed capital market IT system capacity planning models using machine learning techniques and analyzed those performances. In addition, the performance of the best proposed model was improved by using sentiment index that can promptly reflect the behavior of investors. The model uses empirical data including the COVID-19 period, and has high performance and stability that can be used in practice. In practical significance, this study maximizes the cost-efficiency of a company, but also presents optimal parameters in consideration of the practical constraints involved in changing the system. Additionally, by proving that the sentiment index can be used as a major variable in system capacity planning, it shows that the sentiment index can be actively used for various other forecasting demands.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1127-1136
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• 2004

This paper proposes a novel multicasting algorithm, called ANMAS (Ad hoc Network Multicasting with Ant System), for Mobile Ad hoc Network (MANET). The algorithm utilizes the indirect communication method of the ants via 'pheromone' to effectively obtain dynamical topology change information, generating safer multicasting paths, and adapts the well-known CBT (Core Based Tree) multicasting algorithm into the ANMAS framework with proper modificiations to make 'tolerable' multicasting group in the MANET environment. We show the efficiency and the effectiveness of ANMAS via simulation studies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.148-152
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• 2006

제품(또는 서비스)을 생산하기 위하여 여러 순차적인 작업이 수행되어야 하는 환경에서 생산자원(기계 또는 작업자)에게 얼마만큼의 요소작업을 배정하는가를 결정하는 작업배정(Work Assignment) 문제는 중요한 의사결정 문제이다. 일반적으로 이용하는 작업배정 방식은 각 생산자원에게 가급적 균등한 작업량을 배정하는 라인밸런싱(LB: Line Balancing) 전략이다. 그러나 LB 방식은 작업자의 작업속도 차이나 시스템의 여러 가지 변동 상황(기계고장, 품질문제 등)의 고려 없이 작업을 배정하기 때문에 실제로는 계획된 밸런싱효율을 달성하기 어렵다. Bucket Brigade (BB)는 이러한 문제에 대응하기 위한 새로운 작업배정 방법으로 제시되고 있다. BB는 개미의 협력작업 개념을 바탕으로 하는 분산 자율적인 작업배정 방법이다. 본 발표에서는 생산 및 물류시스템에서 BB의 적용 가능성과 문제점을 논의하고, 시뮬레이션을 통하여 여러 작업 환경에서 BB의 수행도를 분석한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.234-235
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• 2012

본 논문에서는 개미 집단 최적화(Ant Colony Optimization, ACO) 알고리즘을 적용한 감속률에 따른 동적 상황인식 경로 선정 방법을 제안한다. 최근 ITS(Intelligent Transportation Systems)의 개발과 함께 차량용 내비게이션의 실시간 교통 정보를 이용하는 수요가 급증하면서, 경로탐색의 중요성이 더욱 가속화되고 있다. 현재 차량용 내비게이션은 멀티미디어 및 정보통신 기술의 결합과 함께 다양한 기능 및 정보를 사용자에게 제공하고 있으며, 이러한 경로탐색 알고리즘은 교통시스템, 통신 네트워크, 운송 시스템 등 다양한 분야에 적용되고 있다. 본 논문에서는 감속률에 따른 동적 상황인식 경로 선정 방법을 제안함으로써, 최단 시간 및 최소 비용의 정보를 제공해 줄 뿐만 아니라 교통정체로 인한 사회적 비용 감소의 효과를 가져다 줄 것으로 기대한다.