• Korea Logistics Conference
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• v.10 no.2
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• pp.83-98
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• 2002

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.4
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• pp.62-72
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• 2013

To operate an automatic picking system in distribution center with high precision and high dynamics, this paper presents a robust control scheme of a linear induction motor (LIM) using the mass estimation and disturbance force observer. The force disturbance which gives a direct influence on the control performance of LIM is estimated in real-time through the disturbance observer and compensated by a feedforward manner. To get a satisfactory performance even under the mass variation by reducing the disturbance force due to the mismatched mass during the speed transient such as the acceleration and deceleration periods, a mass estimation algorithm is proposed. A Simulink model for LIM is developed and the validity of the proposed scheme is verified through the comparative simulation studies using Matlab - Simulink.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.499-502
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• 2009

유비쿼터스 시대에서 요구하는 가장 핵심적인 요소기술 즉 인프라이다. 최근의 유통산업에서 크게 부각되고 있는 것은 지능형 매장운영과 Future Store(미래형 매장)이다. 이러한 매장의 지능화는 RFID 및 USN 등의 기술을 활용하여 적용되어 지고 있으며 또는 이로 인한 업무 프로세스의 개선을 통한 효율적인 매장운영과 고객의 쇼핑의 편리성을 제공하기 위한 서비스 개발에 초점이 맞춰져 있다. 본 논문에서는 효율적인 고객서비스를 위한 기본적인 인프라를 구축하고 고객의 참여를 통한 매장 운영의 간소화를 통하여 운영인력의 절감과 Picking 및 배달의 활성화를 통한 매장을 직접 방문하는 고객수의 감소로 인한 운영비용 감소효과와 지능형 시스템으로 인한 잉여 인력 및 비용을 고객서비스에 집중 가능하도록 하였다.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.41-45
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• 1998

본 연구는 자동물류센터에서 수요자들에게 운송하기 위한 제공품의 Order-Picking을 위한 로봇장착 적하장비를 이용할 경우의 최적 운송예약계획 수립을 위한 시뮬레이션 모델의 연구이다. 로봇장착 적하장비Order-Picking을 할 경우의 물류흐름의 효율성을 분석하고 시스템의 성능산정을 위한 시뮬레이션 모델을 개발하고 이를 이용한 최적 운송예약시스템의 운영계획을 수립하였다. 운송예약으로부터 운송량, 운반-도착지점 및 요구시산 등의 정보를 On-Line System으로 예약 받고 운송회사의 운송능력 등을 고려하여 최적운송계획을 수립하였다. 이를 위한 전산 프로그램을 개발하고 Sample 예제의 결과를 보였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.255-256
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• 2019

본 논문에서는 물체를 집기(picking) 위해 필요한 깊이 값을 특수카메라인 리얼센스를 사용하여 받아와서 2D 카메라로는 하지 못하는 로봇 팔 피킹 시스템을 구현하였다. 객체 인식은 텐서플로우 객체 검출 라이브러리를 사용하여 정확도를 높였고, ROS 기반의 rviz, moveit, gazebo 등의 패키지를 사용하여 아두이노와 통신하며 로봇팔 하드웨어로 인식된 객체를 피킹하는 시스템을 구현하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.1
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• pp.82-86
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• 2009

This work is design of clock and data recovery circuit using system clock. This circuit is composed by PLL(Phase Locked Loop) to make system clock and data recovery circuit. The data recovery circuit using 1/4-rate phase picking Detector helps to reduce clock frequency. It is advantageous for high speed PLL. It can achieve a low jitter operation. The designed CDR(Clock and data recovery) has been designed in a standard $0.18{\mu}m$ 1P6M CMOS technology and an active area $1{\times}1mm^2$.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.67-78
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• 2021

The number of domestic e-commerce transactions has been breaking its own record by an annual average growth rate of over 20% based on volume for the past 5 years. Due to the rapid increase in e-commerce market, retail companies that have difficulty meeting consumers in person are in fierce competition to take the lead in the last mile service, which is the only point of contact with customers. Especially in the delivery area, where competition is most intense, the role of the fulfillment center is very important for service differentiation. It must be capable of fast product preparation ordered by consumers in accordance with the delivery service level. This study focuses on the order picking system for rapid order processing in the fulfillment center as an alternative for companies to gain competitive advantage in the e-commerce market. A mixed integer programming model was developed and implemented to optimize the stock replenishment in order picking facilities. The effectiveness was scientifically and objectively verified by simulation using the actual operation process and data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3566-3582
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• 2019

In intelligent warehouse picking system, the allocation of tasks has an important influence on the efficiency of the whole system because of the large number of robots and orders. The paper proposes a method to solve the task allocation problem that multi-robot task allocation problem is transformed into transportation problem to find a collision-free task allocation scheme and then improve the capability of task processing. The task time window and the power consumption of multi-robot (driving distance) are regarded as the utility function and the maximized utility function is the objective function. Then an integer programming formulation is constructed considering the number of task assignment on an agent according to their battery consumption restriction. The problem of task allocation is solved by table working method. Finally, simulation modeling of the methods based on table working method is carried out. Results show that the method has good performance and can improve the efficiency of the task execution.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• Geophysics and Geophysical Exploration
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• v.5 no.3
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• pp.193-198
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• 2002

In crosswell ray tomography, the resultant velocity structure could be affected by source static, first-arrival-time picking errors, convergence to a local minimum due to an inappropriate initial velocity model and etc. In the paper, I propose an algorithm that automatically correct the souce static among these error-prone factors. The algorithm automatically corrects source static using the picking times' differences along the source direction. The application of the algorithm to real data produces a quite satisfactory result. Tile algorithm seems to be helpful for users to apply the souce static correction consistently and to acquire accurate velocity structure.