• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.39-49
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• 2018

In the satellite operation phase, a ground station should continuously monitor the status of the satellite and sends out a tasking order, and a satellite should transmit data acquired in the space to the Earth. Therefore, the communication between the satellites and the ground stations is essential. However, a satellite and a ground station located in a specific region on Earth can be connected for a limited time because the satellite is continuously orbiting the Earth, and the communication between satellites and ground stations is only possible on a one-to-one basis. That is, one satellite can not communicate with plural ground stations, and one ground station can communicate with plural satellites concurrently. For such reasons, the efficiency of the communication schedule directly affects the utilization of the satellites. Thus, in this research, considering aforementioned unique situations of spacial communication, the mixed integer programming (MIP) model for the optimal communication planning between multiple satellites and multiple ground stations (MS-MG) is proposed. Furthermore, some numerical experiments are performed to verify and validate the mathematical model. The practical example for them is constructed based on the information of existing satellites and ground stations. The communicable time slots between them were obtained by STK (System Tool Kit), which is a well known professional software for space flight simulation. In the MIP model for the MS-MG problems, the objective function is also considered the minimization of communication cost, and ILOG CPLEX software searches the optimal schedule. Furthermore, it is confirmed that this study can be applied to the location selection of the ground stations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1059-1065
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• 2014

Wind turbine system can obtain the maximum wind energy using torque control under the rated wind speed, and wind turbine power is controlled as the rated power using pitch control over the rated wind speed. In this paper, we present a method for wind turbine pitch controller using neural networks. The purpose of the pitch control is to control generator speed and power in the above rated wind speed. To improve the neural network pitch controller, the difference between a rated and current speed of generator has been used for another input of neural networks as well as wind speed. Error back-propagation algorithm is used for training the neural network pitch controller and simulation and Matlab/Simulink is used for verifying that this system is controlled well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.31-39
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• 2022

The Army, Navy, and Air Force are currently making various efforts to apply defense IoT technology by reflecting the characteristics of each military. However, there are concerns that comprehensive collection, management, and analysis may be limited because each military has no overlapping system or guaranteed interoperability of data, and there are inefficient aspects in terms of using and investing a limited defense budget. In this study, evaluation items and priorities for pilot projects were selected by applying Delphi technique and AHP method to determine which projects are preferentially effective when commonly applied in terms of Army, Navy, and Air force. As a result of the analysis, the project basis and driving force, project feasibility, performance and ripple effect, redundancy and connection were identified in the order of IoT-based small detachment units and unmanned base construction, intelligent smart unit, smart ground ammunition depot, and smart training management system. According to the comprehensive results reflecting the weights of each evaluation item, the fact that small detachment units and unmanned base construction project are recognized as the first project to be applied to the Army, Navy, and Air Force is a valid approach to be effective while each military is burdened with personnel management because of the reduction of manpower. Through the research results, it is expected that the direction of application to the policy of the defense IoT project can be confirmed in terms of efficient use of limited budgets.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.234-242
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• 2010

3D CAD technology has been extended to a medical area including dental clinic beyond industrial design. The 2D images obtained by CT(Computerized Tomography) and MRI(Magnetic Resonance Imaging) are not intuitive, and thus the volume rendering technique, which transforms 2D data into 3D anatomic information, has been in practical use. This paper has focused on a method and its implementation for forming 3D geometric surface model from laminated CT images of the pubis. The implemented system could support a dental clinic to observe and examine the status of a patient's pubis before implant surgery. The supplement of 3D implant model would help dental surgeons settle operation plans more safely and confidently. It also would be utilized with teaching materials for a practice and training.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.107-112
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• 1998

In this paper, we propose a new paradigm (NEW_BP) to be capable of overcoming limitations of the traditional backpropagation(OLD_BP). NEW_BP is based on the method of conjugate gradients with the normalized direction vectors and computes step size through the linear search which may be characterized by order statistics and golden section. Simulation results showed that NEW_BP was definitely superior to both the stochastic OLD_BP and the deterministic OLD_BP in terms of accuracy and rate of convergence and might sumount the problem of local minima. Furthermore, they confirmed us that stagnant phenomenon of training in OLD_BP resulted from the limitations of its algorithm in itself and that unessential approaches would never cured it of this phenomenon.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.253-257
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• 2004

Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• Journal of Fisheries and Marine Sciences Education
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• v.3 no.1
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• pp.21-26
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• 1991

The Korean economic condition needs continuous development of the marine product industries basically, and for this purpose a study on the education and training system of the technical manpower for this field is required. Moreover, the sea and its resources are not only to be utilized these days but also to be conserved for our descendants. To achieve this goal, the national support and the people's understanding on the marine product industries are very important at the first, and also the fisheries education must be activated to educate and train the technical manpower who will engage in this industrial field in the future. Especially it is necessary to develop and operate the most appropriate curricula drawn up inconsideration of each local characteristics for the fisheries education at the middle schools and high schools in Korea.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.316-326
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• 2012

Purpose: In this paper, a Design for Six Sigma(DFSS) methodology based on DMADV(Define-Measure-Analyze-Design-Verify) roadmap is presented. Methods: DFSS tools are given for each DMADV phase which is suitable for the aircraft development process. A cost reduction case study of a navigation simulation is demonstrated. Results: DFSS roadmap are presented with implementation tools for each phase. Conclusion: We propose a DFSS methodology which can benefit the design and development personnel to implement DFSS not only in aircraft industry but also in other order-based industries in general.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.171-175
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• 2000

Neural networks are in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.