• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.79.3-79.3
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• 2019

GMACS is one of the first light instruments for the Giant Magellan Telescope (GMT). The development of GMACS control software follows Agile software development process, and the design of the software is based on the Unified Model Language (UML). In this poster, we present the architecture of the GMACS software and the development processes. As an example of the software development, we show the software of the Slit Mask Exchange Mechanism Prototype (SMEM-P) which is part of the GMACS Device Control Package (DCP).

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.237-250
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• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.150-153
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• 2022

This paper reports a technique that automatically extracts object shapes through Dense-Net, and subsequently, detects the objects using Mask R-CNN in a manufacturing site, in which workers and objects are mixed. It is based on the customized factory dataset by targeting workers, machines, tools, control boxes, and products as the objects. Mask R-CNN supports multi-object recognition as a well-known object recognition method, while Dense-Net effectively extracts a feature from multiple and overlapping objects. After immediate implementation using the two technologies, the object is naturally extracted from a still image of the manufacturing site to describe image. Afterwards, the result is planned to be used to detect workers' abnormal behavior by adding a label on the objects.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.97-102
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• 2020

Multi-Channel Switch ICs for IoT have integrated several solid state structure low ON-resistance bi-directional relay MOS switches with level shifter to drive high voltage and they should be independently controlled by external serialized logic control. These devices are designed for using in applications requiring high-voltage switching control by low-voltage control signals, such as medical ultra-sound imaging, ink-jet printer control, bare board open/short and leakage test system using Kelvin 4-terminal measurement method. This paper describes implementation of analog switch control block and its verification using Field programmable Gate Array (FPGA) test pattern generation. Each block has been implemented using Verilog hardware description language then simulated by Modelsim and prototyped in a FPGA board. Compare to conventional IC, The proposed architecture can be applied to fields where multiple entities need to be controlled simultaneously in the IoT environment and the proposed pattern generation method can be applied to test similar types of ICs.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.371-376
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• 2007

This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.148-152
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• 2007

In recent days, on account of the cultural development and the improvement of citizen's consciousness level, it is the real situation that the construction of small-scaled Multi-Purpose Hall where various cultural events could be performed, is on increasing. However, since the most of Multi-Purpose Hall had been designed and built up without any consideration on Acoustic Factor, many problems are on occurring thereat. Since those small-scaled Multi-Purpose Hall have been mostly used with the finishing material which contains a high degree of Acoustic Absorption indiscreetly, both diffusion and reflection of sound are not establishing properly, and because thereverberation of sound is very low, in case of musical performance by musical instrument, its sound hears too arid and stiff, there occurs some acoustic defect such as it becomes difficult for music appreciation with sufficient timbre, so that the capability improvement on the matter is urgently requiring situation. Therefore, this Study has tried to seize the satisfaction level about the small-scaled Multi-Purpose Hall after betterment of the acoustic performance by appraise the acoustic condition of the Hall, using Auralization Technique that can experience Virtual Acoustic Field regarding to the small-scaled Multi-Purpose Hall as its object. It is deemed that such research result could be practically used as the useful material which enables to bring a reduction effect of construction cost as well asenhancement of the acoustic performance through its presupposition?control on the acoustic problem when construction or renovation of other similar small-scaled Multi-Purpose Hall in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.637-643
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• 2010

In this study, we developed a Portable Multi-sensor System, which consists of a video camera, a GPS/MEMS IMU and a UMPC to acquire video images and position/attitude data. We performed image georeferencing based on the bundle adjustment without ground control points using the acquired data and then evaluated the effectiveness of our system through the accuracy verification. The experimental results showed that the RMSE of relative coordinates on the ground point coordinates obtained from our system was several centimeters. Our system can be efficiently utilized to obtain the 3D model of object and their relative coordinates. In future, we plan to improve the accuracy of absolute coordinates through the rigorous calibration of the system and camera.

• ETRI Journal
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• v.27 no.2
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• pp.140-152
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• 2005

In this paper, we present design features, implementation, and validation of a satellite simulator subsystem for the Korea Multi-Purpose Satellite-2 (KOMPSAT-2). The satellite simulator subsystem is implemented on a personal computer to minimize costs and trouble on embedding onboard flight software into the simulator. An object-oriented design methodology is employed to maximize software reusability. Also, instead of a high-cost commercial database, XML is used for the manipulation of spacecraft characteristics data, telecommand, telemetry, and simulation data. The KOMPSAT-2 satellite simulator subsystem is validated by various simulations for autonomous onboard launch and early orbit phase operations, anomaly operation, and science fine mode operation. It is also officially verified by successfully passing various tests such as the satellite simulator subsystem test, mission control element system integration test, interface test, site installation test, and acceptance test.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.103-110
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• 2003

With significant development of power electronics technology, the proliferation of nonlinear loads such as static power converters has deteriorated power quality in power transmission and distribution systems. Notably, voltage harmonics resulting from current harmonics produced by the nonlinear loads have become a serious problem in many countries. Many photovoltaic power generation systems installed in building systems have harmonics that are the worst object for distribution systems as a utility interactive system, and it tends to spread out continuously. Proposed and implemented in this paper is a multi-function inverter control strategy that allows a shunt active filter function to the power inverter of the photovoltaic power generation system established on a building system. The effectiveness of the proposed system is demonstrated through the simulation of a hypothetical power system using PSCAD/EMTDC.