• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.3
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• pp.257-265
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• 2000

Brushless DC(BLDC) motors are widely used as AC servo motors in factory automation fields because of their quick instantaneous mobility, good energy saving efficiency and easiness of design for control system comparing with induction motors. Recently, a Two-Degree-of-Freedom(2DOF) PI control law has been adopted to some application parts to accomplish an advanced speed control of BLDC motors. The method can treat the two conflicting performances, minimum tracking errors versus reference inputs without large overshoot and rejection of some disturbances including modeling errors, independently. However, the method can not design the optimal system which is able to minimize tracking errors and energy consumption simultaneously. In this paper, a 2DOF integral type optimal servo control method is investigated to promote the speed control performances of BLDC motors considering energy consumption. In order to applicate the method to the speed servo system of the BLDC motor, the motor is modeled in the state space using the vector control and decoupling technique. To verify the validity of the suggested method, some simulations and experiments are performed.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1000-1015
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• 2010

In this paper, we propose a novel algorithm for hand gesture recognition. The hand detection method is based on human skin color, and we use the boundary energy information to locate the hand region accurately, then the moment method will be employed to locate the hand palm center. Hand gesture recognition can be separated into 2 step: firstly, the hand posture recognition: we employ the parallel NNs to deal with problem of hand posture recognition, pattern of a hand posture can be extracted by utilize the fitting ellipses method, which separates the detected hand region by 12 ellipses and calculates the white pixels rate in ellipse line. the pattern will be input to the NNs with 12 input nodes, the NNs contains 4 output nodes, each output node out a value within 0~1, the posture is then represented by composed of the 4 output codes. Secondly, the hand gesture tracking and recognition: we employed the Kalman filter to predict the position information of gesture to create the position sequence, distance relationship between positions will be used to confirm the gesture. The simulation have been performed on Windows XP to evaluate the efficiency of the algorithm, for recognizing the hand posture, we used 300 training images to train the recognizing machine and used 200 images to test the machine, the correct number is up to 194. And for testing the hand tracking recognition part, we make 1200 times gesture (each gesture 400 times), the total correct number is 1002 times. These results shows that the proposed gesture recognition algorithm can achieve an endurable job for detecting the hand and its' gesture.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.72-79
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• 2013

In the paper, a pattern analysis to decide whether the 1st local peak power point near open circuit voltage is the global peak power point or not, in case that the voltage and current at the 1st local peak power point are in a specific range, for Maximum Power Point Tracking on the photo voltaic power conversion system. When a solar cell panel array is shaded partially, multi-local peak power points can occur. That makes it hard to search the global peak power point. Through Tableau analysis using by piecewise linear solar cell model, V-I characteristic of a solar cell panel array circuit when partial shading problem happens, is simulated. The global peak power and the local peak power points is confirmed by simulations. Voltage and current values and patterns of V-I characteristic are analyzed. The generating efficiency of the solar cell panel array is improved, when the solar cell panel array circuit is operated at the power point estimated by setting up specific range.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.111-121
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• 2011

This paper discusses a method for optimizing the semi-actuated traffic signal control system by adjusting the initial interval according to the number of vehicles waiting for the green light in the actuated phase. We also present a Left-Turn actuated traffic signal control strategy that examines the vehicular noise in the detection area and determines the phase extension and the gap-out. In order to detect the vehicles in real-time, an image detector's Video Image Tracking technology was adopted. A 'Zone in Zone'method was implemented, and the image detection area is segmented into three zones: 1) Zone1 for verifying a vehicles obligatory presence, 2) Zone2 for counting the standby vehicles, and 3) Zone3 for examining the number of vehicles that have passed. The on-site assessment of the Left Turn Actuated Control is carried out using CORSIM, and the results show that the Control Delay decreased by 23.10%, 15.06%, and 4.34% compared to the delays resulted from pre-timed control, semi-actuated control-1 and semi-actuated control-2 traffic signal control systems respectively. The Queue Time also decreased by 36.24%, 20.10% and the Total Time by 14.36%, 7.02% for the same scenario. Which clearly demonstrates the operational efficiency. A sensitivity analysis reveals that the improvement from the propose traffic control strategy tends to increase as the through traffic volume reaches a saturated condition and the left-turn traffic volume decreases.

• Journal of Korean Neurosurgical Society
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• v.48 no.5
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• pp.391-398
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• 2010

Objective : This study was designed to validate the cell trafficking efficiency of the in vivo bioluminescence image (BLI) study in the setting of transplantation of the luciferase expressing bone marrow-derived mesenchymal stem cells (BMSC), which were delivered at each different time after transient middle cerebral artery occlusion (MCAO) in a mouse model. Methods : Transplanting donor BMSC were prepared by primary cell culture from transgenic mouse expressing luciferase (LUC). Transient focal infarcts were induced in 4-6-week-old male nude mice. The experiment mice were divided into five groups by the time of MSC transplantation : 1) sham-operation group, 2) 2-h group, 3) 1-day group, 4) 3-day group, and 5) 1-week group. BLI for detection of spatial distribution of transplanted MSC was performed by detecting emitted photons. Migration of the transplanted cells to the infarcted area was confirmed by histological examinations. Differences between groups were evaluated by paired t-test. Results : A focal spot of bioluminescence was observed at the injection site on the next day after transplantation by Signal intensity of bioluminescence. After 4 weeks, the mean signal intensities of 2-h, 1-day, 3-day, and 1-week group were $2.6{\times}10^7{\pm}7.4{\times}10^6$. $6.1{\times}10^6{\pm}1.2{\times}10^6$, $1.7{\times}10^6{\pm}4.4{\times}10^5$, and $8.9{\times}10^6{\pm}9.5{\times}10^5$, respectively. The 2-h group showed significantly higher signal intensity (p<0.01). The engrafted BMSC showed around the infarct border zones on immunohistochemical examination. The counts of LUC-positive cells revealed the highest number in the 2-h group, in agreement with the results of BLI experiments (p<0.01). Conclusion : In this study, the results suggested that the transplanted BMSC migrated to the infarct border zone in BLI study and the higher signal intensity of LUC-positive cells seen in 2 hrs after MSC transplantation in MCAO mouse model. In addition, noninvasive imaging in real time is an ideal method for tracking stem cell transplantation. This method can be widely applied to various research fields of cell transplantation therapy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.27-35
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• 2002

A knowledge-based image retrieval technique is image searching methods using some features from the queried image. The materials in this study are automobile head lamps. The input data is composed of characters and images which have various pattern. The numbers, special symbols, and general letters are under the category of the character. The image informations are made up of the distribution of pixel data, statistical analysis, and state of pattern which are useful for the knowledge data. In this paper, we implemented a retrieval system for the scientific crime detection at traffic accident using the proposed multi knowledge-based image retrieval technique. The values for the multi knowledge-based image features were extracted from color and gray scale each. With this 22 features, we improved the retrieval efficiency about the color information and pattern information. Visual basic, crystal report and MS access DB were used for this application. We anticipate the efficient scientific detection for the traffic accident and the tracking of suspicious vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.737-744
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• 2010

The use of RFID recently tends to increase and is expected to expand all over the industry and life. However, RFID is much vulnerable to the malign threats such as eavesdropping, replay attack, spoofing attack, location tracking in the process of authentication. In particular, it is difficult to apply authentication protocol used in the other previous system to low-priced RFID tag. After all, this paper suggests the scheme of efficient authentication protocol for RFID privacy protection. Compared to the previous scheme, suggested scheme reinforces the checking process of transmission data and is secure from eavesdropping and spoofing attack. It minimizes the operation work of the tag and is very useful to apply to the low-priced tag. It also has the merit to confirm the efficiency of communication by reducing the communication rounds.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.6
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• pp.111-117
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• 2009

In the wideband code division access (WCDMA) systems, a pilot channel is used to determine WCDMA network coverage, cell identification, synchronization, timing acquisition and tracking, user-set handoff, channel estimation, and so on. A wireless repeater, which is deployed in the urban area for the WCDMA system to meet the growing demand on wireless communication services, has the possibility to receive several pilot signals from a large number of base stations, however, cannot distinguish its service base station's signal among them. This pilot interference results in frequent handoffs in the user equipment, which degrades the radio reception, transmission efficiency, quality of service, and channel capacity and increases the unwanted power consumption. In this paper, thus, we propose a pilot pollution interference cancellation scheme using one of the adaptive estimation algorithms, normalized least mean square (NLMS), which is applicable to a wireless repeater. We carried out link-level and network-level computer simulations to evaluate the performance of the proposed scheme in a wireless repeater. The simulation results verify the bit error rate (BER) improvement in the link level and the call drop probability improvement in the network level.