• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.28-33
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• 2017

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.584-588
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• 2019

Wireless body area network (WBAN) is a networking technology that enables early detection of abnormal health conditions, real-time medical monitoring, and telemedicine support systems. The internet of things (IoT) for healthcare, which has become an issue recently, is one of the most promising areas for improving the quality of human life. It must meet the high QoS requirements of the medical communication system like any other communication system. Therefore, the bit error rate (BER) threshold was chosen to accommodate the QoS requirements of the WBAN communication system. In this paper, we calculated BER performance of WBAN channel using IR-UWB PPM modulation and analyzed link budget and system margin of WBAN according to various system parameters.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.544-547
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• 2008

As the mobile electronic product is getting slimmer and smaller, the necessity of keypad is being increased. But the possibility of mis-typing keypad is increased rapidly due to the integrated keypad in the small mobile product. The business division has not considered the methodology of keypad design essentially. In this paper, analysis method and design evaluation standard to reduce the mis-typing of UMPC(Ultra Mobile Personal Computer) is suggested. First, the finite element analysis model and the biomechanical human body model are implemented in order to simulate the exact contact characteristic between finger and keypad. The reliability of analysis model is guaranteed by the comparison of the contact pressure between analysis result and experiment result of the pressure sensor. The design optimization of key shape and layout is derived through the response surface method. The prototype model is produced with the optimized design of keypad, and then it verified the advanced function with user mis-typing detection test. The optimized keypad design reduced the mis-typing ratio from 35% of existing model to 75 of proposed model. If this paper is widely applied to not only UMPC but also the other electronic products, the emotional quality of all products could be improved considerably.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.2058-2065
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• 2010

This paper presents the sensor location and step estimation algorithm for personal navigation system (PNS). PNS has the disadvantage in that the position of the sensor must be fixed on a human body. Three-axis acceleration sensor is used to solve the disadvantage and to consider the real situation. We simplify the measurement data by using the band pass filter, witch It has the advantage in the detection of characteristic point. Through the detected characteristic points, it is possible to setup the parameter for the pattern detection. Depending on the sensor location, the parameters have the different type of noise covariance. Particularly, when the position of the sensor is changed, the impulse noise shows up. Considering the noise, we apply the recursive least square algorithm using the variable forgetting factors, which can classify the sensor location based on the estimated parameters. We performed the experiment for the verification of the proposed algorithm in the various environments. Through the experimental results, the effectiveness of the proposed method is verified.

• Journal of Oral Medicine and Pain
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• v.33 no.1
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• pp.59-66
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• 2008

Ribosomal Protein S4Y(RPS4Y) gene is the human sex-linked gene on the Y chromosome. There are a number of reports on the sex determination using RPS4Y gene analysis for prevention and diagnosis in sex-linked disease. Thus RPS4Y gene is a reliable genetic marker for sex determination in forensic medicine. In general, the sex determination of an unidentified body can be achieved based on anatomical characteristics, but sometimes sex determination was considered to be difficult such as pre-adolescent bodies or decomposed, mutilated bodies. In this case, Sex determination using PCR method in human teeth produces good results. Because human teeth have a great structural durability, the DNA well preserved in the teeth. So author isolated nuclear DNA from the 20 human teeth(10 males, 10 females), performed to detect RPS4Y gene by PCR method. Samples were divided four group(10 pulp and 10 dentinal tissue in male, 10 pulp and 10 dentinal tissue in female). It was found that detection of RPS4Y gene for sex determination was possible in all the male pulp tissues and 6 out of 10 male dentinal tissues. But there was not detected in female pulp and dentinal tissues. In the view of this results demonstrates the possibility that detection of RPS4Y gene with other sex chromosome genes from the human teeth is useful to sex determination in forensic medicine.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.403-409
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• 2016

Recently, harmful content (such as images and photos of nudes) has been widely distributed. Therefore, there have been various studies to detect and filter out such harmful image content. In this paper, we propose a new method using Haar-like features and an AdaBoost algorithm for robustly extracting navel areas in a color image. The suggested algorithm first detects the human nipples through color information, and obtains candidate navel areas with positional information from the extracted nipple areas. The method then selects real navel regions based on filtering using Haar-like features and an AdaBoost algorithm. Experimental results show that the suggested algorithm detects navel areas in color images 1.6 percent more robustly than an existing method. We expect that the suggested navel detection algorithm will be usefully utilized in many application areas related to 2D or 3D harmful content detection and filtering.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.47-57
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• 2010

The object detection is essential for identifying objects, location information, and user context-aware in the image. In this paper, we propose a robust object detection system. The System linearly transforms learning data obtained from the background images to Principal components. It organizes the Eigen-background with the selected Principal components which are able to discriminate between foreground and background. The Fuzzy-C-means (FCM) carries out clustering for images with inputs from the Eigen-background information and classifies them into objects and backgrounds. It used various patterns of backgrounds as learning data in order to implement a system applicable even to the changing environments, Our system was able to effectively detect partial movements of a human body, as well as to discriminate between objects and backgrounds removing noises and shadows without anyone frame image for fixed background.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.661-664
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• 2009

Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a moving wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, body of moving robot used for A4WD1 Combo kit for RC, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.260-269
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• 2021

To verify performance or conduct experiments using actual robots, a lot of costs are needed such as robot hardware, experimental space, and time. Therefore, a simulation environment is an essential tool in robotics research. In this paper, we develop the HUMIC simulator using ROS and Gazebo. HUMIC is a humanoid robot, which is developed by HCIR Lab., for human-robot interaction and an upper body of HUMIC is similar to humans with a head, body, waist, arms, and hands. The Gazebo is an open-source three-dimensional robot simulator that provides the ability to simulate robots accurately and efficiently along with simulated indoor and outdoor environments. We develop a GUI for users to easily simulate and manipulate the HUMIC simulator. Moreover, we open the developed HUMIC simulator and GUI for other robotics researchers to use. We test the developed HUMIC simulator for object detection and reinforcement learning-based navigation tasks successfully. As a further study, we plan to develop robot behavior intelligence based on reinforcement learning algorithms using the developed simulator, and then apply it to the real robot.

• Archives of Pharmacal Research
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• v.22 no.1
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• pp.86-88
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• 1999

An advance d and sensitive high-performance liquid chromatographic (HPLC) method for determination of omeparzole in human plasma has been developed. After omeprazole was extracted from plasma with diethylether, the organic phase was transferred to another tube and trapped back with 0.1 N NaOH solution. The alkaline aqueous layer was injected into a reversed-phase C8 column. Lansoprazole was used as an internal standard. The mobile phase consisted of 30% of acetonitrile and 70% of 0.2 M $ KH_{2}PO_{4}$, pH 7.0. Recoveries of the analytes and internal standard were >75.48%. The coefficients of variation of intra- and inter-day assay were <5.78 and 4.59% for plasma samples. The detection limit in plasma was 2 ng/ml. The clinical applicability of this assay method was evaluated by determining plasma concentration-time courses of the respective analytes in 24 healthy volunteers after oral administration 40 mg of omeprazole. The present assay is considered to be simple, accurate, economical and suitable for the study of the kinetic disposition of omeprazole in the body.