• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.71-78
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• 2017

Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.

• Fire Science and Engineering
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• v.24 no.6
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• pp.61-68
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• 2010

In this paper, a research and development result for the implementation of single station fixed temperature detector for residential fire prevention is described. The detector was developed for the certification in Japanese market because of very low domestic market situation. It is in the situation that there is no other regulation especially for residential detectors in Korea, Japanese case has been reviewed. Investigation of domestic legal circumstances and a comparative study for the test standard owned by KFI (Korea Institute of Fire Industry & Technology) and JFEII (Japan Fire Equipment Inspection Institute) respectively are also indicated. The detector alarms with a buzzer and an indicating LED. In the implementation ultra low power MCU(Micro Controller Unit) is applied to control the sleeping state and the monitoring state properly with low current consumption. To sense the temperature fast response thermistor is adopted in the design of fixed temperature residential detector. Automatic test function and alarm stop function are also considered in the design. The major factors which influence to current consumption are explained for the purpose of design reference. Main electronics circuit parts related to it's characteristics of the detector are described. It is explained that the measured current and experimental result of the battery discharge can be met over 10 years operation.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.337-349
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• 2020

In this study, Helikite, Low Altitude Remote Sensing (LARS) platform, was used to acquire coastal images. In the obtained image, the land and water masses were divided using four types of region clustering algorithms, and then waterline was extracted using edge detection. Quantitative comparisons were not possible due to the lack of in-situ waterline data. But, based on the image of the infrared band where water masses and land are relatively clear, the waterlines extracted by each algorithm were compared. As a result, it was found that each algorithm differed significantly in the part where the distinction between water masses and land was ambiguous. This is considered to be a difference in the process of selecting the threshold value of the digital number that each algorithm uses to distinguish the regions. The extraction of waterlines through various algorithms is expected to be used in conjunction with a Low Altitude Remote Sensing system that can be continuously monitored in the future to explain the rapid changes in coastal shape through several years of long-term data from fixed areas.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.15-23
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• 2003

Recently, there have been many attempts to develop BCI (brain computer interface) based on EEG (electroencephalogram). Measurement and analysis of EEG evoked by particular stimulation is important for the design of brain wave pattern and interface of BCI. The purpose of this study is to develop a general-purpose system that measures subject's reaction time after audio-visual stimulation which can work together with any other biosignal measurement systems. The entire system is divided into four modules, which are stimulation signal generation, reaction time measurement, evoked potential measurement and synchronization. Stimulation signal generation module was implemented by means of Flash. Measurement of the reaction time (the period between the answer request and the subject reaction) was achieved by self-made microcontroller system. EEG measurement was performed using the ready-made hardware and software without any modification. Synchronization of all modules was achieved by, first, the black-and-white signals on the stimulation screen synchronized with the problem presentation and the answer request, second, the photodetectors sensing the signals. The proposed method offers easy design of purpose-specific system only by adding simple modules (reaction time measurement, synchronization) to the ready-made stimulation and EEG system, and therefore, it is expected to accelerate the researches requiring the measurement of evoked response and reaction time.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.6
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• pp.827-836
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• 2013

Due to the stringent drinking water quality, formaldehyde will be included in Korean drinking water standard from year 2014. However, its standard analytical method has not yet been established. This study compares two analytical methods, DNPH-LC and ACFAS with respect to their analysis principles, Method Detection Limit (MDL), Limit Of Quantitation(LOQ), precision, accuracy, reproducibility, convenience, number of samples analyzed per hour and analysis cost. These methods measure absorption intensity at 360 nm by using HPLC after DNPH-derivatization (DNPH-LC) and at 410 nm by using Automated Continuous Flow Absorption Spectrophotometer (ACFAS), respectively. Reproducibility was tested by repeating the analysis 7 times using a standard solution for each method. For DNPH-LC method, MDL was $0.5{\mu}g/L$, LOQ was $1.58{\mu}g/L$ with standard deviation of $0.16{\mu}g/L$. For ACFAS method, they were $0.27{\mu}g/L$, $0.85{\mu}g/L$L with standard deviation of $0.09{\mu}g/L$, respectively. Both methods satisfied the requirement set by the Korean drinking water quality standard. Complexity of sample pretreatment procedure for DNPH-LC method may cause large error and, consequently, the analytical result will depend on the level of skill of analyst. In contrast, ACFAS method which used only one reagent equipped with an automated injection device showed little analytical error. It costs about $5.00 and $1.00 for one sample to analyze by the DNPH-LC method and the ACFAS method, respectively. Compared to the DNPH-LC method, ACFAS method provided more reliable analytical results. In terms of convenience, easiness and analytical cost, ACFAS method was demonstrated to be superior to the DNPH-LC method. The results of this study suggested that the ACFAS method could be adapted as a proper method for determining formaldehyde content in drinking water.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.369-374
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• 2015

In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.183-190
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• 1999

The purpose of this study was to develop a portable and convenient closed-loop contrel type electrical stimulator for patients with foot drop. This system restores walking movement as well as prevents from atrophy or necrosis of lower limb muscles and increases blood circulation in hemiplegic patients caused by traffic accident, industrial disaster or stoke. This system detects the changes of the ankle joint angle during walking, and then controls the stimulus intensity automatically to maintain the programmed level of the ankle joint angle. Also, this automatic system controls the stimulus intensity which is affected by increased electrode impedance resulting from long time use. The system detects the joint angle by an optical sensor and includes modified PID control which adjusts the stimulus intensity if the joint angle deviates from the preset value. Stimulus parameters are 30~80 volt, 40 Hz, and 0.2 ms. The system was applied to five hemiplegic patients for 42 days. Duration of stimulation was 15 min/day for the first week and then the duration was gradually increased to 30, 60, 90 and 120 min/day. The muscle force was increased up to 29.7%, muscle fatigue was decreased compared with the level before stimulation and the pattern of locomotion was improved. These results suggest that the electrical stimulator with closed-loop control type is more convenient and effective in restoration of locomotion of patients with foot drop than open-loop system.

• Progress in Medical Physics
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• v.13 no.4
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• pp.224-228
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• 2002

Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. However, the accuracy of the estimation of tag intersection can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) in in-vivo study. Two healthy volunteers were undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner. Horizontally modulated stripe patterns were imposed with a range from 3.6 to 9.6 mm of tagline spacing. Images of the left ventricle(LV) wall were acquired at the mid-ventricle level during cardiac cycle with FE-EPI (TR/TE = 5.8/2.2 msec, FA= 10$^{\circ}$. Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of narrow tagline spacing than in case of wide tagline spacing. In the same heart phase, CNR was increased corresponding with tagline spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing. The results indicated that the optimization of tagline spacing provides better tagging CNR in order to analyze the myocardial motion more accurately.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.25-33
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• 2006

We propose a method that automatically classifies the images into the object and non-object images. An object image is the image with object(s). An object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. We define four measures based on the characteristics of an object to classify the images. The center significance is calculated from the difference in color distribution between the center area and its surrounding region. Second measure is the variance of significantly correlated colors in the image plane. Significantly correlated colors are first defined as the colors of two adjacent pixels that appear more frequently around center of an image rather than at the background of the image. Third one is edge strength at the boundary of candidate for the object. By the way, it is computationally expensive to extract third value because central objects are extracted. So, we define fourth measure which is similar with third measure in characteristic. Fourth one can be calculated more fast but show less accuracy than third one. To classify the images we combine each measure by training the neural network and SYM. We compare classification accuracies of these two classifiers.