• 전자공학회논문지 IE
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• v.47 no.2
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• pp.38-46
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• 2010

In this paper, an autonomous surveillance-tracking system for Workers monitoring basing on the stereo vision scheme is proposed. That is, analysing the characteristics of the cross-axis camera system through some experiments, a optimized stereo vision system is constructed and using this system an intelligent worker surveillance-tracking system is implemented, in which a target worker moving through the environments can be detected and tracked, and its resultant stereo location coordinates and moving trajectory in the world space also can be extracted. From some experiments on moving target surveillance-tracking, it is analyzed that the target's center location after being tracked is kept to be very low error ratio of 1.82%, 1.11% on average in the horizontal and vertical directions, respectively. And, the error ratio between the calculation and measurement values of the 3D location coordinates of the target person is found to be very low value of 2.5% for the test scenario on average. Accordingly, in this paper, a possibility of practical implementation of the intelligent stereo surveillance system for real-time tracking of a target worker moving through the environments and robust detection of the target's 3D location coordinates and moving trajectory in the real world is finally suggested.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.71-79
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• 2008

High voltage distribution lines in the electric railway system placed according track with communication lines and signal equipments. Case of the over head lines is occurrence the many fault because lightning, rainstorm, damage from the sea wind and so on. According this fault caused protection device to wrong operation. One line ground fault that occurs most frequently in railway high voltage distribution lines and sort of faults is line short, three line ground breaking of a wire, and so on. For this reason we need precise maintenance for prevent of the faults. The most important is early detection and fast restoration in time of fault for a safety transit. In order to develop an advanced fault location device for 22.9[kV] distribution power network in electric railway system this paper deals with new fault locating algorithm using flow technique which enable to determine the location of the fault accurately. To demonstrate its superiorities, the case studies with the algorithm and the fault analysis using PSCAD/EMTDC (Power System Computer Aided Design/Electro Magnetic Transients DC Analysis Program) were carried out with the models of direct-grounded 22.9[kV] distribution network which is supposed to be the grounding method for electric railway system in Korea.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.97-106
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• 2019

The purpose of this study was to investigate the effect of the type and measurement location of a fabric strain gauge sensor on the detection performance for respiratory signals. We implemented two types of sensors to measure the respiratory signal and attached them to a band to detect the respiratory signal. Eight healthy males in their 20s were the subject of this study. They were asked to wear two respiratory bands in turns. While the subjects were measured for 30 seconds standing comfortably, the respiratory was given at 15 breaths per minute were synchronized, and then a 10-second break; subsequently, the entire measurement was repeated. Measurement locations were at the chest and abdomen. In addition, to verify the performance of respiratory measurement in the movement state, the subjects were asked to walk in place at a speed of 80 strides per minute(SPM), and the respiratory was measured using the same method mentioned earlier. Meanwhile, to acquire a reference signal, the SS5LB of BIOPAC Systems, Inc., was worn by the subjects simultaneously with the experimental sensor. The Kruskal-Wallis test and Bonferroni post hoc tests were performed using SPSS 24.0 to verify the difference in measurement performances among the group of eight combinations of sensor types, measurement locations, and movement states. In addition, the Wilcoxon test was conducted to examine whether there are differences according to sensor type, measurement location, and movement state. The results showed that the respiratory signal detection performance was the best when the respiratory was measured in the chest using the CNT-coated fabric sensor regardless of the movement state. Based on the results of this study, we will develop a chest belt-type wearable platform that can monitor the various vital signal in real time without disturbing the movements in an outdoor environment or in daily activities.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.185-194
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• 2014

One in every 10 persons suffer from chronic gastritis in Korea. Endoscopy is most commonly used to diagnose the chronic gastritis. Endoscopic diagnosis is precise but it is accompanied with pain and high cost. According to pulse diagnosis in Traditional East Asian Medicine, health problems in stomach can be diagnosed with radial pulse signals in 'Guan' location in the right wrist, which are non-invasive and cost-effective. In this study, we developed a classification model of chronic gastritis using pulse signals in right 'Guan' location. We used both linear discrimination method and logistic regression model with respect to pulse features obtained with a peak-valley detection algorithm and a Gaussian model. As a result, we obtained sensitivity ranged between 77%~89% and specificity ranged between 72%~83% depending on classification models and feature extraction methods, and the average classification rates were approximately 80%, irrespective of the models. Specifically, the Gaussian model were featured by superior sensitivities (89.1% and 87.5%) while the peak-valley detection method showed superior specificities (82.8% and 81.3%), and the average classification rate (sensitivity + specificity) of the Gaussian model was 80.9% which was 1.2% ahead of the peak-valley method. In conclusion, we obtained a reliable classification model for the chronic gastritis based on the radial pulse feature extraction algorithms, where the Gaussian model was featured by outperformed sensitivity and the peak-valley method was featured by outperformed specificity.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.17-28
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• 2005

About 91.1% of Railway-Highway Crossings (RHC) in Korea use a Constant Distance Warning System(CDWS), while about 8.9% use a Constant Warning Time System(CWTS). The CDWS does not recognize speed differences of approaching trains and provides only waiting times to vehicles and pedestrians based on the highest speed of approaching trains. Under the CDWS, therefore, low speed trains provide unnecessary waiting times at crossings which often generates complains to vehicle drivers and pedestrians and may cause wrong decisions to pass the crossings. The objective of this research is to improve the safety of the RHC by developing accurate a CWTS. In this research a train speed and location detection system was developed with ultra sonic detectors. Locations of the detectors was decided based on the highest speed and the minimum warning time of Saemaul of 160 km/h. To validate the algorithms of the newly developed systems the lab tests were conducted. The results show that the train detection system provides accurate locations of trains and the maximum error between real speeds of trains and those of the system was 0.07m/s.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.323-330
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• 2009

The objective of this research was to develop a practical integrated approach using extracted features from electrical resistance measurements and coupled electromechanical models of damage, for in-situ damage detection and sensing in carbon fiber reinforced plastic(CFRP) composites. To achieve this objective, we introduced specific known damage (in terms of type, size, and location) into CFRP laminates and established quantitative relationships with the electrical resistance measurements. For processing of numerous measurement data, an autonomous data acquisition system was devised. We also established a specimen preparation procedure and a method for electrode setup. Coupon and panel CFRP laminate specimens with several known damage were tested. Coupon specimens with various sizes of artificial delaminations obtained by inserting Teflon film were manufactured and the resistance was measured. The measurement results showed that increase of delamination size led to increase of resistance implying that it is possible to sense the existence and size of delamination. A quasi-isotropic panel was manufactured and electrical resistance was measured. Then three different sizes of holes were drilled at a chosen location. The panel was prepared using the established procedures with six electrode connections on each side making a total of twenty-four electrodes. Vertical, horizontal, and diagonal pairs of electrodes were chosen and the resistance was measured. The measurement results showed the possibility of the established measurement system for an in-situ damage detection method for CFRP composite structures.

• Korean Journal of Cognitive Science
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• v.20 no.1
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• pp.51-77
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• 2009

Using a modified Posner's cue-target paradigm, we investigated whether negative cues attract more attention than neutral cues in anxious people. Previous studies used commonly an unbalanced proportion of valid and invalid trials(75% vs. 25% respectively). But in the present study, an equivalent proportion of valid and invalids trials was used for measuring detection speed of cues without participant's expectancy caused by the unbalanced proportion. Emotional words(Experiment 1) and facial expressions(Experiment 2) were used as cues for target locations. The result of Experiment 1 and 2 showed that threatening cues facilitated target detection in valid trials and interfered with it in invalid trials in anxious participants and a, reverse response patterns were found in non-anxious participants. This indicates that threatening cues attract more attention to the cued location in anxious people and in contrast, non-anxious people avoid threatening stimuli. In Experiment 3, we investigated the difference of validity effect across anxiety levels. The results showed that anxious participants gave less attention to cued location when the cues were non-informative whereas non-anxious participants gave more attention to cued locations in the same condition. We discussed two kinds of cognitive bias caused by anxiety levels: attentional bias and proportion related bias.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.43-53
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• 2019

In recent years, there have been many cases of damage to indoor air hazardous materials, and major damage due to the lack of quick action. In this regard, the system is intended to establish for sending push messages to the user's mobile when the concentration of hazardous substances is exceeded. This system extracts data with IoT system such as Arduino and Raspberry Pi and then constructs database through MongoDB and MySQL in cloud computing system. The database is imported through the application server using NodeJS and sent to the application for visualization. Also, when receiving signals about a dangerous situation in IoT system, push message is sent using Google FCM library. Mobile application is developed using Android Web view, and page to enter Web view is developed using HTML5 (HTML, Javascript CSS). The application of this system enables real-time monitoring of indoor air-dangerous substances. In addition, real-time information on indoor/outdoor detection location and concentration can be sent to the user's mobile in case of a risk situation, which can be expected to help the user respond quickly.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.19-26
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• 2003

Recently, the number of internet service companies is increasing and so is the number of malicious attackers. Damage such as distrust about credit and instability of the service by these attacks may influence us fatally as it makes companies image failing down. One of the frequent and fatal attacks is DoS(Denial-of-Service). Because the attacker performs IP spoofing for hiding his location in DoS attack it is hard to get an exact location of the attacker from source IP address only. and even if the system recovers from the attack successfully, if attack origin has not been identified, we have to consider the possibility that there may be another attack again in near future by the same attacker. This study suggests to find the attack origin through MAC address marking of the attack origin. It is based on an IP trace algorithm, called Marking Algorithm. It modifies the Martins Algorithm so that we can convey the MAC address of the intervening routers, and as a result it can trace the exact IP address of the original attacker. To improve the detection time, our algorithm also contains a technique to improve the packet arrival rate. By adjusting marking probability according to the distance from the packet origin we were able to decrease the number of needed packets to traceback the IP address.