• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.6
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• pp.403-410
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• 2018

Lifestyle of adolescents cause a lot of health effects in the future. Therefore, in Korea, school health law was enacted and relevant business such as school education program is being carried out. This study was conducted to recognize symptom according to grade. A survey of youth health status was conducted at 19 middle and high schools in Seongnam city from May 2015 to December 2015. The survey made up of 14 questions which was about the health status satisfaction on the adolescent was conducted to investigate frequency by year and the respective health status of 6 grades. A total of 9,584 students responded to the survey, 58.22% answered that they were not free of constipation. 25.69% of respondents had no symptoms of headache, consequently over 70% of respondents had headache. 57.06% of respondents had no symptoms of low back pain and 34.7% had no symptoms of neck & shoulder pain, therefore over 50% of respondents had muscular skeletal symptoms. In menstrual history, only 17.95% of respondents said their period was regular and painless. In respiratory history, except cold, no nasal drop & obstruction has appeared in the group of 54.02%. And 62.97% of respondents had persistent cough usually with cold and 23.41% had cough with cold breeze even if not catch cold. In the third grade of high school students, there were many complaints of pain in various parts such as headache, back pain and shoulder pain, neck pain and menstrual pain, and there was a high rate of complaints of digestive system symptom and defecation symptom. More than half of respondent had constipation discomfort, headache and musculo-skeletal symptoms, menstrual problems and cough. In the third grade of high school students, the rate of complaints of pain complaints, digestive system symptoms, and bowel symptoms was high. Therefore, there is a need for measures and management for continuous health care and health promotion in accordance with students' symptoms and age at each grade level.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.9-21
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• 2022

In this paper, we developed a 100% detection system for entering and leaving vehicles by improving the detection rate of existing detection cameras based on the LiDAR sensor, which is one of the core technologies of the 4th industrial revolution. Since the currently operating parking lot depends only on the recognition rate of the license plate number of about 98%, there are various problems such as inconsistency in the entry/exit count, inability to make a reservation in advance due to inaccurate information provision, and inconsistency in real-time parking information. Parking status information should be managed with 100% accuracy, and for this, we built a parking lot entrance/exit detection system using LIDAR. When a parking system is developed by applying the LIDAR sensor, which is mainly used to detect vehicles and objects in autonomous vehicles, it is possible to improve the accuracy of vehicle entry/exit information and the reliability of the entry/exit count with the detected sensing information. The resolution of LIDAR was guaranteed to be 100%, and it was possible to implement so that the sum of entering (+) and exiting (-) vehicles in the parking lot was 0. As a result of testing with 3,000 actual parking lot entrances and exits, the accuracy of entering and exiting parking vehicles was 100%.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.82-96
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• 2024

While analyzing traffic flow, speed, traffic volume, and density are important macroscopic indicators, and acceleration and spacing are the important microscopic indicators. The speed and traffic volume can be collected with the currently installed traffic information collection devices. However, acceleration and spacing data are necessary for safety and autonomous driving but cannot be collected using the current traffic information collection devices. 'You Look Only Once'(YOLO), an object recognition technique, has excellent accuracy and real-time performance and is used in various fields, including the transportation field. In this study, to measure acceleration and spacing using YOLO, we developed a model that measures acceleration and spacing through changes in vehicle speed at each interval and the differences in the travel time between vehicles by setting the measurement intervals closely. It was confirmed that the range of acceleration and spacing is different depending on the traffic characteristics of each point, and a comparative analysis was performed according to the reference distance and screen angle to secure the measurement rate. The measurement interval was 20m, and the closer the angle was to a right angle, the higher the measurement rate. These results will contribute to the analysis of safety by intersection and the domestic vehicle behavior model.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Journal of Digital Forensics
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• v.13 no.1
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• pp.35-44
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• 2019

The voice-phishing is done by inducing victims to send money, only with voice through the personal information illegally obtained. The amount of damage caused by voice-phishing continues to increase every year, and it became a social problem. Recently, the Financial Supervisory Service (i.e. the FSS) in Republic of Korea has been collecting the voices of voice-phishing scamer from victims. In this paper, we describe an effective forensic speaker analysis method for detecting the voice from the same person compared with the large-scale speech files stored in database(DB), and apply the aforementioned forensic speaker analysis method with the collected voice-phising speech files from victims. At first, an i-vector of each speech file had been extracted from the DB, then, the cosine similarity matrix for the all speech files had been generated through the cosine distance among the extracted the i-vectors of all speech file in DB. In other words, it performed the speaker analysis as grouping a set of candidates with high common similarity among i-vectors of all speech files in DB. As a result of EER(Error Equal Rate) measurement for 6,724 speech files composed of 82 speakers, it was confirmed that the EER of the i-vector-based method is improved than that of the GMM-based method. Finally, as a result of comparing the collected 2,327 voice-phishing speech files collected by the FSS, it was shown that some of the speech files having similar voice features were grouped each other.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.63-70
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• 2014

Process of recognizing objects in binary images consists of image segmentation and pattern matching. If binary objects in the image are assumed to be separated, global features such as area, length of perimeter, or the ratio of the two can be used to recognize the objects in the image. However, if such an assumption is not valid, the global features can not be used but local features such as points or line segments should be used to recognize the objects. In this paper points with large curvature along the perimeter are chosen to be the feature points, and pairs of points selected from them are used as local features. Similarity of two local features are defined using elastic deformation energy for making the lengths and angles between gradient vectors at the end points same. Neighbour support value is defined and used for robust recognition of partially occluded binary objects. An experiment on Kimia-25 data showed that the proposed algorithm runs 4.5 times faster than the maximum clique algorithm with same recognition rate.

• Journal of Korea Technology Innovation Society
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• v.17 no.4
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• pp.733-762
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• 2014

The government mandates that national research facilities & equipments through R&D business budget should be registered on the National Science and Technology Information Service (NTIS) for the purpose of the efficient use of the research facilities & equipments. This study is to contribute to the national policies on the efficient management of the research facilities & equipments by recognition methodology with the university's members and analysis of the impact factors of the universities' registration process improvement through the Define level and Measure level of the Six Sigma DAMIC. The survey and interview were conducted on research directors, professors joining university administration, graduate students, researchers, and staffs of A University. The findings are the lack of understanding specific steps and life-cycle management of research facilities & equipments. It is necessary to collect suggestions from universities and pursue policies considered the unique characteristics of the university for advanced operating and maximizing use of university's national research facilities & equipments. Research facilities & equipments enrollment compliance rate and registration accuracy were selected as CTQ-Y through the Six Sigma. 72 potential cause variables were derived through Process Map and C & E Diagram. 13 variables were determined as core potential factors through the X-Y Matrix and Pareto Chart. Research institutions should maximize utilization of research facilities & equipments through deriving a potential variables of the process improvements and designing a detail improvements based on the characteristics of each institutions.

• Korean Journal of Community Nutrition
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• v.12 no.1
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• pp.3-12
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• 2007

This study was performed to investigate the body image perception by BMI and the dietary behaviors in 803 college students(408 males and 395 females). The degree of obesity was divided into an underweight group with BMI less than $18.5kg/m^2$, a normal group with BMI of $18.5{\sim}22.9kg/m^2$, an overweight group with BMI of $23{\sim}24.9kg/m^2$ and an obese group with BMI over $25.0kg/m^2$. The average ages of subjects were 22.9 years in males and 20.2 years in females. The average weight and height of male subjects were 175.3 cm and 69.6 kg, respectively and those of female subjects were 162.5 cm and 52.0 kg, respectively. The average BMIs of male and female subjects were $22.6kg/m^2$ and $19.7kg/m^2$, respectively. The distribution of subjects who perceived their current body image as ideal body image was 25.7% in males and 10.9% in females, showing that the body image satisfaction of male subjects was 1.5 times higher than that of female subjects. Body image perception for their own bodies was mostly shown as the average or standard shape both in males and females with 64.2% and 54.2%, respectively, but males showed a higher perception rate than females and 31.1% of females and 19.5% of males perceived their bodies as lean shape(p<0.01). The body image satisfaction was 4.20 in males and 3.70 in females, showing more satisfaction in the male subjects(p<0.001). The correlation between body image and physical variables in male subjects indicated that CBI and IBI showed statistically significant correlation and also BMI showed statistically significant correlation with IBI(p<0.001) and CBI(p<0.001). The frequency of eating out increased as the frequency of skipping meals increased(p<0.001) and the frequency of having snacks increased as the frequency of eating out increased(p<0.01). The correlation between body image and physical variables in female subjects showed that CBI and IBI(p<0.001) had statistically significant correlation. Body weight showed statistically significant correlation with CBI(p<0.001), BMI(p<0.001) and height(p<0.001). The frequency of eating out increased as height(p<0.01) and the frequency of skipping meals(p<0.001) increased. When both male and female subjects wanted leaner body shapes, they preferred much leaner shapes despite their current body images belonging in the normal range. Additionally subjects preferred the body image in the normal range in cases when their current body images were lean. In particular, more female subjects had strong desires to become leaner in their body images than male subjects, which could be analyzed as a risk factor for physical him. From the above results, it is considered that both male and female subjects need to establish proper recognition and dietary behaviors for their body images and also need nutritional education and counseling for desirable weight control methods.