• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.55-58
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• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.2
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• pp.93-101
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• 1999

A simple experimental method was used in an attempt to realize the elevation of the fishing ability of purse seine in the sea area of Cheju Island, the changes of seine volume and tension in the purseline during pursing. Experiments carried out on the six types simplified reduced model seines which were made of knotless nettings. The nettings were woven in different leg length 4.3, 5.0, 5.5, 6.0, 6.6 and 7.7mm of polyester 28 tex two threads two-ply twine, and each of the seines were named I, II, III, IV, V and Ⅵ seine. Dimension of seine models were 450cm for corkline and 85cmfor seine depth, each seines rigged up 160g of float for a floatline and 50g (underwater weight) of lead for a leadline. These model purse seines were made of the scale of 1/200 of its full scale, a 120 ton in the near sea of Cheju Island. Designing and testing for the model purse seines were based on the Tauti's law. Experiments were measured in the observation channel of a flume tank at the static conditions set up shooting and pursing equipments. Motion of purse seine during purse line was recorded by the two sets video camera for VTR which were placed in top and front of the model seine. The reading coordinate of seine volume carried out by the video digitization system, disk data for the purseline tension. An analysis were performed on the changes seine volume and tension in the purseline during pursing. The results obtained were as follows: 1. The seine volume during pursing was largest for Ⅵ seine with smallest d/l followed by V, IV, III, II and I seines, and tension in the purseline was small. 2. Seine volume during pursing can be expressed by the following equation; CVt=l-EXP[｛2.79 (d/l）＋0.35｝t-33.37 (d/l) ＋ 0.57] Where CVt is volume ratio, d is twine diameter, l is leg length and t is pursing time (sec). 3. Tension in the purse line during pursing can be expressed by the following equation; T= 1- EXP ｛0.57t ＋ 13.36 (d/l)+2.97｝ Where T is tension (kg) in the purseline during pursing.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.17-32
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• 2002

The purpose of this study was to find the rational method to analyze golf swing with specific property of club shaft. Three subjects were filmed by two high speed digital cameras with 500 fps. The phase analyzed was downswing of each subject. The three-dimensional coordinates of the anatomical landmarks were obtained with motion analysis system Kwon3d 3.0 version and smoothed by lowpass digital filter with cutoff frequency 6Hz. From these data, kinematic and kinetic variables were calculated using Matlab(ver 5.0) The variables for this study were angular velocity and accelerations, which were calculated and following conclusions have been made : 1) Golf swing time of stiff club is faster than that of regular club. 2) In shoulder joint motion of swing with the stiff club, x-stiff showed mort rapid negative acceleration than that of regular club. 3) In regular club, the velocity of club head would be more effective velocity, which was increasing, than those of other clubs before impact. 4) In wrist joint motion of swing with stiff club, x-stiff club showed faster than regular club in the downswing and impact more rapid negative acceleration.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.233-239
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• 2013

In this paper, a method of combining numerical analyses and experimental tests is used to evaluate fracture toughness of copper thin films of $15{\mu}m$ thickness. Far-field loadings of a global-local finite element model are inversely estimated by matching crack opening profiles in experiments with numerical results. The fracture toughness is then evaluated using the J-integral for cracks in thin films under far-field loadings. In experiments, Cu thin films attached to Aluminum sheets are loaded indirectly, and crack opening profiles are observed by microscope camera. Stress versus strain curves of Cu thin films are obtained through micro-tensile tests, and the grain size of Cu thin films is observed by TEM analysis. The results show that the fracture toughness of Cu thin films with $500nm{\sim}1{\mu}m$ sized grains is $6,962J/m^2$.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.132-145
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• 2020

By coming of the 4th industrial revolution era, HD map have became a key infrastructure for determining precise location of autonomous driving in areas of futuristic cars, logistics and robots. Autonomous vehicles have became more dependent on HD map to determine the exact location of objects detected by various sensors such as LiDAR, GNSS, Radar, and stereo cameras as well as self-location decisions. By actualizing autonomous driving and C-ITS technologies, the demand for precise information on HD map have increased. And also the demand for the creation of new information based on the convergence of various changes and real-time information have increased. In this study, domestic and international HD map standards and related environments have analyzed. Based on this, usability has researched which comparison with standard HD map established by various institutions. Additionally, usability of standard HD map have studied for applying actual autonomous vehicles by reworking HD map. By the result of study, standard HD map have well established to use by various institutions. If further research about layer classification and definition by institutions will carried out based on this study, it has expected that and efficient establishment and renewal of HD map will take place.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.425-435
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• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.797-807
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• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.197-206
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• 2002

The purpose of this study was to investigate the putter head movement during the putting strokes. Highly skilled 5 golfers(less than 3 handicaps) and 5 novice golfers(having no golf experience) participated in this study. A target distance was 3 m. Movements of the putter head were recorded at 60 Hz with two video cameras. The results showed that the novice golfers moved the club significantly longer than the expert golfers(p<.0001). Accoring to a movement time, novice golfers moved their club significantly faster than the expert golfers(p<0.001). Novice golfers could not control the club head effectively, and could not hit the ball correctly. Based on the impact zone movement, sweet spot of novice golfers moved faster(along the line of putt), higher(along the vertical line), and wider(along the side to side line) than that of expert golfers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.305-313
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• 2019

Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3833-3838
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• 2009

This paper introduces a measurement system for mechanical properties of sport shoes using an industrial robot. The robot system used in this paper is a commercial Puma type robot system(FARA AT2 made by SAMSUNG Electronics) with 6 joints and the end-effector is modified to produce a human walking motion. After analyzing human walking with a high speed video camera, each joint angle of the robot system is extracted to be used in the robot system. By using this system, ground impact forces were measured during stepping motion with 3 different shoe specimens made of 3 different hardness outsoles, respectively. As other mechanical properties, both bending moments to bend the toe part of the same specimen shoes and pronation quantities during walking motion were measured as well. In the impact test with the same depth of deformation under the ground level, the effect of the outsole hardness was clearly appeared such that the harder outsole produces the higher ground reaction force. The bending test and the pronation test also show proportional increments in the bending stiffness and the moment Mx according to the outsole hardness. Throughout such experiments, the robot system has produced consistent results so that the system could be used in obtaining valuable informations for a shoe designing process.