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Threat Situation Determination System Through AWS-Based Behavior and Object Recognition (AWS 기반 행위와 객체 인식을 통한 위협 상황 판단 시스템)

  • Ye-Young Kim;Su-Hyun Jeong;So-Hyun Park;Young-Ho Park
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.4
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    • pp.189-198
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    • 2023
  • As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

Motion Vector Based Overlay Metrology Algorithm for Wafer Alignment (웨이퍼 정렬을 위한 움직임 벡터 기반의 오버레이 계측 알고리즘 )

  • Lee Hyun Chul;Woo Ho Sung
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.3
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    • pp.141-148
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    • 2023
  • Accurate overlay metrology is essential to achieve high yields of semiconductor products. Overlay metrology performance is greatly affected by overlay target design and measurement method. Therefore, in order to improve the performance of the overlay target, measurement methods applicable to various targets are required. In this study, we propose a new algorithm that can measure image-based overlay. The proposed measurement algorithm can estimate the sub-pixel position by using a motion vector. The motion vector may estimate the position of the sub-pixel unit by applying a quadratic equation model through polynomial expansion using pixels in the selected region. The measurement method using the motion vector can calculate the stacking error in all directions at once, unlike the existing correlation coefficient-based measurement method that calculates the stacking error on the X-axis and the Y-axis, respectively. Therefore, more accurate overlay measurement is possible by reflecting the relationship between the X-axis and the Y-axis. However, since the amount of computation is increased compared to the existing correlation coefficient-based algorithm, more computation time may be required. The purpose of this study is not to present an algorithm improved over the existing method, but to suggest a direction for a new measurement method. Through the experimental results, it was confirmed that measurement results similar to those of the existing method could be obtained.

Learning Data Model Definition and Machine Learning Analysis for Data-Based Li-Ion Battery Performance Prediction (데이터 기반 리튬 이온 배터리 성능 예측을 위한 학습 데이터 모델 정의 및 기계학습 분석 )

  • Byoungwook Kim;Ji Su Park;Hong-Jun Jang
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.3
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    • pp.133-140
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    • 2023
  • The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

Variation of Earth Pressure Acting on the Cut-and-Cover Tunnel Lining due to Geotextile Mat Reinforcement (지오텍스타일 매트의 설치에 의한 개착식 터널 라이닝에 작용하는 토압의 변화)

  • Bautista, F.E.;Park, Lee-Keun;Im, Jong-Chul;Joo, In-Gon
    • Journal of the Korean Geotechnical Society
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    • v.23 no.3
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    • pp.25-40
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    • 2007
  • Excessive earth pressure is one of the major mechanical factors in the deformation and damage of Cut-and-Cover Tunnel lining in shallow tunnels and portals of mountain tunnels (Kim, 2000). Excessive earth pressure may be attributed to insufficient compaction and consolidation of backfill material due to self-weight, precipitation and vibration caused by traffic (Komiya et al., 2000; Taylor et al., 1984; Yoo, 1997). Even though there were a lot of tests performed to determine the earth pressure acting on the tunnel lining, unfortunately there were almost no case histories of studies performed to determine remedial measures that reduce differential settlement and excessive earth pressure. In this study the installation of geotextile mat was selected to reduce the differential settlement and excessive earth pressure acting on the cut-and-cover tunnel lining. In order to determine settlement and earth pressure reduction effect (reinforcement effect) of geotextile mat reinforcement, laboratory tunnel model tests were performed. This study was limited to the modeling of rigid circular cut-and-cover tunnel constructed at a depth of $1.0D\sim1.5D$ in loose sandy ground and subjected to a vibration frequency of 100 Hz. Model tests with varying soil cover, mat reinforcement scheme and slope roughness were performed to determine the most effective mat reinforcement scheme. Slope roughness was adjusted by attaching sandpaper #100, #400 and acetate on the cut slope surface. Mat reinforcement effect of each mat reinforcement scheme were presented by the comparison of earth pressure obtained from the unreinforced and mat reinforced model tests. Soil settlement reduction was analyzed and presented using the Picture Analysis Method (Park, 2003).

A Study of Obtaining Reliable Travel Time Information in Downhole Seismic Method (다운홀 기법에서 신뢰성 있는 도달시간 정보 산출 방법에 대한 고찰)

  • Bang, Eun-Seok;Lee, Sei-Hyun;Kim, Jong-Tae;Kim, Dong-Soo
    • Journal of the Korean Geotechnical Society
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    • v.23 no.8
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    • pp.17-33
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    • 2007
  • Downhole seismic method is widely used for obtaining shear wave velocity profile of a site because it is simple and economical. Determining accurate travel time of shear wave is very important to obtain reliable result in downhole seismic method. In this paper, comparison study of various travel time determination methods was performed. Numerical study and model chamber test were performed for effective comparison study. Signal traces were acquired by performing downhole test at each numerical simulation and soil box test. Travel time data for each signal traces were determined by using six different methods and Vs profiles were evaluated. Comparing travel time data and Vs profiles with the reference value, the first arrival picking method proved to be ambiguous and unreliable. Other methods also did not always provide accurate results and the magnitude of error was dependent on the signal to noise ratio. Cross-correlation method proved to be the most adequate method for the field application and it was verified additionally with field data.

Rotational Prism Stitching Interferometer for High-resolution Surface Testing (고해상도 표면 측정을 위한 회전 프리즘 정합 간섭계)

  • In-Ung Song;Woo-Sung Kwon;Hagyong Khim;Yun-Woo Lee;Jong Ung Lee;Ho-Soon Yang
    • Korean Journal of Optics and Photonics
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    • v.34 no.3
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    • pp.117-123
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    • 2023
  • The size of an optical surface can significantly affect the performance of an optical system, and high spatial frequency errors have a greater impact. Therefore, it is crucial to measure the surface figure error with high frequency. To address this, a new method called rotational prism stitching interferometer (RPSI) is proposed in this study. The RPSI is a type of stitching interferometer that enhances spatial resolution, but it differs from conventional stitching interferometers in that it does not require the movement of either the mirror tested or the interferometer itself to obtain sub-aperture interferograms. Instead, the RPSI uses a beam expander and a rotating Dove prism to select particular sub-apertures from the entire aperture. These sub-apertures are then stitched together to obtain a full-aperture result proportional to the square of the beam expander's magnification. The RPSI's effectiveness was demonstrated by measuring a 40 mm diameter spherical mirror using a three-magnification beam expander and comparing the results with those obtained from a commercial interferometer. The RPSI achieved surface testing results with nine times higher sampling density than the interferometer alone, with a small difference of approximately 1 nm RMS.

Ordinary Kriging of Daily Mean SST (Sea Surface Temperature) around South Korea and the Analysis of Interpolation Accuracy (정규크리깅을 이용한 우리나라 주변해역 일평균 해수면온도 격자지도화 및 내삽정확도 분석)

  • Ahn, Jihye;Lee, Yangwon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.1
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    • pp.51-66
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    • 2022
  • SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

Factors Affecting Consumers' Acceptance of e-Commerce Consumer Credit Service: Multiple Group Path Analysis by Naver Shopping and Coupang (이커머스 후불결제(BNPL) 수용에 영향을 미치는 요인: 네이버쇼핑과 쿠팡 간 다중집단 비교)

  • Kim, Su Jin;Mo, Jeonghoon
    • The Journal of Society for e-Business Studies
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    • v.27 no.2
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    • pp.105-135
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    • 2022
  • As COVID-19 has led to a surge in e-commerce Buy Now Pay Later(BNPL) has become preferred choice among millennials. In Korea Coupang followed by Naver Pay offers a deferred payment, aiming to create customer lock-in effect, save credit card processing fee and lay the groundwork for entering into new financial services. However the literature related to the influential factors of customers' usage intention toward a deferred payment is scarce. For the study, a multi-group analysis was carried out to find differences between Naver shopping and Coupang. The results revealed that the important factors that affect a deferred payment adoption were compatibility, impulsive buying tendency in Naver shopping, whereas compatibility, relative advantage, additional value in Coupang(listed in order of most important). In addition, impulsive buying tendency had a positive effect on adoption intention in Naver shopping and on perceived risk in Coupang. The results imply that Naver shopping need to focus on managing delinquency while Coupang should provide sufficient information on how late fees and credit rating downgrade work and try not to make a deferred payment option stand out. In order to increase adoption rate it is recommendable to narrow down target segment of a deferred payment and expand it to a specialized vertical such as travel.

Comparison of the 2D/3D Acoustic Full-waveform Inversions of 3D Ocean-bottom Seismic Data (3차원 해저면 탄성파 탐사 자료에 대한 2차원/3차원 음향 전파형역산 비교)

  • Hee-Chan, Noh;Sea-Eun, Park;Hyeong-Geun, Ji;Seok-Han, Kim;Xiangyue, Li;Ju-Won, Oh
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.203-213
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    • 2022
  • To understand an underlying geological structure via seismic imaging, the velocity information of the subsurface medium is crucial. Although the full-waveform inversion (FWI) method is considered useful for estimating subsurface velocity models, 3D FWI needs a lot-of computing power and time. Herein, we compare the calculation efficiency and accuracy of frequency-domain 2D and 3D acoustic FWIs. Thereafter, we demonstrate that the artifacts from 2D approximation can be partially suppressed via frequency-domain 2D FWI by employing diffraction angle filtering (DAF). By applying DAF, which employs only big reflection angle components, the impact of noise and out-of-plane reflections can be reduced. Additionally, it is anticipated that the DAF can create long-wavelength velocity structures for 3D FWI and migration.

CKFont2: An Improved Few-Shot Hangul Font Generation Model Based on Hangul Composability (CKFont2: 한글 구성요소를 이용한 개선된 퓨샷 한글 폰트 생성 모델)

  • Jangkyoung, Park;Ammar, Ul Hassan;Jaeyoung, Choi
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.12
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    • pp.499-508
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    • 2022
  • A lot of research has been carried out on the Hangeul generation model using deep learning, and recently, research is being carried out how to minimize the number of characters input to generate one set of Hangul (Few-Shot Learning). In this paper, we propose a CKFont2 model using only 14 letters by analyzing and improving the CKFont (hereafter CKFont1) model using 28 letters. The CKFont2 model improves the performance of the CKFont1 model as a model that generates all Hangul using only 14 characters including 24 components (14 consonants and 10 vowels), where the CKFont1 model generates all Hangul by extracting 51 Hangul components from 28 characters. It uses the minimum number of characters for currently known models. From the basic consonants/vowels of Hangul, 27 components such as 5 double consonants, 11/11 compound consonants/vowels respectively are learned by deep learning and generated, and the generated 27 components are combined with 24 basic consonants/vowels. All Hangul characters are automatically generated from the combined 51 components. The superiority of the performance was verified by comparative analysis with results of the zi2zi, CKFont1, and MX-Font model. It is an efficient and effective model that has a simple structure and saves time and resources, and can be extended to Chinese, Thai, and Japanese.