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Analysis of influence and factors of Christian characters (기독교인성의 영향력과 요인들에 대한 분석)

  • Han, Man-oh
    • Journal of Convergence for Information Technology
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    • v.8 no.3
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    • pp.91-97
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    • 2018
  • The purpose of this study is to identify the factors affecting the Christian characters of Korean church members. In addition, this study also examined the virtues and measurement index of Christian characters, general factors of church members and relationship between 9 virtues of Christian characters of church members and related influences. In this study, a questionnaire survey was conducted with one to one interview through the assistance of church officials. The results based on the survey showed no significant differences in Christian characters according to the personal factors and church factors. However, it was identified that the church satisfaction among the church factors affected the Christian character. In order to improve the negative image of Korean church through this study, this study tries to show the relationship with Christian characters and the importance of Christian characters in the church and to suggest the necessity of education. This study seeks to review the correlation that the faith of Korean Christians, their status and title within the church, length of year they've had faith and their satisfaction with church life have with their well-rounded character as a Christian, what factors or values affect the personality of Christians in Korean chruches, and what programs or action steps can be taken to provide the most optimal and feasible way to promote a better well-rounded character in Korean Christians.

A Synchronized Playback Method of 3D Model and Video by Extracting Golf Swing Information from Golf Video (골프 동영상으로부터 추출된 스윙 정보를 활용한 3D 모델과 골프 동영상의 동기화 재생)

  • Oh, Hwang-Seok
    • Journal of the Korean Society for Computer Game
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    • v.31 no.4
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    • pp.61-70
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    • 2018
  • In this paper, we propose a synchronized playback method of 3D reference model and video by extracting golf swing information from learner's golf video to precisely compare and analyze each motion in each position and time in the golf swing, and present the implementation result. In order to synchronize the 3D model with the learner's swing video, the learner's golf swing movie is first photographed and relative time information is extracted from the photographed video according to the position of the golf club from the address posture to the finishing posture. Through applying time information from learners' swing video to a 3D reference model that rigs the motion information of a pro-golfer's captured swing motion at 120 frames per second through high-quality motion capture equipment into a 3D model and by synchronizing the 3D reference model with the learner's swing video, the learner can correct or learn his / her posture by precisely comparing his or her posture with the reference model at each position of the golf swing. Synchronized playback can be used to improve the functionality of manually adjusting system for comparing and analyzing the reference model and learner's golf swing. Except for the part where the image processing technology that detects each position of the golf posture is applied, It is expected that the method of automatically extracting the time information of each location from the video and of synchronized playback can be extended to general life sports field.

A Study on the Habitat Mapping of Meretrix lyrata Using Remote Sensing at Ben-tre Tidal Flat, Vietnam (원격탐사를 활용한 베트남 Ben-tre 갯벌의 Meretrix lyrata 서식지 매핑 연구)

  • Hwang, Deuk Jae;Woo, Han Jun;Koo, Bon Joo;Choi, Jong-Kuk
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.975-987
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    • 2021
  • Potential habitat mapping of Meretrix lyrata which is found in large parts of South East Asian tidal flat was carried out to find out causes of collective death. Frequency Ratio (FR) method, one of geospatialstatistical method, was employed with some benthic environmental factors; Digital elevation model (DEM) made from Landsat imagery, slope, tidal channel distance, tidal channel density, sedimentary facesfrom WorldView-02 image. Field survey was carried out to measure elevation of each station and to collect surface sediment and benthos samples. Potential habitat maps of the all clams and the juvenile clams were made and accuracy of each map showed a good performance, 76.82 % and 69.51 %. Both adult and juvenile clams prefer sand dominant tidal flat. But suitable elevation of adult clams is ranged from -0.2 to 0.2 m, and that of juvenile clams is ranged from 0 to 0.3 m. Tidal channel didn't affect the habitat of juvenile clams, but it affected the adult clams. In the furtherstudy, comparison with case of Korean tidal flat will be carried out to improve a performance of the potential habitat map. Change in the benthic echo-system caused by climate change will be predictable through potential habitat mapping of macro benthos.

Hand Motion Recognition Algorithm Using Skin Color and Center of Gravity Profile (피부색과 무게중심 프로필을 이용한 손동작 인식 알고리즘)

  • Park, Youngmin
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.411-417
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    • 2021
  • The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

Comparative Analysis of CNN Deep Learning Model Performance Based on Quantification Application for High-Speed Marine Object Classification (고속 해상 객체 분류를 위한 양자화 적용 기반 CNN 딥러닝 모델 성능 비교 분석)

  • Lee, Seong-Ju;Lee, Hyo-Chan;Song, Hyun-Hak;Jeon, Ho-Seok;Im, Tae-ho
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.59-68
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    • 2021
  • As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

Prediction of Land Surface Temperature by Land Cover Type in Urban Area (도시지역에서 토지피복 유형별 지표면 온도 예측 분석)

  • Kim, Geunhan
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.1975-1984
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    • 2021
  • Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

Improved Compressive·Flexural Performance of Hybrid Fiber-Reinforced Mortar Using Steel and Carbon Fibers (강 및 탄소 섬유를 사용한 하이브리드 섬유보강 모르타르의 압축·휨성능 향상)

  • Heo, Gwang-Hee;Park, Jong-Gun;Seo, Dong-Ju;Koh, Sung-Gon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.25 no.5
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    • pp.48-59
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    • 2021
  • In this study, experiments were conducted to investigate the compressive·flexural performances of single fiber-reinforced mortar (FRM) using only steel fiber or carbon fiber which has different material properties as well as hybrid FRM using a mixture of steel and carbon fibers. The mortar specimens incorporated steel and carbon fibers in the mix proportions of 1+0%, 0.75+0.25%, 0.5+0.5%, 0.25+0.75% and 0+1% by volume at a total volume fraction of 1.0%. Their mechanical performance was compared and examined with a plain mortar without fiber at 28 days of age. The experiments of mortar showed that the hybrid FRM using a mixture of 0.75% steel fibers + 0.25% carbon fibers had the highest compressive and flexural strength, confirming by thus the synergistic reinforcing effect of the hybrid FRM. On the contrast, in the case of hybrid FRM using a mixture of 0.5% steel fibers + 0.5% carbon fibers witnessed the highest flexural toughness, suggesting as a result the optimal fiber mixing ratio of hybrid FRM to improve the strength and flexural toughness at the same time. Moreover, the fracture surface was observed through a scanning electron microscope (SEM) for image analysis of the FRM specimen. These results were of great help for images analysis of hybrid reinforcing fibers in cement matrix.

A Study on Photovoltaic Panel Monitoring Using Sentinel-1 InSAR Coherence (Sentinel-1 InSAR Coherence를 이용한 태양광전지 패널 모니터링 효율화 연구)

  • Yoon, Donghyeon;Lee, Moungjin;Lee, Seungkuk
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.233-243
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    • 2021
  • Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

A Study on the Effect of Artificial Cutting Slot on the Fragmentation and Vibration Propagation in the Full-scaled Concrete Block Blasting (콘크리트 블록 발파 실험을 통한 인공 슬롯 자유면이 진동전파 및 파쇄효과에 미치는 영향에 관한 연구)

  • Oh, Se-Wook;Min, Gyeong-Jo;Park, Se-Woong;Park, Hoon;Noh, You-Song;Suk, Chul-Gi;Cho, Sang-Ho
    • Tunnel and Underground Space
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    • v.28 no.6
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    • pp.692-705
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    • 2018
  • Ground vibration is one of the remarkable issues in tunnel blasting. In recent studies, to improve the fragmentation with reduction of ground vibration in tunnel blasting, a vibration-controlled blasting method with artificial cutting slot near the center-cut holes has been suggested. This study examines the effect of the different arrangement of artificial cut-slot on the vibration reduction and fragmentation by performing the full-scaled concrete block blast experiments and the numerical simulations with 3D-DFPA. The results show that the existence of artificial slot contributes to the improvement of vibration reduction, blast fragmentation and the efficiency of the cutting slot blast. It can be explained that the artificial slot play a free surface role and should decrease the burden between the cut holes. Crater volumes of the blasted concrete blocks were measured by 3-dimensional digital image analysis and compared with the ideal standard crater volume which can be calculated by theoretical standard blast design method. As a result, the ratio of burden and hole diameter which should achieve the standard crater in the cut-hole blasting were suggested.

Dual CNN Structured Sound Event Detection Algorithm Based on Real Life Acoustic Dataset (실생활 음향 데이터 기반 이중 CNN 구조를 특징으로 하는 음향 이벤트 인식 알고리즘)

  • Suh, Sangwon;Lim, Wootaek;Jeong, Youngho;Lee, Taejin;Kim, Hui Yong
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.855-865
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    • 2018
  • Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.