• Title/Summary/Keyword: IT융합

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Entropy-Based 6 Degrees of Freedom Extraction for the W-band Synthetic Aperture Radar Image Reconstruction (W-band Synthetic Aperture Radar 영상 복원을 위한 엔트로피 기반의 6 Degrees of Freedom 추출)

  • Hyokbeen Lee;Duk-jin Kim;Junwoo Kim;Juyoung Song
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1245-1254
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    • 2023
  • Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

Study on Disaster Response Strategies Using Multi-Sensors Satellite Imagery (다종 위성영상을 활용한 재난대응 방안 연구)

  • Jongsoo Park;Dalgeun Lee;Junwoo Lee;Eunji Cheon;Hagyu Jeong
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.755-770
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    • 2023
  • Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

Development of future education programs through edutech utilization programs (에듀테크 활용 프로그램을 통한 미래교육 프로그램 개발)

  • Lee Min-hye
    • Journal of the International Relations & Interdisciplinary Education
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    • v.2 no.2
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    • pp.81-95
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    • 2022
  • The core of this study is to develop an edutech utilization program to be applied to 5th grade students by utilizing school curriculum time, and the conclusions based on the results of the study are as follows. First, for the development of future educational programs using edutech, a content preference survey was conducted and significant responses were confirmed from 27 teachers and 216 students, excluding missing values. In the future education implementation, UCC (video shooting, editing, etc.) and work activities (3D pen, 3D printer, etc.) were selected based on the need for separate edtech devices. Second, in order to develop a future education program using edutech, the future education class module was set in 4 stages based on previous research. First of all, in Make a foundation, theories by subject are developed, and in Open an activity, future education experience activities using key edutech are developed. In Organize evaluation, individual self-evaluation was conducted, and based on this, customized in-depth supplementary activities were conducted in Act individually. Third, in order for future education programs using edutech to be organized in the regular curriculum, sufficient connectivity with the curriculum must be secured. The basis for systematic and stable research was prepared by analyzing the curriculum of the 5th grade subject of the study and securing hours in connection with creative experiential activities. The data developed through this process were modified and supplemented based on the content validity test. The fact that the program application and verification steps were not performed is a limitation of this study, but it is expected that this program will expand the possibility of future education practice in the school field.

National Disaster Management, Investigation, and Analysis Using RS/GIS Data Fusion (RS/GIS 자료융합을 통한 국가 재난관리 및 조사·분석)

  • Seongsam Kim;Jaewook Suk;Dalgeun Lee;Junwoo Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.743-754
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    • 2023
  • The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

Methodology for Developing a Predictive Model for Highway Traffic Information Using LSTM (LSTM을 활용한 고속도로 교통정보 예측 모델 개발 방법론)

  • Yoseph Lee;Hyoung-suk Jin;Yejin Kim;Sung-ho Park;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.1-18
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    • 2023
  • With the recent developments in big data and deep learning, a variety of traffic information is collected widely and used for traffic operations. In particular, long short-term memory (LSTM) is used in the field of traffic information prediction with time series characteristics. Since trends, seasons, and cycles differ due to the nature of time series data input for an LSTM, a trial-and-error method based on characteristics of the data is essential for prediction models based on time series data in order to find hyperparameters. If a methodology is established to find suitable hyperparameters, it is possible to reduce the time spent in constructing high-accuracy models. Therefore, in this study, a traffic information prediction model is developed based on highway vehicle detection system (VDS) data and LSTM, and an impact assessment is conducted through changes in the LSTM evaluation indicators for each hyperparameter. In addition, a methodology for finding hyperparameters suitable for predicting highway traffic information in the transportation field is presented.

Effect of Parental Support for Multicultural Youth on Career Attitude Determinism: Mediating Effect of Bicultural Acceptance Attitude (다문화 청소년에 대한 부모 지지가 진로 태도 결정성에 미치는 영향: 이중문화 수용 태도의 매개효과)

  • In-Suk Jeong
    • Industry Promotion Research
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    • v.8 no.4
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    • pp.91-99
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    • 2023
  • The purpose of this study was to confirm the determination of the career attitude of multicultural youth, which will be the growth engine of Korean society in the future, and to determine the effect of parental support for multicultural youth on career attitude determination. Multicultural adolescents experience more difficulties in parental support and career attitude determination than ordinary adolescents due to confusion over biculturalism exposed at birth. Therefore, this study confirmed the effect of parental support of multicultural adolescents on career attitude determination and verified the effect of bicultural acceptance attitude. To this end, data from the 8th year of the Multicultural Youth Panel (MAPS) conducted by the Korea Youth Policy Institute were used, and a total of 1,229 multicultural teenagers in the 2nd year of high school participated in the study. For data analysis, frequency analysis, descriptive statistical analysis, correlation analysis, path model suitability verification, path model coefficient, and mediating effect verification were conducted. Based on the results of these studies, it was intended to provide basic data for developing an integrated program that improves parental support and career attitude determination of multicultural adolescents.

Recent Trends in Cryptanalysis Techniques for White-box Block Ciphers (화이트 박스 블록 암호에 대한 최신 암호분석 기술 동향 연구)

  • Chaerin Oh;Woosang Im;Hyunil Kim;Changho Seo
    • Smart Media Journal
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    • v.12 no.9
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    • pp.9-18
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    • 2023
  • Black box cryptography is a cryptographic scheme based on a hardware encryption device, operating under the assumption that the device and the user can be trusted. However, with the increasing use of cryptographic algorithms on unreliable open platforms, the threats to black box cryptography systems have become even more significant. As a consequence, white box cryptography have been proposed to securely operate cryptographic algorithms on open platforms by hiding encryption keys during the encryption process, making it difficult for attackers to extract the keys. However, unlike traditional cryptography, white box-based encryption lacks established specifications, making challenging verify its structural security. To promote the safer utilization of white box cryptography, CHES organizes The WhibOx Contest periodically, which conducts safety analyses of various white box cryptographic techniques. Among these, the Differential Computation Analysis (DCA) attack proposed by Bos in 2016 is widely utilized in safety analyses and represents a powerful attack technique against robust white box block ciphers. Therefore, this paper analyzes the research trends in white box block ciphers and provides a summary of DCA attacks and relevant countermeasures. adhering to the format of a research paper.

Learning Flow and Problem-solving Confidence of Nursing Students Experienced Team-based Nursing Practice Learning: The Mediating Effect of Perceived Interactivity (팀기반 실습 수업을 경험한 간호대학생의 학습몰입과 문제해결 자신감: 인지된 상호작용의 매개효과)

  • Hyunsim Kim;Ju-Young Hong
    • Journal of Industrial Convergence
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    • v.21 no.11
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    • pp.57-65
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    • 2023
  • This study was attempted to verify the mediating effect of perceived interaction in the relationship between learning flow and problem-solving confidence of nursing students who experienced team-based nursing practice learning. The subjects of this study were 148 senior nursing students who experienced team-based nursing practice learning classes. Data were collected using a structured questionnaire. For data analysis, descriptive statistics, Pearson correlation analysis, hierarchical multiple regression analysis, and Sobel test were conducted. The results of the study showed that nursing students' learning flow was 3.58±0.56 points, perceived interaction was 4.06±0.56 points, and problem-solving confidence was 3.67±0.53 points on average. Learning flow of nursing students showed a positive correlation with perceived interaction(r=0.63, p<.001) and problem-solving confidence(r=0.74, p<.001). Perceived interaction showed a partial mediating effect in the relationship between learning flow and problem-solving confidence(z=5.31, p<.001). It may be necessary to develop programs to improve nursing students' learning flow, perceived interaction, and problem-solving confidence, and to improve their clinical practice ability to solve nursing problems in various nursing settings.

The Effect of Forest Experience Program on the Lung Capacity, Health & Fitness, Emotional Intelligence, and Psychological Well-being of Local Children (숲 체험 프로그램이 지역아동의 폐활량과 건강체력, 감성지능, 심리적 안녕감에 미치는 효과)

  • Ju-Young Lee
    • Journal of Industrial Convergence
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    • v.21 no.11
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    • pp.135-145
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    • 2023
  • The purpose of this study is to investigate the effect of a forest experience program on the lung capacity, health & fitness, emotional intelligence, and psychological well-being of local children.This study was conducted on 3rd and 4th grade elementary school students for 12 weeks from July 10 to September 30, 2022, at a local children's center in D City. Changes were analyzed and verified using t-test. Verified. The changes in the lung capacity, health & fitness, emotional intelligence, and psychological well-being of the experimental group and the control group were analyzed and verified using t-test.For the changes in lung capacity and health & fitness, there was a statistically significant difference between the control group and the experimental group in lung capacity (t=24.56, p<.05), and there was also a statistically significant difference between the two groups in cardiorespiratory endurance among the elements of health & fitness (t=16.64, p<.05). As for the changes in emotional intelligence and psychological well-being, there was statistically significant differences between the experimental group and the control group in the emotional intelligence (t=2.31, p<.05) and in psychological well-being (t=3.21, p<.05). Through this study, the positive effects of the forest experience program were confirmed, and it is believed that institutional arrangements are needed to improve children's participation conditions by expanding forest experience education spaces and developing customized forest experience programs to suit the characteristics of the region.

Examination of Aggregate Quality Using Image Processing Based on Deep-Learning (딥러닝 기반 영상처리를 이용한 골재 품질 검사)

  • Kim, Seong Kyu;Choi, Woo Bin;Lee, Jong Se;Lee, Won Gok;Choi, Gun Oh;Bae, You Suk
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.6
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    • pp.255-266
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    • 2022
  • The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.