• Title/Summary/Keyword: Digital Network

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Deep survey using deep learning: generative adversarial network

  • Park, Youngjun;Choi, Yun-Young;Moon, Yong-Jae;Park, Eunsu;Lim, Beomdu;Kim, Taeyoung
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.78.1-78.1
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    • 2019
  • There are a huge number of faint objects that have not been observed due to the lack of large and deep surveys. In this study, we demonstrate that a deep learning approach can produce a better quality deep image from a single pass imaging so that could be an alternative of conventional image stacking technique or the expensive large and deep surveys. Using data from the Sloan Digital Sky Survey (SDSS) stripe 82 which provide repeatedly scanned imaging data, a training data set is constructed: g-, r-, and i-band images of single pass data as an input and r-band co-added image as a target. Out of 151 SDSS fields that have been repeatedly scanned 34 times, 120 fields were used for training and 31 fields for validation. The size of a frame selected for the training is 1k by 1k pixel scale. To avoid possible problems caused by the small number of training sets, frames are randomly selected within that field each iteration of training. Every 5000 iterations of training, the performance were evaluated with RMSE, peak signal-to-noise ratio which is given on logarithmic scale, structural symmetry index (SSIM) and difference in SSIM. We continued the training until a GAN model with the best performance is found. We apply the best GAN-model to NGC0941 located in SDSS stripe 82. By comparing the radial surface brightness and photometry error of images, we found the possibility that this technique could generate a deep image with statistics close to the stacked image from a single-pass image.

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Building the Irrigated Area and Canal Network of Agricultural Reservoir Based on High-Resolution Images (고해상도 영상기반 농업용 저수지 수혜면적 및 수로 네트워크 구축)

  • Yoon, Dong-Hyun;Nam, Won-Ho;Jung, In-Kyun;Bae, Kyoung-Ho;Cho, Jung-ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.29-29
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    • 2021
  • 최근 물 사용에 대한 각 부문 간의 경쟁이 심화되고 있으며, 미래 기후변화에 대응하기 위해 체계적이고 효율적인 수자원 활용이 요구되고 있다. 농업용수는 우리나라 수자원의 40% 이상을 차지하고 있지만, 생활용수, 공업용수와 달리 경험에 기반한 관행적 관리가 이루어지고 있어 체계적인 관리가 필요하다. 농업용수의 체계적 관리와 분석을 위해 최신화된 수혜면적 파악 및 수혜구역 내 수로 네트워크 구축은 필수적 요소이다. 현재 활용하고 있는 농업용 저수지 수혜면적 및 수로 자료는 한국농어촌공사의 RIMS 자료를 기반으로 하고 있다. 하지만 기존 자료의 경우 준공 당시 설계기준으로 작성되거나 수년 전 갱신된 자료로 최신현황을 반영하지 못하고 있다. 이러한 문제점을 보완하기 위해 직접 측량을 통한 자료 취득 또는 농림축산식품부의 스마트팜맵과 같은 대체, 보완자료가 활용되고 있다. 직접 측량의 경우 최신화된 정확한 자료 취득이 가능하지만, 많은 시간이 소요되며, 스마트팜맵의 경우 취득 주기가 1~2년으로 주기에 따라 최신자료의 활용이 어려울 수 있다. 본 연구에서는 자료 산정 시간 단축 및 최신자료 취득을 위해 고해상도 영상을 활용하고자 하였으며, 여주시 삼합저수지를 대상으로 검증하였다. 영상자료로는 위성영상, 항공영상, 드론영상을 활용하였으며, 위성영상의 경우 구글어스 프로의 2020년 11월 고해상도 영상, 국토리지정보원의 2019~2020년 51cm급 항공 영상, 2020년 10월 촬영한 4cm급 드론영상을 사용하였다. 수혜면적 산정은 기존 RIMS 자료와 스마트팜맵을 통해 확인한 수혜면적에서 영상을 통해 확인한 토지이용 변경지역을 추출하여 재산정하였으며, 수로 네트워크의 경우 RIMS 자료를 기반으로 드론영상을 통해 확인된 수로 추가 및 DEM (Digital Elevation Model) 영상을 활용한 용수 흐름도 작성을 통해 구축하였다. 본 연구에서 재산정한 수혜면적과 수로 네트워크는 정확한 용수 수요량 및 공급량 산정, 관개 효율 분석 등과 같은 농업용수 분석 전반에 기초자료로 활용 가능할 것으로 판단된다.

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Pediatricians' perception of factors concerning the clinical application of blockchain technology to pediatric health care: a questionnaire survey

  • Yong Sauk Hau;Min Cheol Chang;Jae Chan Park;Young Joo Lee;Seong Su Kim;Jae Min Lee
    • Journal of Yeungnam Medical Science
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    • v.40 no.2
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    • pp.156-163
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    • 2023
  • Background: Interest in digital medical information has increased because it allows doctors to easily access a patient's medical records and provide appropriate medical care. Blockchain technology ensures data safety, reliability, integrity, and transparency by distributing medical data to all users over a peer-to-peer network. This study attempted to assess pediatricians' thoughts and attitudes toward introducing blockchain technology into the medical field. Methods: This study used a questionnaire survey to examine the thoughts and attitudes of 30- to 60-year-old pediatricians regarding the introduction of blockchain technology into the medical field. Responses to each item were recorded on a scale ranging from 1 (never agree) to 7 (completely agree). Results: The scores for the intentions and expectations of using blockchain technology were 4.0 to 4.6. Pediatricians from tertiary hospitals responded more positively (4.5-4.9) to the idea of using blockchain technology for hospital work relative to the general population (4.3-4.7). However, pediatricians working in primary and secondary hospitals had a slightly negative view of the application of blockchain technology to hospital work (p=0.018). Conclusion: When introducing the medical records of related pediatric and adolescent patients using blockchain technology in the future, it would be better to conduct a pilot project that prioritizes pediatricians in tertiary hospitals. The cost, policy, and market participants' perceptions are essential factors to consider when introducing technology in the medical field.

Runoff Analysis Based on Rainfall Estimation Using Weather Radar (기상레이더 강우량 산정법을 이용한 유출해석)

  • Kim, Jin Geuk;Ahn, Sang Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1B
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    • pp.7-14
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    • 2006
  • The radar relationship was estimated for the selected rainfall event at Yeongchun station within Chungjudam basin where the discharge record was the range of from 1,000 CMS to 9,000 CMS. By calibrating the rainfall coefficient parameter estimated by radar relationship in small hydrology basin, rainfall with the topography properties was calculated. Three different rainfall estimation methods were compared:(1) radar relationship method (2) Thiessen method (3) Isohyetal method (4) Inverse distance method. Basin model was built by applying HEC-GeoHMS which uses digital elevation model to extract hydrological characteristic and generate river network. The proposed basin model was used as an input to HEC-HMS to build a runoff model. The runoff estimation model applying radar data showed the good result. It is proposed that the radar data would produce more rapid and accurate runoff forecasting especially in the case of the partially concentrated rainfall due to the atmospheric change. The proposed radar relationship could efficiently estimate the rainfall on the study area(Chungjudam basin).

Ashbery's Aesthetics of Difficulty: Information Theory and Hypertext

  • Ryoo, Gi Taek
    • Journal of English Language & Literature
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    • v.58 no.6
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    • pp.1001-1021
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    • 2012
  • This paper is concerned with John Ashbery's poetics of difficulty, questioning in particular the nature of communication in his difficult poems. Ashbery has an idea of poetry as 'information' to be transmitted to the reader. Meaning, however, is to be created by a series of selections among equally probable choices. Ashbery's poetry has been characterized by resistance to the interpretive system of meaning. But the resistance itself, as I will argue, can be an effective medium of communication as the communicated message is not simply transmitted but 'selected' and thus created by the reader. In Ashbery's poetry, disruptive 'noise' elements can be processed as constructive information. What is normally considered a hindrance or noise can be reversed and added to the information. In Ashbery's poems, random ambiguities or noises can be effectively integrated into the final structure of meaning. Such a stochastic sense of information transfer has been embodied in Ashbery's idea of creating a network of verbal elements in his poetry, analogous to the interconnecting web of hypertext, the most dynamic medium 'information technology' has brought to us. John Ashbery, whose poems are simultaneously incomprehensible and intelligent, employs ambiguities or noise in his poetry, with an attempt to reach through linear language to express nonlinear realities. It is therefore my intention to examine Ashbery's poetics of difficulty, from a perspective of communication transmission, using the theories of information technology and the principles of hypertext theory. Ashbery's poetry raises precisely the problem confronted in the era of communication and information technology. The paper will also show how his aesthetics of difficulty reflects the culture of our uncertain times with overflowing information. With his difficult enigmatic poems, Ashbery was able to move ahead of the technological advances of his time to propose a new way of perceiving the world and life.

Analysis of Water Distribution Network using Digital Data in Agricultural Watershed (농업용수 디지털 정보를 활용한 용수공급 네트워크 분석)

  • Shin, Ji-Hyeon;Nam, Won-Ho;Yoon, Dong-Hyun;Yang, Mi-Hye;Jung, In-Kyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.510-511
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    • 2022
  • 물관리기본법의 시행 및 제1차 국가물관리기본계획의 이행에 따라 물관리 자료의 정보화 요구가 증가하고 있다. 과거 농업용수관리는 기초자료의 오류, 계측데이터의 부족 등이 한계점으로 지적되었으며, 과학화·표준화된 농업용수 물수급 분석 체계 구축 및 물정보의 정확성이 요구된다. 최근 통합물관리 국가정책 대응을 위한 물수급 분석 기반 마련을 목적으로 한국농어촌공사에서는 농업용수 용 배수 계통 정밀조사, 공간자료 재구축 등을 통한 농업용수 디지털 정보체계 구축 사업이 진행되고 있다. 연속수치지형도 및 토지피복, 스마트팜맵 등의 디지털 공간자료를 수집하고 현장조사와 영농조사를 바탕으로 최신화된 용배수계통도, 수혜면적 자료를 구축하였다. 본 연구에서는 디지털화한 용배수계통도를 이용하여 수리해석 모델 기초자료를 구축하고, 들녘단위 (주·보조수원, 저수지 및 양수장 등) 용수계통도 구현함으로써 수원공별 용수공급 네트워크를 분석하고자 한다. 농업용수 공급체계 반영이 가능한 EPA-SWMM (United States Environmental Protection Agency Storm Water Management Model)을 활용하여 다양한 물공급 시나리오를 적용하여 최적의 물관리 방안을 제시하고자 한다. 본 연구에서는 경기도 안성시 고삼저수지를 대상으로 연속수치지형도, 농경지전자지도, 고해상도 DEM 등을 활용한 디지털 조사와 수로 표고, 길이 및 너비 등 현장조사를 수행하였으며, 현장 물관리 방안을 적용하여 물분배 모의가 가능한 EPA-SWMM 기반 수원공-용수로-수혜구역을 연결하는 용수공급 네트워크를 구축하였다. 농촌용수종합정보시스템 (Rural Agricultural Water Resource Information System, RAWRIS)에서 제공하는 계측 자료를 활용하여 관개기간의 강수량, 소비수량, 증발산량, 공급량 등을 적용하여 농업용수 공급량, 배분량을 추정하였다. 본 연구의 결과는 물관리 담당자에게 상세한 현행 용수공급량 및 용수공급체계 정보 제공과 향후 국가물관리기본계획, 농어촌용수이용합리화계획의 물수급 분석 기초자료로 활용 가능할 것으로 사료된다.

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Improvement of Current Legal System for Promoting Scientific Analysis and Utilization of Maritime Data (해사데이터의 과학적 분석 및 활용을 위한 현행 법제도 개선방안)

  • KwangHyun Lim;JongHwa Baek;DeukJae Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.304-305
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    • 2022
  • Recently, as digital communication technology is widely applied to the maritime field, large amounts of maritime data are being accumulated. Accordingly, attempts to create new value by applying data science and Artificial Intelligence(AI) technologies are emerging. Typically, Ministry of Oceans and Fisheries has been providing korean e-Navigation service since 2021 based on LTE-Maritime communication network, as well as R&D for creating value-added service through analyzing huge-sized maritime traffic data is underway. By the way, to do any data-based research, legal system, as a research infra, that researchers can get the data whenever they need is essential. This paper looked at types of data in maritime fields, checked related legal system about scientific analysis and utilization. It is confirmed that there are some legal factors which restrict its scientific analysis and utilization, and suggested ways of improvement to boost R&D using maritime data as a conclusion.

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Current State of Animation Industry and Technology Trends - Focusing on Artificial Intelligence and Real-Time Rendering (애니메이션 산업 현황과 기술 동향 - 인공지능과 실시간 렌더링 중심으로)

  • Jibong Jeon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.821-830
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    • 2023
  • The advancement of Internet network technology has triggered the emergence of new OTT video content platforms, increasing demand for content and altering consumption patterns. This trend is bringing positive changes to the South Korean animation industry, where diverse and high-quality animation content is becoming increasingly important. As investment in technology grows, video production technology continues to advance. Specifically, 3D animation and VFX production technologies are enabling effects that were previously unthinkable, offering detailed and realistic graphics. The Fourth Industrial Revolution is providing new opportunities for this technological growth. The rise of Artificial Intelligence (AI) is automating repetitive tasks, thereby enhancing production efficiency and enabling innovations that go beyond traditional production methods. Cutting-edge technologies like 3D animation and VFX are being continually researched and are expected to be more actively integrated into the production process. Digital technology is also expanding the creative horizons for artists. The future of AI and advanced technologies holds boundless potential, and there is growing anticipation for how these will elevate the video content industry to new heights.

Analysis of Korean Research Trends on Records Management Standards (기록관리표준에 관한 국내 연구동향 분석)

  • Sujin Heo;Sanghee Choi
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.351-373
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    • 2023
  • This study aimed to analyze and collect research trends of archival management standards in Korea. For this purpose, keywords from the titles, author keywords, and abstracts of papers related to records management standards were statistically analyzed to investigate the major keywords with high-frequency. Network analysis with high frequency keywords was also conducted to identify the subject areas of research in archival management standards. The analysis period is from 2000 to the present, and a total of 212 papers were collected from domestic academic paper search sites such as RISS and ScienceON. As a result of the analysis, from 2000 to 2010, OAIS for archive design, digital record preservation with OAIS, and analysis on ISO standards were mainly conducted in research areas. From 2011 until now, records management certification and ISAD(G)'s conversion to RiC emerged as new research areas. This study will be expected to be basic data to understand research trends in records management standards in Korea and to be a reference for research on records management standards studies.

Development of Deep Learning AI Model and RGB Imagery Analysis Using Pre-sieved Soil (입경 분류된 토양의 RGB 영상 분석 및 딥러닝 기법을 활용한 AI 모델 개발)

  • Kim, Dongseok;Song, Jisu;Jeong, Eunji;Hwang, Hyunjung;Park, Jaesung
    • Journal of The Korean Society of Agricultural Engineers
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    • v.66 no.4
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    • pp.27-39
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    • 2024
  • Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.