• Title/Summary/Keyword: Software Studies

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딥 러닝 기반의 영상처리 기법을 이용한 겹침 돼지 분리 (Separation of Occluding Pigs using Deep Learning-based Image Processing Techniques)

  • 이한해솔;사재원;신현준;정용화;박대희;김학재
    • 한국멀티미디어학회논문지
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    • 제22권2호
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    • pp.136-145
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    • 2019
  • The crowded environment of a domestic pig farm is highly vulnerable to the spread of infectious diseases such as foot-and-mouth disease, and studies have been conducted to automatically analyze behavior of pigs in a crowded pig farm through a video surveillance system using a camera. Although it is required to correctly separate occluding pigs for tracking each individual pigs, extracting the boundaries of the occluding pigs fast and accurately is a challenging issue due to the complicated occlusion patterns such as X shape and T shape. In this study, we propose a fast and accurate method to separate occluding pigs not only by exploiting the characteristics (i.e., one of the fast deep learning-based object detectors) of You Only Look Once, YOLO, but also by overcoming the limitation (i.e., the bounding box-based object detector) of YOLO with the test-time data augmentation of rotation. Experimental results with two-pigs occlusion patterns show that the proposed method can provide better accuracy and processing speed than one of the state-of-the-art widely used deep learning-based segmentation techniques such as Mask R-CNN (i.e., the performance improvement over Mask R-CNN was about 11 times, in terms of the accuracy/processing speed performance metrics).

Q-omics: Smart Software for Assisting Oncology and Cancer Research

  • Lee, Jieun;Kim, Youngju;Jin, Seonghee;Yoo, Heeseung;Jeong, Sumin;Jeong, Euna;Yoon, Sukjoon
    • Molecules and Cells
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    • 제44권11호
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    • pp.843-850
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    • 2021
  • The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

웹서비스 전략

  • 정철용
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2002년도 e-Biz World Conference
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    • pp.331-334
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    • 2002
  • Loosely coupled software components delivered over Internet standard technologies - SOAP over HTTP for transport - UDDI for registry and discovery - e-Business XML standards - Security and trust frameworks - Event notification(omitted)

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Real-Time Enterprise Management

  • Hadavi, K.Cyus
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2002년도 e-Biz World Conference
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    • pp.9-16
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    • 2002
  • Adexa is a leading provider of supply chain planning and collaboration software. Our iCollaboration solution is used by Global 2000 companies to create Real-time Enterprise Management solutions(omitted)

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오픈소스 모바일 UI컴포넌트 선정 절차 프레임워크 (The Framework of Selection Process for Open Source Mobile UI Component)

  • 손효정;이민규;성백민;김종배
    • 한국정보통신학회논문지
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    • 제18권11호
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    • pp.2593-2599
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    • 2014
  • 최근 모바일 앱에서도 오픈소스 소프트웨어를 이용한 개발이 활발하게 이루어지고 있다. 오픈소스 모바일 컴포넌트의 경우 사용자 인터페이스 구현을 위한 컴포넌트의 재사용성이 용이하다는 이유로 기능적 역할의 컴포넌트보다 더욱 많이 사용되는 경향이 있다. 이런 특징으로 인해 기존의 오픈소스 소프트웨어 선정절차나 상용 컴포넌트 선정절차 두 가지 연구 모두 오픈소스 모바일 컴포넌트 선정에 그대로 적용하기에는 무리가 있다. 본 논문에서는 기존에 연구된 오픈소스 소프트웨어 선정절차를 모바일 컴포넌트 선정에 적합하도록 수정, 보완하였다. 본 연구는 모바일 앱을 개발할 경우, 요구되는 기능을 충족하는 오픈소스 컴포넌트를 쉽게 검색하고 선정할 수 있는 효율적인 절차를 제시함으로써 모바일 앱 개발의 생산성을 높여줄 수 있다.