• Title/Summary/Keyword: 자가진단모델

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Hair loss self-diagnosis application using deep learning (딥러닝 학습을 이용한 탈모 자가 진단 앱)

  • Ji, Kim Hyun;Yoon, Young-Don;Kim, Yu-Sung;Lee, Gun-Ho;Son, Bum-Su;Park, Joon-Ho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.451-452
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    • 2022
  • 본 논문에서는 딥러닝 영상인식 기술을 활용한 객체검출 모델인 YOLOv4를 활용하여 탈모 자가 진단 앱을 제안한다. 본 논문에서 제안하는 앱은 실시간 영상처리기술인 YOLOv4를 사용하여 탈모 유무와 탈모 유형에 대해 학습을 하고, 앱에서 사용자가 자신의 이마 라인을 촬영하여 사진이 서버에 전송이 되고 서버에서 학습된 모델을 이용하여 검출된 탈모 유무 판단과 탈모 단계 판단의 결과값을 다시 앱으로 전송한다. 탈모에 대한 정확한 진단을 통하여 치료 방법과 치료 시기 결정에 대하여 도움을 줄 것으로 기대된다.

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A Diagnosis Engine Using Bayesian Network for Self-management of Adaptive Middleware (적응형 미들웨어의 자가 진단을 위한 베이지안 네트워크를 사용한 진단엔진)

  • Choi Bo-Yoon;Kim Kyung-Joong;Cho Sung-Bae
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.220-222
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    • 2006
  • 분산 어플리케이션은 동시에 여러 사용자가 각기 다른 환경에서 동기화된 프로세서를 사용하기 때문에 일정 한 성능을 유지하는 것이 무엇보다 중요하다. 진단엔진은 시스템을 진단하여 시스템 결함의 원인을 발견하여 시스템이 자가치료가 가능하게 한다. 적응형 미들웨어는 진단엔진을 사용해서 분산 어플리케이션이 로컬환경에 맞는 고른 서비스를 유지 할 수 있도록 한다. 본 논문은 베이지안 네트워크를 사용한 적응형 미들웨어의 진단엔진을 제안한다. 베이지안 네트워크는 상황인지분야에서 널리 사용되는 추론기법으로서, 수집 된 데이터를 통해서 그 구조를 학습하고 데이터를 증거 값으로 시스템 진단을 한다. 본 논문은 실험 대상자로부터 윈도우시스템에서 두 시간 동안 데이터를 수집하여 한 시간은 베이지안 네트워크 학습에 사용하고, 나머지는 베이지안 네트워크 성능평가에 사용하였다. 실험 결과 학습된 두 개의 베이지안 네트워크 모델은 각각 95.41%, 99.77%의 정확성을 보였다.

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An Exploratory Study for Development of Self Diagnose Scale on the Healthy Family - Uses the GAMMA Model - (건강한 가정만들기를 위한 자가진단 척도 개발의 기초연구 - 감마모델을 중심으로 -)

  • Kim, Sung-Hee
    • Journal of Family Resource Management and Policy Review
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    • v.11 no.4
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    • pp.55-71
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    • 2007
  • The purpose of this study was to explore a self-diagnostic indicator for measuring a healthy family by adopting the theme of "happiness", which has surfaced as the most interesting in many academic fields recently. Though the basic concept of a healthy family may be shared by everyone, the criterion of happiness varies from one family to another. Therefore, it is desirable that the tool be made in such a way that every member of the family can check their health from a holistic perspective, rather than diagnosing health and happiness from the perspective of professionals. So, this study was aimed at diagnosing a family by using a tool named GAMMA model, so each family member can recognize problems and find the best options to solve it. This study. has a significant meaning in that it has tried to diagnose families by introducing the GAMMA model into domestic science for the first time.

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A Study on the Evaluation of Public Librarian's Core Competency Value (공공도서관 사서의 공통역량 평가에 관한 연구)

  • Park, Heejin;Kim, Jinmook;Cha, Sung-Jong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.32 no.1
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    • pp.335-360
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    • 2021
  • This study aimed to develop self-diagnosis tools to evaluate the common competence level of public library librarians, apply them to actual public library librarians, and analyze the factors of competency value evaluation through empirical research methods. To this end, the study modify the existing capacity value evaluation indicators of librarians from a public library perspective and conducted a survey to self-diagnose the common capabilities of public library librarians. As the results of analysis showed that librarians of public libraries themselves think that the level of core competence that professional librarians should acquire is relatively higher than the average. Among the overall capabilities of librarians, the average of the 'librarians' behavior and attitude' area was the highest, followed by the 'librarians' skill' and 'librarian's knowledge' areas. The study suggested to strengthen the capacity of public library librarians for various duties, the re-education system for librarians should be established, and a systematic system for promoting librarians' duties as professionals, and a personnel system for professional development.

Comparative Study of AI Models for Reliability Function Estimation in NPP Digital I&C System Failure Prediction (원전 디지털 I&C 계통 고장예측을 위한 신뢰도 함수 추정 인공지능 모델 비교연구)

  • DaeYoung Lee;JeongHun Lee;SeungHyeok Yang
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.6
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    • pp.1-10
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    • 2023
  • The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

An Exploration of Career Competency Mobility Map (CCMM) Focusing on Engineering Students in K University (경력역량이동지도(CCMM) 적용사례 연구: K 대학을 중심으로)

  • Park, Jiwon;Woo, Heajung;Noh, Kyungwon;Yi, Yejih;Hwang, Seong-jun;Kim, Woocheol
    • Journal of Practical Engineering Education
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    • v.11 no.2
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    • pp.195-206
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    • 2019
  • Accelerated technological advances and the convergence of information and communication technologies have led to changes of career concepts from one of lifetime employment to that of lifetime career. Given the importance of continuous career development for workers these days, systematic supports for workers' career development at the national level is necessary. Accordingly, a conceptual model of career competency mobility map (CCMM) has been proposed to support the development of workers' career competencies. The purpose of this study is to identify key issues that we should consider for real implementation by applying to each stage of the CCMM conceptual model as a case study. Based on the procedure presented in the conceptual model, the research process which includes collecting user information, conducting self-diagnosis of NCS-based job competencies, deriving necessary training competency, offering the guidance of training programs and job information were conducted. The results of the case study showed our participants' scores of competencies required further development and ranged from 1.83 to 4.52. Sequentially, a personalized information profile was offered for competency development, including training, certificates, and job information. Participants stated that the diagnosis results and profiles were meaningful and helped to explore further career development. Based on the results, implications are suggested.

The Classification Scheme of ADHD for children based on the CNN Model (CNN 모델 기반의 소아 ADHD 분류 기법)

  • Kim, Do-Hyun;Park, Seung-Min;Kim, Dong-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.5
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    • pp.809-814
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    • 2022
  • ADHD is a disorder showing inattentiveness and hyperactivity. Since symptoms diagnosed in childhood continue to the adulthood, it is important to diagnose ADHD and start treatments in early stages. However, it has the problems to acquire enough and accurate data for the diagnosis because the mental state of children is immature using the self-diagnosis method or the computerized test. In this paper, we present the classification method based on the CNN model and execute experiment using the EEG data to improve the objectiveness and the accuracy of ADHD diagnosis. For the experiment, we build the 3D convolutional networks model and exploit the 5-folds cross validation method. The result shows the 97% accuracy on average.

A Study on Creating a Dataset(G-Dataset) for Training Neural Networks for Self-diagnosis of Ocular Diseases (안구 질환 자가 검사용 인공 신경망 학습을 위한 데이터셋(G-Dataset) 구축 방법 연구)

  • Hyelim Lee;Jaechern Yoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.580-581
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    • 2024
  • 고령화 사회에 접어들면서 황반 변성과 당뇨 망막 병증 등 시야결손을 동반하는 안구 질환의 발병률은 증가하지만 이러한 질환의 조기 발견에 인공지능을 접목시킨 연구는 부족한 실정이다. 본 논문은 안구 질환 자가 검사용 인공 신경망을 학습시키기 위한 데이터 베이스 구축 방법을 제안한다. MNIST와 CIFAR-10을 합성하여 중첩 이미지 데이터셋인 G-Dataset을 생성하였고, 7개의 인공신경망에 학습시켜 최종적으로 90% 이상의 정확도를 얻음으로 그 유효성을 입증하였다. G-Dataset을 안구 질환 자가 검사용 딥러닝 모델에 학습시켜 모바일 어플에 적용하면 사용자가 주기적인 검사를 통해 안구 질환을 조기에 진단하고 치료할 수 있을 것으로 기대된다.

Multi-Aspect Model based Self-Adaptive System (다중 모델 기반의 자가 적응형 시스템)

  • Lee, Sang-Hee;Jung, Chul-Ho;Lee, Eun-Seok
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.1161-1167
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    • 2006
  • 본 논문에서는 구조, 행위, 리소스, 환경의 여러 관점을 적용한 다양한 모델들을 이용하는 적응 프레임워크를 제안한다. 또한, 대상 시스템에 대해 앞에서 언급한 4 가지 모델을 위한 모델링 방법론과 각 모델링 요소들에 대한 효과적인 표기법을 제시하였다. 다양한 모델들을 통해 시스템의 구성 요소들 간의 관계 구조와 시스템의 계층적 상태와 행위 정보, 실행 환경을 구성하는 시스템 의존적인 요소 및 독립적인 요소까지의 정보들이 표현된다. 이들 모델간의 유기적인 상호 운용으로 통합적인 추론과 보다 정확한 평가가 가능하다. 이를 통해 시스템은 예상치 못한 변화에 대해 통합된 관점의 더욱 정확한 진단과 반영할 수 있다. 이를 기반으로 다양한 수준에서 적응 동작의 조절을 수행함으로써 하이브리드하고 보다 확장된 적응이 가능해진다. 논문에서 정의한 모델과 제안 프레임워크는 다른 도메인으로 재사용이 가능하다. 제안 시스템은 평가를 위해 프로토타입을 구현하여 원격 화상 회의 시스템에 적용하였으며, 그 기능과 유효성을 확인하였다.

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A Series of Rearch for the Theory of Self-estimating Internet Shopping-mall, Business model which uses BMO Estimating Model (BMO 평가모형을 이용한 인터넷 쇼핑몰 비즈니스모델 자가평가 방법론에 관한 사례 연구)

  • Eun, Jong-Seong;Min, Kyung-Se
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.2 no.2
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    • pp.49-68
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    • 2007
  • This paper develop self pre-checkup lists for the validity of business model as web business starters can utilize to open business. In particular, self pre-checkup lists invented by Dr. Bruce Merrifield, is reapplied and modified in appropriate to internet shopping mall business. This paper complete many literature reviews to identify appropriate factors of evaluation such as about the characters of internet business, business validity testing theory for internet business model, pros and cons of e-business and startup ventures, factor analysis of technology valuation, and pros and cons for internet shopping mall. This paper define six different factors; scale of sales, the growth rate of market, competitiveness, risk portfolio, industry upside down, and social conditions, as the factors of evaluating the business attractiveness. Meanwhile, it define characters of CEO, content's power, mutual inclusion, commerce, fulfillment, marketing power as the factors of business appropriateness. This paper also conducts several case studies; company I, D, G of applying the former model. This paper sort out internet business model in imaginations by utilizing self pre-checkup lists of business evaluation. Also, the outcomes of evaluation is expected to provide meaningful future business implications.

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