• 제목/요약/키워드: artificial categories

검색결과 182건 처리시간 0.024초

Gestures as a Means of Human-Friendly Communication between Man and Machine

  • Bien, Zeungnam
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.3-6
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    • 2000
  • In this paper, ‘gesture’ is discussed as a means of human-friendly communication between man and machine. We classify various gestures into two Categories: ‘contact based’ and ‘non-contact based’ Each method is reviewed and some real applications are introduced. Also, key design issues of the method are addressed and some contributions of soft-computing techniques, such as fuzzy logic, artificial neural networks (ANN), rough set theory and evolutionary computation, are discussed.

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규범적 표상의 방향성 효과 (The effect of orientation on recognizing object representation)

  • 정효선;이승복;정우현
    • 감성과학
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    • 제11권4호
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    • pp.501-510
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    • 2008
  • 규범적 표상은 단어나 주제가 주어졌을 때 자연스럽게 떠오르는 심상이다. 이러한 규범적 표상은 대상의 특징을 가장 잘 드러낼 수 있는 특정한 조망이나 방향으로 떠오르게 된다. 규범적 표상이 측면임을 시사하는 선행 연구를 바탕으로 본 연구에서는 규범적 표상의 방향성을 검토하였다. 규범적 표상을 자연범주와 인공범주로 구분하여 자극의 제시 방향에 따른 차이를 알아보았다. 실험은 그림의 방향성(왼쪽/오른쪽)과 범주(동물, 자연범주/도구, 인공범주)를 두 가지 독립변인으로 하여 설계하였으며 단어-그림 일치 판단과제를 사용하여 정답 반응률과 반응시간을 측정하였다. 그 결과, 정답 반응률은 범주 내에서 방향성에 따른 모든 조건에서 천장효과를 보였으며 아주 근소한 차이만 있었다. 반응시간에서 범주변인의 주효과, 범주와 방향성의 상호작용 효과가 나타났다. 특히 자연범주에 속하는 동물 그림에서 방향성 효과가 관찰되었다. 동물의 머리가 왼쪽으로 향하는 그림이 오른쪽으로 향하는 그림 보다 반응시간이 유의하게 빨랐다. 그러나 인공범주에 속하는 도구 그림에서는 방향성의 효과가 나타나지 않았다. 이러한 결과는 동물의 규범적 표상의 방향성은 왼쪽을 향하는 것임을 시사한다.

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A Study on Prediction of Business Status Based on Machine Learning

  • Kim, Ki-Pyeong;Song, Seo-Won
    • 한국인공지능학회지
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    • 제6권2호
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    • pp.23-27
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    • 2018
  • Korea has a high proportion of self-employment. Many of them start the food business since it does not require high-techs and it is possible to start the business relatively easily compared to many others in business categories. However, the closure rate of the business is also high due to excessive competition and market saturation. Cafés and restaurants are examples of food business where the business analysis is highly important. However, for most of the people who want to start their own business, it is difficult to conduct systematic business analysis such as trade area analysis or to find information for business analysis. Therefore, in this paper, we predicted business status with simple information using Microsoft Azure Machine Learning Studio program. Experimental results showed higher performance than the number of attributes, and it is expected that this artificial intelligence model will be helpful to those who are self-employed because it can easily predict the business status. The results showed that the overall accuracy was over 60 % and the performance was high compared to the number of attributes. If this model is used, those who prepare for self-employment who are not experts in the business analysis will be able to predict the business status of stores in Seoul with simple attributes.

요구사항 분석 및 아키텍처 정의 분야의 인공지능 적용 현황 및 방향 (Application of AI Technology in Requirements Analysis and Architecture Definition - status and prospects)

  • 김진일;염충섭;신중욱
    • 시스템엔지니어링학술지
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    • 제18권2호
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    • pp.50-57
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    • 2022
  • Along with the development of the 4th Industrial Revolution technology, artificial intelligence technology is also being used in the field of systems engineering. This study analyzed the development status of artificial intelligence technology in the areas of systems engineering core processes such as stakeholder needs and requirements definition, system requirement analysis, and system architecture definition, and presented future technology development directions. In the definition of stakeholder needs and requirements, technology development is underway to compensate for the shortcomings of the existing requirement extraction methods. In the field of system requirement analysis, technology for automatically checking errors in individual requirements and technology for analyzing categories of requirements are being developed. In the field of system architecture definition, a technology for automatically generating architectures for each system sector based on requirements is being developed. In this study, these contents were summarized and future development directions were presented.

농업에서의 ICT와 인공지능을 활용한 연구 개발 현황 조사 (A Survey of The Status of R&D Using ICT and Artificial Intelligence in Agriculture )

  • 강선호
    • 반도체디스플레이기술학회지
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    • 제22권1호
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    • pp.104-112
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    • 2023
  • Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.

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As how artificial intelligence is revolutionizing endoscopy

  • Jean-Francois Rey
    • Clinical Endoscopy
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    • 제57권3호
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    • pp.302-308
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    • 2024
  • With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.

분만통증 관련 간호요구에 대한 내용분석 (A Contents Analysis of Nursing Needs at Labor Pain)

  • 여정희;백설향
    • 여성건강간호학회지
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    • 제7권4호
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    • pp.499-507
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    • 2001
  • The purpose of this study was to explore nursing needs during labor pain that had been suffered by women who have given birth. It is essential to identify the nursing needs in order to solve nursing problems and to provide better care for the parturients. The sample consisted of 20 women of primiparas and 17 women of multiparas. They underwent normal labor and delivered a healthy baby at term. The data had been collected through the unstructured interviews conducted 1-2 days after delivery in the admission room from March 1998 to March 1999. On average, the interviews lasted for about 30 minutes. Interviews were taken with the consent of the subjects. The data are categorized according to the similarities of their contents. Seventeen subordinate categories and six superordinate categories have been identified. Six superordinate categories are 1) physical nursing needs 2) nursing needs of medical behavior 3) emotional nursing needs 4) informational and teaching nursing needs 5) nursing needs of pain control 6) nursing needs of respect(personality). Seventeen subordinate categories include: comfortable posture, touch, professional knowledge and techniques, duty execution, support, company and talk, stable surroundings, reassurance, information on delivery, explanation of medical behavior, information on surroundings, instruction on the case of pain, arbitrary adjustment, artificial adjustment, respect, interest and reflection of opinions. The result of this research is the same as that of foreign research and the items of the questionnaire in Korea are the same as the foreign one. Despite the same result, however, this dissertation is significant in that the research identifies the parturients nursing needs and classified the data and thus the basis has been formed to develop the tools to assess the nursing needs of the Korean parturients. The findings can be used as the guide for nursing intervention of parturients.

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인공지능 기반 구글넷 딥러닝과 IoT를 이용한 의류 분류 (Classification of Clothing Using Googlenet Deep Learning and IoT based on Artificial Intelligence)

  • 노순국
    • 스마트미디어저널
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    • 제9권3호
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    • pp.41-45
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    • 2020
  • 최근 4차 산업혁명 관련 IT기술 중에서 머신러닝과 딥러닝으로 대표되는 인공지능과 사물인터넷은 다양한 연구를 통해 여러 분야에서 우리 실생활에 적용되고 있다. 본 논문에서는 사물인터넷과 객체인식 기술을 활용한 인공지능을 적용하여 의류를 분류하고자 한다. 이를 위해 이미지 데이터셋은 웹캠과 라즈베리파이를 이용하여 의류를 촬영하고, 촬영된 이미지 데이터를 전이학습된 컨벌루션 뉴럴 네트워크 인공지능망인 구글넷에 적용하였다. 의류 이미지 데이터셋은 온전한 이미지 900개와 손상이 있는 이미지 900 그리고 총 1800개를 가지고 상하의 2개의 카테고리로 분류하였다. 분류 측정 결과는 온전한 의류 이미지에서는 약 97.78%의 정확도를 보였다. 결론적으로 이러한 측정결과와 향후 더 많은 이미지 데이터의 보완을 통해 사물인터넷 기반 플랫폼상에서 인공지능망을 활용한 여타 사물들의 객체 인식에 대한 적용 가능성을 확인하였다.

능동적 지능형 가상 비서의 사용자 경험 연구 : Google의 'Nest Hub Max'를 중심으로 (An User Experience of Proactive Intelligent Personal Assistant: Focusing on Google 'Nest Hub Max')

  • 조수경;김재엽
    • 디지털융복합연구
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    • 제18권9호
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    • pp.379-389
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    • 2020
  • 본 연구는 능동적 IPA(지능형 가상 비서)가 탑재된 Google의 Nest Hub Max의 사용 행태별 사용자 경험 분석을 위한 질적 연구이다. 근거이론 방법론에 착안하여, 한 달 동안 해당 기기를 사용한 6명의 연구 참여자를 대상으로 인터뷰를 진행하였다. 총 186개의 개념이 추출되었으며, 24개의 하위 범주와 11개의 상위 범주로 정리되었다. 개방 코딩을 통해 축 코딩을 이용한 패러다임 모형을 제시하였고 선택 코딩을 거쳐 사용 행태 유형을 구분하였다. 그 결과, 능동적 IPA의 소극적 사용자와 적극적 사용자 유형을 도출하였으며, 유형별 해당 기기의 사용자 경험을 분석하였다. 유형별 다른 사용 행태의 패러다임을 보였으나 결론적으로 소극적 사용자와 적극적 사용자는 모두 해당 기기의 능동적 IPA로부터 긍정적인 사용 경험을 유발하지 못하였다. 본 연구는 앞으로 출시될 능동적 IPA가 탑재된 기기 및 서비스의 사용자 경험 설계를 위한 기초 자료를 제시하였다.

실내공간에 사용되는 재활용 신재료의 소재 및 가공방법 연구 (A Study on the Base Material Specific and Processing Methods of Recycled New Materials in Space)

  • 서지은;정희정
    • 한국실내디자인학회논문집
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    • 제21권3호
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    • pp.22-30
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    • 2012
  • Nowadays the issue of environmental pollution and ecological destruction is not a simple issue but an important issue to be continuously considered. It is deemed that a study for recycled new materials is immediately required and this study is to analyze features and processing methods of new materials which can be used to interior space. We found the recycled new materials used for space through researching various web sits. And then we analyzed what the base materials are and classified that base materials are whether natural or artificial of the recycled materials. We classified processing methods of the recycled new materials after researching general processing methods. The result of this study would be an important material to the research and development of new finishing materials with consideration of environment and to the research for a guideline of applicable new materials. The results of this study are as follows : First, we could classify widely 2 categories into natural material and artificial material and then 10 subcategories into metal, glass, wood, rubber, stone, plastic, leather or fabric, ceramic, concrete and so on, and analyzed that which material is mostly used and whether it is single material or multiple material. In order to analyze the feature of processing method. Second, we could classify into 4 categories such as junction, surface process, molding, and insert, and found out which processing method is applied based on objects of research. Third, as an analysis result of the recycled new material feature, in order to develop various new materials, it is required to study on combination and application of 2 materials or more rather than single material. Four, as a analysis result of the processing method feature, I would like to suggest that development and application of various processing methods are required. Especially, it is necessary to grope for a way to develop new functional materials for interior space through a systemic research and analysis of processing method of other fields. Furthermore, a way to reuse recycled new materials should be considered in a stage of selection and application of processing method.

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