• Title/Summary/Keyword: Intelligence Based Society

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Development of Rotating Equipment Anomaly Detection Algorithm based-on Artificial Intelligence (인공지능 기반 회전기기 이상탐지 알고리즘 개발)

  • Jeon, Yechan;Lee, Yonghyun;Kim, Dong-Ju
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.57-60
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    • 2021
  • 본 논문에서는 기지 설비 중 주요 회전기기인 펌프의 이상탐지 알고리즘을 제안한다. 현재 인공지능을 활용하여 생산현장을 혁신하고자 하는 시도가 진행되고 있으나 외산 솔루션에 대한 의존도가 높은 것에 비해 국내 실정에 맞지 않는 경우가 많다. 이에 따라, 선행 연구를 통해 국내 실정에 맞는 인공지능 기술 도입이 필요하다. 본 연구에서는 VAE(Variational Auto Encoder) 알고리즘을 활용해 회전기기의 고장을 진단하는 알고리즘을 개발하였다. 본 연구 수행을 통한 회전기기의 고장 예지·진단 시스템 개발로 설비의 이상 징후 포착, 부품의 교환 시기 등 보수 일정을 예측하고 최종적으로 이를 통한 설비 가동의 효율 증대와 에너지 비용 감소의 효과를 기대한다.

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Construction of Korean symptom articulation data using rule-based data augmentation technique (규칙기반 데이터 증강기법을 활용한 한국어 증상발화 데이터 구축)

  • Seong-Won Jeon;Dong-Jun Lee;Dong-Ho Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.360-362
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    • 2023
  • 건강정보 검색 요구가 증가하면서 다양한 건강정보 검색 서비스가 제공되고 있다. 하지만 최근의 건강정보 검색 서비스는 정형화 된 전문적인 의료정보와 그 해석을 제공하기 때문에 사용자는 이러한 정보를 스스로 이해하여 원하는 건강정보를 검색해야 한다. 사용자의 검색 피로를 줄이고 원하는 정보를 정확하게 얻을 수 있는 건강정보 검색 시스템 개발을 위하여 사용자의 비의료적 표현인 한국어 증상발화 데이터 구축이 선행되어야 한다. 이러한 데이터 구축은 많은 시간과 비용이 필요하기 때문에 이를 줄이기 위한 규칙기반 데이터 증강기법을 제시하고, 이를 활용하여 한국어 증상발화 데이터를 증강하였다. 증강된 데이터의 유효성을 보이기 위하여 KoBERT 기반의 증상분류 실험을 진행하였으며, 증강된 데이터가 그 전의 데이터보다 F1 스코어가 더 높음을 확인할 수 있었다.

Artificial Intelligence-based Crack Segmentation Algorithm for Safety diagnosis of old buildings (노후 건축물 안전진단을 위한 AI기반 균열 구획화 알고리즘)

  • Hee Ju Seo;Byeong Il Hwang;Dong Ju Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.13-14
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    • 2023
  • 집중 안전 점검의 대상인 노후 건축물에서 균열은 건물의 안전도를 점검할 수 있는 지표이다. 안전 점검에 드론을 활용하면서 고해상도의 드론 기반 균열 이미지 수집이 가능해졌고, 육안이 아닌 AI기반으로 균열을 탐지, 구획화할 수 있다. 본 연구에서는 주변 사물과 배경에 구애받지 않고 안전 점검이 가능한 구획화 알고리즘을 제안한다. METU와 POC데이터셋을 가공하여 데이터셋을 구축하고, 이를 바탕으로 ResNet50을 통해 균열과 유사한 배경을 분류하였으며, 균열 구획화 모델을 선정하여 DesneNet201-UNet++으로 mIoU 82.27%를 달성하였다. 본 연구는 노후 건축물 안전 점검에 필요한 균열 폭 추정에 도움이 될 것으로 기대된다.

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Analysis of major research trends in artificial intelligence based on domestic/international patent data (국내외 특허데이터 기반의 인공지능분야 기술동향 분석)

  • Chung, Myoung Sug;Jeong, So-Hee;Lee, Joo Yeoun
    • Journal of Digital Convergence
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    • v.16 no.6
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    • pp.187-195
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    • 2018
  • Recently, the 4th industrial revolution has emerged as the core for enhancing national competitiveness, the development of a technology roadmap to efficiently develop related technologies to realize super intelligence as a main feature of the 4th Industrial Revolution is a major task has been highlighted. The objective of this study is to analyze the domestic and foreign technology level in the artificial intelligence field which is the core technology of the 4th Industrial Revolution era and to present the direction of development based on this. The keyword network analysis and the blank technical analysis based on the IPC classification were performed on the data derived from the keyword search of 'AI (Artificial Intelligence)' among domestic and foreign patent data. As a result, the number of domestic artificial intelligence related technology development was 1.2% compared with developed countries such as USA and Europe. In the major development fields, data recognition technology and digital information transmission technology were relatively insufficient. Through this study, we obtained the blank technology as a result of comparative analysis of domestic artificial intelligence related technologies compared to advanced countries and suggested the direction of domestic artificial intelligence technology development in future.

A Study on the Artificial Intelligence Ethics Measurement indicators for the Protection of Personal Rights and Property Based on the Principles of Artificial Intelligence Ethics (인공지능 윤리원칙 기반의 인격권 및 재산보호를 위한 인공지능 윤리 측정지표에 관한 연구)

  • So, Soonju;Ahn, Seongjin
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.111-123
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    • 2022
  • Artificial intelligence, which is developing as the core of an intelligent information society, is bringing convenience and positive life changes to humans. However, with the development of artificial intelligence, human rights and property are threatened, and ethical problems are increasing, so alternatives are needed accordingly. In this study, the most controversial artificial intelligence ethics problem in the dysfunction of artificial intelligence was aimed at researching and developing artificial intelligence ethical measurement indicators to protect human personality rights and property first under artificial intelligence ethical principles and components. In order to research and develop artificial intelligence ethics measurement indicators, various related literature, focus group interview(FGI), and Delphi surveys were conducted to derive 43 items of ethics measurement indicators. By survey and statistical analysis, 40 items of artificial intelligence ethics measurement indicators were confirmed and proposed through descriptive statistics analysis, reliability analysis, and correlation analysis for ethical measurement indicators. The proposed artificial intelligence ethics measurement indicators can be used for artificial intelligence design, development, education, authentication, operation, and standardization, and can contribute to the development of safe and reliable artificial intelligence.

Artificial Intelligence Based Medical Imaging: An Overview (AI 의료영상 분석의 개요 및 연구 현황에 대한 고찰)

  • Hong, Jun-Yong;Park, Sang Hyun;Jung, Young-Jin
    • Journal of radiological science and technology
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    • v.43 no.3
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    • pp.195-208
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    • 2020
  • Artificial intelligence(AI) is a field of computer science that is defined as allowing computers to imitate human intellectual behavior, even though AI's performance is to imitate humans. It is grafted across software-based fields with the advantages of high accuracy and speed of processing that surpasses humans. Indeed, the AI based technology has become a key technology in the medical field that will lead the development of medical image analysis. Therefore, this article introduces and discusses the concept of deep learning-based medical imaging analysis using the principle of algorithms for convolutional neural network(CNN) and back propagation. The research cases application of the AI based medical imaging analysis is used to classify the various disease(such as chest disease, coronary artery disease, and cerebrovascular disease), and the performance estimation comparing between AI based medical imaging classifier and human experts.

Application of Artificial Intelligence-based Digital Pathology in Biomedical Research

  • Jin Seok Kang
    • Biomedical Science Letters
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    • v.29 no.2
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    • pp.53-57
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    • 2023
  • The main objective of pathologists is to achieve accurate lesion diagnoses, which has become increasingly challenging due to the growing number of pathological slides that need to be examined. However, using digital technology has made it easier to complete this task compared to older methods. Digital pathology is a specialized field that manages data from digitized specimen slides, utilizing image processing technology to automate and improve analysis. It aims to enhance the precision, reproducibility, and standardization of pathology-based researches, preclinical, and clinical trials through the sophisticated techniques it employs. The advent of whole slide imaging (WSI) technology is revolutionizing the pathology field by replacing glass slides as the primary method of pathology evaluation. Image processing technology that utilizes WSI is being implemented to automate and enhance analysis. Artificial intelligence (AI) algorithms are being developed to assist pathologic diagnosis and detection and segmentation of specific objects. Application of AI-based digital pathology in biomedical researches is classified into four areas: diagnosis and rapid peer review, quantification, prognosis prediction, and education. AI-based digital pathology can result in a higher accuracy rate for lesion diagnosis than using either a pathologist or AI alone. Combining AI with pathologists can enhance and standardize pathology-based investigations, reducing the time and cost required for pathologists to screen tissue slides for abnormalities. And AI-based digital pathology can identify and quantify structures in tissues. Lastly, it can help predict and monitor disease progression and response to therapy, contributing to personalized medicine.

Explanable Artificial Intelligence Study based on Blockchain Using Point Cloud (포인트 클라우드를 이용한 블록체인 기반 설명 가능한 인공지능 연구)

  • Hong, Sunghyuck
    • Journal of Convergence for Information Technology
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    • v.11 no.8
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    • pp.36-41
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    • 2021
  • Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

Text Mining-based Fake News Detection Using News And Social Media Data (뉴스와 소셜 데이터를 활용한 텍스트 기반 가짜 뉴스 탐지 방법론)

  • Hyun, Yoonjin;Kim, Namgyu
    • The Journal of Society for e-Business Studies
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    • v.23 no.4
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    • pp.19-39
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    • 2018
  • Recently, fake news has attracted worldwide attentions regardless of the fields. The Hyundai Research Institute estimated that the amount of fake news damage reached about 30.9 trillion won per year. The government is making efforts to develop artificial intelligence source technology to detect fake news such as holding "artificial intelligence R&D challenge" competition on the title of "searching for fake news." Fact checking services are also being provided in various private sector fields. Nevertheless, in academic fields, there are also many attempts have been conducted in detecting the fake news. Typically, there are different attempts in detecting fake news such as expert-based, collective intelligence-based, artificial intelligence-based, and semantic-based. However, the more accurate the fake news manipulation is, the more difficult it is to identify the authenticity of the news by analyzing the news itself. Furthermore, the accuracy of most fake news detection models tends to be overestimated. Therefore, in this study, we first propose a method to secure the fairness of false news detection model accuracy. Secondly, we propose a method to identify the authenticity of the news using the social data broadly generated by the reaction to the news as well as the contents of the news.

A Study on Concept of Chongmyeong and Chongmyeong-tang Based on Visual, Auditory Sense and Brain Science Based on Complex System (시각, 청각과 복잡계 기반 뇌과학에 근거한 총명개념과 총명탕 연구)

  • Jeon, Hong-Seok;Baek, Kyu-Tae;Jeon, Kyung-Bae;Kwon, Kang
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.30 no.4
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    • pp.104-130
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    • 2017
  • Objectives : This study was designed to signpost the study of brain, intelligence and memory, while interpreting the concept of 'Chongmyeong(聰明)' neotrically and linking it to the clinic of Korean medicine. Methods : In this paper, the meaning of the word 'Chongmyeong(聰明)' is divided into two parts, intelligence and memory. We also explored the relationship between brain science and 'Chongmyeong(聰明)' based on complex system theory, cognitive science and embodied cognition. Results : Through the process of refining the concept of 'Chongmyeong(聰明)' neoterically, we proposed the new method to understand the concept of 'Chongmyeong(聰明)'. Conclusions : The concept of 'Chongmyeong(聰明)' should be interpreted not as a reductionistic viewpoint of brain science but as a viewpoint of brain science based on visual and auditory system and complex system. Human cognition is physically embodied in the environment, from the viewpoint of embodied cognition that it is constituted and formed in an interactive context with society and culture connected with the environment.