• Title/Summary/Keyword: 인공지능기기

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Analysis of Edu-Tech Trends Using Virtual and Augmented Reality (가상·증강현실을 활용한 에듀테크 동향 분석)

  • Hwang, Eui-Chul
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.115-116
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    • 2021
  • 5세대(5G) 이동통신망의 보급과 코로나19 여파로 비대면 시대가 열리면서 가상 증강현실(VR·AR)을 기반으로 한 '실감(XR·Extended Reality)경제가 본격화 되었다. 가상증강현실의 적용분야로는 게임·영화 등 엔터테인먼트, 제조업, 쇼핑 및 전자상거래, 병원·의료기기, 고객서비스, 지식서비스교육 분야 등이 있다. 본 논문은 VR·AR&교육콘텐츠를 키워드로 최근 3년(2018.1.1.~2020.12.31.)간 중앙지, 경제지 등 54개 언론사 기사를 빅카인즈와 데이터랩을 이용하여 관계도 분석, 월간 키워드 트렌드, 연관어 분석을 하였다. 'VR, AR, 에듀테크'를 키워드로 뉴스 검색결과 63,959건 중 '에듀테크' 검색결과 2018년 632건, 2019년 1043건, 2020년 2389건으로 해마다 급 상승하였다. '(AR+VR)AND 교육콘텐츠'에 대한 검색 결과 연관성(키워드 빈도수)이 높은 키워드로는 증강현실(120), 가상현실(116), 인공지능(114), 에듀테크(100), 코로나19(66), 실감형(65), 아이들(61), VR·AR(56), ICT(35), 빅데이터(25) 순으로 가상·증강현실 기술 발전, 코로나19의 장기화, 교육의 효율성으로 에듀테크 분야의 활용도가 급격히 증가함을 확인할 수 있었다.

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Strategies for Autonomous MUM-T Defense Industry (자율화 MUM-T 국방산업 전략)

  • Byungwoon Kim
    • Journal of Aerospace System Engineering
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    • v.17 no.2
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    • pp.56-61
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    • 2023
  • Recently, advancement of AI-enabled autonomous MUM-T combat system and industrial revitalization are rapidly emerging as global issues. However, the Defense Business Act of the Ministry of National Defense in Korea is judged to be somewhat insufficient compared to NATO leading countries in advancement of operation part of a weapon system as MUM-T is centered on a weapon system's own device. We established the concept of AI-enabled autonomous MUM-T to strengthen international competitiveness of complex combat systems such as future global UGV, UAV, and UMS. In addition, NATO and US-centered autonomy, interoperability, and data standardization-based defense AI MUM-T top-level platform construction and operation plan, establishment of a national defense innovation committee such as the National Science and Technology Advisory Council, review and advisory function reinforcement, and additional governance measures are proposed.

Research on Semiconductor Technology Roadmap by the Institute of Semiconductor Engineers (반도체공학회의 반도체 기술 발전 로드맵 연구 )

  • Hyunchol Shin;Ilku Nam;Jun-Mo Yang;Byung-Wook Min;Kyuho Lee;Chiweon Yoon;Jean Ho Song
    • Transactions on Semiconductor Engineering
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    • v.2 no.3
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    • pp.19-26
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    • 2024
  • Semiconductors are considered as one of the essential technologies in modern electronic devices and systems. Thus, it is required to predict and propose the semiconductor technology development roadmap. This study describes the key semiconductor technology issues, research and development trends, and their future roadmap, in the four areas such as the semiconductor device More-Moore integration technology, system-specific application processor technology, artificial intelligence/machine learning (AI/ML) processor technology, and outside system connectivity via optical and wireless communication.

Blood glucose prediction using PPG and DNN in dogs - a pilot study (개의 PPG와 DNN를 이용한 혈당 예측 - 선행연구)

  • Cheol-Gu Park;Sang-Ki Choi
    • Journal of Digital Policy
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    • v.2 no.4
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    • pp.25-32
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    • 2023
  • This paper is a study to develop a deep neural network (DNN) blood glucose prediction model based on heart rate (HR) and heart rate variability (HRV) data measured by PPG-based sensors. MLP deep learning consists of an input layer, a hidden layer, and an output layer with 11 independent variables. The learning results of the blood glucose prediction model are MAE=0.3781, MSE=0.8518, and RMSE=0.9229, and the coefficient of determination (R2) is 0.9994. The study was able to verify the feasibility of glycemic control using non-blood vital signs using PPG-based digital devices. In conclusion, a standardized method of acquiring and interpreting PPG-based vital signs, a large data set for deep learning, and a study to demonstrate the accuracy of the method may provide convenience and an alternative method for blood glucose management in dogs.

Blockchain based SDN multicontroller framework for Secure Sat_IoT networks (안전한 위성-IoT 네트워크를 위한 블록체인 기반 SDN 분산 컨트롤러 구현)

  • June Beom Park;Jong Sou Park
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.141-148
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    • 2023
  • Recent advancements in the integration of satellite technology and the Internet of Things (IoT) have led to the development of a sophisticated network ecosystem, capable of generating and utilizing vast amounts of big data across various sectors. However, this integrated network faces significant security challenges, primarily due to constraints like limited latency, low power requirements, and the incorporation of diverse heterogeneous devices. Addressing these security concerns, this paper explores the construction of a satellite-IoT network through the application of Software Defined Networking (SDN). While SDN offers numerous benefits, it also inherits certain inherent security vulnerabilities. To mitigate these issues, we propose a novel approach that incorporates blockchain technology within the SDN framework. This blockchain-based SDN environment enhances security through a distributed controller system, which also facilitates the authentication of IoT terminals and nodes. Our paper details the implementation plan for this system and discusses its validation through a series of tests. Looking forward, we aim to expand our research to include the convergence of artificial intelligence with satellite-IoT devices, exploring new avenues for leveraging the potential of big data in this context.

Analysis of facial expression recognition (표정 분류 연구)

  • Son, Nayeong;Cho, Hyunsun;Lee, Sohyun;Song, Jongwoo
    • The Korean Journal of Applied Statistics
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    • v.31 no.5
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    • pp.539-554
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    • 2018
  • Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

A Study on the Crime Prevention Smart System Based on Big Data Processing (빅데이터 처리 기반의 범죄 예방 스마트 시스템에 관한 연구)

  • Kim, Won
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.75-80
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    • 2020
  • Since the Fourth Industrial Revolution, important technologies such as big data analysis, robotics, Internet of Things, and the artificial intelligence have been used in various fields. Generally speaking it is understood that the big-data technology consists of gathering stage for enormous data, analyzing and processing stage and distributing stage. Until now crime records which is one of useful big-sized data are utilized to obtain investigation information after occurring crimes. If crime records are utilized to predict crimes it is believed that crime occurring frequency can be lowered by processing big-sized crime records in big-data framework. In this research the design is proposed that the smart system can provide the users of smart devices crime occurrence probability by processing crime records in big-data analysis. Specifically it is meant that the proposed system will guide safer routes by displaying crime occurrence probabilities on the digital map in a smart device. In the experiment result for a smart application dealing with small local area it is showed that its usefulness is quite good in crime prevention.

A Survey Analysis of Internet of Things Security Issues and Combined Service

  • Kim, HyunHo;Lee, HoonJae;Lee, YoungSil
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.8
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    • pp.73-79
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    • 2020
  • Since the start of the 4th industrial revolution, technologies have been developed in the Internet of Things (IoT), artificial intelligence (AI), virtual reality (VR), and 5G. Compared to other technologies IoT is currently being commercialized more than other technologies where the numbers of connected things are increases every year. The IoT has a huge advantage to provide convenience and lots of information to users, but security cannot keep up with the speed of development. IoT services continue to provide services for related devices, but at present, more and more types of new services are being combined with other technologies by utilizing the services of devices. This paper reviews and analyzes research on security issues and services related to the Internet of Things to explore how security trends and service delivery will develop in the future.

A Study on the Efficiency of Deep Learning on Embedded Boards (임베디드 보드에서의 딥러닝 사용 효율성 분석 연구)

  • Choi, Donggyu;Lee, Dongjin;Lee, Jiwon;Son, Seongho;Kim, Minyoung;Jang, Jong-wook
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.668-673
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    • 2021
  • As the fourth industrial revolution begins in earnest, related technologies are becoming a hot topic. Hardware development is accelerating to make the most of technologies such as high-speed wireless communication, and related companies are growing rapidly. Artificial intelligence often uses desktops in general for related research, but it is mainly used for the learning process of deep learning and often transplants the generated models into devices to be used by including them in programs, etc. However, it is difficult to produce results for devices that do not have sufficient power or performance due to excessive learning or lack of power due to the use of models built to the desktop's performance. In this paper, we analyze efficiency using boards with several Neural Process Units on sale before developing the performance of deep learning to match embedded boards, and deep learning accelerators that can increase deep learning performance with USB, and present a simple development direction possible using embedded boards.

Technical Survey on the Real Time Eye-tracking Pointing Device as a Smart Medical Equipment (실시간 시선 추적기반 스마트 의료기기 고찰)

  • Park, Junghoon;Yim, Kangbin
    • Smart Media Journal
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    • v.10 no.1
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    • pp.9-15
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    • 2021
  • The eye tracking system designed in this paper is an eye-based computer input device designed to give an easy access for those who are uncomfortable with Lou Gehrig's or various muscle-related diseases. It is an eye-based-computer-using device for users whose potential demand alone amounts to 30,000. Combining the number of Lou Gehrig's patients in Korea estimated at around 1,700, and those who are unable to move their bodies due to various accidents or diseases. Because these eye input devices are intended for a small group of users, many types of commercial devices are available on the market. It is making them more expensive and difficult to use for these potential users, less accessible. For this reason, each individual's economic situation and individual experience with smart devices are slightly different. Therefore, making it difficult to access them in terms of cost or usability to use a commercial eye tracking system. Accordingly, attempts to improve accessibility to IT devices through low-cost but easy-to-use technologies are essential. Thus, this paper proposes a complementary superior performance eye tracking system that can be conveniently used by far more people and patients by improving the deficiencies of the existing system. Through voluntary VoCs(Voice of Customers) of users who have used different kinds of eye tracking systems that satisfies it through various usability tests, and we propose a reduced system that the amount of calculation to 1/15th, and eye-gaze tracking error rate to 0.5~1 degree under.