• Title/Summary/Keyword: 도구로서 인공지능

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A Study on the Cognitive Judgment of Pedestrian Risk Factors Using a Second-hand Mobile Phones (중고스마트폰 업사이클링을 통한 보행위험요인 인지판단 연구)

  • Chang, IlJoon;Jeong, Jongmo;Lee, Jaeduk;Ahn, Se-young
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.274-282
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    • 2022
  • In order to secure pedestrians' right to walk, we have up-cycled second hand mobile phones to overcome limitations of the existing survey methods, analysis methods, and diagnosis to reduce pedestrian traffic accidents. Second hand mobile phones were up-cycled to produce mobile CCTVs and installed in areas where pedestrian deaths rate is high to secure image data sets for the period of more than 24 hours. It was analyzed by applying image visualization technology and clouding reporting technology, and more precise and accurate results were derived through modeling based on artificial intelligence learning and GIS-based diagnostic guidance. As a result, it was possible to analyze the risk factors and number of pedestrian safety, and even factors that were not known in the existing method could be derived. In addition, the traffic accident risk index was derived by converting data into one year to verify whether second hand mobile phone up-cycling mobile CCTV will be an objective tool for finding pedestrian risk factors. Up-cycling mobile CCTV of second hand mobile phones newly applied through research can be used as a new tool to find pedestrian risk factors, and it can be used as a service to protect the safety of the traffic vulnerable other than pedestrians.

Domestic Occupational Therapist Awareness Survey for the Need to Apply Artificial Intelligence Measurement Technology for Clinical Observation Evaluation Based on Sensory Integration (감각통합에 기초한 임상 관찰 평가의 AI 측정 기술 적용 필요성을 위한 국내 작업치료사 인식 조사)

  • Cho, Sun-Young;Jung, Young-Jin;Kim, Jung-Ran
    • Therapeutic Science for Rehabilitation
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    • v.12 no.1
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    • pp.23-35
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    • 2023
  • Objective : This study is to examine the practical use of clinical observational evaluation of sensory integration therapy and the difficulty and importance of measuring results for each sub-item, and through this, to confirm the usefulness of the application of Artificial Intelligence measurement technology in clinical observational measurement and the need for application. Methods : The questionnaire consisted of the actual use of the sensory integration evaluation tool, the difficulty of measurement for each detailed item of clinical observation, the usefulness of AI measurement technology, the importance of evaluation for each detailed item, and the need for developing AI measurement technology. Results : The detailed items that were difficult to measure during clinical observation were the Finger-to-Nose Test and Postural control (71.0%), followed by Eye movement and Protective Extension Test (67.7%). 83.9% of the study subjects answered that it would be useful to apply AI measurement technology when observing images. Postural control (on the ball) (90.3%) was the highest item that answered that AI measurement technology was needed, followed by Eye movement (83.9%), and Prone Extension and Protective Extension Test (77.4%). Conclusion : The results confirmed the desire of therapists that clinical observation is an important evaluation tool in the field of child occupational therapy in Korea.

Literary Research Using Digital Analysis Tools: A Case Study of 『Dangerous Liaisons』 ('디지털 분석 도구를 활용한 문학 연구 : 라클로의 『위험한 관계Les liaisons dangereuses』를 중심으로)

  • RYU Sun-Jung;YOU Eun-Soon
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.173-180
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    • 2024
  • We This study aimed to quantitatively analyze the theme of 'libertinage' and the associated issues of reason and emotion in 『Dangerous Liaisons』, a novel considered a masterpiece of libertine literature and an epistolary novel of the 18th century, using digital analysis tools. First, based on the frequency analysis of word usage using Voyant and LIWC 22, we confirmed that libertinage is manifested with keywords such as 'love' and 'time'. With Voyant's 'Contexts' feature, it was found that the letters sent by Valmont to Madame de Tourvel and those sent by Madame de Merteuil both have 'love' as the central theme. However, emotional vocabulary was higher in the former, whereas strategic vocabulary was more prevalent in the latter. Additionally, it was observed that the most frequently used word in the letters sent by Madame de Merteuil is 'time', with a higher frequency than 'love'. Thirdly, using LIWC 22, we measured the analytical thinking and emotional tone of the letters exchanged by the main characters, and analyzed how these values changed according to the chapters. Through these analyses, we confirmed that this novel, alongside Rousseau's "New Eloise," anticipates romanticism by embracing the theme of 'emotion,' which was rejected by 18th-century Enlightenment ideals.

A Study on the Build of Equipment Predictive Maintenance Solutions Based on On-device Edge Computer

  • Lee, Yong-Hwan;Suh, Jin-Hyung
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.4
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    • pp.165-172
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    • 2020
  • In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

A Study on Composition and Utilization of Digital Literacy Education elements Using Open Contents (오픈 콘텐츠를 활용한 디지털 리터러시 학습 요소 구성과 활용)

  • Hong, Myunghui;Lee, Soonyoung
    • Journal of The Korean Association of Information Education
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    • v.22 no.6
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    • pp.711-721
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    • 2018
  • The development of artificial intelligence technology and the shift to a software-driven society are raising the need for digital literacy education on how to access, understand, use, create and share new open content in a variety of sustainable open content. At this point in time, this paper defines the digital literacy as the subliteracy concept for data, tools, and device elements. It is defined as a concept that includes cognitive and non-cognitive abilities and is stratified by computer literacy, ICT literacy, and information literacy. Open content is also defined as teaching-learning materials that can be used and shared freely by anyone, such as the Open Education Resource (OER) and the Open Access movement. Based on the two definitions, a three-step strategy for digital literacy education was developed to select open content in the digital environment, followed by a digital literacy education plan, and finally, an education frame to foster digital literacy capabilities.

Development of a Sign Language Learning Assistance System using Mediapipe for Sign Language Education of Deaf-Mutility (청각장애인의 수어 교육을 위한 MediaPipe 활용 수어 학습 보조 시스템 개발)

  • Kim, Jin-Young;Sim, Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1355-1362
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    • 2021
  • Recently, not only congenital hearing impairment, but also the number of people with hearing impairment due to acquired factors is increasing. The environment in which sign language can be learned is poor. Therefore, this study intends to present a sign language (sign language number/sign language text) evaluation system as a sign language learning assistance tool for sign language learners. Therefore, in this paper, sign language is captured as an image using OpenCV and Convolutional Neural Network (CNN). In addition, we study a system that recognizes sign language behavior using MediaPipe, converts the meaning of sign language into text-type data, and provides it to users. Through this, self-directed learning is possible so that learners who learn sign language can judge whether they are correct dez. Therefore, we develop a sign language learning assistance system that helps us learn sign language. The purpose is to propose a sign language learning assistance system as a way to support sign language learning, the main language of communication for the hearing impaired.

Effect Analysis of Data Imbalance for Emotion Recognition Based on Deep Learning (딥러닝기반 감정인식에서 데이터 불균형이 미치는 영향 분석)

  • Hajin Noh;Yujin Lim
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.8
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    • pp.235-242
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    • 2023
  • In recent years, as online counseling for infants and adolescents has increased, CNN-based deep learning models are widely used as assistance tools for emotion recognition. However, since most emotion recognition models are trained on mainly adult data, there are performance restrictions to apply the model to infants and adolescents. In this paper, in order to analyze the performance constraints, the characteristics of facial expressions for emotional recognition of infants and adolescents compared to adults are analyzed through LIME method, one of the XAI techniques. In addition, the experiments are performed on the male and female groups to analyze the characteristics of gender-specific facial expressions. As a result, we describe age-specific and gender-specific experimental results based on the data distribution of the pre-training dataset of CNN models and highlight the importance of balanced learning data.

Design and Implementation of a Concentration-based Review Support Tool for Real-time Online Class Participants (실시간 온라인 수업 수강자들의 집중력 기반 복습 지원 도구의 설계 및 구현)

  • Tae-Hwan Kim;Dae-Soo Cho;Seung-Min Park
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.3
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    • pp.521-526
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    • 2023
  • Due to the recent pandemic, most educational systems are being conducted through online classes. Unlike face-to-face classes, it is even more difficult for learners to maintain concentration, and evaluating the learners' attitude toward the class is also challenging. In this paper, we proposed a real-time concentration-based review support system for learners in real-time video lectures that can be used in online classes. This system measured the learner's face, pupils, and user activity in real-time using the equipment used in the existing video system, and delivers real-time concentration measurement values to the instructor in various forms. At the same time, if the concentration measurement value falls below a certain level, the system alerted the learner and records the timestamp of the lecture. By using this system, instructors can evaluate the learners' participation in the class in real-time and help to improve their class abilities.

Determination of Optimal Locations for the Variable Message Signs by The Genetic Algorithm (유전자 알고리즘을 이용한 VMS의 최적위치 선정에 관한 연구)

  • Lee, Sooil;Oh, Seung-hoon;Lee, Byeong-saeng
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6D
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    • pp.927-933
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    • 2006
  • The Variable Message Signs (VMS) are useful way to reduce the socio-economic costs due to the traffic congestions and delays by providing the information on traffic condition to drivers. This study provided a methodology to determine the locations of VMS's in terms of the minimization of the delay by applying the genetic algorithm. The optimal number of VMS's was also derived by the economic analysis based on the cost and the benefit. The simulation considered the variation of traffic volume, the frequency and duration of the incident, and the traffic conversion in order to reflect the real situation. I've made a scenario to consider traffic volume and incident, and it can undergo through changing different traffic volume and incident in time and days and seasons. And I've comprised two kinds of result, one is based on empirical studies, the other is based on Genetic Algorithm about optimal allocation VMS. This result of using optimal location VMS, reduce total travel time rather than preceding study based on normal location VMS and we can estimate optimal location VMS each one.

Satellite Imagery and AI-based Disaster Monitoring and Establishing a Feasible Integrated Near Real-Time Disaster Monitoring System (위성영상-AI 기반 재난모니터링과 실현 가능한 준실시간 통합 재난모니터링 시스템)

  • KIM, Junwoo;KIM, Duk-jin
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.3
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    • pp.236-251
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    • 2020
  • As remote sensing technologies are evolving, and more satellites are orbited, the demand for using satellite data for disaster monitoring is rapidly increasing. Although natural and social disasters have been monitored using satellite data, constraints on establishing an integrated satellite-based near real-time disaster monitoring system have not been identified yet, and thus a novel framework for establishing such system remains to be presented. This research identifies constraints on establishing satellite data-based near real-time disaster monitoring systems by devising and testing a new conceptual framework of disaster monitoring, and then presents a feasible disaster monitoring system that relies mainly on acquirable satellite data. Implementing near real-time disaster monitoring by satellite remote sensing is constrained by technological and economic factors, and more significantly, it is also limited by interactions between organisations and policy that hamper timely acquiring appropriate satellite data for the purpose, and institutional factors that are related to satellite data analyses. Such constraints could be eased by employing an integrated computing platform, such as Amazon Web Services(AWS), which enables obtaining, storing and analysing satellite data, and by developing a toolkit by which appropriate satellites'sensors that are required for monitoring specific types of disaster, and their orbits, can be analysed. It is anticipated that the findings of this research could be used as meaningful reference when trying to establishing a satellite-based near real-time disaster monitoring system in any country.