• Title/Summary/Keyword: Artificial Intelligence

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AI Chatbot-Based Daily Journaling System for Eliciting Positive Emotions (긍정적 감정 유발을 위한 AI챗봇기반 일기 작성 시스템)

  • Jun-Hyeon Kim;Mi-Kyeong Moon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.105-112
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    • 2024
  • In contemporary society, the expression of emotions and self-reflection are considered pivotal factors with a positive impact on stress management and mental well-being, thereby highlighting the significance of journaling. However, traditional journaling methods have posed challenges for many individuals due to constraints in terms of time and space. Recent rapid advancements in chatbot and emotion analysis technologies have garnered significant attention as essential tools to address these issues. This paper introduces an artificial intelligence chatbot that integrates the GPT-3 model and emotion analysis technology, detailing the development process of a system that automatically generates journals based on users' chat data. Through this system, users can engage in journaling more conveniently and efficiently, fostering a deeper understanding of their emotions and promoting positive emotional experiences.

Study on the Positioning Method using BLE for Location based AIoT Service (위치 기반 지능형 사물인터넷 서비스를 위한 BLE 측위 방법에 관한 연구)

  • Ho-Deok Jang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.1
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    • pp.25-30
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    • 2024
  • Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

An Analysis of Artificial Intelligence Education Research Trends Based on Topic Modeling

  • You-Jung Ko
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.197-209
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    • 2024
  • This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.

A Study on XR Technology for Digital Twin of Smart Factory (스마트 공장의 디지털 트윈을 위한 XR기술에 관한 연구)

  • Soek-Hee Lee
    • Journal of Practical Engineering Education
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    • v.16 no.1_spc
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    • pp.1-9
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    • 2024
  • The introduction of smart factory digital twins is a concept that has already been proposed to increase productivity in the manufacturing industry through CPS(Cyber Physics System), and has been applied to specific industrial process stages or partially introduced in stages where simulation is required. However, with the recent development of the 4th Industrial Revolution technology, it is receiving attention again along with XR (Extended Reality) technology. However, because there are not many effective cases, this study analyzed the devices, equipment, and technology of the manufacturing process to build a digital twin applying digital threads and synchronized signals and information to control, remote control, and produce intelligent process automation equipment. A platform capable of analyzing information was proposed and developed. Through this, we designed and built an XR content service platform that can support artificial intelligence and developed it to enable control, remote control, and analysis of production information. A possible platform was proposed and developed. We hope that this study will be helpful in conducting research on many cases, and in the future, expanded research on increasing productivity in each part of the process and production is needed through intelligent models.

Development of the Artificial Intelligence Literacy Education Program for Preservice Secondary Teachers (예비 중등교사를 위한 인공지능 리터러시 교육 프로그램 개발)

  • Bong Seok Jang
    • Journal of Practical Engineering Education
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    • v.16 no.1_spc
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    • pp.65-70
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    • 2024
  • As the interest in AI education grows, researchers have made efforts to implement AI education programs. However, research targeting pre-service teachers has been limited thus far. Therefore, this study was conducted to develop an AI literacy education program for preservice secondary teachers. The research results revealed that the weekly topics included the definition and applications of AI, analysis of intelligent agents, the importance of data, understanding machine learning, hands-on exercises on prediction and classification, hands-on exercises on clustering and classification, hands-on exercises on unstructured data, understanding deep learning, application of deep learning algorithms, fairness, transparency, accountability, safety, and social integration. Through this research, it is hoped that AI literacy education programs for preservice teachers will be expanded. In the future, it is anticipated that follow-up studies will be conducted to implement relevant education in teacher training institutions and analyze its effectiveness.

Research on Artificial Intelligence Based De-identification Technique of Personal Information Area at Video Data (영상데이터의 개인정보 영역에 대한 인공지능 기반 비식별화 기법 연구)

  • In-Jun Song;Cha-Jong Kim
    • IEMEK Journal of Embedded Systems and Applications
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    • v.19 no.1
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    • pp.19-25
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    • 2024
  • This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

Hard Example Generation by Novel View Synthesis for 3-D Pose Estimation (3차원 자세 추정 기법의 성능 향상을 위한 임의 시점 합성 기반의 고난도 예제 생성)

  • Minji Kim;Sungchan Kim
    • IEMEK Journal of Embedded Systems and Applications
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    • v.19 no.1
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    • pp.9-17
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    • 2024
  • It is widely recognized that for 3D human pose estimation (HPE), dataset acquisition is expensive and the effectiveness of augmentation techniques of conventional visual recognition tasks is limited. We address these difficulties by presenting a simple but effective method that augments input images in terms of viewpoints when training a 3D human pose estimation (HPE) model. Our intuition is that meaningful variants of the input images for HPE could be obtained by viewing a human instance in the images from an arbitrary viewpoint different from that in the original images. The core idea is to synthesize new images that have self-occlusion and thus are difficult to predict at different viewpoints even with the same pose of the original example. We incorporate this idea into the training procedure of the 3D HPE model as an augmentation stage of the input samples. We show that a strategy for augmenting the synthesized example should be carefully designed in terms of the frequency of performing the augmentation and the selection of viewpoints for synthesizing the samples. To this end, we propose a new metric to measure the prediction difficulty of input images for 3D HPE in terms of the distance between corresponding keypoints on both sides of a human body. Extensive exploration of the space of augmentation probability choices and example selection according to the proposed distance metric leads to a performance gain of up to 6.2% on Human3.6M, the well-known pose estimation dataset.

Prediction model for dental implants utilization in the elderly after the national health insurance coverage of dental implants: focusing on socioeconomic factors (치과 임플란트 국민건강보험 급여화 이후 노인의 치과 임플란트 이용에 대한 예측 모형: 사회경제적 요인 중심으로)

  • Sang-Hee Lee;Kyu-Seok Kim;Hye-Young Mun;Jung-Yun Kang
    • Journal of Korean society of Dental Hygiene
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    • v.24 no.1
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    • pp.9-16
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    • 2024
  • Objectives: The demand for dental care is expected to increase as the population ages. This study aimed to predict the utilization of dental implant care following the expansion of national health insurance benefits for dental implants. Methods: Multiple linear regression analysis was performed on HIRA big data open portal data and DNN-based artificial intelligence models to forecast the utilization of dental care in relation to the national health insurance coverage for dental implants. Results: National health insurance coverage of dental implants was found to be associated with the number of patients using dental implant services and demonstrated a statistical significance. The dental implant services utilization increased with the increased dental implant health insurance benefits for the elderly population, increased mean by region, increased number of dental institutions by region, and increased health insurance coverage rate for dental implants. However, the dental implant services utilization decreased with the increased number of older people living alone and increased size of dental institutions. Conclusions: With the expansion of the national health insurance coverage for dental implants, it is predicted that the utilization of dental implant medical services will increase in the future.

Descriptive Review of Patents in Healthcare and Nursing: Based on Network Analysis (네트워크 분석을 활용한 보건의료 및 간호관련 특허의 특징: 서술적 고찰)

  • Jeon, Misun;Youn, Nayung;Kim, Sanghee
    • Journal of Korean Academy of Nursing
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    • v.54 no.1
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    • pp.1-17
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    • 2024
  • Purpose: The significance of the healthcare industry has grown exponentially in recent years due to the impact of the fourth industrial revolution and the ongoing pandemic. Accordingly, this study aimed to examine domestic healthcare-related patents comprehensively. Big data analysis was used to present the trend and status of patents filed in nursing. Methods: The descriptive review was conducted based on Grant and Booth's descriptive review framework. Patents related to nursing was searched in the Korea Intellectual Property Rights Information Service between January 2016 to December 2020. Data analysis included descriptive statistics, phi-coefficient for correlations, and network analysis using the R program (version 4.2.2). Results: Among 37,824 patents initially searched, 1,574 were selected based on the inclusion criteria. Nursing-related patents did not specify subjects, and many patents (41.4%) were related to treatment in the healthcare delivery phase. Furthermore, most patents (56.1%) were designed to increase effectiveness. The words frequently used in the titles of nursing-related patents were, in order, "artificial intelligence," "health management," and "medical information," and the main terms with high connection centrality were "artificial intelligence" and "therapeutic system." Conclusion: The industrialization of nursing is the best solution for developing the healthcare industry and national health promotion. Collaborations in education, research, and policy will help the nursing industry become a healthcare industry of the future. This will prime the enhancement of the national economy and public health.

Development and Application of an Artificial Intelligence Convergence Education Program Linked to School Library Reading Activities for Middle School Students (중학생을 위한 학교도서관의 독서활동 연계 인공지능 융합교육 프로그램의 개발과 적용)

  • Yonju No;Ji Won You
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.439-463
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    • 2024
  • Recently, there has been a growing demand for school libraries to take on the role of curriculum convergence and content development. This study purposed to develop a program that integrates reading activities and artificial intelligence (AI) education in a middle school library as a platform for convergence education. The program aimed to enhance creative problem-solving skills by integrating an understanding of AI concepts and principles through reading activities related to AI topics. The program, comprising 18 sessions (6 modules), was implemented with 36 first-year students at A Middle School, Gyeonggi-do, in 2022. After implementation, a paired-sample t-test revealed significant improvements in AI learning self-efficacy and creative problem-solving skills. Participants also showed positive attitudes toward class engagement and reading activities. Implications for AI convergence education in connection with school libraries were discussed.