• Title/Summary/Keyword: AI-based System and Technology

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The Impact of Edu-Tech and Tangible and Intangible Services of Private Institutes on parents' Intention for Re-Enrollment: The Moderating Effect of Rapport-Building Behavior (학원의 에듀테크특성과 유·무형적서비스가 학부모의 재수강의도에 미치는 영향: 라포형성행동의 조절효과)

  • Jeon, Ji-Yeon;Ha, Tae-Kwan
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.4
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    • pp.127-139
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    • 2024
  • This study investigates the impact of edutech characteristics and both tangible and intangible educational services on the intention to re-enroll, which is directly related to the management performance of private institutes. The study aims to propose strategies to improve re-enrollment intentions and management performance based on the findings. Private education has grown continuously, complementing the limitations of public education and increasing parental dependence. This study tested the hypothesis that edutech characteristics, intangible services, and tangible services, increasingly utilized with the development of information and communication technology, would influence re-enrollment intentions. It also examined whether rapport-building behavior with parents would have a moderating effect on this relationship. The hypothesis testing results showed that among the edutech characteristics, content, intangible services such as reliability and empathy, and tangible services such as tangibility and payment accessibility positively impacted re-enrollment intentions. The hypothesis that rapport-building behavior would moderate the relationship between educational services and re-enrollment intentions was supported for empathy in intangible services and tangibility in tangible services. Based on these findings, the study proposed three strategies to improve management performance of private institutes. First, in terms of improving and managing edutech characteristics, it suggested introducing and updating edutech content and ensuring operational stability. Second, for improving and managing intangible services, it recommended managing instructor recruitment and training to enhance quality and competence, maintaining professionalism through continuous education by credible institutions, and providing level-based education for students based on the qualitative improvement of educational programs. Third, to improve and manage tangible services, it suggested setting appropriate tuition fees, offering various payment methods (online, mobile, card, bank transfer) unrestricted by time and place, and equipping interiors and facilities that enable focused learning. Additionally, considering the moderating effect of rapport-building behavior, it emphasized that improvements and management requiring costs are necessary, but making parents feel a high level of tangibility through rapport-building is also important. Furthermore, given the increasing importance of edutech based on information and communication technology, the study highlighted the need for various support measures such as government technological support and venture certification system support for institutes with an entrepreneurial spirit aiming to introduce innovative technologies such as AI technology based on large language models and AR/VR-applied metaverse environments. This study is expected to help improve the management performance of private institutes by specifically suggesting items and methods for improvement and management in the educational field.

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Changes and Perspects in the Regulation on Medical Device Approval Report Review, etc. : Focus on Traditional Korean Medical Devices (의료기기 허가·신고·심사 등에 관한 규정 변화와 전망 : 한의 의료기기 중심으로)

  • DaeJin Kim;Byunghee Choi;Taeyeung Kim;Sunghee Jung;Woosuk Kang
    • Journal of Society of Preventive Korean Medicine
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    • v.28 no.1
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    • pp.31-42
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    • 2024
  • Objective : In order to understand the changes in domestic approval regulations applicable to traditional Korean medical device companies, this article will explain the major amendments 「Regulation on Medical Device Approval Report Review, etc.」 from 2005 to the present on a year-by-year basis, and provide a counter plan to the recent changes in approval regulations. Methods : We analysed the changes in approval regulatory amendments related to the traditional Korean medical devices from 2005 to the present. Results : The Ministry of Food and Drug Safety is continuously improving medical device approval regulations to ensure the global competitiveness of domestic medical devices and contribute to the improvement of public health. Recent major approval regulatory amendments include the establishment of a review system for software medical devices and digital therapeutics, the recognition of real world evidence materials, the introduction of a biological evaluation of medical devices within a risk management process and a medical device approval licence renewal system. Conclusions : It is expected that the range of medical devices available to Korean medicine doctors will continue to expand in the future through the provision of non-face-to-face medical services and the development of advanced and new medical devices, as well as wearable medical devices and digital therapeutics. In order to increase the market entry potential of traditional Korean medical devices that incorporate advanced technologies such as digital technology and AI-based diagnosis and prediction technology, it is urgent that the government provide significant support to traditional Korean medical device companies to improve approval regulatory compliance.

Edge Computing Model based on Federated Learning for COVID-19 Clinical Outcome Prediction in the 5G Era

  • Ruochen Huang;Zhiyuan Wei;Wei Feng;Yong Li;Changwei Zhang;Chen Qiu;Mingkai Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.826-842
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    • 2024
  • As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

Design of silicon-graphite based composite electrode for lithium-ion batteries using single-walled carbon nanotubes (단일벽 탄소나노튜브를 이용한 리튬이온전지용 실리콘-흑연 기반 복합전극 설계)

  • Jin-young Choi;Jeong-min Choi;Seung-Hyo Lee;Jun Kang;Dae-Wook Kim;Hye-Min Kim
    • Journal of Surface Science and Engineering
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    • v.57 no.3
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    • pp.214-220
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    • 2024
  • In this study, three-dimensional (3D) networks structure using single-walled carbon nanotubes (SWCNTs) for Si-graphite composite electrode was developed and studied about effects on the electrochemical performances. To investigate the effect of SWCNTs on forming a conductive 3D network structure electrode, zero-dimensional (0D) carbon black and different SWCNTs composition electrode were compared. It was found that SWCNTs formed a conductive network between nano-Si and graphite particles over the entire area without aggregation. The formation of 3D network structure enabled to effective access for lithium ions leading to improve the c-rate performance, and provided cycle stability by alleviating the Si volume expansion from flexibility and buffer space. The results of this study are expected to be applicable to the electrode design for high-capacity lithium-ion batteries.

A Study on the Operational Planning Assist System for Ground Forces (지상군 작전계획 수립 보조 시스템 설계 연구)

  • Ikhyun Kim;Sunju Lee
    • Journal of The Korean Institute of Defense Technology
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    • v.5 no.1
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    • pp.7-18
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    • 2023
  • The military leader makes an operation plan to accomplish combat missions. The current doctrine for an operation planning requires the use of simple and clear procedures and methods that can be carried out with human effort under adverse conditions in the field. The work in the process of an operation planning can be said to be a series of decision-making, and the criteria for decision-making generally apply mission variables. However, detailed standards are not fixed as doctrine, but are creatively established and applied. However, for AI-based decision-making, it is necessary to formalize the criteria and the format used. This paper first aims to standardize various criteria and forms to present a method that can be used in a semi-automated assist system, and to seek a plan to artificialize it. To this end, mathematical models and decision-making methods established in the field of operations research were applied to improve efficiency.

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Escape Route Prediction and Tracking System using Artificial Intelligence (인공지능을 활용한 도주경로 예측 및 추적 시스템)

  • Yang, Bum-Suk;Park, Dea-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1130-1135
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    • 2022
  • In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office has built a control center for CCTV control and is performing 24-hour CCTV video control for the safety of citizens. Seoul Metropolitan Government is building a smart city integrated platform that is safe for citizens by providing CCTV images of the ward office to enable rapid response to emergency/emergency situations by signing an MOU with related organizations. In this paper, when an incident occurs at the Seoul Metropolitan Government Office, the escape route is predicted by discriminating people and vehicles using the AI DNN-based Template Matching technology, MLP algorithm and CNN-based YOLO SPP DNN model for CCTV images. In addition, it is designed to automatically disseminate image information and situation information to adjacent ward offices when vehicles and people escape from the competent ward office. The escape route prediction and tracking system using artificial intelligence can expand the smart city integrated platform nationwide.

Implementation of Facility Movement Recognition Accuracy Analysis and Utilization Service using Drone Image (드론 영상 활용 시설물 이동 인식 정확도 분석 및 활용 서비스 구현)

  • Kim, Gwang-Seok;Oh, Ah-Ra;Choi, Yun-Soo
    • Journal of the Korean Institute of Gas
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    • v.25 no.5
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    • pp.88-96
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    • 2021
  • Advanced Internet of Things (IoT) technology is being used in various ways for the safety of the energy industry. At the center of safety measures, drones play various roles on behalf of humans. Drones are playing a role in reaching places that are difficult to reach due to large-scale facilities and space restrictions that are difficult for humans to inspect. In this study, the accuracy and completeness of movement of dangerous facilities were tested using drone images, and it was confirmed that the movement recognition accuracy was 100%, the average data analysis accuracy was 95.8699%, and the average completeness was 100%. Based on the experimental results, a future-oriented facility risk analysis system combined with ICT technology was implemented and presented. Additional experiments with diversified conditions are required in the future, and ICT convergence analysis system implementation is required.

A Study on the Blockchain-Based Bill of Lading System to Improve Usability (사용성 개선을 위한 블록체인 기반 선하증권 거래 시스템 연구)

  • Lee, Ju-young;Kim, Hyun-a;Sung, Chae-min;Kim, Joung-min;Kim, Sungwook
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.7
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    • pp.283-290
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    • 2022
  • Blockchain is a technology that secures integrity and transparency by distributing and storing transaction details within multiple node networks. Recently, research is being conducted to secure integrity by applying blockchain to Bill of Lading (B/L documents) of monetary value. In this paper, we study a blockchain-based bill of lading system to improve usability. The shippers register the issued bill of lading on the blockchain, and banks in each country read it to conduct L/C transactions. The consignees receive the goods after completing certification with a quick response code (QR) containing the bill of lading information. Through this, shippers enjoy merits in that they can shorten the time and cost of sending shipping documents by mail and prove the integrity of the documents. The consignees have the advantage of being able to check the documents at the same time as they are registered and trust the transaction. Finally, on the bank side, the security of shipping documents is ensured and verification can be done quickly.

Battery swelling detection system based on adaptive resistance change on battery pack surface (적응적 배터리 팩 피막 저항 변화 감지를 통한 배터리 스웰링 감지 기법)

  • Sunghyun Park;Kibum Sung;Jaehyun Park;Donghwa Shin
    • Journal of IKEEE
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    • v.27 no.1
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    • pp.85-92
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    • 2023
  • Recently, as the era of the 4th Industrial Revolution approaches, IoT devices that emphasize portability are increasing. At the same time, battery usage is also increasing rapidly. With the rapid increase in battery usage, issues related to battery safety have become inevitable problems and many studies have been conducted. This paper deals with explosion issues caused by swelling among various battery issues, and includes research and development of a system that detects battery swelling by identifying resistance changes. The core technology of this study is to develop a system that frequently detects changes in the resistance of wires drawn on the battery through changes in volume that occur when the battery swelling, and uses the resistance changes to prevent battery explosion. In addition, through pattern analysis, it was analyzed how the wire should be constructed to cause a lot of resistance changes.

Automation of Online to Offline Stores: Extremely Small Depth-Yolov8 and Feature-Based Product Recognition (Online to Offline 상점의 자동화 : 초소형 깊이의 Yolov8과 특징점 기반의 상품 인식)

  • Jongwook Si;Daemin Kim;Sungyoung Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.3
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    • pp.121-129
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    • 2024
  • The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.