• Title/Summary/Keyword: Machine Learning Educational Platform

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Design and Implementation of YouTube-based Educational Video Recommendation System

  • Kim, Young Kook;Kim, Myung Ho
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.37-45
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    • 2022
  • As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.

Development of Artificial Intelligence Education based Convergence Education Program for Classifying of Reptiles and Amphibians (파충류와 양서류 분류를 위한 인공지능 교육 기반의 융합 교육 프로그램 개발)

  • Yi, Soyul;Lee, YoungJun
    • Journal of Convergence for Information Technology
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    • v.11 no.12
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    • pp.168-175
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    • 2021
  • In this study, a transdisciplinary convergence education program was developed to enhance the understanding for classification of reptiles and amphibians in biology education and also to increase AI (Artificial Intelligence) capability by using artificial intelligence education. The main content is to solve the classification of reptiles and amphibians that has been dealt with for a long time in biology education, using a decision tree and ML4K (Machine Learnig for Kids), it was designed for a total of 3 lessons. Experts review was conducted on the developed education program, as a result, the I-CVI(Item Content Validity Index) value was .88~1.00 so that can secure content validity. This education program has the advantage of being able to simultaneously learn about the learning contents of artificial intelligence in informatics and the classification of vertebrates in the biological education. In addition, since it is configured to minimize the cognitive load in the AI using part, it is characterized by the fact that all of any teachers can apply it their lesson easily.

Design, Development and Testing of the Modular Unmanned Surface Vehicle Platform for Marine Waste Detection

  • Vasilj, Josip;Stancic, Ivo;Grujic, Tamara;Music, Josip
    • Journal of Multimedia Information System
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    • v.4 no.4
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    • pp.195-204
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    • 2017
  • Mobile robots are used for years as a valuable research and educational tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers to utilize them as an affordable research platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for research purposes can be found. Aim of this paper is to present the development of open-design USV drone with integrated multi-level control hardware architecture. Proposed catamaran - type water surface drone enables direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Developed USV is planned to be utilized as a part of the system for detection and identification of marine and lake waste. Cameras mounted to the USV would record sea or lake surfaces, and recorded video sequences and images would be processed by state-of-the-art computer vision and machine learning algorithms in order to identify and classify marine and lake waste.