• Title/Summary/Keyword: Mobile-learning Mobile application

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Deep Learning-based Real-time Heart Rate Measurement System Using Mobile Facial Videos (딥러닝 기반의 모바일 얼굴 영상을 이용한 실시간 심박수 측정 시스템)

  • Ji, Yerim;Lim, Seoyeon;Park, Soyeon;Kim, Sangha;Dong, Suh-Yeon
    • Journal of Korea Multimedia Society
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    • v.24 no.11
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    • pp.1481-1491
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    • 2021
  • Since most biosignals rely on contact-based measurement, there is still a problem in that it is hard to provide convenience to users by applying them to daily life. In this paper, we present a mobile application for estimating heart rate based on a deep learning model. The proposed application measures heart rate by capturing real-time face images in a non-contact manner. We trained a three-dimensional convolutional neural network to predict photoplethysmography (PPG) from face images. The face images used for training were taken in various movements and situations. To evaluate the performance of the proposed system, we used a pulse oximeter to measure a ground truth PPG. As a result, the deviation of the calculated root means square error between the heart rate from remote PPG measured by the proposed system and the heart rate from the ground truth was about 1.14, showing no significant difference. Our findings suggest that heart rate measurement by mobile applications is accurate enough to help manage health during daily life.

Mapless Navigation with Distributional Reinforcement Learning (분포형 강화학습을 활용한 맵리스 네비게이션)

  • Van Manh Tran;Gon-Woo Kim
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.92-97
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    • 2024
  • This paper provides a study of distributional perspective on reinforcement learning for application in mobile robot navigation. Mapless navigation algorithms based on deep reinforcement learning are proven to promising performance and high applicability. The trial-and-error simulations in virtual environments are encouraged to implement autonomous navigation due to expensive real-life interactions. Nevertheless, applying the deep reinforcement learning model in real tasks is challenging due to dissimilar data collection between virtual simulation and the physical world, leading to high-risk manners and high collision rate. In this paper, we present distributional reinforcement learning architecture for mapless navigation of mobile robot that adapt the uncertainty of environmental change. The experimental results indicate the superior performance of distributional soft actor critic compared to conventional methods.

XML-based Retrieval System for E-Learning Contents using mobile device PDA

  • Park Yong-Bin;Yang Hae-Sool
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2006.05a
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    • pp.241-248
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    • 2006
  • Web is greatly contributing in providing a variety of information. Especially, as media for the purpose of development and education of human resources, the role of web is important. Furthermore, E-Learning through web plays an important role for each enterprise and an educational institution. Also, above all, fast and various searches are required in order to manage and search a great number of educational contents in web. Therefore, most of present information is composed in HTML, so there are lots of restrictions. As a solution to such restriction, XML a standard of Web document, and its various search functions is being extended and studied variously. This paper proposes a search system able to search XML in E-Learning or var ious contents of non-XML using mobile device PDA.

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Functional Requirements to Increase Acceptance of M-Learning Applications among University Students in the Kingdom of Saudi Arabia (KSA)

  • Badwelan, Alaa;Bahaddad, Adel A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.21-39
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    • 2021
  • The acceptance of smartphone applications in the learning field is one of the most significant challenges for higher education institutions in Saudi Arabia. These institutions serve large and varied sectors of society and have a tremendous impact on the knowledge gained by student segments at various ages. M-learning is of great importance because it provides access to learning through a wide range of mobile networks and allows students to learn at any time and in any place. There is a lack of quality requirements for M-learning applications in Saudi societies partly because of mandates for high levels of privacy and gender segregation in education (Garg, 2013; Sarrab et al., 2014). According to the Saudi Arabian education ministry policy, gender segregation in education reflects the country's religious and traditional values (Ministry of Education, 2013, No. 155). The opportunity of many applications would help the Saudi target audience more easily accept M-learning applications and expand their knowledge while maintaining government policy related to religious values and gender segregation in the educational environment. In addition, students can share information through the online framework without breaking religious restrictions. This study uses a quantitative perspective to focus on defining the technical aspects and learning requirements for distributing knowledge among students within the digital environment. Additionally, the framework of the unified theory of acceptance and use of technology (UTAUT) is used to modify new constructs, called application quality requirements, that consist of quality requirements for systems, information, and interfaces.

Design and Implementation of Plant's Life Cycle Educational Application (식물의 한살이 교육용 어플리케이션 설계 및 구현)

  • Kim, Kapsu;Kim, Hyosung
    • Journal of The Korean Association of Information Education
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    • v.17 no.3
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    • pp.357-365
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    • 2013
  • The purpose of this paper is to implement the educational application related to the Plant's Life Cycle Unit in 4th Grade Science Textbook, based on the National Curriculum. This should lead to teachers incorporating them into classes and for students to get practical help when they are studying about plants. Through this application, teachers will be able to experience the so-called Blended Learning while using both off-line and mobile teaching methods. It will also be possible for students to review what they learn during the classes and do their projects regardless of time and place. This type of learning is expected to motivate learners and enhance the learning experience by stimulating the students' interest.

Deep Reinforcement Learning in ROS-based autonomous robot navigation

  • Roland, Cubahiro;Choi, Donggyu;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.47-49
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    • 2022
  • Robot navigation has seen a major improvement since the the rediscovery of the potential of Artificial Intelligence (AI) and the attention it has garnered in research circles. A notable achievement in the area was Deep Learning (DL) application in computer vision with outstanding daily life applications such as face-recognition, object detection, and more. However, robotics in general still depend on human inputs in certain areas such as localization, navigation, etc. In this paper, we propose a study case of robot navigation based on deep reinforcement technology. We look into the benefits of switching from traditional ROS-based navigation algorithms towards machine learning approaches and methods. We describe the state-of-the-art technology by introducing the concepts of Reinforcement Learning (RL), Deep Learning (DL) and DRL before before focusing on visual navigation based on DRL. The case study preludes further real life deployment in which mobile navigational agent learns to navigate unbeknownst areas.

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Analyzing the market of corporate e-learning (기업 이러닝 시장 분석 연구)

  • Byun, Sook-Young;Lee, Soo-Kyoung
    • Journal of Digital Contents Society
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    • v.10 no.4
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    • pp.543-550
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    • 2009
  • In these days mobile handsets have come to be used at almost every user. The performance improvement of mobile devices and networks have made this trend possible. As a great variety of mobile applications are published, the necessity of running large-scale mobile applications becomes greater than before. To accomplish this, the existing researchers have developed mobile cluster computing libraries like Mobile-JPVM. In this paper, we implement a compute-intensive Animated GIF generating application and its cell phone viewer software using Mobile-JPVM library. We find out by the real execution of our softwares on the KTF handsets that they can sufficiently run on cellular phones. Our Animated GIF generator and its viewer are going to be commercially used for the mobile fashion advertisement systems.

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Design of Autonomous Mobile Robot System Based on Artificial Immune Network and Internet (인공 면역망과 인터넷에 의한 자율이동로봇 시스템 설계)

  • Lee, Dong-Je;Lee, Min-Jung;Choi, Young-Kiu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.11
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    • pp.522-531
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    • 2001
  • Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

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Smart Agents and Multimedia Systems

  • Kim, Steven H.
    • Proceedings of the Korea Database Society Conference
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    • 1997.10a
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    • pp.215-269
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    • 1997
  • Outline $\textbullet$ Introduction $\textbullet$ Multimedia - Types of Data - Motivation - Key issue - Hardware Products - Application Areas $\textbullet$ Agents - Rationale for Agents - Sedentary vs. Mobile - Functional Categories - Application Areas $\textbullet$ Data Mining - 2-D Framework for Data Mining Tools - Classification of Tool - Application Areas - Learning Methodologies * Case Based Reasoning * Neural Networks * Statistical Learning: Orthogonal Arrays * Multi-strategy Learning $\textbullet$ Case Study - Finbot $\textbullet$ Conclusion

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Development of Augmented Reality (AR) Smartphone Application for Hwaseong Fortress Tourism (수원 화성 증강현실(AR) 관광 모바일 애플리케이션 개발)

  • Kim, Changhyuk;Song, Kisu;Baek, Seunghyeun;Kim, Jinyoung
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.34 no.8
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    • pp.87-94
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    • 2018
  • Hwaseong Fortress was designated as a World Heritage Site by UNESCO in 1997 in recognition of its architectural, cultural, and historical significance. In order to provide a compelling and active experience to the visitors of Hwaseong Fortress more effectively and intuitively, an augmented reality (AR) mobile application is developed. The main objective of this paper is to describe the implementation of AR technology in the developed application; and most importantly, how the application is designed for the visitors to actively and intuitively experience the various architectural and historical contents of Hwaseong. The tour routes and their point of interests were selected carefully after deliberation of their contents. To maximize the user interaction with the application and the architectural contents of Hwaseong, not only the conventional AR technology (marker method), but also the markerless AR method is adopted in the developed application. It is expected that visitors of Hwaseong Fortress enjoy the tour, while learning the architectural, historical, and cultural contents through the active and intuitive interaction with the developed AR mobile application.