• International Journal of Contents
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• 제13권3호
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• pp.25-31
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• 2017

With tremendous advancement of information and communication technologies, mobile learning systems have been widely adopted in language learning contexts, and several frameworks have been developed for identifying and categorizing different factors of mobile-assisted language learning (MALL). However, pre-existing frameworks have limitations when evaluating the importance level of criteria. The purpose of this study is to develop a comprehensive hierarchical framework for identifying and categorizing success factors of MALL and prioritizing them according to the importance level. To do that, AHP method is used to quantitatively estimate weight values of MALL criteria. Results reveal that the priority of MALL criteria is ordered as follows: content, system, learner, language learning. Local weights of each criterion are also analyzed; for example, usefulness, accuracy, and authenticity are critical factors for improving MALL contents. Ease of use and mobility of MALL systems are also considered more critical than other systematic factors. In addition, availability of immediate feedback and self-directness has the highest weight values of importance. The findings of the study are discussed regarding hierarchical orders of MALL criteria and conclude that successful MALL implementation may be achieved if related elements are diversely measured and evaluated. Pedagogical implications and suggestions for further research are also presented.

• 한국정밀공학회지
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• 제21권7호
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• pp.92-100
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• 2004

A service robot is expected to be useful in indoor environment such as a hotel, a hospital and so on. However, many service robots are driven by wheels so that they cannot climb stairs to move to other floors. If the robot cannot use elevators. In this paper, the mobile manipulator system was developed, which can operate numeral buttons on the operating panel in the elevator. To perform this task, the robot is composed of an image recognition module, an ultrasonic sensor module and a manipulator. The robot can recognize numeral buttons and an end-effector in manipulator by the vision system. The Learning vector quantization (LVQ) algorithm is used to recognize the number on the button. The barcode mark on the end-effector is used to recognize the end-effector. The manipulator can push numeral buttons using informations captured by the vision system. The proposed method is evaluated by experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3413-3430
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• 2017

With the fast increasing popularity of mobile services, ubiquitous mobile devices with enhanced sensing capabilities collect and share local information towards a common goal. The recent Mobile Crowd Sensing (MCS) paradigm enables a broad range of mobile applications and undoubtedly revolutionizes many sectors of our life. A critical challenge for the MCS paradigm is to induce mobile devices to be workers providing sensing services. In this study, we examine the problem of sensing task assignment to maximize the overall performance in MCS system while ensuring reciprocal advantages among mobile devices. Based on the overlapping coalition game model, we propose a novel workload determination scheme for each individual device. The proposed scheme can effectively decompose the complex optimization problem and obtains an effective solution using the interactive learning process. Finally, we have conducted extensive simulations, and the results demonstrate that the proposed scheme achieves a fair tradeoff solution between the MCS performance and the profit of individual devices.

• 한국정보통신학회논문지
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• 제19권2호
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• pp.258-264
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• 2015

본 연구에서는 최초로 출현한 모바일 운영시스템인 Palm OS을 시작으로 주요 모바일 운영 시스템의 성공과 실패에 영향을 미치는 요인들이 무엇인지 제시하였다. 이를 위하여 성공한 사례와 실패한 사례에 대한 분석을 실시하고, 성공과 실패에 영향을 미치는 주요 변수를 도출한 후 이를 기반으로 ID 3 알고리즘 기반의 귀납적 분석을 실시하였다. 이를 통하여 모바일 운영 시스템의 성공과 실패에 있어서의 규칙들을 도출하여, 모바일 운영 시스템이 상업적으로 성공하는데 혁신성과 글로벌화 관점에서 전략적 시사점으로 제시하였다.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.295-304
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• 2021

Learning assistance system that continuously measures user's concentration will be helpful to grasp the concentration pattern and adjust the learning method accordingly to improve the learning efficiency. Although a lot of various learning aids have been proposed, there have been few studies on the concentration monitoring system in real time. Therefore, in this study, we developed an Android-based mobile application that can measure concentration during study by using functional near-infrared spectroscopy, which is used to measure brain activity. First, the task accuracy was predicted at a maximum level of 93.75% from the prefrontal oxygenation characteristics measured while performing the visual Q&A task on 11 college students, and a concentration calculation formula based on a linear regression model was derived. Then, a survey on the usability of the mobile application was conducted, overall high satisfaction and positive opinions were obtained. From these findings, this application can be used as a customized learning aid application for users, and further, it can help educators improve the quality of classes based on the level of concentration of learners.

• 정보교육학회논문지
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• 제12권2호
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• pp.131-139
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• 2008

본 연구는 협력적 지식구축을 목적으로 하는 CSCL (Computer-Supported Collaborative Learning) 환경을 이용하여 교육주체간의 협동적 상호작용이 원활히 이루어질 수 있도록 하는 모바일 학급경영지원시스템을 구현하는데 목적이 있다. 이러한 목적을 위해 학급경영과 CSCL, 무선인터넷을 이론적으로 탐색하고 학급경영과 무선인터넷의 관계를 파악하여 학급경영을 지원하는 모바일 학급경영지원 시스템의 설계요소 및 전략을 수립하였다. 이를 기반으로 모바일 학급경영지원시스템을 설계하고 개발하였다.

• 방송공학회논문지
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• 제27권3호
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• pp.341-350
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• 2022

본 논문은 온디바이스 환경에서 다중 시점 영상을 입력 받아 객체를 증강하고, 현실 공간에 의한 가려짐을 구현하는 딥러닝 기반의 증강현실 시스템을 제안한다. 이는 세부적으로 카메라 자세 추정, 깊이 추정, 객체 증강 구현의 세 기술적 단계로 나눠지며 각 기법은 온디바이스 환경에서의 최적화를 위해 다양한 모바일 프레임워크를 사용한다. 카메라 자세 추정 단계에서는 많은 계산량을 필요로 하는 특징 추출 알고리즘을 GPU 병렬처리 프레임워크인 OpenCL을 통해 가속하여 사용하며, 깊이 영상 추론 단계에서는 모바일 심층신경망 프레임워크 TensorFlow Lite를 사용하여 가속화된 단안, 다중 영상 기반의 깊이 영상 추론을 수행한다. 마지막으로 모바일 그래픽스 프레임워크 OpenGL ES를 활용해 객체 증강 및 가려짐을 구현한다. 제시하는 증강현실 시스템은 안드로이드 환경에서 GUI를 갖춘 애플리케이션으로 구현되며 모바일과 PC 환경에서의 동작 정확도 및 처리 시간을 평가한다.

• 전자통신동향분석
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• 제37권4호
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• pp.60-69
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• 2022

So far, artificial intelligence (AI)/machine learning (ML) has produced impressive results in speech recognition, computer vision, and natural language processing. AI/ML has recently begun to show promise as a viable means for improving the performance of 5G mobile telecommunication systems. This paper investigates standardization activities in 3GPP and O-RAN Alliance regarding AI/ML applications on mobile telecommunication system. Future trends in AI/ML technologies are also summarized. As an overarching technology in 6G, there appears to be no doubt that AI/ML could contribute to every part of mobile systems, including core, RAN, and air-interface, in terms of performance enhancement, automation, cost reduction, and energy consumption reduction.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• 한국콘텐츠학회논문지
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• 제13권2호
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• pp.8-18
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• 2013

본 논문은 Html5 모바일 웹상에서 학습 동영상을 수강하면서 재학습이 필요한 영역을 타임라인의 비디오 프레임 형태로 재생 시간과 함께 캡쳐하여 저장한다. Html5의 Video 태그를 활용하여 최대 9개까지 캡쳐 프레임의 목록을 표시할 수 있고 프레임 이미지를 선택하면 저장한 재생 시간 위치부터 실행하는 방식으로 구현한다. 캡쳐 프레임 실행은 전체 학습에 비해 재학습 프레임만 부분적인 학습이며 집중 학습의 효과로 학습자 맞춤형 스토리텔링을 구현할 수 있다. 무작위 순서에 따라 구간 반복 학습 할 수 있으므로 학습자 수준별 맞춤 반복 학습에 따른 학업 성취도에 긍정적인 효과를 줄 수 있다.