• 디지털융복합연구
• /
• 제10권11호
• /
• pp.395-402
• /
• 2012

본 연구는 운동부 지도자들이 운동선수들의 기량을 향상시키기 위하여 효율적으로 기록관리 할 수 있는 스마트폰 어플리케이션을 설계하고 구현한 것이다. 운동선수들이 기량을 향상시키기 위해서는 실전과 같은 훈련을 하여야 하며 그에 대한 방안으로 기구, 시설, 장비, 상황 등에 맞추어 훈련하는 방법도 있겠지만, 훈련 시 달성한 기록을 체크하여 운동선수에게 기록에 대한 동기부여를 하는 방안도 생각할 수 있다. 본 연구에서는 유소년 농구클럽을 대상으로 사전 조사를 통하여 실제 농구경기에서 쓰이는 기록관리 시스템으로 운동을 하였을 때와, 그렇지 않았을 때 경기 기록 활용이 동기 부여가 되는 것을 확인하였다. 그리하여 스마트폰 기반 기록관리 어플리케이션을 설계하고 개발하였으며, 이 시스템을 이용한 후 지도자들의 설문조사를 통하여 훈련 효율성을 측정한 결과 실력향상을 위한 동기부여가 있는 것으로 나타났다.

• 한국융합학회논문지
• /
• 제10권11호
• /
• pp.33-39
• /
• 2019

교육업계에 교육과 정보기술(IT)을 융합한 '에듀테크' 바람이 불고 있다. 4차 산업혁명 핵심 기술이 최근 교육 분야에 적극 활용되고 있는데 학습자들은 인공지능 기반 학습 플랫폼을 이용해 자신이 부족한 부분을 스스로 진단하고, 클라우드 학습 플랫폼으로 온라인상에서 개인 맞춤형 교육을 받는다. 최근 인공지능 기술과 음성인식 기술을 접목한 스마트 스피커와 같은 새로운 교육 매체가 등장하게 되어 다양한 교육서비스가 시도되고 있다. 본 연구에서는 기존 교육의 한계를 극복하기 위해 스마트 스피커를 교육적으로 활용하는 방안을 제시하고자 하였다. 이를 위해 스마트 스피커의 개념 및 특성을 알아보고 스마트 스피커에서 제공하는 콘텐츠를 분석하여 시사점을 도출하였다. 또한 스마트 스피커이용의 문제점에 대해서도 고찰하였다.

• 한국공간구조학회논문집
• /
• 제21권1호
• /
• pp.79-86
• /
• 2021

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

• 대한안전경영과학회지
• /
• 제26권1호
• /
• pp.45-53
• /
• 2024

A Smart factories are systems that enable quick response to customer demands, reduce defect rates, and maximize productivity. They have evolved from manual labor-intensive processes to automation and now to cyber-physical systems with the help of information and communication technology. However, many small and medium-sized enterprises (SMEs) are still unable to implement even the initial stages of smart factories due to various environmental and economic constraints. Additionally, there is a lack of awareness and understanding of the concept of smart factories. To address this issue, the Cooperation-based Smart Factory Construction Support Project was launched. This project is a differentiated support project that provides customized programs based on the size and level of the company. Research has been conducted to analyze the impact of this project on participating and non-participating companies. The study aims to determine the effectiveness of the support policy and suggest efficient measures for improvement. Furthermore, the research aims to provide direction for future support projects to enhance the manufacturing competitiveness of SMEs. Ultimately, the goal is to improve the overall manufacturing industry and drive innovation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권12호
• /
• pp.3889-3903
• /
• 2022

To address the problem of low detection accuracy due to training noise caused by mislabeling when Tri-training for network intrusion detection (NID), we propose a Tri-training algorithm based on cross entropy and K-nearest neighbors (TCK) for network intrusion detection. The proposed algorithm uses cross-entropy to replace the classification error rate to better identify the difference between the practical and predicted distributions of the model and reduce the prediction bias of mislabeled data to unlabeled data; K-nearest neighbors are used to remove the mislabeled data and reduce the number of mislabeled data. In order to verify the effectiveness of the algorithm proposed in this paper, experiments were conducted on 12 UCI datasets and NSL-KDD network intrusion datasets, and four indexes including accuracy, recall, F-measure and precision were used for comparison. The experimental results revealed that the TCK has superior performance than the conventional Tri-training algorithms and the Tri-training algorithms using only cross-entropy or K-nearest neighbor strategy.

• International journal of advanced smart convergence
• /
• 제12권2호
• /
• pp.159-166
• /
• 2023

Due to the aging workforce in the construction industry in South Korea, the accident rate has been increasing. The cognitive abilities of older workers are closely related to both safety incidents and labor productivity. Therefore, there is a need to improve cognitive abilities through personalized training based on cognitive assessment results, using cognitive training content, in order to enable safe performance in labor-intensive environments. The provided cognitive training content includes concentration, memory, oreintation, attention, and executive functions. Difficulty levels were applied to each content to enhance user engagement and interest. To stimulate interest and encourage active participation of the participants, the difficulty level was automatically adjusted based on feedback from the MMSE-DS results and content measurement data. Based on the accumulated data, individual training scenarios have been set differently to intensively improve insufficient cognitive skills, and cognitive training programs will be developed to reduce safety accidents at construction sites through measured data and research. Through such simple cognitive training, it is expected that the reduction of accidents in the aging construction workforce can lead to a decrease in the social costs associated with prolonged construction periods caused by accidents.

• 스마트미디어저널
• /
• 제2권4호
• /
• pp.9-19
• /
• 2013

This paper gives a review on three illumination issues of face tracking on smart phones: dark scenes, sudden lighting change and backlit effect. First, we propose a fast and robust face tracking method utilizing continuous adaptive mean shift algorithm (CAMSHIFT) and CbCr skin locus. Initially, the skin locus obtained from training video data. After that, a modified CAMSHIFT version based on the skin locus is accordingly provided. Second, we suggest an enhancement method to increase the chance of detecting faces, an important initialization step for face tracking, under dark illumination. The proposed method works comparably with traditional CAMSHIFT or particle filter, and outperforms these methods when dealing with our public video data with the three illumination issues mentioned above.

• 한국콘텐츠학회:학술대회논문집
• /
• 한국콘텐츠학회 2019년도 춘계종합학술대회
• /
• pp.467-468
• /
• 2019

Alcoholics Anonymous(AA)/Narcotic Anonymous(NA)의 12 단계 중독 회복 프로그램과 선배 회복자의 지지는 중독 치료 모델에서 성공적인 회복에 기여하는 주요한 역할을 한다. 12단계 중독회복 프로그램의 특징은 특정 종교를 기반으로 하지 않지만 자신의 무력감과 영적 존재에 대한 인정을 바탕으로 한다. 어떤 이들에게는 성공의 요인으로 작용하는 이 특징이 일부 참여자에게 거부하게 하는 요인으로 작용한다. 또한 AA/NA의 오프라인 모임에서 발생하는 다양한 부작용으로 인해 사회적 지지가 필요하지만 사회적 지지를 포기하는 이탈이 발생하여 참석자의 회복에 지장을 주기도 한다. 이에 서구 여러 나라에서 AA/NA와 유사하지만 오프라인뿐만 아니라 온라인 모임이 가능하고, 외부의 존재에 대한 의존이 아닌 중독자 스스로가 중독을 극복하게 도와주며 다양한 형태의 중독의 문제를 다루도록 돕는 SMART(Self Management and Recovery Training) Recovery가 대안으로 부상하였다. 따라서 본 연구에서는 중독회복에 상호자조집단의 도움이 필요하지만 12단계 프로그램이나 오프라인 모임 외에 다른 대안이 없는 국내 상황에 대한 새로운 대안으로 SMART Recovery에 대한 정보와 접근방법들을 심도 있게 탐색하고자 한다.

• Journal of Information Processing Systems
• /
• 제16권6호
• /
• pp.1437-1446
• /
• 2020

For the last few years, smart devices have begun to occupy an essential place in the life of children, by allowing them to access a variety of language activities and books. Various studies are being conducted on using smart devices for education. Our study extracts images and texts from kids' book with smart devices and matches the extracted images and texts to create new images that are not represented in these books. The proposed system will enable the use of smart devices as educational media for children. A deep convolutional generative adversarial network (DCGAN) is used for generating a new image. Three steps are involved in training DCGAN. Firstly, images with 11 titles and 1,164 images on ImageNet are learned. Secondly, Tesseract, an optical character recognition engine, is used to extract images and text from kids' book and classify the text using a morpheme analyzer. Thirdly, the classified word class is matched with the latent vector of the image. The learned DCGAN creates an image associated with the text.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2007년도 춘계학술대회논문집
• /
• pp.924-927
• /
• 2007

In this study, adaptation of two-way shape memory effect of SMA wire to the actuator is examined. Therefore the SMA characteristics which are training, material properties, response time at different thermal cycling rates are tested. During training, permanent deformation is accumulated till a certain number of cycle and then saturated. The amount of two-way strain is unchangeable over all cycle and the slope of strain(or stress)-temperature curve is slower as the increase of applied stress. The rate effect is observed resulted from the thermal distribution which heating profile differs from cooling as thermal cycling time. Using the estimated SMA properties, an experimental test for the simple smart wing is performed.