• Educational Technology International
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• 제21권2호
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• pp.155-191
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• 2020

The aim of this study was to examine the trends (e.g., the distribution of the studies by year, country, research methods, and participants' education level) and fundamental findings [e.g., interaction in Virtual Reality (VR) environments, educational content through VR and Augmented Reality (AR) technologies, learning environment in AR, etc.] regarding immersive learning technologies such as VR and AR in English Language Teaching (ELT) between 2010 and 2019. Employing a systematic review research methodology, data was gathered from 59 academic articles published in the following databases: EBSCOhost, ERIC, Web of Science, and Taylor & Francis. The studies were analyzed using a content analysis approach, and findings demonstrated that immersive learning technologies in ELT came to prominence in 2017. Mixed methods research was the most widely employed research method. The most studied language skill was vocabulary for AR and speaking for VR. The results also revealed advantages and challenges with regards to the use of immersive learning technologies in ELT. Further analysis illustrated the findings related to characteristics of immersive learning technologies in ELT. Based on this review, research and design implications for researchers and practitioners are presented.

• Toxicological Research
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• 제17권
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• pp.257-261
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• 2001

Recently, a traditional medicine called Gouteng-san, which consists of eleven herbs, was reported to be effective in treating vascular dementia with a double-blind, placebo-controlled study. Gout-eng-san is also used for patients with vascular dementia in combination with Si-Wu-Tang. The effect of Gouteng-san and Si-Wu-Tang on deficit of learning behavior was investigated using step-down passive avoidance task in mice. Hot-water extract of Gouteng-san (1.5 and 6 g/kg, p.o.) significantly prolonged the step-down latency shortened by scopolamine. The extract of Uncaria hook (150 mg/kg, p.o.), one of the component herb of Gouteng-san, significantly prevented the decrease in the latency after scopolamine. Hot-water extract of Si-Wu-Tang (1.5 and 6 g/kg of dried herbs, p.o.) prevented dose-dependently scopola-mine-induced disruption qf learning behavior. Si-Wu-Tang also prevented the ischemia-induced deficit of learning behavior. Both hot water extract of peony and angelica (1.5 g/kg, p.o.), which are component herbs qf Si-Wu-Tang, prevented the scopolamine-induced learning behavior deficit. Scopolamine (10 uM) suppressed long-term potentiation (LTP) of population spike in the CA1 region of the rat hippocampal slices. Peoniflorin (0.1~ 1uM) extracted from paeony root significantly ameliorated scopolamine-induced inhibition of LTR These results suggest that improvement of deficit of learning behavior by Gouteng-san and Si-Wu-Tang is mediated by direct and/or indirect activation of the cholinergic system in the brain.

• 전자통신동향분석
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• 제35권4호
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• pp.115-134
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• 2020

Several studies on machine learning (ML) based self-organizing networks (SONs) have been conducted, specifically for LTE, since studies to apply ML to optimize mobile communication systems started with 2G. However, they are still in the infancy stage. Owing to the complicated KPIs and stringent user requirements of 5G, it is necessary to design the 5G SON engine with intelligence to enable users to seamlessly and unlimitedly achieve connectivity regardless of the state of the mobile communication network. Therefore, in this study, we analyze and summarize the current state of machine learning studies applied to SONs as solutions to the complicated optimization problems that are caused by the unpredictable context of mobile communication scenarios.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 2005년도 춘계학술발표대회 논문집
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• pp.251-252
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• 2005

The present design, which is English Zone Development Project for 'G' Elementary School at Seo gu, Incheon, contained various booths for experiential learning corners as well as spaces of teaching learning through group study, dramas and role plays, breaking away from the structure and atmosphere of traditional language labs, and at the same time it include a school building as an affiliated space where the whole students can gather for discussion and learning. The general design concept adopted the atmosphere of an exotic street, installing five theme booths (airport, bank, hospital, book/game store and shop) along the wall and applying the image of road to the floor in order to perform role plays. The blackboard and furniture were also designed to produce the atmosphere of street so that elementary students take interest and actively participate in learning.

• 한국전자통신학회논문지
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• 제19권3호
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• pp.515-522
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• 2024

전 세계적으로 전력 소비량이 꾸준히 증가하고 있으며, 특히 빌딩의 전력 소비 비율은 세계 전력 소비 비율의 20% 이상을 차지할 만큼 그 비중이 크다. 이에 따라 빌딩에서의 전력 소비를 효율적으로 관리하는 빌딩 에너지 관리 시스템(BEMS, Building Energy Management System)의 연구 및 개발이 활발히 진행되고 있으며, 특히 최근에는 인공지능 기술의 발달로 인해 Smart BEMS 연구가 주목받고 있다. 본 논문에서는 강화학습 기반 V2G(Vehicle-to-Grid) Station 연계형 스마트 에너지 빌딩 전력 제어 기법을 제안한다. 실제 빌딩의 전력량 데이터 기반 성능평가 결과, 학습이 진행됨에 따라 빌딩에서의 전력 요금이 감축하는 것을 확인하였다.

• 전자통신동향분석
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• 제34권3호
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• pp.93-105
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• 2019

This study emphasizes the importance of the newly added Ultra-Reliable and Low-Latency Communications (URLLC) service as an important evolutionary step for 5G mobile communication, and proposes a remedial application. We analyze the requirements for the application of 5G mobile communication technology in high-precision vertical industries and applications, introduce the 5G URLLC design principles and standards of 3GPP, and summarize the current state of applied artificial intelligence technology in wireless communication. Additionally, we summarize the current state of research on ultra-reliable and low-latency machine learning-based wireless communication technology for application in ultra-high-precision vertical industries and applications. Furthermore, we discuss the technological direction of artificial intelligence technology for URLLC wireless communication.

• 전자통신동향분석
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• 제38권6호
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• pp.95-106
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• 2023

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.129-134
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• 2024

Object Detection is an emerging technology in the field of Computer Vision and Image Processing that deals with detecting objects of a particular class in digital images. It has considered being one of the complicated and challenging tasks in computer vision. Earlier several machine learning-based approaches like SIFT (Scale-invariant feature transform) and HOG (Histogram of oriented gradients) are widely used to classify objects in an image. These approaches use the Support vector machine for classification. The biggest challenges with these approaches are that they are computationally intensive for use in real-time applications, and these methods do not work well with massive datasets. To overcome these challenges, we implemented a Deep Learning based approach Convolutional Neural Network (CNN) in this paper. The Proposed approach provides accurate results in detecting objects in an image by the area of object highlighted in a Bounding Box along with its accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1573-1576
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• 1997

In this paper we present an associative menory network(AMN) controller for learning of robot trajectories. We use AMN controller in order to improve the performance of conventional learning control, e.g. RCL, which had studied by Sadegh et al. Computer simulations show the feasibility and effectiveness of the proposed AMN controller.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.341-342
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• 2011