웹 기반 탐구 학습 환경이 뇌성마비학생의 사고력에 미치는 영향

이재욱 ( Lee¸ Jae-uk ) 대구대학교 특수교육재활과학연구소 2021 특수교육재활과학연구 Vol.60 No.3

본 연구는 웹 기반 탐구 학습 환경이 뇌성마비학생의 사고력에 미치는 영향을 분석하는 목적으로 실시되었다. 이를 위한 구체적인 연구문제는 다음과 같다. 첫째, 웹 기반 탐구 학습 환경이 뇌성마비학생의 비판적 사고력에 미치는 영향은 어떠한가? 둘째, 웹 기반 탐구 학습 환경이 뇌성마비학생의 창의적 사고력에 미치는 영향은 어떠한가? 이를 위하여 지체장애학교의 고등학교 과정에 재학 중인 뇌성마비학생 3명을 대상으로 대상자간 중다 간헐 기초선 설계를 적용하여 웹 기반 탐구 학습 환경이 사고력에 미치는 효과를 분석하였다. 연구 결과 웹 기반 탐구 학습 환경은 뇌성마비학생의 비판적 사고력과 창의적 사고력 점수를 향상시켰다. 특히 비판적 사고력의 '사실과 의견 구분하기', '충분한 근거에 따라 주장하기', '다양한 관점으로 조망하기'와 창의적 사고력의 '유창성' 향상에 효과가 있는 것으로 나타났다. The purpose of this study is to analyze the effect of the web-based inquiry learning environment on the thinking ability of students with cerebral palsy. Research questions are as follows: First, what is the effect of the web-based inquiry learning environment on the critical thinking ability of students with cerebral palsy? Second, what is the effect of the web-based inquiry learning environment on the creative thinking ability of students with cerebral palsy? To solve the research questions, the effect of a web-based inquiry learning environment on thinking ability was analyzed for three students with cerebral palsy attending high school courses at a school for physical disabilities by applying the multiple probe baseline across participants design. As a result of the study, the web-based inquiry learning environment improved the critical thinking ability and creative thinking ability scores of students with cerebral palsy. In particular, it was found to be effective in 'distinguishing facts and opinions', 'arguing based on sufficient evidence', 'viewing from various perspectives' of critical thinking ability, and improving 'fluency' of creative thinking ability.

The application of nanotransistor by using selectively grown vertical carbon nanotubes

Jaeuk Chu,Kwangseok Jeong,Eunju Bae,Jujin Kim,Wonbong Choi 한국진공학회 2002 한국진공학회 학술발표회초록집 Vol.- No.-

Overlapped Nanoparticles Identification Framework based on Convolutional Neural Networks and Center-to-Edge Distance Graph Analysis

Jaeuk Jang,Hyunsoo Lee 대한산업공학회 2023 대한산업공학회 춘계학술대회논문집 Vol.2023 No.5

• Nanotechnology, which derives characteristics of a desired material through control of the composition and arrangement of nanoparticles constituting the material, has been applied in various fields. • Most nanoparticle images are obtained using high-magnification electron microscopy. However, processing numerous nanoparticle images and improving accuracy requires considerable time and labor. • Although automatic analysis studies have been conducted for the analysis of a large amount of images generated through an electron microscope, it is difficult to grasp the shape of nanoparticles due to the lost shape due to overlapping of nanoparticles. • To solve this problem, this study derives the features of overlapped nanoparticles images generated using SEM through Convolutional Neural Networks (CNN) and estimate the center point and radius of each nanoparticle by applying the derived features to Center-to-Edge Distance Graph Analysis. Silicon image dataset [그림 본문 참조] • 24 image data → 296 cropping images • Size (1024 X 768) • Grey-scaled images

Performance Analysis of Real-time Orbit Determination and Prediction for Navigation Message of Regional Navigation Satellite System

Jaeuk Park,Bu-Gyeom Kim,Changdon Kee,Donguk Kim 사단법인 항법시스템학회 2023 Journal of Positioning, Navigation, and Timing Vol.12 No.2

This study presents the performance analysis of real-time orbit determination and prediction for navigation message generation of Regional Navigation Satellite System (RNSS). Since the accuracy of ephemeris and clock correction in navigation message affects the positioning accuracy of the user, it is essential to construct a ground segment that can generate this information precisely when designing a new navigation satellite system. Based on a real-time architecture by an extended Kalman filter, we simulated orbit determination and prediction of RNSS satellites in order to assess the accuracy of orbit and clock prediction and signal-in-space ranging errors (SISRE). As a result of the simulation, the orbit and clock accuracy was at 0.5 m and 2 m levels for 24 hour determination and six hour prediction after the determination, respectively. From the prediction result, we verified that the SISRE of RNSS for six hour prediction was at a 1 m level.

Co-design Development of Smartphone-based Stress Management Application with College Students

Jaeuk Jeong,Chaerin Lee,Juho Kim,Jeongha Kim,Doyoon Kim,Hyunjoo Na 한국간호과학회 2019 한국간호과학회 학술대회 Vol.2019 No.10

The more transparent, the better? : Effect of transparency regime changes on large/actively traded stocks in KRX

Jaeuk Khil,Young S. Park,Jhinyoung Shin 한국재무학회 2011 한국재무학회 학술대회 Vol.2011 No.09

In an effort to improve market transparency, Korea Exchange (KRX) has continuously adopted measures to publicly disclose more information regarding quotes and orders. This paper studies the effects of four events initiated by KRX aimed to enhance the pre-trade transparency: two for market opening by single-price call auction, and two for regular trading hours operated by continuous auction. Our focus is on the effect of the improved pre-trade transparency on the trading of large and/or most actively traded stocks. We select 20 stocks, 10 largest stocks in market capitalizations, and another 10 most actively traded stocks based on trading volumes, before and after each event. We proceed to directly analyze on how liquidity, depth, and investors trading behavior were affected by these events. Market liquidity and depth were generally improved but not by statistically significant margin. Investors adjusted their trading strategies as smaller number of orders was cancelled and it took less time to for traders to cancel their orders. Our study shows that policies aimed to enhance pre-trade transparency might have only marginal impact on the trading of large and/or actively traded stocks as they have limited success in providing additional information to the investors of these stocks.

Overlapped Nanoparticles Identification Framework based on Convolutional Neural Networks and Center-to-Edge Distance Graph Analysis

Jaeuk Jang,Hyunsoo Lee 한국경영과학회 2023 한국경영과학회 학술대회논문집 Vol.2023 No.5

• Nanotechnology, which derives characteristics of a desired material through control of the composition and arrangement of nanoparticles constituting the material, has been applied in various fields. • Most nanoparticle images are obtained using high-magnification electron microscopy. However, processing numerous nanoparticle images and improving accuracy requires considerable time and labor. • Although automatic analysis studies have been conducted for the analysis of a large amount of images generated through an electron microscope, it is difficult to grasp the shape of nanoparticles due to the lost shape due to overlapping of nanoparticles. • To solve this problem, this study derives the features of overlapped nanoparticles images generated using SEM through Convolutional Neural Networks (CNN) and estimate the center point and radius of each nanoparticle by applying the derived features to Center-to-Edge Distance Graph Analysis. Silicon image dataset [그림 본문 참조] • 24 image data → 296 cropping images • Size (1024 X 768) • Grey-scaled images

A Study of Bodily Desire and Moral Struggle at the Fin de Siecle in Dr. Jekyll and Mr. Hyde and The Picture of Dorian Gray

( Jaeuk Choo ) 21세기영어영문학회 2015 영어영문학21 Vol.28 No.3

This essay conducts a study of the relation or interaction between body and mind in the nineteenth century novels Dr. Jekyll and Mr. Hyde and The Picture of Dorian Gray. The focus here is on the moral issues raised by the interaction between body and mind, in particular, between body and desire and on the evolutionary issues raised by the transformation and mutation of the body observed in the novels. It seems that Charles Darwin``s evolution theory changed not only the ontological status of the people, but also writers`` concept of morality. A sense of morality had been deeply rooted in the unconsciousness of the Victorian people for a long time, but the theory began to pull down the solid wall of the moral consciousness. Gray``s and Jekyll``s attitudes toward life have degenerated slowly but surely. In a sense, the driving force of evolution comes from each individual``s desire to survive. The desire is so influential to humans`` and nonhumans`` lives that it works as a fundamental power sustaining them in social, cultural, and natural environments. Each individual``s desire interacts with his or her body in a certain way, which in return responds quickly to the desire. Besides the generally accepted notion that humans are faithful to the instinct and desire, the other law of nature that exercises influence over them is Darwininan evolution to survive, reproduce, and thrive, regardless of morality, in any social and cultural environment. As examined in this essay, nevertheless, it is well revealed in Dr. Jekyll and Mr. Hyde and The Picture of Dorian Gray that Jekyll and Gray seem to live on, simultaneously suffering from, and struggling against, the immoral desires and laws.

Learning Korean Vocabulary through Cooking in the Digital Kitchen

( Jaeuk Park ),( Jieun Kiaer ) 국제한국어교육학회 2016 국제한국어교육학회 학술대회논문집 Vol.2016 No.-

Hypergraph based Multi-Agents Representation Learning for Similarity Analysis

Jaeuk Baek,Changeun Lee 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10

As a lot of agents with diverse sensing capabilities are expected to collaborate in the near future, the needs to process a huge number of multi-modal data are emerging to recognize global situations, events or environment. In this paper, we propose a hypergraph based multi-agents representation learning (HMARL) to obtain agent embedding vectors, which can be used to classify agents in the same region and correlate the collected data of similar properties. To this end, the proposed HMARL transforms the multi-modal data into the same graph structure with nodes and their relations. Then, a hypergraph is constructed to integrate local graphs and a hypergraph random walk is applied to obtain the sequence of adjacent agents, which is used to train the agent embedding vectors. Experiments on public datasets are provided for similarity analysis on agents and their collected data.