• 한국전자거래학회지
• /
• 제25권2호
• /
• pp.15-27
• /
• 2020

본 연구는 일정계획을 위한 간트 차트(Gantt Chart) 생성과정을 세로로 세우면 일자형만 존재하는 테트리스(Tetris) 게임과 유사하다는 아이디어에서 출발하였다. 테트리스 게임에서 X축은 M개의 설비(Machine)들이 되고 Y축은 시간이 된다. 모든 설비에서 모든 종류(Type)의 주문은 분리 없이 작업 가능하나 작업물 종류가 다를 경우에는 시간지체 없이 작업 준비비용(SetupCost)이 발생한다는 가정이다. 본 연구에서는 앞에서 설명한 게임을 간트리스(Gantris)라 명명하고 게임환경을 구현 하였으며, 심층 강화학습을 통해서 학습한 인공지능이 실시간 스케줄링한 일정계획과 인간이 실시간으로 게임을 통해 수립한 일정계획을 비교하였다. 비교연구에서 학습환경은 단일 주문목록 학습환경과 임의 주문목록 학습환경에서 학습하였다. 본 연구에서 수행한 비교대상 시스템은 두 가지로 4개의 머신(Machine)-2개의 주문 종류(Type)가 있는 시스템(4M2T)과 10개의 머신-6개의 주문종류가 있는 시스템(10M6T)이다. 생성된 일정계획의 성능지표로는 100개의 주문을 처리하는데 발생하는 Setup Cost, 총 소요 생산시간(makespan)과 유휴가공시간(idle time)의 가중합이 활용되었다. 비교연구 결과 4M2T 시스템에서는 학습환경에 관계없이 학습된 시스템이 실험자보다 성능지표가 우수한 일정계획을 생성하였다. 10M6T 시스템의 경우 제안한 시스템이 단일 학습환경에서는 실험자보다 우수한 성능 지표의 일정계획을 생성하였으나 임의 학습환경에서는 실험자보다 부진한 성능지표를 보였다. 그러나 job Change 횟수 비교에서는 학습시스템이 4M2T, 10M6T 모두 사람보다 적은 결과를 나타내어 우수한 스케줄링 성능을 보였다.

• 문화기술의 융합
• /
• 제9권2호
• /
• pp.475-481
• /
• 2023

머신러닝과 같은 소프트웨어가 일상생활에 매우 큰 영향력을 발휘하고 있는 상황에서, 소프트웨어의 개발비용을 평가하는 비용 모델의 중요성이 지속적으로 증가하고 있다. 비용 모델로서 LOC(Line of Code)와 M/M(Man-Month) 모델은 소프트웨어의 양적인 요소들을 측정하는 비용모델이다. 이와는 달리, FP(Function Point)는 소프트웨어의 기능적 특징들을 평가하는 비용모델로서 소프트웨어의 질적인 요소를 평가한다는 점에서 효과적이다. 그러나 FP는 머신러닝 소프트웨어의 주요한 요소들을 평가하지 않기 때문에 머신러닝 소프트웨어를 평가하는데 한계를 가진다. 본 논문은 확장형 FP(Extended Function Point, ExFP)를 제안한다. 확장형 FP는 머신러닝의 주요 특징인 하이퍼 파라미터와 그것의 최적화에 대한 복잡도를 반영하여 소프트웨어의 기능적 요소를 평가하도록 확장하였기 때문에 머신러닝과 같은 최신 소프트웨어에의 비용 평가에 적합하다. 머신러닝 소프트웨어의 특징을 반영한 평가를 통해 제안된 확장형 FP의 효용성을 보였다.

• 대한통합의학회지
• /
• 제4권1호
• /
• pp.65-72
• /
• 2016

Purpose : This study was carried out to find out the relationship between emotion intelligence, learning flow and career stress of nursing students and influence factors for career stress. Methods : This study targeted 197 university students in their freshman-senior year attending College of Nursing located in P Metropolitan City. For collected data, real numbers and percentage, mean and standard deviation and multiple regression analysis were carried out by using PASW 21.0 program and the correlation between emotion intelligence, learning flow and career stress was analyzed with Pearson's correlation coefficients. Results : Emotional self-awareness(M=3.80, SD =.71), clear goals(M=3.39, SD=.90) and school environment stress(M=2.97, SD=.96) were found to be high in the degree of emotion intelligence, learning flow and career stress of the subjects. The relationship between emotion intelligence and learning flow showed a positive correlation(r=.489, p<.01) in the correlation between emotion intelligence, learning flow, career stress and emotion intelligence showed a negative correlation with career stress(r=-.204, p<.01). Emotion intelligence and learning flow show that career stress is predicted significantly (${\beta}$ =-.15, p < .01) and explained a career stress variate as 18%(F = 24.5, p < .01). Conclusion : Emotion intelligence of nursing students was found to be very influential on the degree of learning flow or career stress. Based on the results of this study, replication studies on emotion intelligence and career stress are needed and the development of intervention programs to increase emotion intelligence is needed.

• 정보교육학회논문지
• /
• 제16권3호
• /
• pp.309-318
• /
• 2012

E-러닝, U-러닝, M-러닝에 이어 요즘의 대세는 스마트 러닝이다. 정부는 지난 2011년 6월 스마트교육 추진 전략을 발표하여 우리나라 스마트 교육의 비전과 추진 방향을 제시하였다. 하지만 현재 정부에서 주도하는 스마트 교육 정책의 추진에 있어 무엇보다도 현장의 현실과 환경적 고려, 교육의 주체자들의 능력 등 다양한 요인의 고려가 없이 무조건적인 적용이 이루어지고 있는 것이 현실이다. 이에 본 연구는 교육현장의 현실과 스마트 환경을 파악하고 이를 교육할 초등학교 교사들의 스마트 기기 활용현황과 현재 정부에서 추진하고 있는 스마트 교육의 여러 요소에 대한 활용인식 및 실태를 조사하여 문제점을 분석하고 개선 방안을 모색하여 보다 체계적인 스마트 교육의 기반을 마련함에 있다.

• Educational Technology International
• /
• 제9권1호
• /
• pp.1-23
• /
• 2008

Despite considerable commitment to the application of action learning as an organization development intervention, no identified systematic investigation of action learning practices has been reported. Based on a systematic literature review, the purpose of this paper is to identify whether researchers strike a balance between action and learning in their studies of action learning. Research findings in this study included: (1) only 32 empirical studies were found from the electronic database search; (2) based on the hypothesized continuum of Revans' original proposition of balancing action and learning, the author categorized 32 studies into three groups: action-oriented, learning-oriented, and balanced action learning; (3) there were only nine studies on balanced action learning among 32 empirical studies, whose insights included an effective use of project teams, applications of action learning for organization development, and key success factors such as time, reflection, and management support; (4) case study was among the most frequently used research method and only six quality studies met key methodological traits; and (5) therefore, more rigorous empirical research employing quantitative methods as well as case studies is needed to determine whether researchers strike a balance between action and learning in studies on action learning.

• 한국통신학회:학술대회논문집
• /
• 한국통신학회 2006년도 하계종합학술발표회 논문 초록집
• /
• pp.339-339
• /
• 2006

• 지식경영연구
• /
• 제20권4호
• /
• pp.149-168
• /
• 2019

In the era of the Fourth Industrial Revolution, digital transformation is emerging in the education and learning fields. As the use of the mobile Internet and mobile devices has become a daily life, mobile learning that supports a variety of learning in a mobile environment is drawing attention. Mobile learning applications (apps) are expected to expand their use by providing a convenient learning environment anytime, anywhere. This study investigates the use of mobile learning apps in English education, which is one of the most popular learning areas, and empirically examines the factors that influence the continuous use of mobile learning apps. In particular, it analyzes the differences between Chinese and Korean users. The results of this study provide theoretical and practical implications to promote the development of mobile apps suitable for mobile learning environments and the sustainable user growth in mobile learning.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제31권2호
• /
• pp.93-107
• /
• 1992

The purpose of this study is to make out teaching-learning method for developing mathematical abilities of the 1st grade children in elementary school by investigating cognitive effects which mathematical pre-experiences given intentionally by teachers have on children's learning mathematics. The research questions for this purpose are as follows: In learning effects through mathematical pre-experiences given intentionally by teachers. 1) is there any differences between children with pre-experiences and children without them in Mathematics Achievement Test\ulcorner 2) is there any differences between children with pre-experiences and children without them in Transfer Test for learning effects\ulcorner For this study, a class with 41 children in H elementary school located in a Myon near Chong-ju was selected as an experimental group and a class with 43 children in G elementary school in the same Myon was selected as a control group. Nonequivalent Control Group Design of Quasi-Experimental Design was applied to this study. To give pre-experiences to the children in experimental group, their classroom was equipped with materials for pre-experiences, so children could always observe the materials and play with them. The materials were a round-clock on the wall, two pairs of scales, fifty dice, some small pebbles, two pairs of weight scales, two rulers on the wall, and various cards for playing games. Pre-experiences were given to the children repeatedly through games and observations during free time in the morning (00:20-09:00) and intervals between periods. There was a pretest for homogeneity of mathematics achievement between the two groups and were Mathematics Achievement Test (30 items) and Transfer Test (25 items) for learning effects as post-tests. The data were collected from the pretest on April 8 (control group), on April 11 (experimental group) and from the Mathematics Achievement Test and Transfer Test on July 15 (experimental group) and on July 16 (control group). T-test was used to analyze if there were any differences in the results of the test. The results of the analysis were as follows: (1) As the result of pretest, there was not a significance difference between the experimental group (M=17.10. SD=7.465) and the control group (M=16.31, SD=6.974) at p<.05 (p=0.632). (2) For the question 1. in the Mathematics Achievement Test, there was a significant difference between the experimental group (M=26.08, SD=4.827) and the control group (M=22.28. SD=5.913) at p<.01 (p=.003). (3) For the question 2. in the Transfer Test for learning effects. there was a significant difference between the experimental group (M=16.41, SD=5.800) and the control group (M=11.84, SD=4.815) at p<001, (p=.000). From the results of the analyses obtained in this study. the following conclusions can be drawn: First, mathematical pre-experiences given by teachers are effective in increasing mathematical achievement and transfer in learning mathematics. Second, games. observations, and experiments given intentionally by teachers can make children's mathematical experiences rich and various, and are effective in adjusting individual differences for the mathematical experiences obtained before they entered elementary schools. Third, it is necessary for teachers to give mathematical pre-experiences with close attention in order to stimulate children's mathematical interests and intellectual curiosity.

• ETRI Journal
• /
• 제44권5호
• /
• pp.837-848
• /
• 2022

Analog circuit design is comparatively more complex than its digital counterpart due to its nonlinearity and low level of abstraction. This study proposes a novel low-level hybrid of the sine-cosine algorithm (SCA) and modified grey-wolf optimization (mGWO) algorithm for machine learning-based design automation of CMOS analog circuits using an all-CMOS voltage reference circuit in 40-nm standard process. The optimization algorithm's efficiency is further tested using classical functions, showing that it outperforms other competing algorithms. The objective of the optimization is to minimize the variation and power usage, while satisfying all the design limitations. Through the interchange of scripts for information exchange between two environments, the SCA-mGWO algorithm is implemented and simultaneously simulated. The results show the robustness of analog circuit design generated using the SCA-mGWO algorithm, over various corners, resulting in a percentage variation of 0.85%. Monte Carlo analysis is also performed on the presented analog circuit for output voltage and percentage variation resulting in significantly low mean and standard deviation.

• 한국측량학회지
• /
• 제37권6호
• /
• pp.517-523
• /
• 2019

PM₁₀ 농도는 시간 및 공간 의존성을 동시에 가지는 시공간 데이터이지만 현실적으로 연속적인 시공간 데이터를 획득하는 것은 쉬운 일이 아니다. 본 연구에서는 위성영상과 대기질 및 기상 관측 센서 데이터를 복합적인 딥러닝 모델에 적용하여 시공간 해상도를 향상시키는 모델을 설계하였다. 설계된 딥러닝 모델은 기상, 토지 이용 등 PM₁₀ 농도에 영향을 줄 수 있는 인자를 이용하여 학습하였으며, 대기질 및 기상 관측 데이터만을 이용하여 15분 단위의 30m×30m의 공간해상도를 PM₁₀ 영상을 생성하였다.