• 한국경영정보학회:학술대회논문집
• /
• 2007.06a
• /
• pp.435-440
• /
• 2007

본 연구는 무리행동과 인지적 유용성을 중심으로, e-learning 컨텐츠 구매에 미치는 영향을 e-learning 수강경험자 집단과 경험하지 못한 잠재구매자 집단의 차이점을 경험적인 측면에서 밝히고자 시도하였다. 전체 528명의 표본을 경험자(395명)와 비경험자(133명)로 나누어 PLS(Partial Least Square)를 통하여 분석한 결과 e-learning 구매 경험자는 인지적 유용성이 구매의도에 주는 영향이 무리행동의 영향보다 큰 것으로 나타났고, 잠재 구매자는 무리행동이 구매의도에 주는 영향이 더 큰 것으로 나타났다.

• Journal of information and communication convergence engineering
• /
• v.5 no.1
• /
• pp.50-53
• /
• 2007

This paper presents face features detection and a new physiological neuro-fuzzy learning method by using two-dimensional variances based on variation of gray level and by learning for a statistical distribution of the detected face features. This paper reports a method to learn by not using partial face image but using global face image. Face detection process of this method is performed by describing differences of variance change between edge region and stationary region by gray-scale variation of global face having featured regions including nose, mouse, and couple of eyes. To process the learning stage, we use the input layer obtained by statistical distribution of the featured regions for performing the new physiological neuro-fuzzy algorithm.

• ETRI Journal
• /
• v.43 no.6
• /
• pp.1004-1012
• /
• 2021

The collaboration productively interacting between multi-agents has become an emerging issue in real-world applications. In reinforcement learning, multi-agent environments present challenges beyond tractable issues in single-agent settings. This collaborative environment has the following highly complex attributes: sparse rewards for task completion, limited communications between each other, and only partial observations. In particular, adjustments in an agent's action policy result in a nonstationary environment from the other agent's perspective, which causes high variance in the learned policies and prevents the direct use of reinforcement learning approaches. Unexpected social loafing caused by high dispersion makes it difficult for all agents to succeed in collaborative tasks. Therefore, we address a paradox caused by the social loafing to significantly reduce total returns after a certain timestep of multi-agent reinforcement learning. We further demonstrate that the collaborative paradox in multi-agent environments can be avoided by our proposed effective early stop method leveraging a metric for social loafing.

• International journal of advanced smart convergence
• /
• v.10 no.4
• /
• pp.141-148
• /
• 2021

This study was tried to explore the mediating effect of workplace learning and self-efficacy on the relationship between technostress and job satisfaction in convalescent hospital nurses. Data were collected from 149 nurses working at one of 10 convalescent hospitals located in Korea's D region and between July 20 and August 12, 2019 and analyzed using SPSS 24.0. The mediating effects of workplace learning and self-efficacy in the relationship between technostress and job satisfaction were investigated by conducting hierarchical regression analysis and testing for significance based on bootstrapping p values. We found that workplace learning had a complete mediating effect, and self-efficacy a partial mediating effect, in the relationship between technostress and job satisfaction in convalescent hospital nurses. Exploring diverse factors and environmental features affecting job satisfaction in convalescent hospital nurses is highly relevant to clinicians, especially given the gradually increasing number of convalescent hospitals, changes during the era of technology fusion, and the strategic demands arising from an aging society.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.383-384
• /
• 2022

Gas Combustion Unit (GCU) onboard liquefied natural gas carriers handles boil-off to stabilize tank pressure. There are many factors for LNG cargo operators to take into consideration to determine whether to use GCU or not. Gas consumption of main engine and re-liquefied gas through the Partial Re-Liquefaction System (PRS) are good examples of these factors. Human gas operators have decided the operation so far. In this paper, some deep learning neural network models were developed to provide human gas operators with a decision support system. The models consider various factors specially into GCU operation. A deep learning model with Sigmoid activation functions in input layer and hidden layers made the best performance among eight different deep learning models.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.67-76
• /
• 2024

Diabetic retinopathy is a threatening complication of diabetes, caused by damaged blood vessels of light sensitive areas of retina. DR leads to total or partial blindness if left untreated. DR does not give any symptoms at early stages so earlier detection of DR is a big challenge for proper treatment of diseases. With advancement of technology various computer-aided diagnostic programs using image processing and machine learning approaches are designed for early detection of DR so that proper treatment can be provided to the patients for preventing its harmful effects. Now a day machine learning techniques are widely applied for image processing. These techniques also provide amazing result in this field also. In this paper we discuss various machine learning and deep learning based techniques developed for automatic detection of Diabetic Retinopathy.

• Korean Journal of Human Ecology
• /
• v.24 no.6
• /
• pp.755-768
• /
• 2015

The purpose of this study was to verify the mediating effects on self-regulated learning ability and sense of community in the relationship between parents' neglect and children's academic achievement. The subjects used in this study were 2,218 6th grade elementary school students from the third wave sample of the 2012 Korean Children and Youth Panel Survey (KCYPS). For data analysis, the three-step mediated regression analysis by Baron and Kenny (1986) was performed and the Sobel test was carried out in order to verify the effectiveness of mediation effects. The main results of the present study were as follows. First, the self-regulated learning ability and sub-component factors of achievement value, mastery goal orientation, behavioral control, academic time-management revealed to have a partial mediation effect in the relationship between parents' neglect and children's academic achievement. Second, the sense of community also showed to have a partial mediation effect on the relationship between parents' neglect and children's academic achievement. The findings of this study provide a viewpoint to deeply observe the problem of parents' neglect in connection with children's self-regulated learning ability and sense of community, and can be used as practical data to develop various programs for the benefit of improving children's academic achievement.

• Journal of Industrial Convergence
• /
• v.20 no.6
• /
• pp.73-81
• /
• 2022

This study is a descriptive research study to analyze the relationship between learning motivation, learning immersion, and self-directed learning. For this study, data were collected from August 1 to 30, 2021. The collected data were analyzed using the IBM SPSS/WIN 22.0 program. The learning motivation was positively correlated with learning immersion and self-directed learning. In analysis results, the factors affecting learning immersion are learning motivation and self-directed learning. And it was confirmed that self-direction was a partial mediating factor in the relationship between learning motivation and learning immersion. Learning motivation is an important factor for nursing students' learning immersion and self-directed learning. Therefore, specific measures to improve self-directed learning should be prepared for learning immersion. Therefore, nursing students' self-directed learning is an important factor for learning motivation and learning immersion, and specific measures to improve that should be prepared.

• Information Systems Review
• /
• v.12 no.2
• /
• pp.25-45
• /
• 2010

Today, as potential uses of the Internet continue to grow, e-learning in university an education course has taken on an important role. Accordingly, to provide good e-learning services, university officials attempt to develop high quality educational content in their courses. In this study, we investigate e-learning adoption by students using the extended technology acceptance model (TAM). In particular, trust in the online environment plays an extremely crucial role in student willingness to adopt e-learning. Therefore, in this study, we analyzed the relationships of perceived ease of use, perceived usefulness, attitude, and actual use on students' level of trust using a partial least squares (PLS) approach. This study suggests valuable implications for developing e-learning strategies and implementing e-learning.

• The Journal of the Korea Contents Association
• /
• v.13 no.2
• /
• pp.8-18
• /
• 2013

In this paper, we capture learning while taking a video, play time and time line of the video frame in the form of areas that require re-learning in HTML5 mobile web store. When you select an image frame can display a list of the frame to take advantage of HTML5 Video tag up to 9 capture and save the playing time at the position. Implemented in a manner that runs Effects as compared to learning to run the entire frame capture learning and re-learning frame partial immersion learners matchumhyeong storytelling can be implemented. Interval Iterative Learning in a random order, so learners can level alignment by iterative learning on academic performance can have a positive effect.