• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.155-173
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• 2010

Although online education service markets are growing fast, previous studies have been limited to the studies on media types or system qualities of online education. In order to provide timely implications for online education service providers to maintain and increase the number of users, other factors such as interactivity and community perspectives should be considered. In this study, social capital and service quality were adopted as antecedents of learning motivation. Also, service quality dimensions, as well as learning motivation, were chosen to examine its impact on intention to repurchase of online education services. Research findings show that structural and cognitive dimensions of social capital are proved as antecedents of relational capital; structural and relational social capital positively influence on learning motivation; tangibility positively makes impact on learning motivation; and intention to repurchase is positively influenced by responsiveness and learning motivation. Practical implications based on the research findings are presented.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.225-232
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• 2023

With the recent increase of multiple robots cooperating in smart manufacturing logistics environments, it has become very important how to predict the safety and efficiency of the individual tasks and dynamically assign them to the best one of available robots. In this paper, we propose a novel task policy learner based on deep relational reinforcement learning for predicting the safety and efficiency of tasks in a multi-robot manufacturing logistics environment. To reduce learning complexity, the proposed system divides the entire safety/efficiency prediction process into two distinct steps: the policy parameter estimation and the rule-based policy inference. It also makes full use of domain-specific knowledge for policy rule learning. Through experiments conducted with virtual dynamic manufacturing logistics environments using NVIDIA's Isaac simulator, we show the effectiveness and superiority of the proposed system.

• Journal of Multimedia Information System
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• v.7 no.3
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• pp.205-214
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• 2020

Crime has become one of the major problems in modern society. Even though visual surveillances through closed-circuit television (CCTV) is extensively used for solving crime, the number of crimes has not decreased. This is because there is insufficient workforce for performing 24-hour surveillance. In addition, CCTV surveillance by humans is not efficient for detecting dangerous situations owing to accuracy issues. In this paper, we propose the autonomous detection of dangerous situations in CCTV scenes using a deep learning model with relational inference. The main feature of the proposed method is that it can simultaneously perform object detection and relational inference to determine the danger of the situations captured by CCTV. This enables us to efficiently classify dangerous situations by inferring the relationship between detected objects (i.e., distance and position). Experimental results demonstrate that the proposed method outperforms existing methods in terms of the accuracy of image classification and the false alarm rate even when object detection accuracy is low.

• Communications of Mathematical Education
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• v.29 no.2
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• pp.215-239
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• 2015

A goal of this study is figuring out how fraction learning centered on various representation activities influences the fraction comprehension and mathematical attitudes. The study focused on 33 4th-grade students of B elementary school in Seoul. In the study, 15 fraction learning classes comprising enactive, iconic, and symbolic representations took place over 6 weeks. After the classes, the ratio of the students who achieved relational understanding increased and the students averagely recorded 90 pt or more on the fraction comprehension test I, II and III. Two-dependent samples t-test was conducted to analyze a significant difference in mathematical attitudes between pre-test and post-test. On the test result, there was the meaningful difference with 0.01 level of significance. To conclude, the fraction learning centered on various representation activities improves students' relational understanding and fraction understanding. In addition, the fraction learning centered on various representation activities gives positive influences on mathematical attitudes since it increases learning orientation, self-control, interests, value cognition, and self-confidence of the students and decreases fears of the students.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• Journal of the Korean Geographical Society
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• v.36 no.5
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• pp.539-560
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• 2001

This paper aims to critically review the geographical literature on learning and proximity that stresses the role of the regions and geographical proximity in sustaining competitive advantage, and to conceptualize a relational/organizational perspective on the sources of knowledge and learning in the firm. In the first part of the paper, I argue that the geographical literature lacks the deliberate scrutiny of how learning occurs in the firm and where the sources of knowledge and learning come from. Secondly, I attempt to elaborate the concept of proximity through a relational/organizational perspective. Thirdly, I delve into how learning takes place and is realized in the firm through communities in the firm such as communities of practice, epistemic communities and task-force teams and how such communities in the firm generate knowledge and sustain loaming by drawing on relational/organizational proximity. This paper concludes by claiming that the sources of learning exist in organizational spaces, with complex geographies mobilizing distributed knowledge and competences and combining varied forms of knowledge beyond the simple demarcation of tacit and codified knowledge.

• Journal of Contemporary Eastern Asia
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• v.17 no.1
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• pp.94-111
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• 2018

This study examines Korea's international development volunteer program as a citizen diplomacy initiative. Informed by a cultural perspective of transmission and relational models of public diplomacy, I examine the ways in which volunteer training incorporates cultural-learning into its program. The study finds that volunteer training is largely based on an instrumentalist approach to culture that places emphasis on learning the "explicit" side of culture, such as Korean traditional dance, art, and food as a strategy to promote the country's national image. In contrast, much less covered in the training program is a relational approach to culture-learning that is guided by a reflexive understanding of the "implicit" side of culture, or the values and beliefs that guide the worldviews and behavior of both volunteers and host constituents. Whereas the value of the volunteer program as a citizen diplomacy initiative is in its potential to build relationships based on two-way engagement, its conception of culture is mostly guided by that of the transmission model of public diplomacy. Based on the findings, this study calls for an integrated approach to culture-learning in volunteer training program to move the citizen diplomacy initiative forward.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1187-1190
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• 1993

The problem of the optimization of fuzzy relational models for dealing with (non-fuzzy) numerical data is investigated. In this context, interfaces optimization assumes particular importance, becoming a determinant factor in what concerns the overall model performance. Considering this, several scenarios for building fuzzy relational models are presented. These are: (i) optimizing I/O interfaces in advance (independently from the linguistic part of the model); (ii) optimizing I/O interfaces in advance and allowing that their optimized parameters may change during the learning of the linguistic part of the model; (iii) build simultaneously both interfaces and the linguistic subsystem; and (iv) build simultaneously both linguistic subsystem and interfaces, now subject to semantic integrity constraints. As linguistic subsystems, both a basic type and an extended versions of fuzzy relation equations are exploited in each one of these scenarios. A comparative analysis of the differ nt approaches is summarized.

• Journal of the Korean School Mathematics Society
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• v.15 no.4
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• pp.643-671
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• 2012

The purpose of this study was to examine How the exploratory activities using Excel and GSP which are exploratory software, in learning analytic geometry affected on the underachievers' analytic geometry concept development process. The subjects of 5 students who received the 8th~9th grades from their examination of the last semester, participated in a total of 7 units based on Skemp's intelligent learning model. The results of the study showed that there were two important cases found to nearly achieve the category $R_2$. One was reflective thinking could happen through exploratory software in category $R_1$. The other was the exploratory activities which could have the same effectiveness as the relational understanding in category $I_2$, as Skemp mentioned that there is a room to be achieved in the elementary level when such relational understanding is achieved.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.605-615
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• 2005

This paper represent a method of U-Learning based on advanced e-Learning. Ubiquitous computing configuration and advanced Information technology. As we know well, the 21th century is called knowledge based informational society. Many scholar stress that the improved 21th century's educational paradigm be able to success based on advanced educational paradigm. Therefore, we discuss the material for e-Learning fields including with necessity, vision, law, quality authorization etc. Also, we discuss the relational technologies including with meta data, standardization, identification etc. Finally, we propose a method for constructing the U-Learning based on advanced e-Learning and Ubiquitous computing configuration.