• Design Convergence Study
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• v.16 no.5
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• pp.125-140
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• 2017

This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.

• Information Systems Review
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• v.20 no.4
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• pp.25-41
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• 2018

Applying predictive analytics to enterprise processes is an effective way to reduce operation costs and enhance productivity. Accordingly, the ability to predict business processes and performance indicators are regarded as a core capability. Recently, several works have predicted processes using deep learning in the form of recurrent neural networks (RNN). In particular, the approach of predicting the next step of activity using static or dynamic RNN has excellent results. However, few studies have given attention to applying deep learning in the form of dynamic RNN to predictions of process performance indicators. To fill this knowledge gap, the study developed an approach to using process mining and dynamic RNN. By utilizing actual data from a large domestic company, it has applied the suggested approach in estimating timely stocking in purchasing process, which is an important indicator of the process. The analytic methods and results of this study were presented and some implications and limitations are also discussed.

• International Commerce and Information Review
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• v.13 no.2
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• pp.121-148
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• 2011

Korean small and medium sized firms are dramatically expanding during the past two decades. Since small and medium sized firms begun to invest overseas to cope with the external and internal business environment. the influencing factors should defined for the successful foreign investment. This paper presents the research model explaining successful knowledge transfer between Korean small and medium sized firms and partners for foreign investment. This model examines investing companies' organizational characteristics, partners' learning capability and relational characteristics between two partners. Detail variables include the learning culture and codifiability of investing companies, and absorptive capability of partners, and communication and trust as a relational factors between investing companies and partners. The result of empirical analysis of sample companies shows that knowledge culture and codifiability of investing companies, and communication from the relational factors are important for knowledge transfer. These results provide some implications for the successful foreign investment of small and medium sized firms. Firstly the investing company should develop its own learning culture and internal procedure for the successful foreign investment. And frequent communication channel is necessary for knowledge transfer and the trustful relationship between investors and partner.

• Journal of The Korean Association For Science Education
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• v.22 no.3
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• pp.571-585
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• 2002

This is one of the basic research for inspecting the possibility of the development of logical thinking capability to make possible formal thinking. The 5th grade students (n=306) in the elementary school were participated in this study. Performing the 6 variable-controlling activities in the 'Thinking Science' program for one semester, the SRT II test and the Variable-Controlling test were operated to examine the effects on the development of the variable-controlling ability by treatments, gender, and cognitive levels. Performing of the variable-controlling activities was highly successive on the development of students' variable-controlling ability. Although learning effect on the ability of identifying causal variable was moderate, the abilities of controlling experimental condition, measurement of variable, and identifying result variable were significantly developed. There was statistically significant difference by gender. Girls showed better performance all the time in both groups. Boys in the experimental group were getting better gradually, so the difference by gender was somewhat decreased. Examining the variable-controlling ability by cognitive levels, students in the experimental group show significant increase in all levels, especially the students in early, mid, and mature concrete level show substantial learning effects. The results of this study implied that the variable-controlling activities in the 'Thinking Science' could be effective for learning of variable-controlling and eventually for the development of logical thinking capability to make possible formal thinking.

• Journal of Korean Home Economics Education Association
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• v.29 no.1
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• pp.111-124
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• 2017

The purpose of this study was to determine the perception and understanding of Free Learning Semester (FLS) in home economics teachers and to provide basic informations for effective implement of FLS in future school curricula. Home economics teachers perceived that the objective of FLS was to help students explore their careers and make preliminary decisions. In addition, teachers thought that FLS should be run by active students' participation to find out their dreams and talents. However, teachers felt difficulties in obtaining information or documents related to implementing FLS. Moreover, there were lack of connected activities with local communities to operate FLS. Teachers recognized that it is necessary to receive FLS-related education. Regarding home economics teachers' role in FLS implement, they should provide career education with a perspective of lifelong career and nurture students' capability to lead their lives by themselves. In that sense, FLS should help students find out their dreams and talents, think about their career, set up lifelong career plan through home economics education, and nurture capability to lead their lives. In addition, home economics teachers should provide continuous career education in home economics education at academic semesters.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.383-392
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• 2013

In order to promote social responsibility, a company reads to engage in various activities to increase their competitiveness to ensure stable and continuous development. One of the activities is to input human/material resources in order to draw and develop the core abilities of member for the productivity improvement of the company. This study is concerned with capability improvement of members in relation to core company performance, the focus of the study is to identify how education training in a company may contribute to team performance by leaning transfer through empirical study. As a result of this study, it was found that the personality of members, as well as the training programs, within the company can be a significant factor for improving productivity and performance of the company. In addition, team members noted that learning transfer take place when effectively lead through the leadership of a boss and identified that this leadership ultimately has a significant effect on team performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.147-152
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• 2016

One of major issues in machine learning that extracts and acquires knowledge implicit in data is to find an appropriate way of representing it. Knowledge can be represented by a number of structures such as networks, trees, lists, and rules. The differences among these exist not only in their structures but also in effectiveness of the models for their problem solving capability. In this paper, we propose partition utility as a criterion function for clustering that can lead to simplification of the model and thus avoid overfitting problem. In addition, a heuristic is proposed as a way to construct balanced hierarchical models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5097-5106
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• 2010

Two perspectives on developing better decision capabilities for a warranty system can be identified: one involving the inclusion of a 'learning' module and the other the inclusion of a 'prioritization' capability. This paper demonstrates how a warning process can be included in a warranty system by coupling with a neural network's learning capabilities. In addition to the neural network, a method is employed for assigning priorities to warning criteria by using the analytic hierarchy process (AHP). Thus, it is possible to construct an integrated system with three components: the warranty system, the AHP module, and the neural network system. A case study is provided to enhance the accuracy of warning/detection judgment in a warranty system for automobile companies, having many factors related to the warranty system.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1438-1454
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• 2016

Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.