• Journal of Intelligence and Information Systems
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• v.2 no.2
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• pp.69-83
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• 1996

The objective of this research is to develop a knowledge acquisition and refinement method for a multi-objective and multi-decision FMS scheduling problem. A competitive neural network and an inductive learning algorithm are integrated to extract and refine necessary scheduling knowledge from simulation outputs. The obtained scheduling knowledge can assist the FMS operator in real-time to decide multiple decisions simultaneously, while maximally meeting multiple objective desired by the FMS operator. The acquired scheduling knowledge for an FMS scheduling problem is tested by comparing the desired and the simulated values of the multiple objectives. The result show that the knowledge acquisition and refinement method is effective for the multi-objective and multi-decision FMS scheduling problems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.213-226
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• 2013

Recently, the social commerce on Facebook.com and Twitter.com, which is represented by SNS (Social Network Service), has been expanding in the form of a combination of SNS market. This study attempted to examine the cost-effect analysis between portal-based advertisement and SNS-based advertisement in order to establish an effective advertising strategy for e-learning content providers. The results showed that portal-based advertisement is more effective than SNS-based advertisement in terms of advertising effectiveness against cost. According to these empirical research results, this article discusses the practical implications for e-learning content providers in an attempt to enable them to take competitive advantage.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.146-158
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• 2022

With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.273-282
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• 2022

In this paper, we propose a new concept for error estimation in finite element solutions, which we call mode-based error estimation. The proposed error estimation predicts a posteriori error calculated by the difference between the direct finite element (FE) approximation and the recovered FE approximation. The mode-based FE formulation for the recently developed self-updated finite element is employed to calculate the recovered solution. The formulation is constructed by searching for optimal bending directions for each element, and deep learning is adopted to help find the optimal bending directions. Through various numerical examples using four-node quadrilateral finite elements, we demonstrate the improved predictive capability of the proposed error estimator compared with other competitive methods.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.257-269
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• 2021

Intellectual capital is becoming a crucial factor for a firm's long-term profit and performance in the knowledge-based economy as more firms identify their core competence as invisible assets rather than visible assets (Itami, 1987). The company was encouraged to measure financial and non-financial factors, including the customer perspective groups, the internal business process, learning and growth perspective, then to link all these measurements in a coherent system. This paper seeks to investigate the influence of intellectual capital elements on company performance, as well as the relationship among intellectual capital elements from a cause-effect perspective. Resource-Based View (RBV) considers intellectual capital as resource and capability to sustain competitive advantage on company performance. The partial least squares approach is used to examine listed banks in Indonesia Stock Exchange for year 2017-2019. Results show that human capital directly has positive influences on innovation capital, customer capital, and process capital. Innovation capital has positive, but less significant influence on process capital, which in turn influences customer capital. Human capital and process capital also influence customer capital. Finally, customer capital contributes to performance. This study helps management to identify relevant intellectual capital elements as competitive advantage and their indicators to enhance business performance.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.459-472
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• 2006

This paper examines the implication of competition and collaboration in the innovation process for regional economic development in an increasingly knowledge-based economy. While competition is an important force in securing the competitive advantage of firms, collaboration between firms and organizations should be necessary for promoting the innovative capacity of a region. This study shows that collaboration relations based on trust and stability is important for the long-term development of learning and innovation in competitive environment, and the way how spatial proximity plays an important role in interactive learning processes. It also discusses the reason why the innovative networks facilitating the exchange of tacit knowledge should be embedded in region. Finally, the paper examines the possibility of the networks based on collaboration relationship in less-favored regions such as Chonbuk, and suggests the policy implication of the result for achieving regional innovation systems in the region successfully.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.711-718
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• 2011

The k-Nearest Neighbor classifier that does not require a training phase is appropriate for a variable number of classes problem like face recognition, Recently distance metric learning methods that is trained with a given data set have reported the significant improvement of the kNN classifier. However, the performance of a distance metric learning method is variable for each application, In this paper, we focus on the face recognition and compare the performance of the state-of-the-art distance metric learning methods, Our experimental results on the public face databases demonstrate that the Mahalanobis distance metric based on PCA is still competitive with respect to both performance and time complexity in face recognition.

• The Journal of Korean Association of Computer Education
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• v.22 no.2
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• pp.39-50
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• 2019

We designed and applied team project based learning for effective computer programming education and analyzed the effect on learning effect. Throughout simplified traditional theories and practices, teamed up with random lottery, divided role & responsibility, and conducted problem solving projects in a competitive way for a given task. When after completion of the course, we conducted questionnaires on learners in order to grasp the influence factors on the learning effect. As a result of the structural equation model analysis, it was shown that Team Project had a direct effect on the learning effect. The learning effect based on the relationships among the factors derived through exploratory factor analysis. Based on this analysis, we propose a more effective computer programming education way.

• Journal of Distribution Science
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• v.20 no.5
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• pp.1-11
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• 2022

Purpose: This study attemptsto investigate the moderating effects of environmental turbulence (ET) between learning orientation (LO) and SMEs' performance. Research design, data, and Methodology: To gain insights and provide implications for manufacturing SMEs in Pakistan, this study adopted simple random sampling to collect 379 valid responses. Data were collected through a self-administrative questionnaire from manufacturing SMEs owners/managers. Partial least squares of structural equation modeling have been used to test research hypotheses by using SmartPLS® 3.0 software. Results: The study's primary finding is that LO has a significantly positive effect on SMEs' performance and this relationship is strengthened under the moderating influence of environmental turbulence (ET). Conclusion: Environmental turbulence (ET) enables SMEs to focus on learning capability to get a more competitive advantage. Moreover, SMEs owner/managers ought to emphasize continuous learning that accentuates the capability to compete with environmental changes. Findings support notifying Pakistan's Small and Medium Enterprise Development Authority (SMEDA) in dealings with Manufacturing SMEs in terms of improving their internal capabilities. This research contributes to the literature as it provides a more detailed and in-depth explanation of distribution management-related issues faced by SMEs. This research carries a significant influence on literature and relevant Resource-based view and contingency theories.

• Management & Information Systems Review
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• v.37 no.1
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• pp.19-40
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• 2018

The purpose of this study is to analyze the effects of a firm's dynamic capabilities measured by sensing, seizing, transforming, coordinating, and learning capabilities on its competitive capabilities, such as product quality, process flexibility, delivery speed, and low cost. The relationship among dynamic capabilities, competitive capabilities, and export firm performance is set up as a research model based on empirical studies related to the existing dynamic capability perspective and competitive capabilities. To test this research model, this study collected 102 samples of data using a questionnaire survey on both manufacturing and exporting firms. The partial least squares method is used and the following results are derived from an empirical analysis. First, dynamic capabilities have a positive effect on competitive capabilities, such as product quality, process flexibility, delivery speed, and low cost. Second, product quality and process flexibility have a positive effect on export firm performance. Third, unlike previous research results, this study finds that the competitive capabilities of a firm in the areas of delivery speed and low cost do not significantly affect its performance. These findings provide meaningful implications for export venture firms that need to acquire and maintain competitive advantage in a rapidly changing environment.