• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.117-125
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• 2018

As various types of information technology systems are becoming more pervasive than ever, many studies have evaluated the systems from the user perspective. Some of them have used surveys to measure consumers' cognitive responses to the target technology. However, this method may cause problems if the survey participants do not have a useful frame of reference for evaluating an unfamiliar system. To examine this issue, the current study empirically tested the effect of personal product knowledge on the predictability of a behavioral model, such as Technology Acceptance Model. A series of measurement invariance tests as well as multi-group comparison tests were conducted for rigorous examination of the data. Our analysis showed that the variance of attitude that is explained by the two believes (perceived usefulness and ease of use) was relatively small when the survey respondents had lower amount of product knowledge. Moreover, the group had weaker causal relationship between attitude and intention to use the technology, hindering the predictability of the research model. The results indicated that respondents should have a certain amount of knowledge of the target system in order to form accurate beliefs and behavioral decisions. The findings of this study provide important implications on sampling strategies for researchers with new technology.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.251-258
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• 2011

The existing evaluation systems based on financial performance summarize the information about past results and focus on short-term performance, and so they have the limits to explain the future value of firms and to make a long-term strategic performance. By this reason, as a way to increase the future value, the development of the integrated performance evaluation system with which we may manages financial performance and knowledge assets together has been required recently. This study puts together various researches for the evaluation of knowledge assets, and analyzes the existing studies for the domestic medical devices industry and the tendency of introduction for business practice. Under this analysis, this study develops the knowledge asset evaluation indexes for medical devices industry by using the Balanced Score Card (BSC) of Kaplan & Norton(1992), and then presents the evaluation model by applying the Analytic Hierarchy Process (AHP) of Saaty(1980) to get the weight for each index. With the final evaluation model, we can calculate the evaluation score combined with both the quantitative indexes and the qualitative indexes at once.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.79-90
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• 1995

The material handling equipment selection, that is a key task in the material handling system design, is a complex, difficult task, and requires a massive technical knowledge and systematic analysis. It is invaluable to justify the selected equipment model by the performance evaluation before its actual implementation. This paper presents an intelligent knowledge-based expert system called "IMESE" created by authors, for the selection and evaluation of material handling equipment model suitable for movement and storage of materials in a manufacturing facility. The IMESE is consisted of four modules: a knowledge base to select an appropriate equipment type, a multiple criteria decision making procedure to choose the most favorable commercial model of the selected equipment type, a database to store the list of commercial models of equipment types with their specifications, and simulators to evaluate the performance of the equipment model. The whole process of IMESE is executed under VP-Expert expert system environment.vironment.

• Journal of Information Technology Applications and Management
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• v.18 no.1
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• pp.15-39
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• 2011

A deeper understanding of how organizations behave as social complex adaptive systems is needed. In this paper we demonstrate how the Leadership Invigorating Flows of Energies model can help with this understanding. The model highlights the role of emergent leadership as a force encouraging the creation, diffusion, and utilization of knowledge through self-organizing mechanisms. We illustrate our approach by examining Wikipedia and show how it can be described as a social CAS. Our analysis of Wikipedia describes how emerging intrapreneurship behaviors result in dynamic flows of knowledge and self-organizing feedback mechanisms across the organization. We provide implications for organization studies and present evidence to support claims made by advocates of complexity theory. We conclude by proposing that Wikipedia can be seen as a new form of organization, and finish with a brief note highlighting a possible way forward.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.133-141
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• 2022

This paper introduces model compression algorithms which make a deep neural network smaller and faster for embedded systems. The model compression algorithms can be largely categorized into pruning, quantization and knowledge distillation. In this study, gradual pruning, quantization aware training, and knowledge distillation which learns the activation boundary in the hidden layer of the teacher neural network are integrated. As a large deep neural network is compressed and accelerated by these algorithms, embedded computing boards can run the deep neural network much faster with less memory usage while preserving the reasonable accuracy. To evaluate the performance of the compressed neural networks, we evaluate the size, latency and accuracy of the deep neural network, DenseNet201, for image classification with CIFAR-10 dataset on the NVIDIA Jetson Xavier.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.479-481
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• 2023

Generative Adversarial Networks (GANs) have facilitated substantial improvement in single-image super-resolution (SR) by enabling the generation of photo-realistic images. However, the high memory requirements of GAN-based SRs (mainly generators) lead to reduced performance and increased energy consumption, making it difficult to implement them onto resource-constricted devices. In this study, we propose an efficient and compressed architecture for the SR-GAN (generator) model using the model compression technique Knowledge Distillation. Our approach involves the transmission of knowledge from a heavy network to a lightweight one, which reduces the storage requirement of the model by 58% with also an increase in their performance. Experimental results on various benchmarks indicate that our proposed compressed model enhances performance with an increase in PSNR, SSIM, and image quality respectively for x4 super-resolution tasks.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.201-217
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• 2024

This introductory review study sought to conceptualize elementary school teachers' pedagogical content knowledge in science teaching (science PCK) by reinterpreting 11 science PCK research papers published in the Korean Journal Database from 2012 to 2023 based on the synthesized perspective of the model of teacher professional knowledge and skill (Consensus Model) proposed at the first PCK Summit in 2012 and the Revised Consensus Model (RCM) proposed at the second PCK Summit in 2016. Elementary teachers' science PCK was mainly analyzed based on Magnusson et al.'s (1999) PCK elements and described as the form of enacted PCK or personal PCK at the subject or discipline level. Personal PCK studies, which involved emotional factors, included the features of collective PCK from the RCM perspective. It was inferred that elementary school teachers' science PCK needs to be conceptualized by comprehensively considering the enacted PCK through individual teacher experiences and the collective PCK and personal PCK defined by experts.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.349-381
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• 2002

The 21st century survive only who creating, taking, and managing to knowledge. Digital contents industry becomes to the core in the future. That is, to win in a competition have to the digitalizing knowledge contents to all knowledge and information resources. Therefore, it needs to the digital contents management and the distribution framework. This study aims to propose a model stages in the knowledge contents-decision process, KM Matrix, and KMI Score founded on digital contents framework and diffusion of innovation.