• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.819-832
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• 2022

Cross-domain recommender system transfers knowledge across different domains to improve the recommendation performance in a target domain that has a relatively sparse model. However, they suffer from the "negative transfer" in which transferred knowledge operates as noise. This paper proposes a novel Multiple Fusion-based Deep Cross-Domain Recommendation named MFDCR. We exploit Doc2Vec, one of the famous word embedding techniques, to fuse data user-wise and transfer knowledge across multi-domains. It alleviates the "negative transfer" problem. Additionally, we introduce a simple multi-layer perception to learn the user-item interactions and predict the possibility of preferring items by users. Extensive experiments with three domain datasets from one of the most famous services Amazon demonstrate that MFDCR outperforms recent single and cross-domain recommendation algorithms. Furthermore, experimental results show that MFDCR can address the problem of "negative transfer" and improve recommendation performance for multiple domains simultaneously. In addition, we show that our approach is efficient in extending toward more domains.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.593-599
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• 2006

Including technical device and general information system, the information-technical(IT) system is defined as the technical system for acquiring, processing, storing and transferring information to a person. This paper presents Knowledge-based Heuristic Evolution Model for creating the advanced information-technical system. This Evolution Model is derived from the historical review on definition of evolution, the research on the architecture of the general IT system, history of IT system, technology innovation theory and multi-case study research. The evolution model is applicable to the conceptual creation of the advanced product in R&D organization requiring development methodologies like rapid-prototyping to develop next generation product. For the detailed theoretical construction and practical application of Evolution Model, the case study research based on action research is performed. the object of the case study is mobile device, especially mobile hand-held phone. Thus, we obtain the Evolution Model for creating the advanced information-technical system.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.133-143
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• 2023

In this study, we propose a big data set of strawberry pests collected directly for diagnosis model learning and an automatic pest diagnosis model architecture based on deep learning. First, a big data set related to strawberry pests, which did not exist anywhere before, was directly collected from the web. A total of more than 12,000 image data was directly collected and classified, and this data was used to train a deep learning model. Second, the deep-learning-based automatic pest diagnosis module is a module that classifies what kind of pest or disease corresponds to when a user inputs a desired picture. In particular, we propose a model architecture that can optimally classify pests based on a convolutional neural network among deep learning models. Through this, farmers can easily identify diseases and pests without professional knowledge, and can respond quickly accordingly.

• Journal of Korean Clinical Nursing Research
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• v.18 no.1
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• pp.126-135
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• 2012

Purpose: This study was aimed to develop a simulation training program of an advanced cardiac life support (ACLS) based on the mastery learning model (Simulation-MLM), and evaluate the effects of the program on critical care nurses. Methods: As an experimental pre-post test with a non-equivalent control group, the study employed convenience sampling of 38 critical care nurses. The experimental group received the Simulation-MLM including a theoretical lecture, formative evaluation, and simulation training, whereas only a theoretical lecture for the control group. The knowledge, self-efficacy, and performance degrees of respondents were measured to verify the effects of the Simulation-MLM. The statistical processing of the collected data utilized the SPSS WIN 17.0 program. Results: After receiving Simulation-MLM, the participants in the experimental group reported higher marks in the knowledge, self-efficacy and performance of ACLS compared with those in the control group. However, both experimental and control groups demonstrated no significant differences in knowledge, self-efficacy and performance. Conclusion: Despite of the limitation of a small sample size, this study was considered meaningful in a sense that it showed a venue for improving ACLS training efficiency. Future research with more distinct treatment differentiation and better adequate outcome variables was warranted in order to prove the effects of a theory-based simulation education.

• Journal of Astronomy and Space Sciences
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• v.14 no.1
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• pp.166-178
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• 1997

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human expert's knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in an easy way.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.372-394
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• 2009

This study investigates the ontology-based public participation GIS(PPGIS). The major reason that ontology-based GIS has attracted attention in semantic communication in recent year is due to the wide availability of geographical variable and the imminent need for turning such recommendation into useful geographical knowledge. Therefore, this study has been focused on designing and implementing the pilot tested system for public participation GIS. The applicability of the pilot tested was validated through a simulation experiment for history tourism in Guri city Gyeongi-do, Focused on the methodology, the life cycle model which involves regional statues and user recognition, can be viewed as an important preprocessing step(specification, conceptualization, formalization, integration and implementation) for recommended geographical knowledge discovery by axiom. Focusing on practicality, ontology in this study would be recommended for geographical knowledge through reasoning. In addition, ontology-based public participation GIS would show integration epistemological and ontological approach, and be utilized as an index which is connected with semantic communication. The results of the pilot system was applied to the study area, which was a part of scenario. The model was carried out using axiom of logical constraint in the meaning of human-activity.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.405-414
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• 2014

This research aims to strengthen the ethical decision-making capability of nursing students, and involves 82 fourth-year undergraduate nursing students in a nonequivalent control group pre-post quasi experimental research design from March 4 to June 3, 2013. Experimental group took a discussion-based class and control group took a traditional lecture-based class and we identified the differences in ethical knowledge, class satisfaction and ethical values between the two groups. Experimental group had higher scores for ethical knowledge after the class. There was no significant change in ethical values after the class in the two groups. The experimental group achieved significantly higher scores for the comprehension of class contents and practical application within the class satisfaction criteria. So we propose to use this model as an effect teaching method to apply ethical principles in nursing practice.

• Knowledge Management Research
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• v.11 no.1
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• pp.97-113
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• 2010

Given the large investment and prevalence of knowledge management (KM) in organizations, it has become important to analyze the effects of KM activities on organizational performances. A theoretical framework is proposed to investigate the impact of KM activities on innovation capabilities in the IT service industry. This study considers KM activities as the major determinant that enhances absorptive capacity. KM activities enhance employees'ability to obtain external knowledge, resulting in increasing intellectual capital. Thus, this study proposes that absorptive capacity plays a mediating role between KM activities and innovation capability. Additionally, this study investigates the key antecedents of KM activities that promote employees' knowledge sharing. Based on prior studies on KM, this study posits KM team activities and top manager support as KM activities. The proposed research model was tested by using survey data collected from 556 employees in the IT service industry. PLS (partial least squares) was employed for the analysis of the data. The findings of this study showed that KM activities and absorptive capabilities play a significant role in enhancing service innovation and process innovation in the IT service industry. The results also shed light on the mediating role of absorptive capacity between KM activities and innovation capability. Moreover, both KM team activities and top manager support serve as the salient antecedents of promoting employees' knowledge sharing.

• Journal of Engineering Education Research
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• v.24 no.3
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• pp.50-57
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• 2021

Although the mathematics education process in AI education is a very important issue, little cases are reported in developing effective methods on AI and mathematics education at the university level. The universities cover all fields of mathematics in their curriculums, but they lack in connecting and applying the math knowledge to AI in an efficient manner. Students are hardly interested in taking many math courses and it gets worse for the students in humanities, social sciences and arts. But university education is very slow in adapting to rapidly changing new technologies in the real world. AI is a technology that is changing the paradigm of the century, so every one should be familiar with this technology but it requires fundamental math knowledge. It is not fair for the students to study all math subjects and ride on the AI train. We recognize that three key elements, SW knowledge, mathematical knowledge, and domain knowledge, are required in applying AI technology to the real world problems. This study proposes a modular approach of studying mathematics knowledge while connecting the math to different domain problems using AI techniques. We also show a modular curriculum that is developed for using math for AI-driven autonomous driving.

• Korea Trade Review
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• v.45 no.1
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• pp.259-277
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• 2020

The purpose of this study is to analyze the relationship between logistics safety climate, logistics safety behavior, and logistics safety performance and the mediating effects of safety knowledge and safety motivation, and to suggest its strategic implications for the improvement of the logistics safety performance. Based on previous researches related to logistics safety, safety climate, safety knowledge, safety motivation, safety behavior and safety performance, research models and hypotheses were set up and questionnaires were conducted. For the hypothesis test, reliability analysis and validity analysis, confirmatory factor analysis, structural equation model analysis, and bootstrapping were applied. As a result of the empirical analysis, the logistics safety climate had a significant positive effect on logistics safety knowledge, logistics safety motivation, and logistics safety behavior, whereas logistics safety knowledge and logistics safety motivation had a meaningful positive effect on logistics safety behavior. Further, logistics safety behavior was found to have a significant positive effect on logistics safety performance. Safety behavior had a significant mediating effect, but safety knowledge and safety motivation did not. However, logistics safety climate, logistics safety knowledge, and logistics safety motivation did not have a significant effect on logistics safety performance.