• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.455-456
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• 2024

현재 폐교된 학교의 데이터들과 후에 폐교될 위험이 있는 학교들의 데이터를 활용하여, 민간, 국가기관 모두에 유용한 데이터를 제공할 수 있는 시스템을 구축하였다. 사용한 데이터로는 22년도 출산율, 14년도 출산율, 지역별 폐교 이용 현황, 전체 폐교 데이터, 현재 학교 인원 현황에 관한 자료를 활용했다. 이같은 데이터를 통해 현재 운영되고 있는 학교 중 폐교 위험의 범주 안에 들어가 있는 학교를 가중치 전략으로 추출할 수 있게 만들었다. 시스템 예측 결과, 현재까지 폐교된 학교들보다 더 많은 학교들이 폐교위기에 처해있고, 더 많은 학교들이 폐교될 것으로 예상된다. 급감하는 출산률을 보아 폐교되는 추세를 줄일 수 없다. 따라서 정부 차원에서 폐교 대부와 경매, 폐교활용 조건을 완화시키고, 학교 건물들을 대책없이 방치시키는 일을 미리 대비해야 한다고 사료된다.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.187-199
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• 2024

This study based on TAM and D&M model to examine the Kuwaiti employee performance using the electronic document and records management system (EDRMS) in the Ministry of social affairs and labor. Additionally, this study has proposed the moderating effect of work cooperation on employee performance Data of 345 employees were collected from Ministry of social affairs and labor in Kuwait. Smart PLS 3.0 was used to analyze the data. Results indicated that perceived ease of use and perceived usefulness have a positive influence on employee performance. However, findings do not support the relationship between system usage and user satisfaction. Additionally, the results show that there is a significant positive moderating effect of work cooperation. This research provides strong evidence for defining the key factors affecting system usage but also in view of its limits. It should be evaluated. Not all the factors affecting the intentions of end-users to use EDRMS have been fully covered. There are major variables, for example, facilitating state and perceived compatibility are important factors that can be covered in future research. This research is an addition to the current literature and the first attempt in this area to the best of authors' knowledge.

• Fashion & Textile Research Journal
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• v.10 no.4
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• pp.464-472
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• 2008

Wearable computer focuses on functional aspects of fashion to respond to and satisfy needs for daily availability of ubiquitous environment owing to ever-developing digital technologies. The purpose of this study is to examine in possible developmental direction of wearable computer and thereby explore more promising directions of wearable computer to enhance its adaptability to future advanced ubiquitous environment and also satisfy both esthetical and functional needs. Now the wearable computer can be classified broadly into 3 types in the aspect of functionality, i.e. computer containing 'integratability', 'convertibility' and 'interactability'. Beyond simple portability concepts based on digital devices attached on body, it will be necessary that follow-up studies on wearable computer satisfy needs for enhanced digital functionality to comply with ubiquitous environment as well as emotional needs inherent in clothing. It is expected that possibility of future wearable computer will be extended via collaborative relationships between design and functionality, and should be implemented through possible points of contact among computer, telecommunication, design and fashion. Based on the findings of this study, it is expected that follow-up researches and developments for wearable computer to meet both functionality and esthetical values in the aspect of 'fashion design combined with electronic products' will help assure the variety of fashion designs for wearable computer contributing to better life quality of human in future ubiquitous environment.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.61-68
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• 2022

The present study was based on developing an AI based model to facilitate the academic registration needs of blind students. The model was developed to enable blind students to submit academic service requests and tasks with ease. The findings from previous studies formed the basis of the study where functionality gaps from the literary research identified by blind students were utilized when the system was devised. Primary simulation data were composed based on several thousand cases. As such, the current study develops a model based on archival insight. Given that the model is theoretical, it was partially applied to help determine how efficient the associated AI tools are and determine how effective they are in real-world settings by incorporating them into the portal that institutions currently use. In this paper, we argue that voice-activated personal assistant (VAPA), text mining, bag of words, and case-based reasoning (CBR) perform better together, compared with other classifiers for analyzing and classifying the text in academic request submission through the VAPA.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.131-138
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• 2022

Git's commit message is closely related to the project life cycle, and by this characteristic, it can greatly contribute to cost reduction and improvement of work efficiency by identifying risk factors and project status of project operation activities. Among these related fields, there are many studies that classify commit messages as types of software maintenance, and the maximum accuracy among the studies is 87%. In this paper, the purpose of using a solution using the commit classification model is to design and implement a complex classification model that combines several models to increase the accuracy of the previously published models and increase the reliability of the model. In this paper, a dataset was constructed by extracting automated labeling and source changes and trained using the DistillBERT model. As a result of verification, reliability was secured by obtaining an F1 score of 95%, which is 8% higher than the maximum of 87% reported in previous studies. Using the results of this study, it is expected that the reliability of the model will be increased and it will be possible to apply it to solutions such as software and project management.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1212-1223
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• 2022

Skin lesions are common diseases that range from skin rashes to skin cancer, which can lead to death. Note that early diagnosis of skin diseases can be important because early diagnosis of skin diseases considerably can reduce the course of treatment and the harmful effect of the disease. Recently, the development of computer-aided diagnosis (CAD) systems based on artificial intelligence has been actively made for the early diagnosis of skin diseases. In a typical CAD system, the accurate classification of skin lesion types is of great importance for improving the diagnosis performance. Motivated by this, we propose a novel deep ensemble classification with multi-scale attention networks. The proposed deep ensemble networks are jointly trained using a single loss function in an end-to-end manner. In addition, the proposed deep ensemble network is equipped with a multi-scale attention mechanism and segmentation information of the original skin input image, which improves the classification performance. To demonstrate our method, the publicly available human skin disease dataset (HAM 10000) and the private animal skin lesion dataset were used for the evaluation. Experiment results showed that the proposed methods can achieve 97.8% and 81% accuracy on each HAM10000 and animal skin lesion dataset. This research work would be useful for developing a more reliable CAD system which helps doctors early diagnose skin diseases.

• Proceedings of the Korea Society of Design Studies Conference
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• 1998.10a
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• pp.68-69
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• 1998

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.05b
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• pp.266-267
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• 2002

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.241-246
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• 2005

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.424-424
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• 2009