• 유통과학연구
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• 제20권6호
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• pp.57-66
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• 2022

Purpose: Business agility is an important key to survival for SMEs in Indonesia, especially during the COVID-19 pandemic. Indonesian local product distribution and service distribution are mostly served by SMEs. Agile businesses will be able to assist them in the proper distribution of products and services. This research examines how the direct and indirect influence of IT capabilities on business agility through organizational learning and business intelligence for small and medium enterprises in the distribution of Indonesian products and services. Research design, data and methodology: This research uses SEM method with SmartPLS tool. The sample of this research was conducted on small and medium enterprises in the distribution of Indonesian products and services. The sample obtained in this study was 202 SME owners or managers (strategic level). Results: Business intelligence plays a key role in improving business agility. The results of IT capability can directly and indirectly affect business agility through organizational learning. Conclusions: Business intelligence has the biggest role in increasing business agility in SMEs in Indonesia. IT capability has an indirect effect on business agility through organizational learning. The findings of this study prove that IT capabilities do not indirectly affect business agility through business intelligence.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.183-191
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• 2020

Today, taking photos using smartphones has become an essential element of modern people. According to these social changes, modern people need a larger storage capacity, and the number of unnecessary photos has increased. To support the storage, cloud-based photo storage services from various platforms have appeared, and many people are using the services. As the number of photos increases, it is difficult for users to find the photos they want, and it takes a lot of time to organize. In this paper, we propose a cloud-based photo management service that facilitates photo management by classifying photos and recommending unnecessary photos using deep learning. The service provides the function of tagging photos by identifying what the subject is, the function of checking for wrongly taken photos, and the function of recommending similar photos. By using the proposed service, users can easily manage photos and use storage capacity efficiently.

• 한국IT서비스학회지
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• 제12권4호
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• pp.59-75
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• 2013

As education environment is changing rapidly and competition of education industry is more intensive, the importance of service view about education is increasing as a differential competitive advantage. This study attempted to investigate the impact of service convenience as a different competitive advantage on e-learning acceptance by using TAM. The purpose of this study is to examine how five-dimensional service convenience constructs(decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect consumers' perceived usefulness, attitude and usage intention. For this study, data were gathered from respondents who bought or used e-learning services and analyzed by structural equation model. Among the five-dimensional service convenience constructs, two constructs(benefit convenience, post-benefit convenience) affected consumers' positive perceived usefulness, attitude and usage intention about e-learning service. The results show that management and investment to improve benefit and post-benefit service convenience make consumers' positive attitude and usage intention about e-learning service.

• 한국IT서비스학회지
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• 제2권2호
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• pp.87-95
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• 2003

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. in this research we develop e-mail classifiers for e-mail Response Management Systems (ERMS) using naive bayesian learning and centroid-based classification. We analyze which method performs better under which conditions, comparing classification accuracies which may depend on the structure, the size of training data set and number of classes, using the different data set of an on-line shopping mall and a credit card company. The developed e-mail classifiers have been successfully implemented in practice. The experimental results show that naive bayesian learning performs better, while centroid-based classification is more robust in terms of classification accuracy.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.616-617
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• 2010

본 논문에서는 유비쿼터스 컴퓨팅 환경에 기반을 둔 e-라닝 모델을 제안하였다. 제안한 모델은 크게 하드웨어와 소프트웨어 환경, 그리고 각종 서비스에 대하여 제안하였다.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.209-214
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• 2024

This is an extended research paper focusing on the applications of Machine Learing and Artificial Intelligence in virtual learning environment. The world is moving at a fast pace having the application of Machine Learning (ML) and Artificial Intelligence (AI) in all the major disciplines and the educational sector is also not untouched by its impact especially in an online learning environment. This paper attempts to elaborate on the benefits of ML and AI in E-Learning (EL) in general and explain how King Khalid University (KKU) EL Deanship is making the best of ML and AI in its practices. Also, researchers have focused on the future of ML and AI in any academic program. This research is descriptive in nature; results are based on qualitative analysis done through tools and techniques of EL applied in KKU as an example but the same modus operandi can be implemented by any institution in its EL platform. KKU is using Learning Management Services (LMS) for providing online learning practices and Blackboard (BB) for sharing online learning resources, therefore these tools are considered by the researchers for explaining the results of ML and AI.

• 시스템엔지니어링학술지
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• 제17권2호
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• pp.98-105
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• 2021

As the average life expectancy is rising, the population is aging and the number of chronic diseases is increasing. This has increased the importance of healthy life and health management, and interest in mobile health services is on the rise thanks to the development of ICT(Information and communication technologies) and the smartphone use expansion. In order to meet these interests, many mobile services related to daily health are being launched in the market. Therefore, in this study, the characteristics of users who actually use mobile health services were analyzed and a predictive model applied with machine learning modeling was developed. As a result of the study, we developed a prediction model to which the decision tree and ensemble methods were applied. And it was found that the mobile health service users' continued use can be induced by providing features that require frequent visit, suggesting achievable activity missions, and guiding the sensor connection for user's activity measurement.

• 한국실천공학교육학회논문지
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• 제3권1호
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• pp.69-75
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• 2011

본 논문에서는 유비쿼터스 컴퓨팅 환경에 기반을 둔 e-러닝 모델을 제안하였다. 이를 위해 국내외 대학의 진보된 e-러닝 시스템을 조사 및 분석하였으며, 이를 근간으로 유비쿼터스 환경에 기반을 둔 최적의 e-러닝 모델을 제안하였다. 제안한 모델은 최적의 e-러닝 하드웨어 및 소프트웨어, 그리고 다양한 e-러닝 서비스를 포함하고 있다. 여기에는 출결체크 서비스, 수업운영 서비스, 공용지식 서비스, 성적처리 서비스, 편의시설 서비스, 개인운영 서비스, 신용조회 서비스, 캠퍼스안내 서비스, 강의실운영 서비스 등이 있다. 또한, 실험.실습에 관련된 서비스도 포함하고 있다.

• 디지털융복합연구
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• 제18권12호
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• pp.29-36
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• 2020

본 연구의 배경은 최근 포스트 코로나시대의 비대면 행정서비스를 위한 주요 정책수단으로 기계학습 행정서비스가 주목을 받고 있는 가운데 기계학습 행정서비스를 시범적으로 운영하고 있는 서울특별시를 대상으로 기계학습 행정서비스 도입 시 효과가 예상되는 업무유형에 대하여 살펴보았다. 연구방법으로는 2020년 7월 한 달 동안 기계학습 기반 행정서비스를 활용하거나 수행하고 있는 서울시 행정조직을 대상으로 설문조사를 실시하여 조직단위별 도입 가능한 기계학습 행정서비스 및 응용서비스를 분석하고, 지도학습, 비지도학습, 강화학습 등 기계학습 행정서비스의 업무유형별 특성을 분석하였다. 그 결과, 지도학습 및 비지도학습 업무유형의 특성에서 유의미한 차이가 있는 것으로 나타났고, 특히 강화학습 업무유형이 기계학습 행정서비스에 가장 적합한 업무적 특성요인을 포함하고 있는 것으로 밝혀져 그에 대한 정책적 시사점을 도출하였다. 본 연구결과는 기계학습 행정서비스를 도입하고자 하는 실무자들에게는 참고자료로 제공될 수 있고, 향후 기계학습 행정서비스를 연구하고자 하는 연구자들에게는 연구의 기초자료로 활용될 수 있을 것이다.

• 한국응급구조학회지
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• 제27권1호
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• pp.59-70
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• 2023

Purpose: This study was designed to identify the effects of social support, learning flow, and learning satisfaction on academic achievement in university students. Methods: This study involved university students who agreed to participate the investigation in D City using a structured online questionnaire from December 1, 2022 to December 31, 2022. Results: Social support, learning flow, learning satisfaction, and academic achievement had significant correlations. The influencing factors of academic achievement were age and learning flow, with an explanatory power of 20%. Conclusion: Further active management and attention are imperative for vulnerable students in high-age groups to search for the ways to improve learning flow.