• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.8-13
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• 2019

Smart Farming has been regarded as an important application in information and communications technology (ICT) fields. Selecting crops for cultivation at the pre-production stage is critical for agricultural producers' final profits because over-production and under-production may result in uncountable losses, and it is necessary to predict crop production to prevent these losses. The ITU-T Recommendation for Smart Farming (Y.4450/Y.2238) defines plan/production consultation service at the pre-production stage; this type of service must trace crop production in a predictive way. Several research papers present that machine learning technology can be applied to predict crop production after related data are learned, but these technologies have little to do with standardized ICT services. This paper clarifies the relationship between agricultural consultation services and predicting crop production. A prediction scheme is proposed, and the results confirm the usability and superiority of machine learning for predicting crop production.

• 융합정보논문지
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• 제10권12호
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• pp.9-14
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• 2020

현재 NTIS(National Technology Information Service)는 인공지능 기술을 기반으로 대화형 검색 서비스를 구축하고 있다. 이용자의 검색 의도를 파악하고 과제정보를 제공하기 위해 딥러닝 모델과 형태소 분석기를 기반으로 대화형 검색 서비스를 구축한다. 딥러닝 모델은 NTIS와 대화형 검색 서비스를 활용할 때 적재되는 로그 데이터를 기반으로 학습을 진행하고 이용자의 검색 의도를 파악한다. 그리고 단계별 검색을 통해 과제정보를 제공한다. 검색 의도 파악은 예외처리를 용이하게 해주며 단계별 검색은 통합검색보다 쉽고 빠르게 원하는 정보를 얻을 수 있도록 한다. 향후연구로는 인공지능 기술이 접목된 성장형 대화형 검색 서비스로써 이용자에게 제공하는 정보의 범위를 확대해야 한다.

• 한국IT서비스학회지
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• 제6권3호
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• pp.111-128
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• 2007

The purpose of the research is to analyze the status and problems of the e-Learning quality assurance system on e-Learning contents and service provider(institutes) in the field of enterprise education. In addition, the research is to suggest the direction and strategies for revising and developing the system. The research put emphasis on two systems of the e-Learning quality assurance(contents, service provider) which directly influence financial support of government. This study depended mostly on literature review, supplemented by expert panel meetings. In the case of the quality assurance system on e-Learning contents, the followings are suggested; (1)admitting the contents made of the combination of modules in the approved module set, (2)making easier the qualifying of modified contents for maintenance, (3)revising evaluation criteria, (4)providing substantial feedback. In the field of service provider, the followings are requested; (1)differentiating of qualifying system by industry and scale of company, (2)extending the qualifying cycle, (3)improving the feedback and sharing system.

• 한국통신학회논문지
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• 제40권4호
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• pp.653-658
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• 2015

다양한 강점을 지닌 클라우드 서비스는 현대 IT 사업에 주요 이슈 중 하나이다. 클라우드 환경에서 서비스 제공자는 사용자의 동적인 자원 요구량을 예측하여 사용자의 QoS를 만족시켜야 한다. 사용자의 자원 요구량을 예측하는 기존 모델들은 사용자의 QoS는 만족시키지만 서비스 제공자의 이득은 보장하지 않는다. 본 논문에서는 Q-learning 기반의 자원 예측 모델을 제안하여 사용자의 QoS 뿐만 아니라 서비스 제공자의 이득을 최대화하였다. 또한 제안 기법의 성능 분석을 위해 실측 데이터를 이용하여 다른 예측 모델들과 비교함으로써 제안 기법의 우수함을 증명하였다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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• pp.221-228
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• 2006

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the effectiveness assessment of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-learner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on e-learning strategy. The former consists of learning management system, learning content quality and service quality that are provided by e-Loaming. The latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically.

• 한국산업정보학회논문지
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• 제12권5호
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• pp.146-162
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• 2007

본 연구에서는 e-러닝 사이트가 웹 사이트라는 특성을 고려해서 웹 서비스품질의 주요 요인을 추가로 도출하여 e-러닝 사이트의 서비스품질 결정요인을 구성하고, 서비스품질이 고객만족 및 고객 e-로열티에 어떠한 영향을 미치는 지를 실증 분석하였다. 그 결과 유형성, 신뢰성, 반응성, 사용편리성, 개인화 요인이 고객만족 및 고객 e-로열티에 유의한 영향을 미치는 것으로 나타났다. 이러한 연구목적에 따른 결과를 토대로 e-러닝 사이트 운영자가 고객만족 및 고객 e-로열티 형성을 위해 최우선적으로 고려해야 할 요인들과 전략적 시사점을 제시하고자 한다.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.343-350
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• 2020

In the era of the Fourth Industrial Revolution in the digital revolution is taking place, various attempts have been made to provide various contents in a digital environment. In this paper, agent-recruitment service system based on collaborative deep learning is proposed for the intelligent head hunting service. The service system is improved from previous research [7] using collaborative deep learning for more reliable recommendation results. The Collaborative deep learning is a hybrid recommendation algorithm using "Recurrent Neural Network(RNN)" specialized for exponential calculation, "collaborative filtering" which is traditional recommendation filtering methods, and "KNN-Clustering" for similar user analysis. The proposed service system can expect more reliable recommendation results than previous research and showed high satisfaction in user survey for verification.

• Journal of Multimedia Information System
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• 제7권1호
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• pp.11-16
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• 2020

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications. In this paper, an interactive window service based on object recognition technology is proposed. The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye. We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement. To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate. Then the view direction is estimated from the extracted eye pupils from the origin coordinate. Also, we propose a blink detection technique based on the eye apply ratio (EAR). With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations. For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.38-59
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• 2022

Web services instances can be classified into two categories, namely trusted and untrusted from users. A web service with high throughput (TP) and low response time (RT) instance values is a trusted web service. Web services are not trustworthy due to the mismatch in the guaranteed instance values and the actual values achieved by users. To perform web services selection from users' attained TP and RT values, we need to verify the correct prediction of trusted and untrusted instances from invoked web services. This accurate prediction of web services instances is used to perform the selection of web services. We propose to construct fuzzy rules to label web services instances correctly. This paper presents web services selection using a well-known machine learning algorithm, namely REPTree, for the correct prediction of trusted and untrusted instances. Performance comparison of REPTree with five machine learning models is conducted on web services datasets. We have performed experiments on web services datasets using a ten k-fold cross-validation method. To evaluate the performance of the REPTree classifier, we used accuracy metrics (Sensitivity and Specificity). Experimental results showed that web service (WS1) gained top selection score with the (47.0588%) trusted instances, and web service (WS2) was selected the least with (25.00%) trusted instances. Evaluation results of the proposed web services selection approach were found as (asymptotic sig. = 0.019), demonstrating the relationship between final selection and recommended trust score of web services.

• 디지털융복합연구
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• 제18권1호
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• pp.369-377
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• 2020

본 연구의 목적은 한국과 중국의 이러닝 품질과 학습자의 이용동기가 이러닝 만족도에 미치는 영향력을 밝히는데 있다. 또한 두 국가 간 학습자들의 만족도에 영향을 미치는 요인을 비교 분석해 봄으로서 효과적인 이러닝 활용 방안을 제시하고자 하였다. 본 연구는 경상북도에 소재한 Y대학과 K대학의 한국인 대학생과 중국 허난성에 소재한 A대학의 중국인 대학생을 대상으로 설문조사를 실시하였다. 그 결과 한국인 대학생은 학습시간, 학습공간, 학습과정, 유용성 그리고 이러닝 정보 품질, 서비스 품질이 이러닝 만족도에 영향을 미치는 것으로 나타났다. 중국인 대학생은 학습시간, 학습과정 그리고 이러닝 시스템 품질, 정보 품질, 서비스 품질이 이러닝 만족도에 영향을 미치는 것으로 나타났다. 그 중 서비스 품질은 두 국가 모두 이러닝 만족도에 영향을 미치는 중요한 요인으로 나타났지만, 요인별 평균 점수는 매우 낮게 나타났다. 향후 서비스 품질을 개선할 방안에 대해서 논의하였다.