• 한국전자통신학회논문지
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• 제16권6호
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• pp.1231-1238
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• 2021

최근에 대형 온라인 쇼핑몰에서는 텍스트나 카테고리 검색뿐만 아니라 이미지 검색 서비스를 제공하고 있다. 그러나 이미지 검색 서비스의 경우 이미지가 없는 상황에서는 검색 서비스를 이용할 수 없는 문제점이 있다. 본 논문에서는 사용자가 온라인 의류쇼핑몰에서 옷을 검색할 시, 옷의 스타일에 대하여 직접 그릴 수 있는 손그림을 통해 본인이 원하는 옷을 찾을 수 있는 시스템의 개발내용에 대해 기술한다. 사용자가 그린 손그림 데이터는 신경망학습을 통해 매칭의 정확도를 높이고, 다양한 객체인식 알고리즘을 활용하여 의류를 매칭할 수 있도록 한다. 이를 통해 사용자가 찾고자 하는 의류를 빠르게 검색할 수 있음으로써 온라인 쇼핑 이용의 고객 만족도를 높일 수 있을 것으로 기대한다.

• 한국융합학회논문지
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• 제9권2호
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• pp.85-90
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• 2018

본 연구는 최근 핫이슈가 되고 있는 온라인 오프라인 융합 학습전략인 거꾸로 학습 전략이 학습자들에게 학습의 효과가 있을 것이라는 가정 하에 거꾸로 학습 전략을 대학 교양영어 수업에 적용하여 대학 교양 영어 학습자들의 학습 스타일 및 학업수준에 따른 학업 성취도와 태도의 차이를 분석해 보고자 하였다. 학업 성취도 분석을 위해 실험 전 진단 평가와 실험 후 성취도 평가를 실시하여 비교 분석하였고, 학습태도는 크게 동기, 선호, 가치로 분류하여 분석하였다. 본 연구의 결과 학습자의 학습 스타일을 고려한 거꾸로 학습 전략 적용은 학습자들의 학업 성취도에 의미 있는 결과를 나타내지 않았지만 학습 태도에는 의미 있는 결과를 나타내었다. 결과적으로 대학 교양 영어 수업에 있어서의 거꾸로 학습 적용은 학습자들에게 학습에 대한 동기 부여를 줄 수 있고 수업활동에 적극적으로 참여하도록 유도할 수 있는 학습 전략임을 시사하고 있으며 이에 따른 적합한 수업 구성 및 전략을 제고하는데 연구의 가치가 있다.

• Journal of Platform Technology
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• 제10권3호
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• pp.51-59
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• 2022

최근 혁신적으로 발전하고 있는 기계학습은 다양한 최적화 문제를 해결할 수 있는 중요한 기술이 되었다. 본 논문에서는 기계학습을 활용하여 이종망의 채널 공용화 문제를 해결하는 최신 연구 논문들을 소개하고 주된 기술의 특성을 분석하여 향후 연구 방향에 대해 가이드를 제시한다. 기존 연구들은 대체로 온라인 및 오프라인으로 빠른 학습이 가능한 Q-learning을 활용하는 경우가 많았다. 반면 다양한 공존 시나리오를 고려하지 않거나 망 성능에 큰 영향을 줄 수 있는 기계학습 컨트롤러의 위치에 대한 고려는 제한적이었다. 이런 단점을 극복할 수 있는 유력한 방안으로는 ITU에서 제안한 기계학습용 논리적 망구조를 기반으로 망 환경 변화에 따라 기계학습 알고리즘을 선택적으로 사용할 수 있는 방법이 있다.

• 한국간호교육학회지
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• 제15권2호
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• pp.194-204
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• 2009

Purpose: Level of reflective thinking of students are important factors in the area of nursing studies on web-based PBL. These factors were used as a component of learning strategies. One was to understand general recognition to web-based PBL and reaction to the use of reflective journal. The other was to investigate the level of reflective thinking was related to learning activity. Method: PBL was adopted for an online course titled 'Nursing Assessment and Intervention'. Twenty graduate students were evaluated from questionnaire, reflective journals, and individual assignments. Result: Web-based PBL was strong for self-directed learning, team activity, creative thinking, diversity of thinking, and diverse process of learning while hard time, lack of cooperation, uncertainty of outcome, and lack of time were considered as weakness. Reflective journal gave moderate help to learning activities. The learners' learning activities was the lowest in the middle level of reflective thinking. Conclusion: Generally, graduate students in college of nursing showed slightly positive attitude to PBL experience and slightly positive reaction to the learning effect of reflective journal. PBL was estimated to be valuable and meaningful. There was no relationship between the level of reflective thinking and learning activities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Journal of Information Technology Applications and Management
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• 제16권1호
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.890-903
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• 2017

The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. This paper presents GNP-RL based on predicting collision positions as a first attempt to apply it for MR navigation in dynamic environment. The combination between features of the proposed collision prediction and that of GNP-RL provides safe navigation (effective obstacle avoidance) in dynamic environment, smooth movement, and reducing the obstacle avoidance latency time. Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-Learning (QL) and Artificial Potential Field (APF). The simulation results show that the proposed GNP-RL outperforms both QL and APF in terms of smooth movement and safer navigation. In addition, it outperforms APF in terms of preserving maximum possible speed during obstacle avoidance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.141-146
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• 2009

Support vector machine is a classification algorithm based on statistical learning theory. It has shown many results with good performances in the data mining fields. But there are some problems in the algorithm. One of the problems is its heavy computing cost. So we have been difficult to use the support vector machine in the dynamic and online systems. To overcome this problem we propose to use stratified sampling of statistical sampling theory. The usage of stratified sampling supports to reduce the size of training data. In our paper, though the size of data is small, the performance accuracy is maintained. We verify our improved performance by experimental results using data sets from UCI machine learning repository.

• 한국학교ㆍ지역보건교육학회지
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• 제23권4호
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• pp.17-28
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• 2022

Objectives: This study aimed to provide the measures for improving the self-directed learning ability and the reference data for substantializing the educational programs by verifying the main factors affecting the self-directed learning ability of dental hygiene students in reality when the learners' autonomy is emphasized than ever. Methods: From June 20 to July 4, 2022, an online survey was conducted targeting total 218 dental hygiene students. The collected data was analyzed by using the SPSS Program Version 22.0. Results: First, in the results of analyzing differences in detailed items of self-directed learning ability according to the general characteristics, the 'students who entered the department of dental hygiene by considering their aptitude and interest' showed higher results than the 'students who entered the department by considering their high school record'. Second, when the academic efficacy, study immersion, and problem-solving ability of dental hygiene students were higher, their self-directed learning ability was also high. Third, the factor that had the greatest effect on self-directed learning ability of dental hygiene students was problem-solving ability, which was followed by academic efficacy and study immersion. Conclusion: Putting together the results above, in order to cultivate the problem-solving ability of dental hygiene students, it would be necessary to operate the problem-solving-centered simulation course that could foster critical thinking, interactions with others, and creative approach and solution to problems in dental medical site. It would be also possible to improve their academic efficacy by applying the learning mentoring & one-to-one learning counseling program, and also strengthening proper feedbacks for learners. Moreover, the study immersion could be strengthened by developing and operating the emotion-based learning motivation program & learning coaching program through the process of verifying the potential and growth needs of learners, exploring one's own resources through learning diagnosis/introspection, and exploring the career-related vision for strengthening the learning motivation, which could have positive effects on the improvement of self-directed learning ability.