• 한국초등과학교육학회지:초등과학교육
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• 제37권3호
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• pp.254-266
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• 2018

The aim of this study is to analyze STEAM lessons focused on the learner's learning. This study was conducted on 4th-graders in Y city, Kyung-gi province. The lessons were based on a joint teaching plan for students through the teacher learning community (TLC) with three teachers from the same school. Each of the three classes that conducted the class was selected and analyzed as the main center of observation by three students. The conclusions from this study are as follows: First, we identified that different levels of learners are learning in STEAM lessons through a learner-centered class analysis. Some students arrived on their own by taking the initiative in class, others by consulting with a group of friends, and others needed active teacher guidance to learn. Second, Depending on the level and characteristics of the students, some learning criteria were not reached. Some students need guidance at a glance level, and others need individually instructed or guided activities. Teachers need to keep an eye out for students and give them an appropriate level of guidance during class. In STEAM lessons, it appears that students of different levels and characteristics can immerse themselves in their own way, as well as the clear guidance of activity for their students.

• 디지털융복합연구
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• 제11권2호
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• pp.127-135
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• 2013

IT 프로젝트가 성공적으로 실현되기 위해서 개별 컨설턴트의 역량은 매우 중요하다. 특히 IT 프로젝트 수행 동안 발생하는 다양한 문제를 해결하기 위해서는 학습이 필요하며 이 학습은 실행에 의한 학습, 타인을 통한 학습, 투자에 의한 학습으로 구분된다. 본 연구의 목적은 이러한 세 가지 학습프로세스가 컨설턴트의 의사결정 성과에 미치는 영향을 살펴보는 것이다. 연구모형을 수립하기에 앞서 팀장급 이상 컨설턴트와 3회 인터뷰를 수행하였다. 본 과정을 통해 연구모형과 설문문항에 대한 타당성 검증을 수행하였다. 100명 이상의 현직 컨설턴트들의 설문에 참여하였다. 연구결과 타인을 통한 학습은 의사결정에 아무런 영향도 미치지 않는 것으로 나타났다.

• 대한간호학회지
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• 제35권1호
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• pp.65-76
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• 2005

Objective: The aim of this study is to explore the variation in perceptions about problem-based learning(PBL) according to the level of academic achievement and learning attitude in the nursing students of a junior college (3-year program). Method: Students (n=39) learned the respiratory and cardiac system with seven PBL packages and group-based learning for a semester in 2002. Students were asked to write reflective journals that focused on their learning perception after an experience with each learning package. A total of 208 journals were used for analysis. Result: Students positively perceived that PBL making them increase their sense of responsibility for learning and felt satisfaction with the learning process, and had a confidence in the use of clinical nursing interventions. On the other hand, they negatively perceived that PBL was a burden because it took more time than traditional learning tasks, and they experienced an anxiety about regular tests and felt conflicts and diffidences in the learning process. The negative perceptions were expressed more often from students with a low academic achievement and low learning attitude compared to others. Conclusion: Students perceived the PBL as effective in understanding the learning concepts in the clinical practice environment. PBL need to be supplemented by feedback-based lecture and facilitative strategies for academically low-achieved students.Objective: The aim of this study is to explore the variation in perceptions about problem-based learning(PBL) according to the level of academic achievement and learning attitude in the nursing students of a junior college (3-year program). Method: Students (n=39) learned the respiratory and cardiac system with seven PBL packages and group-based learning for a semester in 2002. Students were asked to write reflective journals that focused on their learning perception after an experience with each learning package. A total of 208 journals were used for analysis. Result: Students positively perceived that PBL making them increase their sense of responsibility for learning and felt satisfaction with the learning process, and had a confidence in the use of clinical nursing interventions. On the other hand, they negatively perceived that PBL was a burden because it took more time than traditional learning tasks, and they experienced an anxiety about regular tests and felt conflicts and diffidences in the learning process. The negative perceptions were expressed more often from students with a low academic achievement and low learning attitude compared to others. Conclusion: Students perceived the PBL as effective in understanding the learning concepts in the clinical practice environment. PBL need to be supplemented by feedback-based lecture and facilitative strategies for academically low-achieved students.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.169-180
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• 2021

Since machine learning was invented, there have been many different machine learning-based algorithms, from shallow learning to deep learning models, that provide solutions to the classification tasks. But then it poses a problem in choosing a suitable classification algorithm that can improve the classification/detection efficiency for a certain network context. With that comes whether an algorithm provides good performance, why it works in some problems and not in others. In this paper, we present a data-centric analysis to provide a way for selecting a suitable classification algorithm. This data-centric approach is a new viewpoint in exploring relationships between classification performance and facts and figures of data sets.

• 공학교육연구
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• 제18권2호
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• pp.65-76
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• 2015

Despite its ineffectiveness, the dominant pedagogy for engineering education is still "chalk & talk". Meanwhile, student-centered learning models have been highlighted for strong communication, teamwork skills, deep understanding and analysis on social, environmental and economic issues as well as application of their engineering knowledge in practice. Among others, on problem- and project-based learning, this article examines theoretical background and detailed features and a comparison between both learning models including common and different features from the previous theoretical and empirical studies. It reviews some cases of where they have been practiced successfully in engineering, and further, applied strategies for engineering education are suggested.

• Educational Technology International
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• 제11권2호
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• pp.149-172
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• 2010

Knowledge can be more meaningful when it is shaped and personalized through interaction with others. Implementation of open learning environments such as open courseware or shared knowledge communities has gradually become more common. A case study which investigated instructors' experiences and perceptions of publishing and using open courseware in the classroom was conducted at a university in Korea. Responses from participating students and an evaluation group regarding how they perceived open learning environments were also examined. Based on the inductive analysis of the data, this study discusses advantages and challenges of publishing open courseware and collaborative learning environments. Also, practical guidelines for developing reusable learning materials are suggested.

• 전자공학회논문지C
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• 제34C권9호
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• pp.61-67
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• 1997

The HMM-Net is an architecture for a neural network that implements a hidden markov model(HMM). The architecture is developed for the purpose of combining the classification power of neural networks with the time-domain modeling capability of HMMs. Criteria which are used for learning HMM_Net classifiers are maximum likelihood(ML), maximum mutual information (MMI), and minimization of mean squared error(MMSE). In this classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numbers from /young/to/koo/ show that in the binary inputs the performance of MMSE is better than the others, while in the fuzzy inputs the performance of MMI is better than the others.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.169.3-169
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• 2001

This paper introduces a new approach to analysis of error convergence for a class of iterative learning control systems. First, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established in the form of T-S fuzzy model. We analysis the error convergence in the sense of induced 2 L -norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative learning controller design problem to guarantee the error convergence can be reduced to linear matrix inequality problems. In comparison with others, our learning algorithm ...

• ETRI Journal
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• 제41권5호
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.289-294
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• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.