• 대한공업교육학회지
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• v.31 no.2
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• pp.41-63
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• 2006

The purpose of this study was to establish and apply 'term learning strategy' for learners whose basic skill, interest, and motivation for learning is lower, and to increase the learned capabilities of subjects' 'industry introduction', required for industrial technical high school students. Another purpose was to identify when the learning strategy established was applied, its affect on how well learners understood terms in a particular unit of material, and, after instruction presented in accordance with 'term learning strategy,' evaluate the ease with which subjects understood the teacher's explanation of the unit of subject, how well they understand the main concepts of the unit of subject, and to what extent the presentation interested and motivated the subjects. The researcher established 'term learning strategy' based on the principles of Garg's "Nine Steps for Events of Instruction." The study included 35 first grade participants purposely selected from 33 classes at 1155 students in K industrial technical highschool. Data was collected via tests and surveys. Results indicated that 'term learning strategy' facilitated thorough understanding of terms and concepts related to the unit of subject, as well as a better understanding of the teacher's explanation and increased interest and motivation in learning. In addition, the "term learning strategy" increased interaction among learners in the instruction setting. Finally, implications of this study and implementation recommendations for this instructional strategy were presented.

• Genomics & Informatics
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• v.18 no.1
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• pp.7.1-7.7
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• 2020

In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.79-81
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• 2005

최근 SCORM, Dublin Core등의 국제 표준 메타데이터와 함께, 세계 사실 표준이라 할 수 있는 IMS와 IEEE/LTSC의 LOM이 e-Learning의 특성을 반영한 메타데이터로서 현재 국$\cdot$내외적으로 많은 e-Learning 업체 및 기관에서 활용되고 있다(5). 그러나 LOM에서 정의한 메타데이터는 멀티플랫폼 환경을 고려하지 않고 있고, 제작 및 유통되고 있는 대부분의 e-Learning 콘텐트는 멀티미디어 특성에 대한 메타데이터 요소가 부족한 실정이다. 따라서 , 본 논문에서는 멀티플랫폼 환경에서 e-Learning학습을 지원하기 위해, 메타데이터 및 e-Learning 업체의 Requirement를 조사,분석하고 e-Learning 국제 표준 메타데이터와 플랫폼의 디바이스 특성을 반영하여, 기본적인 PC(Personal Computer) 환경을 포함한 모바일 기기 환경과 디지털TV 환경을 고려한 멀티플랫폼 e-Learning 메타데이터(Multi-platform e-Learning Metadata)를 제안하였다.

• Journal of Engineering Education Research
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• v.6 no.1
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• pp.22-31
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• 2003

The purpose of this study was to develop CD-ROM so that students can understand 8051 Microprocessor unit easily in electronics circuit practice subject of technical high school. The study gives students, who have difficulties in learning, a chance for self-directed and supplementary learning by suggesting interface process with 8051 Practice Kit. To achieve these purposes, literature survey, collecting textbooks and materials, development of CD-ROM were gradually carried out. Each steps were as follows: Firstly, in literature survey, concepts and characteristics of multimedia and application to class were reviewed. Secondly, text contents on 8051 Microprocessor unit were analyzed, main contents were extracted and graphic, sound, animation were made. It was consisted of eight basic learning subjects, and designed to flow systematically. In this study, we presented a kind of teaching-learning material by developing CD-ROM in 8051 microprocessor unit in electronics circuit practice subject as a central matter. This material will be able to help technical high school students in learning

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.344-351
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• 2016

Recently, mobile application for english vocabulary learning is being developed actively. However, most mobile English vocabulary learning applications did not effectively connected with the technical advantages of mobile learning. Also,the study of mobile english vocabulary learning app are still insufficient. Therefore, this paper development a english vocabulary context-learning Agent that can practice context learning more reasonably using a location-based service, a character recognition technology and augmented reality technology based on smart phones. In order to evaluate the performance of the proposed agent, we have measured the precision and usability. As results of experiments, the precision of learning vocabulary is 89% and 'Match between system and the real world', 'User control and freedom', 'Recognition rather than recall', 'Aesthetic and minimalist design' appeared to be respectively 3.91, 3.80, 3.85, 4.01 in evaluation of usability. It were obtained significant results.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.27-60
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• 2005

The purpose of this study is to call attention to the consensus of stakeholders of corporate e-Learning system for the sake of its success. We identified the critical success factors(contents, technical features, management, and organizational support) as major components of corporate e-Learning systems and questioned whether stakeholders' consensus on the importance of these components facilitates the successful implementation of these components. We also questioned whether the influence of these components on user satisfaction could be moderated by contextual factors. Based on empirical testing of 18 e-Learning user companies, we verified that the consensus of stakeholders regarding the importance of content, technological features, and organizational support has a positive influence on the perceived quality of these factors in their e-Learning systems, which in turn is positively related to user satisfaction. The learning subjects and learning style did significantly moderate the influences of these perceived qualities on user satisfaction.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.23-30
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• 2021

Sentiment Analysis has become very important field of research because posting of reviews is becoming a trend. Supervised, unsupervised and semi supervised machine learning methods done lot of work to mine this data. Feature engineering is complex and technical part of machine learning. Deep learning is a new trend, where this laborious work can be done automatically. Many researchers have done many works on Deep learning Convolutional Neural Network (CNN) and Long Shor Term Memory (LSTM) Neural Network. These requires high processing speed and memory. Here author suggested two models simple & bidirectional deep leaning, which can work on text data with normal processing speed. At end both models are compared and found bidirectional model is best, because simple model achieve 50% accuracy and bidirectional deep learning model achieve 99% accuracy on trained data while 78% accuracy on test data. But this is based on 10-epochs and 40-batch size. This accuracy can also be increased by making different attempts on epochs and batch size.

• 대한공업교육학회지
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• v.36 no.2
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• pp.1-23
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• 2011

The purpose of the study was to investigate the generality and applicability of Team-Based Learning model in a technical high school, based on the interviews with students and a teacher. Team-Based Learning model seems to be an effective way in improving the performance of groups as well as the individualized learning and team interaction. We applied a formative research method and identified the strengths of the model including learners' motivation and interests, learner-centered learning, self-efficacy through learning in advance, and concept acquisition from the repetitive learning process. However, we also found the weakness of the model including impracticality of instructional design, a lack of field-oriented problem banks, and needs for identifying learner characteristics and role in instruction. Finally, we analyzed the implications for the Team-Based Learning in the technical high schools in light of team formation, discussion types, active participation, and learners' prior knowledge and attitude, and pre-determined instructional design.

• 대한공업교육학회지
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• v.31 no.2
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• pp.1-40
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• 2006

The purpose of this study was to development a model of the practical skill instruction of the special subject using the problem-based learning in the technical high schools For the study, various literature researches were reviewed intensively about problem solving process, problem -based learning, and learning principals. The process of the practical skill instruction using the problem-based learning was composed with planning, executing, testing and evaluating. In this practical skill instruction using the problem-based learning, the teacher serves as a coach or guide for students' learning. As a facilitator, the teacher challenges, questions, and stimulates the students in their thinking, problem solving and self-directed study. In this process, students represent problem by thinking aloud, assuming responsibility for their own learning, having self-directed study as well as doing cooperative study, and as a result, education changes move from teacher-centered to student-centered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.