• Journal of the Korea Computer Graphics Society
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• v.25 no.4
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• pp.9-16
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• 2019

In this paper, we propose a hydrodynamic scene separation method for wave propagation from video imagery using autoencoder. In the coastal area, image analysis methods such as particle tracking and optical flow with video imagery are usually applied to measure ocean waves owing to some difficulties of direct wave observation using sensors. However, external factors such as ambient light and weather conditions considerably hamper accurate wave analysis in coastal video imagery. The proposed method extracts hydrodynamic scenes by separating only the wave motions through minimizing the effect of ambient light during wave propagation. We have visually confirmed that the separation of hydrodynamic scenes is reasonably well extracted from the ambient light and backgrounds in the two videos datasets acquired from real beach and wave flume experiments. In addition, the latent representation of the original video imagery obtained through the latent representation learning by the variational autoencoder was dominantly determined by ambient light and backgrounds, while the hydrodynamic scenes of wave propagation independently expressed well regardless of the external factors.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.4
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• pp.85-100
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• 2009

This study suggested the expansion strategies of school library catalog considering educational context which should be used teaching and learning process. To achieve the purpose of research, this study derived educational context categories by comparing and analyzing teaching and learning related factors, information resource related factors. Also, this study analysed case system considering educational context. Based on the results, this study designed the catalog data elements as an element to be added to an existing school libraries system(DLS). The derived data element is end user(teacher, students), instructional situations (teaching method, instructional object, curriculum, evaluation type), resource type(feature, discipline, format), reading situation(contextual reading, literature topic), related materials(teacher representation, student representation).

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.412-421
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• 2000

In spite that the main contents of mathematical and scientific learning are understanding principles and their applications, most of existing educational softwares are based on rote learning, thus resulting in limited educational effects. In the artificial intelligence research, some progress has been made in developing automatic tutors based on proving and simulation, by adapting the techniques of knowledge representation, search and inference to the design of tutors. However, these tutors still fall short of being practical and the turor, even a prototype model, for learning problem solving is yet to come out. The geometry problem-solving tutor proposed by this research involves dynamic inference performed in parallel with learning. As an ontology for composing the problem space within a real-time setting, we have employed the notions of propositions, hypotheses and operators. Then we investigated the mechanism of interactive learning of problem solving in which the main target of inference involves the generation and the test of these components. Major accomplishment from this research is a practical model of a problem tutor embedded with a series of inference techniques for algebraic manipulation, which is indispensable in geometry problem solving but overlooked by previous research. The proposed model is expected to be applicable to the design of problem tutors in other scientific areas such as physics and electric circuitry.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.

• English Language & Literature Teaching
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• v.11 no.4
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• pp.365-389
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• 2005

The purpose of this study is to present the task model that is the most effective in English language methodology based on the investigation of task-based performance in Korean EFL classroom practice. The subjects were 538 high school students and 126 high school teachers, each of whom had common experiences using the materials of task-based activities for more than one year. To analyze the data, the program SPSS WIN 11.0 including frequency distribution and chi-square analysis was used. The results of the questionnaire analysis showed that both teachers and students had a comparatively high level of satisfaction in task rationale, but that they had some mixed responses in the fields of input data, settings, and activity types. To conclude, a few suggestions are made to provide some meaningful considerations for the EFL teachers and material developers: a) task goals and rationale that encourage the learner's positive motivation; b) authenticity of input data based on the real-world context; c) collaborative learning environment that enhances communicative interaction; d) proportional representation of the creative problem-solving activities related to discussions and decision-making processes; e) systematic introduction of integrated language skills. It also suggests that the multi-lateral task model, which has some positive assets compared to previous task models, be newly introduced and applied to the second language learning classrooms.

• Journal of The Korean Association of Information Education
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• v.6 no.1
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• pp.117-126
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• 2002

Speaking skill is an important quality in expressing oneself in school life. Quite a few students experience difficulties at school because of the lack of adequate speaking ability. In order to help them, a Web-based speaking enhancement system is designed and developed using computers equipped with multimedia devices with which students can practice speaking while they are observing graphical representation of voices, which is to cause interest and voluntary participation in the learning activity. The learning system was tested on a group of 44 students of 4th grade in an elementary school. The students were divided into three smaller groups in terms of speaking ability. The experiment shows the effectiveness of the system in building speaking ability.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.74-81
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• 1997

This paper proposes an evolutionary learning algorithm to discipline the projection neural nctworks (PNNs) with special type of hidden nodes which can activate radial basis functions as well as sigmoid functions. The proposed algorithm not only trains the parameters and the connection weights hut also c~ptimizes the network structure. Through the structure optimization, the number of hidden node:; necessary to represent a given target function is determined and the role of each hidden node is decided whether it activates a radial basis function or a sigmoid function. To apply the algorithm, PNN is realized by a self-organizing genotype representation with a linked list data structure. Simulations show that the algorithm can build the PNN with less hidden nodes than thc existing learning algorithm using error hack propagation(EE3P) and network growing strategy.

• School Mathematics
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• v.3 no.2
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• pp.295-324
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• 2001

Until now, There have been few studies to investigate a degree of abilities or interesting about mathematical problem-posing of first and second grades in elementary school. This is due to the fact that this students(1st and 2nd grades) have a limited amount of study time and their minds are not fully developed, and are lacking in their representation of ability to use the national language. This being the case, it is difficult to investigate their Mathematical problem-posing in a practical manner. However, our 7th elementary school Mathematics curriculum emphasizes the teaching and learning of Mathematical problem-posing from a basic level of first and second grade with emphasis on activity in teaming Mathematics. Through this study, having analysed the problems those children posed, I have found out they improved in numbers and correctness of their posed problems. And I too could found out showing to their much interesting and confidence to mathematical problem-posing and could confirmed for the children to admit themselves its merits through analyzing some questions to ask their opinions to it. I expect that this study can help to develop the teaching and learning materials for mathematical problem-posing and also to improve its methods of elementary school mathematics. The next study task is, I think, that it is necessary to accumulate the studies to investigate and analyse the practical learning activities of children for problem-posing contents of mathematics text books.

• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.151-156
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• 2001

We describe a new representation for learning concepts that differs from the traditional decision tree and rule induction algorithms. Our algorithm PROLEARN learns one or more prototype per class and follows instance based classification with them. Prototype here differs from psychological term in that we can have more than one prototype per concept and also differs from other instance based algorithms since the prototype is a "ficticious ideal example". We show that PROLEARN is as good as the traditional machine learning algorithms but much move stable than them in an environment that has noise or changing training set, what we call 'stability’.tability’.

• Journal of the Korean School Mathematics Society
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• v.15 no.2
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• pp.259-279
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• 2012

The purposes of this study were to investigate the effects of the use of link sheet in pre-service mathematics teachers' mathematics learning. The study was conducted in Calculus course during 1 semester with 25 pre-service mathematics teachers. According to the results of questionnaires and focused group interviews, the use of the link sheet helped students to develop deeper understandings of mathematical concepts and mathematical communication ability. In addition, the use of the link sheet encouraged students to realize the value of the mathematics and it also played a central role in creating active and self-directed learning atmosphere.