• English Language & Literature Teaching
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• v.8 no.2
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• pp.197-218
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• 2003

The purpose of this study is to help the students in middle school improve their English listening comprehension by presenting effective teaching and learning techniques using animation. A good animation provides a self-contained world with language expressed in a virtual context. A few animation such as "Mulan", "The Emperor's New Clothes", and "Gulliver's Travel" are presented. The materials are primarily for English listening comprehension, enhance awareness of American culture and life-styles, and to encourage students' active role in learning English. It is suggested that their use with content-based instruction, where animation provides relevant schema background, makes language relevant and comprehensible. Practical aspects of classroom instruction are discussed, focusing on the adaption of pre-viewing, while-viewing, and post-viewing activities to the selected animation. It is concluded that careful animation selection, purposeful lesson planning, and the integration of pre-viewing, while-viewing, and post-viewing activities into the content-based lesson encourage natural language skills, especially the listening comprehension and students' interest in English.

• English Language & Literature Teaching
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• v.8 no.1
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• pp.1-13
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• 2002

One of the benefits of the internet-assisted instruction is that it can improve L2 Learners' motivation to express themselves in English. The purpose of this paper is to investigate an effective approach to British-American fiction learning in Korean universities, which can emphasize communicative strategies drawing on video-conferencing system, a chat system(CUSeeMe), and an e-mail system. Students are passive participants who cannot assert their creativity in the traditional teaching method of British-American fiction, which mainly relies upon reading and translation far from literature lessons. In CCDL(Cross-cultural distance learning) class, students can play active roles in asserting their own ideas and assuming considerable responsibility for making a presentation in English. A professor can play a role as a coordinator in supporting the students' activities and in winding up the class. The main significance of this article lies in providing a paradigm for CCDL class beyond the limitation of the traditional teaching method of British-American fiction in Korea and futhermore in exploring the eclectic integration of the traditional one and CCDL.

• Journal of Chest Surgery
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• v.18 no.4
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• pp.598-604
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• 1985

One hundred consecutive patients with the Tetralogy of Fallot underwent total correction at National Medical Center during the period 1977 to 1984, Oct. During this study period, we adopted more active policy towards reconstruction of right ventricular outflow tract across pulmonary valve. The mortality was 48% for patients less than 15 kg and 19% in patients above 15kg. Initially Bretschneider`s solution was used as cardioplegia, which was replaced by St. Thomas` solution since 1983, Jan. After then overall mortality dropped to 9% compared to 45% of initial learning period. Heart block occurred In 11 patients, 10 of whom died of combined low cardiac output syndrome. Pure low cardiac output syndrome was noted in 18 patients, most of whom responded to medical measures well except 4 patients. Recently sepsis of Serratia marcescence, which occurred explosively during several months to open heart surgery patients, attacked 3 tetralogy patients resulting in 2 hospital deaths. Our experience has shown that body weight, choice of cardioplegia and accumulation of experience as well as advance of operative and postoperative techniques are still important factors affecting survival rate at initial learning period.

• Research in Mathematical Education
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• v.3 no.2
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• pp.89-98
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• 1999

The purpose of this review of literature is to investigate what kinds of research have been done on social construction of mathematics understanding among elementary students in small groups. Only empirical studies were reviewed, and then grouping was done in terms of the purpose of the study. This grouping identified three categories: 1) Social and mathematical norms in mathematics classroom, 2) Teaching productive communication behaviors for active learning in small group, and 3) Participation roles and communication behaviors in different group structure. To enhance social construction of mathematics understanding in small group settings two suggestions are made: the importance of the selection of collaborative tasks or problems and teachers' beliefs about mathematics and the teaching an learning of mathematics.

• KSCI Review
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• v.14 no.1
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• pp.221-228
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• 2006

In this paper we propose an active learning method that makes a database for the information about certificates and practical examinations and accesses it easily. First of all, this method makes it possible to evaluate students individually, improves the motive of learning and gives students a sense of achievement by providing a user-specific question filtering technique using user pronto information by weight. And, it elevates the acquisition rate of certificates by advising and managing for certificate-acquisition and it also draw more interest and understanding for future directions.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.270-275
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• 2021

Most of the initial forms of cooperative robots were intended to repeat simple tasks in a given space. So, they showed no significant difference from industrial robots. However, research for improving worker's productivity and supplementing human's limited working hours is expanding. Also, there have been active attempts to use it as a service robot by applying AI technology. In line with these social changes, we produced a mobile manipulator that can improve the worker's efficiency and completely replace one person. First, we combined cooperative robot with mobile robot. Second, we applied speech recognition technology and deep learning based object detection. Finally, we integrated all the systems by ROS (robot operating system). This system can communicate with workers by voice and drive autonomously and perform the Pick & Place task.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.82.3-82.3
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• 2019

In this study, we generate future full disk magnetograms in 12, 24, 36 and 48 hours advance from SDO/HMI images using deep learning. To perform this generation, we apply the convolutional generative adversarial network (cGAN) algorithm to a series of SDO/HMI magnetograms. We use SDO/HMI data from 2011 to 2016 for training four models. The models make AI-generated images for 2017 HMI data and compare them with the actual HMI magnetograms for evaluation. The AI-generated images by each model are very similar to the actual images. The average correlation coefficient between the two images for about 600 data sets are about 0.85 for four models. We are examining hundreds of active regions for more detail comparison. In the future we will use pix2pix HD and video2video translation networks for image prediction.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.593-600
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• 2021

In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.

• Smart Structures and Systems
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• v.26 no.6
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• pp.797-807
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.40-48
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• 2023

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: Zero Crossing Rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies.