• Journal of The Korean Association of Information Education
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• v.10 no.1
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• pp.155-161
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• 2006

Robots evolve from tools to information media since they generates information by interacting with human. As studies on robot-aided education are still in a starting phase, attempts need to be made to use robots for educational purposes and to investigate the effects of the use. It was showed that robot-aided learning was friendlier than other media assisted learning, and especially effective for motivating children. We developed the prototype robot Jenny that can help teachers as a educational media in class(i.e. as a T.A. robot, it can present robot contents on its chest to screen and explain about it when teacher asks). is a schoolmate for 5th or 6th grade children or an elder schoolmate for the rest. We performed the field trial at an elementary school. We carried out 9 classes for three subjects(english, korean, music) with -students in $4th{\sim}5th$ grade. They thought Jenny who was 13 years old as an elder schoolmate in 6th grade. Also, a significant difference was found in the interest and concentration of experimental groups from controlled groups.

• Journal of Korean Academy of Nursing
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• v.36 no.8
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• pp.1324-1330
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• 2006

Purpose. This study developed a web-based wound care course for undergraduate nursing students and evaluated the course's content, system, and student-satisfaction. Methods. This study was done in three stages, the development of the web-based wound care course, the implementation and evaluation of the course. The course was developed based on the ARCS model. 80 under-graduate nursing students to Y University in Korea used the web-based wound care program during four weeks. After that, they completed questionnaires, evaluating the contents, system, and their satisfaction. Results. Eighteen learning objectives were used to create the web-based wound care course and the course was developed with 7 chapters and 20 subsections. The analysis of the questionnaires showed a mean score for content and system-related items of 3.04 each, out of a possible 4 points. Student satisfaction items had a mean score of 2.89. Conclusions. The web-based course allowed students access to the course anytime and anywhere, and according to their own learning abilities. However this advantage would only be possible when nurse educators develop qualitative web-based course to meet the demand of a complex health care system as well as the needs of the students and the effectively incorporate it into traditional lectures.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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• pp.219-229
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• 1999

Nowadays the use of computer has a tendency to be being increased in classroom. Also, Many mathematics teachers are attempting to use computer efficiently in classroom. Computer has unique functions such as graphic, animation, and error correction. As graphic and animation can make the content of mathematics visible and make it easy for learners to study mathematics, it is desirable to develop the computer educational program and use it in teaching and learning mathematics. Especially, before concepts study on the unit of Figure or Function, the use of graphic or animation is efficient by being able to understand easily the content. The purpose of this thesis is to produce the computer program on the Movement of Figure in the unit of Equation of Figure which is in mathematics curriculum for the first grade of high school. In teaching and learning mathematics by use of this program, the educational effects are expected as follows: 1. It is expected that this program will stimulate the interest of learners by using animation and acoustic (sound) effect and so learners' voluntary and active thinking activity will be shown. 2. It will be helpful to form exact concept because it is possible to understand intuitively the basic concepts on the Movement of Figure by using graphic and animation. 3. It is expected that the repeated study of this program already designed will remove the fear of incomplete parts and help review them. 4. It is possible to change from teacher-centered instruction, which is the blind point of recent mathematics education, to the learner-centered instruction. However, it is necessary to realize that using the educational engineering (computer) in mathematics education cannot always cause learners to study mathematics very well and that computer cannot take the place of mathematics teacher. Accordingly, computer will be treated as aids which help learners study difficult part.

• Journal of The Korean Association For Science Education
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• v.22 no.3
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• pp.595-603
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• 2002

The influences of the characteristics of anomalous data on cognitive conflict and conceptual change in learning density were investigated. The subjects were 416 seventh graders. First, the Group Assessment of Logical Thinking and a preconception test were administered. A questionnaire on the responses to anomalous data was then administered. In the questionnaire, four types of anomalous data varying presentation type (movie/text) and authority level (high/low) were randomly presented. After a computer-assisted instruction on density, a conception test was administered. The results indicated that anomalous data presented in movie type significantly induced more cognitive conflict than that in text type. Students presented with anomalous data of high authority scored higher in the conception test than those of low authority. There were no significant interactions between the characteristics of anomalous data and students' logical thinking ability in the scores of both the cognitive conflict and the conception test.

• Korean Journal of Human Ecology
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• v.2 no.1
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• pp.89-98
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• 1999

Kimchi is a traditional food in Korea. It is a fermented food made by several vegetables. Kimchies have traditionally made at home, but the use of commercial Kimchies is increasing. The purpose of this study was to evaluate the intake and evaluation of commercial Kimchies and the perception of desirable learning methods making Kimchies among female high-school students. Three hundred and seventy one female high-school students living in Chonbuk province were participated in the survey. The results obtained were as follows: 1. The percentage of subjects who had consumed commercial Kimchies at least once was 49.7%. It was higher in the subjects living in the rural area(65.6%) than in the urban area(37.9%) at p${\le}$0.001. 2. Positive reasons for the consume of commercial Kimchies was: ‘saving time($4.11{\pm}0.74$)’, ‘convenience to buy when it is needed($4.03{\pm}0.78$)’, ‘variety($3.59{\pm}0.86$)’ and ‘looking good($3.21{\pm}0.98$)’. However, commercial Kimchi received low scores for: ‘sanitation($2.24{\pm}0.96$)’, ‘taste($2.84{\pm}0.96$)’, and ‘economy($2.89{\pm}1.02$)’. 90.5% of the subjects believed that the use of commercial Kimchi will be increased. 3. 24.3% of the subjects had an experience of making Kimchi alone, and 88.7% of the subjects had assisted their mother making Kimchi. 88.9% of the subjects reported that they would like to learn how to make Kimchi from their mothers. 84.0% of the subjects want to make Kimchi by themselves at home when they will be housewives. In conclusion, this report suggests that commercial Kimchi should be produced under more sanitary conditions and Kimchi producers should also develop a variety of tastes to match consumer＇s preferences. There is also a need for education for making high quality Kimchies in school programs of Home Economics. (Korean J of Human Ecology 2(1) : 89-98, 1999)

• Cross-Cultural Studies
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• v.48
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• pp.223-252
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• 2017

This study explores effects of two types of chatbots - voice-based and text-based - on Korean EFL learners' speaking competence and learner perception. Participants were 80 freshmen students taking an English-speaking class at a university in Korea. They were divided into two experimental groups at random. During the sixteen-week experimental period, participants engaged in 10 chat sessions with the two different types of chatbots. To take a close examination of effects on the improvement of speaking competence, they took the TOEIC speaking test as pre- and post-tests. Structured questionnaire-based surveys were conducted before and after treatment to determine if there are changes in perception. Findings reveal two chatbots effectively contribute to improvement of speaking competence among EFL learners. Particularly, the voice-based chatbot was as effective as the text-based chatbot. An analysis of survey results indicates perception of chatbot-assisted language learning changed positively over time. In particular, most participants preferred voice-based chatbot over text-based chatbot. This study provides insight on the use of chatbots in EFL learning, suggesting that EFL teachers should integrate chatbot technology in their classrooms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.361-367
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• 2021

Information search in video streaming services such as YouTube is replacing traditional information search services. To find desired detailed information in such a video, users should repeatedly navigate several points in the video, resulting in a waste of time and network traffic. In this paper, we propose a method to assist users in searching for information in a video by using DBSCAN clustering and LSTM. Our LSTM model is trained with a dataset that consists of user search sequences and their final target points categorized by DBSCAN clustering algorithm. Then, our proposed method utilizes the trained model to suggest an expected category for the user's desired target point based on a partial search sequence that can be collected at the beginning of the search. Our experiment results show that the proposed method successfully finds user destination points with 98% accuracy and 7s of the time difference by average.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.239-260
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• 2023

The underwater acoustic wireless communication networks are generally formed by the different autonomous underwater acoustic vehicles, and transceivers interconnected to the bottom of the ocean with battery deployed modems. Orthogonal frequency division multiplexing (OFDM) has become the most popular modulation technique in underwater acoustic communication due to its high data transmission and robustness over other symmetrical modulation techniques. To maintain the operability of underwater acoustic communication networks, the power consumption of battery-operated transceivers becomes a vital necessity to be minimized. The OFDM technology has a major lack of peak to average power ratio (PAPR) which results in the consumption of more power, creating non-linear distortion and increasing the bit error rate (BER). To overcome this situation, we have contributed our symmetry research into three dimensions. Firstly, we propose a machine learning-based underwater acoustic communication system through long short-term memory neural network (LSTM-NN). Secondly, the proposed LSTM-NN reduces the PAPR and makes the system reliable and efficient, which turns into a better performance of BER. Finally, the simulation and water tank experimental data results are executed which proves that the LSTM-NN is the best solution for mitigating the PAPR with non-linear distortion and complexity in the overall communication system.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.912-921
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• 2021

Objective: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists. Materials and Methods: This clinical retrospective study used 4386-slice computed tomography (CT) images and labels from a training cohort (502 patients with colorectal cancer [CRC] from November 2005 to December 2010) to train the DLLD for detecting liver metastasis, and used CT images of a validation cohort (40 patients with 99 liver metastatic lesions and 45 patients without liver metastasis from January 2011 to December 2011) for comparing the performance of the DLLD with that of readers (three abdominal radiologists and three radiology residents). For per-lesion binary classification, the sensitivity and false positives per patient were measured. Results: A total of 85 patients with CRC were included in the validation cohort. In the comparison based on per-lesion binary classification, the sensitivity of DLLD (81.82%, [81/99]) was comparable to that of abdominal radiologists (80.81%, p = 0.80) and radiology residents (79.46%, p = 0.57). However, the false positives per patient with DLLD (1.330) was higher than that of abdominal radiologists (0.357, p < 0.001) and radiology residents (0.667, p < 0.001). Conclusion: DLLD showed a sensitivity comparable to that of radiologists when detecting liver metastasis in patients initially diagnosed with CRC. However, the false positives of DLLD were higher than those of radiologists. Therefore, DLLD could serve as an assistant tool for detecting liver metastasis instead of a standalone diagnostic tool.