• Communications of Mathematical Education
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• v.23 no.2
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• pp.461-481
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• 2009

The semiotic approach to the mathematics education has been studied in last 20 years by PME, ICME conferences. New cultural developments in multi-media, digital documents and digital arts and cultures may influence mathematical education and teaching and learning activities. Hence semiotical interest in the mathematics education research and practice will be increasing. In this paper the basic ideas of semiotics, such as Peirce triad and Saussure's dyad, are introduced with some mathematical applications. There is some similarities between traditional research topics for concept, representation and social construction in mathematics education research and semiotic approach topics for the same subjects. some semiotic applications for an arithmetic problem for work, induction, deduction and abduction syllogisms with respect to Peirce's triad, its meaning in scientific discoveries and learning in geometry and symmetry.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1081-1094
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• 2020

With the recent development of deep learning, most computer vision-related tasks are being solved with deep learning-based network technologies such as CNN and RNN. Computer vision tasks such as object detection or object segmentation use intermediate features extracted from the same backbone such as Resnet or FPN for training and inference for object detection and segmentation. In this paper, an experiment was conducted to find out the compression efficiency and the effect of encoding on task inference performance when the features extracted in the intermediate stage of CNN are encoded. The feature map that combines the features of 256 channels into one image and the original image were encoded in HEVC to compare and analyze the inference performance for object detection and segmentation. Since the intermediate feature map encodes the five levels of feature maps (P2 to P6), the image size and resolution are increased compared to the original image. However, when the degree of compression is weakened, the use of feature maps yields similar or better inference results to the inference performance of the original image.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.855-861
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• 2021

Neural Architecture Search (NAS) is cutting-edge technology in the machine learning community. NAS Without Training (NASWOT) recently has been proposed to tackle the high demand of computational resources in NAS by leveraging some indicators to predict the performance of architectures before training. The advantage of these indicators is that they do not require any training. Thus, NASWOT reduces the searching time and computational cost significantly. However, NASWOT only considers high-performing networks which does not guarantee a fast inference speed on hardware devices. In this paper, we propose a multi objectives reward function, which considers the network's latency and the predicted performance, and incorporate it into the Reinforcement Learning approach to search for the best networks with low latency. Unlike other methods, which use FLOPs to measure the latency that does not reflect the actual latency, we obtain the network's latency from the hardware NAS bench. We conduct extensive experiments on NAS-Bench-201 using CIFAR-10, CIFAR-100, and ImageNet-16-120 datasets, and show that the proposed method is capable of generating the best network under latency constrained without training subnetworks.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.489-499
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• 2021

This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. However, it is still difficult and cumbersome for those who are not familiar with programming and artificial intelligence. In order to deal with the content creation with new technologies, we analyze related creation tools, services and technologies that process with raw visual and audio data, generate new media contents and visualize intermediate results. We then extract key requirements for a future creation tool for creators who are not familiar with programming and artificial intelligence. We finally introduce an intuitive and integrated content creation tool for end-users. We hope that this tool will allow creators to intuitively and creatively generate new media arts and culture contents based on not only understanding given data but also adopting new technologies.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.375-387
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• 2013

Advanced internet service and smart equipment have caused an environment supporting various online learning anytime and anywhere, which requires learning contents optimized on a new media. Among various on/off line education related to IT, most part if it is office SW. Many oh them cannot make a good education for effective training in practical because many instructors are tend to focus on teaching simple function and use examples of formality repeatedly. In this paper we propose a new office SW education system that make use of LET(Live EduTainer) based on RTE(Real Training Environment) which maximize the effect of learning and it is integrated with GBL(Game Based Learning) which gives rise to interesting in a knowledge as well as simple teaching so that learners are absorbed on it. We'll elaborate a method for teaching and learning required in this system, design and configuration of the system.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.3
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• pp.59-68
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• 2021

Purpose : The purpose of this study was to investigate the lecture method and physical activity level of Korean university students during the COVID-19 pandemic to determine their effect on the students' mental health, self-efficacy, and learning motivation. Methods : A total of 203 participants (53 male, 150 female) completed the study. An online survey was distributed through a social media platform between March 24 and April 7, 2021. Participants completed the international physical activity questionnaire-short form (IPAQ-SF), COVID-19 stress scale for Korean people (CSSK), the Korean version of the general health questionnaire (KGHQ-30), and self-efficacy and learning motivation scales. Results : Among the general characteristics of the study subjects, there were statistically significant differences in the IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation measures by sex. There were no significant differences in the degree of IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation among any of the lecture method and university area groups. The level of physical activity corresponded with significant differences in KGHQ, self-efficacy, and learning motivation, excluding CSSK. There was a statistically significant positive correlation between IPAQ and self-efficacy (r=.273, p<.001), IPAQ-SF and learning motivation (r=.201, p<.01), CSSK and KGHQ (r=.271, p<.001), self-efficacy and learning motivation measures (r=.506, p<.001). There was a statistically significant negative correlation between IPAQ-SF and KGHQ (r=-.203, p<.01) and between KGHQ and self-efficacy (r=-.558, p<.001). Conclusion : CSSK and KGHQ measures were significantly higher in female students than in male students. Therefore, it is important to consider sex as a protective factor in the mental health management of university students in the context of an infectious disease pandemic. The results of this study suggest that university students should continue to engage in physical activities, even during a pandemic, and that it is necessary to prepare health management to improve mental health in such situations.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.353-357
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• 2022

This article identifies the problems and substantiates the directions for the development of distance learning technologies in the training of personnel. An example of using digital media to create a remote access laboratory is given. The article is devoted to the definition of the main aspects of the organization of distance education. Rapid digitization, economic, political and social changes taking place in Ukraine necessitate the reform of the education system. First of all, it concerns meeting the educational needs of citizens throughout their lives, providing access to educational and professional training for all who have the necessary abilities and adequate training. The most effective solution to the above-mentioned problems is facilitated by distance learning. The article analyzes the essence and methods of distance learning organization, reveals the features of the use of electronic platforms for the organization of this form of education in different countries of the world. The positive characteristics of distance learning are identified, namely: extraterritoriality; savings on transport costs; the interest of modern youth in the use of information tools in everyday life; increase in the number of students; simplicity and accessibility of training; convenient consultation system; democratic relations between the student and the teacher; convenience for organizations in training their employees without interrupting their regular work; low level of payment for distance education compared to traditional education; individual learning pace; new teacher status. Among the negative features of online education, the author refers to the following problems: authentication of users during knowledge verification, calculation of the teacher's methodological load and copyright of educational materials; the high labor intensity of developing high-quality educational content and the high cost of distance learning equipment; the need to provide users with a personal computer and access to the Internet; the need to find and use effective motivation mechanisms for education seekers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.290-293
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• 2021

In this paper, we implement a learning efficiency verification system to inspire learning motivation and help improve concentration by detecting the situation of the user studying. To this aim, data on learning attitude and concentration are measured by extracting the movement of the user's face or body through a real-time camera. The Jetson board was used to implement the real-time embedded system, and a convolutional neural network (CNN) was implemented for image recognition. After detecting the feature part of the object using a CNN, motion detection is performed. The captured image is shown in a GUI written in PYQT5, and data is collected by sending push messages when each of the actions is obstructed. In addition, each function can be executed on the main screen made with the GUI, and functions such as a statistical graph that calculates the collected data, To do list, and white noise are performed. Through learning efficiency checking system, various functions including data collection and analysis of targets were provided to users.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.393-399
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• 2012

New and creative skills must be developed, and adapted into a lesson, to motivate learners to acquire a second language easily and enjoyment, Multimedia tools which are of interest to learners, such as; smart phones, computers, and notebooks with wireless internet compatability, will provide learners opportunities to study, and do their work practically anywhere and anytime. Recently, podcasts, which are a type of digital media, consisting of a series of audio episodes or video files, subscribed to and downloaded through web syndication, or streamed online to a computer or mobile device, are used to facilitate ESL (English as a Second Language) learning. Development of a variety of teaching methods, using multimedia tools, is needed. There are advantages and disadvantages to using a variety of multimedia tools. The current research aims to study its characteristics and application, in order to maximize their effective use, in English education. The current study suggests a ubiquitous learning environment using multimedia content tools, internet media, video teleconferencing, cyber-learning, and one-to-one videos used in conjunction with, or as a digital textbook for the English lesson. This study also investigates future educational changes, using state-of-the-art equipment for the self-learning experience, and will present a new direction in English education, through a variety of instructional devices and a marginalized class system model.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.