• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.342-353
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• 2022

This study aims to help revitalize the real-time online education platform market by analyzing the instructor characteristics, content characteristics, and platform characteristics of real-time online education platforms for local learners in China. A total of 670 questionnaires were collected through an online survey and an empirical analysis was conducted. As a result of the analysis, first, except for attractiveness, which is the characteristic of the instructor, professionalism and sincerity had a significant positive influence on both learning satisfaction. Second, the usefulness, abundance, and appropriateness of content characteristics had a significant positive influence on learning satisfaction. Third, except for interaction, which is a platform characteristic, technology and convenience confirmed a significant positive influence relationship on both learning satisfaction. Fourth, learning satisfaction had a significant positive effect on the intention to continue using. This study presented practical implications for real-time online education platform and future research directions.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.581-596
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• 2020

Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.209-238
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• 2023

This study aims to propose the main learning contents, functions and activation plans for building an e-learning platform for libraries through a literature review, case analysis and expert survey. Through the literature review, it was found that libraries must play a role in providing high-quality online education for users in the e-learning ecosystem. Based on the previous studies, a learning function analysis tool was developed for the analysis of the library's e-learning platform. Based on this, the learning contents, learning functions and characteristics of library e-learning platforms were analyzed, and expert surveys and interviews were conducted. As a results, the construction of a platform for effectively applying learning processes and technology is essential for the library's sustainable e-learning services. The contents that should be provided for characteristics of library education, reading guidance, information literacy instruction, library usage instruction, and the latest IT technologies. And The main learning functions include the ability to conduct video lectures and real-time classes among learning types, and learning activity support functions, a cloud platform support function and a personalized environment support function. Additionally, suggested re-education for library staff to improve their technical skills and the formation of an e-learning team.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.271-278
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• 2017

There has been an influx of traders and researchers eager to gain a better understanding of the market due to the rapid growth of the FOREX market. Traders with varying degree of experience are also often inundated with information, analysis methods as well as trading rules when making a trading decision on buying/selling a currency exchange pair. Thus, this paper reviews the current computational tools and analysis methods used within the FOREX trading community and proposes the development of a web-based trading platform with e-learning features to support beginners. Novice traders could also benefit from the use of the proposed e-learning trading platform as it helps them gain valuable knowledge and navigate the FOREX market in real-time. Even experienced traders would find it useful as the platform could be used for actual trading and acts as a reference point to understand the reasoning behind the certain technical analysis implementation that are still unclear to them.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.115-125
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• 2022

As the digital economy has emerged as a means of building a new business order and creating new values, the number of small business owners participating in digital platforms is gradually increasing. This study aims to check whether small business owners participating in the digital platform are being helped to properly respond to the market environment and establish and implement strategies necessary for growth through learning within the platform. To this end, this study attempted to examine the effect of the absorptive capacity of small business owners using e-commerce platforms on market orientation and the moderating effect of vicarious learning and experiential learning, which are two types of learning within the platform. As a result of verifying the hypothesis through the survey, it was found that the absorption capacity of small business owners using digital platforms positively affected their market orientation. In addition, as a result of the moderating effect analysis, it was found that vicarious learning within the platform strengthens the relationship between absorptive capacity and market orientation. This result implies that small business owners can not only prepare for market uncertainties through indirect learning (vicarious learning) but also establish strategies to provide products and services that meet the market's needs. On the other hand, the effect of experiential learning was found to lower market orientation, which means that previous business experiences can rather lower attention to the environment. The significance and implications of the study were presented.

• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.160-172
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• 2024

The characteristic aspects of learning a foreign language require special resources and tools for online learning. Criteria for choosing educational platforms depend on key elements of an academic subject area. Microsoft Teams (hereafter, MT) educational platform is competitive one because it meets most of the needs that arise during the formation of a secondary linguistic persona. Due to the large number of corporate programs, there are a successful acquisition of language skills and the implementation of all types of oral activities of students. A significant MT advantage is the constant analysis and monitoring of the platform of participants' needs in the educational process by developers. The article highlights MT advantages and disadvantages. The attention is drawn to individual programs, which, in the authors' opinion, are the most successful to learn writing, reading, speaking, listening, as well as organize classes that meet needs of modern foreign students.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.79-86
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• 2024

In this paper, we propose a virtual learning platform based on various interactions that occur during real class activities, rather than the existing content delivery-oriented learning metaverse platform. In this study, we provide a learning environment that combines AI and a virtual environment to solve problems by talking to real-time AI. Also, we applied G-learning techinques to improve class immersion. The Virtual Edu platform developed through this study provides an effective learning experience combining self-directed learning, simulation of interest through games, and PBL teaching method. And we propose a new educational method that improves student participation learning effectiveness. Experiment, we test performance on learninng activity based on real-time video classroom. As a result, it was found that the class progressing stably.

• Journal of KIBIM
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• v.11 no.2
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• pp.24-32
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• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.143-149
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• 2024

The role of social networking mobile applications such as WhatsApp in enhancing second language vocabulary learning among English language learners continues to be a subject of interest for many scholars. The current study aimed at examining medical English vocabulary learning among undergraduate students using WhatsApp compared to learning vocabulary via the Blackboard platform during the Covid-19 pandemic. To this end, 108 medical students (51 males, 57 females) enrolled in a first semester English for a specific English course participated in the study. A quasi-experimental design was adopted for two groups. Fifty-three students participated in the WhatsApp group and 55 students formed the Blackboard group. A pretest-posttest design was employed to collect data. Results of t-test scores did not show a significant difference between the WhatsApp and Blackboard groups on a vocabulary test. Results of a survey that measured students' opinion of the use of WhatsApp as a platform for learning new vocabulary showed positive perceptions since participants thought that WhatsApp enhanced their learning experience.