• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.369-374
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• 2024

This study aims to improve the accessibility and efficiency of sign language education for both hearing impaired and non-deaf people. To this end, we developed VR realistic sign language education content that integrates hand tracking technology and conversational AI. Through this content, users can learn sign language in real time and experience direct communication in a virtual environment. As a result of the study, it was confirmed that this integrated approach significantly improves immersion in sign language learning and contributes to lowering the barriers to sign language learning by providing learners with a deeper understanding. This presents a new paradigm for sign language education and shows how technology can change the accessibility and effectiveness of education.

• Korean Journal of Human Ecology
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• v.18 no.5
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• pp.1035-1046
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• 2009

The study was designed to explore mothers' and teachers' beliefs on children's literacy development by comparing their beliefs with the whole language approach. Also, their literacy practices at home and in the classroom were compared and how their literacy beliefs and practices were related was investigated. 176 mothers and 72 daycare teachers participated in this study in Kyunggi-do. Mean, standard deviation, frequency, t-test, and multiple regression were employed to analyze the data. The results showed that the mothers' age, mothers' education, fathers' education and family income mostly predict the mothers' literacy beliefs. Also the teachers' age, education, and their learning experiences with the whole language approach are the main predicting variables in the teachers' beliefs. In practices, the mothers' age, number of children, and fathers' education are independent variables predicting the mothers' practices. The teachers' age, education, interest about the whole language approach, learning experience, and number of children in the classroom are independent variables into the teachers' practices. Overall, teachers showed a higher level of beliefs on the whole language approach and did more literacy practices than the mothers.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.111-128
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• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.95-102
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• 1994

Since parameters influencing the indoor environment of livestock building interrelate so complicatedly, it is of great difficulty to identify the exact cause of environmental problems in a livestock building. Therefore, the approaches for the problem solving based on experience not numerical calculation will be helpful to the management of livestock building This study was attempt to develop the decision supporting system to diagnose environmen- tal problems in a livestock building based on an expert system and a neural network. HClips$^3$), attaching the Hangeul user interface to Clips which is known as a powerful shell for develop- ing expert system, was used. The multilayer perceptron consisting of 4 layers including back propagation learning algorithm was adpoted, which was rapidly converged within the allowable range at 50,000 learning sweeps. The expert system and neural network seemed to work well for this specific application, providing proper suggestions for some environmental problems: particularly, the neural net- work trained by an environmental problem and its corresponding answer with certainty factor, produced the same results as those by expert system.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.5
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• pp.776-784
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• 2010

This study investigated causal relationships between goal orientation, sales and performance towards increasing the effectiveness of up-selling in internal promotion methods in family restaurants and provided implications about the hiring and training of sales people. The subjects were 232 sales people in family restaurants. The data were collected by self-administered questionnaires and analyzed by exploratory factor analysis, reliability analysis, comparative analysis of the average, and regression analysis. Results, showed that variations in goal orientation, sales, and performance depended on the age and experience of salespeople and that goal orientation makes adaptive selling more effective. It turned out that effort selling affects up-selling result than adaptive selling. Long-term workers were better than short-term workers in goal orientation, selling, and up-selling results, so human resource management needs to implement a long-term plan to enhance these effects. And, because effort selling is more effective than adaptive selling in up-selling results in family restaurants, effort selling requires training.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.6-11
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• 2020

In today's world, the design industry is becoming more complex, with the development of networks such as the internet and revolutionary changes in information and telecommunications. As the demand for designers to cope with various situations occurring in these industrial sites or solve problems in practice promptly is required, a capstone design program was developed in collaboration with the industry. Capstone design classes have positive effects on creative problem solving ability, academic achievement and learning satisfaction by allowing students to think and experience the practical problems of the industrial field. It is also effective in improving communication, creative thinking and critical thinking. The purpose of this study is to search for talent training methods needed in the fashion industry and to develop effective programs through capstone design class studies conducted in the fourth grade of fashion design majors from 2017 to 2019 (6 semesters). Through these studies, the aim is to search for talent training methods needed in the fashion industry and to develop effective programs. If the capstone design learning method is used as a method of solving problems through close communication between the company and the educational field as an industry-academia cooperation system, it is expected to be positioned as a field-type human resource education method that is required in the industrial field.

• The Mathematical Education
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• v.43 no.2
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• pp.139-149
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• 2004

This study was initiated by the idea to help students to be more ideally educated following the 7th curriculum that seeks the proactive students along with creativity for the 21st century. Mind-map was the main tool throughout the study and this was performed to find answers for the following questions : 1) to examine how students' drawing a mind-map affects their mathematical tendency or emotional aspects (motivation for study, interest, etc); 2) to investigate the types and characteristics of mind-maps that students draw; 3) to analyze advantages and obstacles that they experience during the process of drawing a mind-map and provide some suggestions for overcoming them. The research shows that students were highly motivated by the drawing a mind-map. There are types of mind-maps: tree shape and radial shape, and each shape has its own advantages. But the more important factor for being a good mind-map is where and how each concept is located and connected. Although it is true that drawing a mind-map helped students to see the bigger structure of what they learned, but there are several hardships taken care of. The study suggests to extend the experiment to various levels of students and diverse contents.

• Hwankyungkyoyuk
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• v.21 no.3
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• pp.1-12
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• 2008

This study is aimed at suggesting ways to develop field trip or learning materials focusing on environment of Jeju seashore in order to make an effective field trip. To perform these purposes, the contents and concepts were analyzed from environment-related 'geological unit' of elementary science textbook. Afterwards, the places having the geological features in coincidence with them are chosen, and investigated, and these regions can develop into geological teaming places for field trip. Each teaming spot focuses on understanding and finding out the characteristic geological environment of rock shore, gravel shore, sand shore, shellfish shore, and tideland shore among Jeju shores. When field trip is conducted at the preparatory stage, students can get advance knowledge on geological concepts from textbook. The activity record paper is presented at the field trip stage where students observe geological phenomena on their own. After field trip is finished, the summary stage is given to solve some problems on the basis of the observed contents. The developed data from this research have its regional limits, but is surely useful for teachers who try to plan field trip when they especially choose the right field trip spots, or plan to make the process for field trip preparation of the environmental education. Furthermore, with this survey and activities, students can take the chance to improve the learning effect through their own experience on environment of Jeju seashore.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.4
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• pp.666-683
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• 2023

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.1-6
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• 2024

In this paper, we develop an AI-based recommendation system that matches the specifications of smartphones from company 'S'. The system aims to simplify the complex decision-making process of consumers and guide them to choose the smartphone that best suits their daily needs. The recommendation system analyzes five specifications of smartphones (price, battery capacity, weight, camera quality, capacity) to help users make informed decisions without searching for extensive information. This approach not only saves time but also improves user satisfaction by ensuring that the selected smartphone closely matches the user's lifestyle and needs. The system utilizes unsupervised learning, i.e. clustering (K-MEANS, DBSCAN, Hierarchical Clustering), and provides personalized recommendations by evaluating them with silhouette scores, ensuring accurate and reliable grouping of similar smartphone models. By leveraging advanced data analysis techniques, the system can identify subtle patterns and preferences that might not be immediately apparent to consumers, enhancing the overall user experience. The ultimate goal of this AI recommendation system is to simplify the smartphone selection process, making it more accessible and user-friendly for all consumers. This paper discusses the data collection, preprocessing, development, implementation, and potential impact of the system using Pandas, crawling, scikit-learn, etc., and highlights the benefits of helping consumers explore the various options available and confidently choose the smartphone that best suits their daily lives.