• International journal of advanced smart convergence
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• v.11 no.2
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• pp.135-141
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• 2022

This thesis examines a significant way to enhancing and improving the term/phenomenon of performer training system in contemporary Korean theatre. To articulate the matters, this research engages in discussing and criticizing those problematic issues that we, as an instructor/trainer, have faced with through the last decades in the field of performer training and education. Specifically, we concern with the necessity of an applicable and appropriate educational/training system where each student-actor would discover his/her own adaptability by evaluating what a specific method and approach is. This atmosphere accurately provided by an instructor/trainer can also facilitate and enhance the young students' potential possibilities and/or talent, that is, as we argue a way to accomplish each performer's true nature. To achieve the goals, we underlie the necessity of establishing and/or settling performer training program/course by means of an alternative path. The research finding shows that within the atmosphere each student could share then interrogate what a possible or ideal way is according to his/her comprehensive understandings with clearer purpose: what kind of performers would you produce, train, and/or educate.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.45-56
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• 2020

Despite extensive research, performance enhancement of keyphrase (KP) extraction remains a challenging problem in modern informatics. Recently, deep learning-based supervised approaches have exhibited state-of-the-art accuracies with respect to this problem, and several of the previously proposed methods utilize Bidirectional Encoder Representations from Transformers (BERT)-based language models. However, few studies have investigated the effective application of BERT-based fine-tuning techniques to the problem of KP extraction. In this paper, we consider the aforementioned problem in the context of scientific articles by investigating the fine-tuning characteristics of two distinct BERT models - BERT (i.e., base BERT model by Google) and SciBERT (i.e., a BERT model trained on scientific text). Three different datasets (WWW, KDD, and Inspec) comprising data obtained from the computer science domain are used to compare the results obtained by fine-tuning BERT and SciBERT in terms of KP extraction.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.24-31
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• 2023

The solid-state drive (SSD) possesses higher input and output speeds, more resistance to physical shock, and lower latency compared with regular hard disks; hence, it is an increasingly popular storage device. However, tiny components on an internal printed circuit board (PCB) hinder the manual detection of malfunctioning components. With the rapid development of artificial intelligence technologies, automatic detection of components through convolutional neural networks (CNN) can provide a sound solution for this area. This study proposes applying the YOLOv5 model to SSD PCB component detection, which is the first step in detecting defective components. It achieves pioneering state-of-the-art results on the SSD PCB dataset. Contrast experiments are conducted with YOLOX, a neck-and-neck model with YOLOv5; evidently, YOLOv5 obtains an mAP@0.5 of 99.0%, essentially outperforming YOLOX. These experiments prove that the YOLOv5 model is effective for tiny object detection and can be used to study the second step of detecting defective components in the future.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.90-95
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• 2023

With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

• Nonlinear Functional Analysis and Applications
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• v.29 no.1
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• pp.209-224
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• 2024

The goal of this study is to instigate various new and novel optimum proximity point theorems using the notion of implicit relation type ℶ-proximal contraction for non-self mappings. An illustrated example is used to demonstrate the validity of the obtained results. Furthermore, some uniqueness results for proximal contractions are also furnished with partial order and graph. Various well-known discoveries in the present state-of-the-art are enhanced, extended, unified, and generalized by our findings. As an application, we generate some fixed point results fulfilling a modified contraction and a graph contraction, using the profundity of the established results.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.77-84
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• 2024

This study delves into the subtle sounds emanating from beneath the earth's surface to unveil hidden messages and the movements of life. It transforms these acoustic phenomena into digital data and reimagines them as visual elements. By employing Sismophone microphones and utilizing the FFT function in p5.js, it analyzes the intricate frequency components of subterranean sounds and translates them into various visual elements, including 3D geometric shapes, flowing lines, and moving particles. This project is grounded in the sounds recorded in diverse 'spaces of death,' ranging from the tombs of Joseon Dynasty officials to abandoned areas in modern cities. We leverage the power of sound to transcend space and time, conveying the concealed narratives and messages of forgotten places .Through the visualization of these sounds, this research blurs the boundaries between 'death' and 'life,' 'past' and 'present,' aiming to explore new forms of artistic expression and broaden perceptions through the sensory connection between sound and vision.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.85-91
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• 2024

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.92-98
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• 2024

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.1
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• pp.43-50
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• 2024

Purpose: People must express their feelings and thoughts to maintain mental health and stability. Expressing one's emotions, experiences, and thoughts in writing relieves inner feelings, promotes self-exploration, and improves individual well-being, resulting in a pleasant state on physical, mental, and social levels. This study aims to reveal the learning experiences of university students who participated in a self-expressive writing course to improve their well-being. Method: To explore the learning experiences of university students who took a self-expressive writing course, this study used qualitative research methods to analyze the students' written reflection notes. Results: Self-expressive writing was found to resolve university students' negative emotions, regulate their emotions, improve their self-reflection and self-awareness, contributing to their problem-solving skills and ability to set new goals, and strengthen their social communication. The meaning of this class experience can be summarized as healing, awareness, reflection, change, and growth. Conclusion: The results of this study provide concrete data on expressive writing classes and are valuable when designing the writing programs.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.603-610
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• 2017

This study was to explore perceived difficulties from before entrance into physical education in graduate school of education to before graduation. Participants were PETE graduate students in Seoul and Gyeonggi province and survey was used to collect data. Among 100 copies of data, 95 copies had been used for actual data processing. Frequency analysis was conducted by using SPSS 21.0. The results are as follows. First, participants had trouble in financial difficulty before entering graduate school, but the financial difficulty was considered normal by other new difficulties. Second, much time spent for graduate school of education was considered one of biggest difficulties, but the burden of curriculum was relatively low. Third, anxiety about future career that started from before entering graduate school lasted until graduation. Fourth, lack of knowledge was considered as one of biggest troubles before graduation. Conclusively, physical education in graduate schools need to develop career education as well as evaluation system for the qualitative growth.