• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.861-866
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• 2023

Individuals with visual impairments face difficulties in accessing accurate information about medical services and medications, making it challenging for them to ensure proper medication intake. While there are healthcare laws addressing this issue, there is a lack of standardized solutions, and not all over-the-counter medications are covered. Therefore, we have undertaken the design of a mobile application that utilizes image recognition technology, barcode scanning, and QR code recognition to provide guidance on how to take over-the-counter medications, filling the existing gaps in the knowledge of visually impaired individuals. Currently available applications for individuals with visual impairments allow them to access information about medications. However, they still require the user to remember which specific medication they are taking, posing a significant challenge. In this research, we are optimizing the camera capture environment, user interface (UI), and user experience (UX) screens for image recognition, ensuring greater accessibility and convenience for visually impaired individuals. By implementing the findings from our research into the application, we aim to assist visually impaired individuals in acquiring the correct methods for taking over-the-counter medications.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.83-90
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• 2023

The recent trend in younger generations of wearing traditional costumes or incorporating fusion hanbok into daily wear necessitates the development of modern hair accessories to complement hanbok. The purpose of this study is to develop practical and modern hair accessory designs inspired by royal women's hair ornaments that complement hanbok, and therefore expand the scope of fashion content development utilizing hanbok culture as well as meeting the demand for various experiences of traditional culture. This research studied the literature on traditional hairstyles and accessories of Queen Yeong and constructed models of these accessories for the purpose of empirical research. The production process first required creating a basic foundation of nylon mesh reflecting the silhouette of a traditional hairstyle, and then grafting a digital textile printed fabric using majestic and extravagant royal relics on top, thus employing the trompe l'oeil technique to ultimately give the impression of wearing traditional jewelry. As a result, a total of six hair accessory designs were completed, produced with hairbands, hair pins, and hair ties. In addition, the accessories are designed to be easily worn regardless of the wearer's hair style, and the stiff yet flexible nylon mesh effectively expresses the shape of a voluminous hairstyle and creates an optical illusion, blending into the hair. These research results present a unique aesthetic and cultural experience to the greater public seeking both daily entertainment and value from rarity.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.101-111
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• 2023

This study conducted systematic review and meta-analysis to analyze the effectiveness of a dual-task for cognitive function in patients with MCI in Korea. A search was conducted using eight databases, and the search terms were MCI, cognition, and dual task. This study includes RCT and nonRCT published from January 2013 to July 2023. A total of 682 studies were searched, and 8 studies that fulfilled the inclusion and exclusion criteria were finally analyzed. Methodological quality was assessed with the RoB, RoBANS. The meta-analysis used CMA 4.0 ver. As a result of the analysis, the overall effect size of the dual task was medium effect size. The effect size according to the outcome variables was large for orientation and executive function, and medium effect size for global cognitive function, visuospatial function, memory, and attention. As a result of analysis according to the intervention period, the effect was greater when applied for 4 to 8 weeks, and the effect size was larger when applied for 24 to 30 sessions. This study presented clinical evidence on the effectiveness and application method of a dual-task applied to improve cognitive function in patients with MCI.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.21-29
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• 2024

This study analyzed the difficulty of scoring in different match situations in relation to which competitor scored first. The study analyzed the data from the 2022 Guadalajara World Taekwondo Championships. The analysis was performed for two separate weight classes: lightweight and heavyweight. Four game content variables were used: whether the athlete scored first, attack type, attack area, and game situation. Descriptive statistics, the Rasch model, and discrimination function questions were applied for data processing. SPSS and Winsteps were used for the statistical analysis, and the statistical significance level was set at 0.05. Consequently, in the lightweight class, the scoring frequency of the first scorer was high for all the game variables. In the heavyweight class, the scoring frequency for the first scorer was high for the attack type and attack area. By contrast, those who did not score first were more frequently found to be in a loss situation. By analyzing the scoring difficulties in different match situations based on whether the competitor scored first, the athletes who scored first in attack type most easily scored first. In losing situations, the athletes who scored first in attack area scored most easily, whereas those who did not score first scored most easily in body and match situations. For the heavyweight class, those who scored first in terms of attack type, counter-attack, and attack area scored the most easily while winning in body and match situations.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.85-91
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• 2024

In this paper, we studied projection mapping, which is being utilized as a digital canvas beyond space and time for theme parks, mega events, and exhibition performances. Since the existing projection technology used for fixed objects has the limitation that it is difficult to map moving objects in terms of utilization, it is urgent to develop a technology that can track and map moving objects and a real-time dynamic projection mapping system based on dynamically moving objects so that it can respond to various markets such as performances, exhibitions, and theme parks. In this paper, we propose a system that can track real-time objects in real time and eliminate the delay phenomenon by developing hardware and performing high-speed image processing. Specifically, we develop a real-time object image analysis and projection focusing control unit, an integrated operating system for a real-time object tracking system, and an image processing library for projection mapping. This research is expected to have a wide range of applications in the technology-intensive industry that utilizes real-time vision machine-based detection technology, as well as in the industry where cutting-edge science and technology are converged and produced.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.55-68
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• 2024

Plant engineering companies create or refer to requirements documents for each related field, such as plant process/equipment/piping/instrumentation, in different engineering departments. The process-related requirements document includes not only a description of the process but also the requirements of the equipment or related facilities that will operate it. Since the authors and reviewers of the requirements documents are different, there is a possibility that inconsistencies may occur between equipment or parts design specifications described in different requirement documents. Ensuring consistency in these matters can increase the reliability of the overall plant design information. However, the amount of documents and the scattered nature of requirements for a same equipment and parts across different documents make it challenging for engineers to trace and manage requirements. This paper proposes a method to analyze requirement sentences and calculate the similarity of requirement sentences in order to identify semantically identical sentences. To calculate the similarity of requirement sentences, we propose a named entity recognition method to identify compound words for the parts and properties that are semantically central to the requirements. A method to calculate the similarity of the identified compound words for parts and properties is also proposed. The proposed method is explained using sentences in practical documents, and experimental results are described.