• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.523-528
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• 2023

The applicability as a material to improve solar cell performance was reviewed by synthesizing a phosphor that emits red wavelengths by a liquid synthesis method using a metal salt aqueous solution and a polymer medium as a starting material. An aqueous solution was prepared using nitrate of metals such as Ca, Zn, Al, and Eu, and a precursor impregnated with starch, a natural polymer, was sintered to synthesize CaZnAlO:Eu phosphor powder. The surface structure and composition analysis of the synthesized CaZnAlO:Eu phosphor powder were analyzed by scanning electron microscope(SEM) and energy-dispersed X-ray spectroscopy(EDS). The crystal structure of CaZnAlO:Eu phosphor particles was analyzed by an X-ray diffraction analyzer (XRD). As a result of measuring the photoluminescence(PL) characteristics of the phosphor, it was confirmed that a red phosphor with a light emitting wavelength of 650-780nm was successfully synthesized. According to SEM and EDS analysis, the synthesized Ca₁₄Zn₆Al_9.93O₃₅:Eu³⁺_0.07 phosphor powder has a uniform particle size, and Eu ions used as an activator are present. The synthesized CZA:Eu³⁺ phosphor can be used as a material that can increase the light absorption efficiency of the solar cell by converting ultraviolet or visible light down conversion into a wavelength in the near-infrared region.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.275-283
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• 2023

The progressive wear of teeth is a physiologic process of aging, but excessive wear can lead to occlusal disharmony, tooth sensitivity and pulp exposure, decreased masticatory efficiency, and aesthetic problems. It should be treated by evaluating the cause of tooth wear and establishing a stable centric relation with appropriate vertical dimension of occlusion and occlusal plane. The present case report successfully rehabilitated a full-mouth case of a severely worn dentition with the use of digital facebow transfer and virtual articulator.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.5
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• pp.196-201
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• 2023

In order to improve the efficiency of the water splitting system for hydrogen energy production, the high overvoltage in the electrochemical reaction caused by the catalyst in the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) must be reduced. Among them, transition metal-based compounds (hydroxide, sulfide, etc.) are attracting attention as catalyst materials to replace currently used precious metals such as platinum. In this study, Ni foam, an inexpensive metal porous material, was used as a support and β-Ni(OH)₂ microcrystals were synthesized through a hydrothermal synthesis process. In addition, changes in the crystal morphology, crystal structure, and water splitting characteristics of β-Ni(OH)₂ microcrystals synthesized by doping Fe to improve electrochemical properties were observed, and applicability as a catalyst in a commercial water electrolysis system was examined.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.21-27
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• 2023

As a means of helping ships navigate safely, navigational aids in operation in the maritime envirionment require periodic management, and due to the nature of the environment, it is difficult to visually check the exact state. As a result, the smart navigation aid system, which improves route safety and operational efficiency, utillizes expertise including sensors, communications, and information technology, unlike general route markings. The communication environment of the smart navigation aid system, which aims to ensure the safety of the navigators operating the ship and the safety of the ship, uses a wireless communication network in accordance with the marine environment. The ship collects the information necessary for the maritime environment on the land and operates. In this process, there is a need to consider the wireless communication security guideline. Basically, based on IHO S-100 a standard for facilitating data exchange and SECOM, which provides an interface for safe communication. This paper research a security system for safe communication in a maritime environment. The security system for the basic interface based on the document was presented, and there were some vulnerabillties to data exchange due to the wireless communication characteristics of the maritime environment, and the user authetication part was added considering the vulnerability that unauthorized users can access the service.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.431-446
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• 2023

Samama wood (Anthocephalus macrophyllus (Roxb) Havil) is a fast-growing and lesser-utilized wood species that has inferior properties; therefore, its quality needs to be improved. This research aimed to determine the effect of citric acid impregnation at high curing temperatures on the dimensional stability and mechanical properties of wood. Citric acid solution with 10% concentration (w/w) was impregnated into wood samples by vacuum-pressure method (-0.5 cmHg, 30 min; 0.7 MPa, 3 h), followed by curing process at 140℃, 160℃, and 180℃ of temperature for 1 h. In comparison, the other wood samples were heat treated at the same temperatures and time. The results showed that the increase in curing and heat temperatures for both treatments were directly proportional to the dimensional stability, but inversely proportional to the mechanical properties. Citric acid impregnated had higher density, dimensional stability, and mechanical properties, except for modulus of rupture, than that of heat treatment. The optimum temperature is suggested at 160℃ in both treatments.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.137-157
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• 2023

The scale of research and development (R&D) investment is increasing to strengthen national competitiveness through technological innovation, leading to an increased interest in investment efficiency. In records management, the National Archives of Korea has been leading the national research and development project since 2008. Accordingly, this study analyzed R&D projects in records management regarding implementing organization, performance or outcomes, and subjects, targeting 111 National Archives of Korea contract research projects from 2008 to 2022. The analysis showed that small and medium-sized enterprises (SMEs) were the most likely to conduct research, the majority of the research outcomes were academic publications, and there were some discrepancies between the reported performance in research and the actual performance. In terms of research subjects, the most common type of records are paper or print documents, establishing an electronic management system among the National Archives' works. In terms of the frequency of keywords in the records management process and research projects, it was found that research was mainly conducted on "preservation." Meanwhile, only 10 cases, or 9% of the 111 projects, were found to be relevant in terms of utilizing big data and developing intelligent technologies related to digital transformation. Therefore, the effectiveness of the R&D project must be improved through follow-up management of the results even after the research project is completed. In addition, in terms of research topics, it was identified that aside from "preservation," studies focusing on "transfer," "classification," "evaluation," and "collection," as well as research that responds to digital transformation, are needed.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.1
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• pp.30-35
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• 2024

In order to improve the efficiency of the water splitting system for hydrogen production, the high overvoltage in the electrochemical reaction caused by the catalyst in the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) must be reduced. Among them, transition metal-based compounds are attracting attention as catalyst materials that can replace precious metals such as platinum that are currently used. In this study, nickel foam, an inexpensive metal porous material, was used as a support, and Fe-doped β-Ni(OH)₂ microcrystals were synthesized through a hydrothermal synthesis process. In addition, in order to improve OER properties, changes in the shape, crystal structure, and water splitting characteristics of Fe-Mo co-doped β-Ni(OH)₂ microcrystals synthesized by co-doping with Mo were observed. The changes in the shape, crystal structure, and applicability as a catalyst for water splitting were examined.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.