• Journal of Distribution Science
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• v.21 no.7
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• pp.51-63
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• 2023

Housing is not only a basic requirement, but also a method to maintain stability and improve living. In the period of rapid social development which has a significant impact on the aging population, the housing issue is an impediment to Gen Y in Asia. Therefore, solving the housing conundrum is the most effective solution to other social problems. Purpose: This research is conducted to investigate factors influencing housing-option decisions of Gen Y and proposes recommendations to them as well as Governments and the real estate investors. Research design, data, and methodology: The Theory of Planned Behavior was employed with the expanded variables (Financial status, Location, Public services and Government incentives) based on literature review. Results: With 445 valid responses, almost all proposed hypotheses are accepted, which supports the positive interrelationship among variables. In the stage of data processing, we have determined the influence of each factor to the dependent variable "Actual Behavior", thereby helping real estate investors understand their desires, as well as improve the ability to meet customer needs. Conclusion: This is the basis to determine the influence of these factors, thereby providing recommendations to customers and what is more, giving real estate enterprises an insight of customers' demand in order to improve product quality and optimize the benefits of each party.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.1-7
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• 2023

The ability of 3D/4D printing technology to create arbitrary 3D structures provides a greater degree of freedom in the design of printed structures. This capability has influenced the field of electronics and biomedical applications by enabling the trends of device miniaturization, customization, and personalization. Here, the current state-of-the-art knowledge of 3D printed electronics and biomedical applications with the unique and unusual properties enabled by 3D/4D printing is reviewed. Specifically, the review encompasses emerging areas involving recyclable and degradable electronics, metamaterial-based pressure sensor, fully printed portable photodetector, biocompatible and high-strength teeth, bioinspired microneedle, and transformable tube array for 3D cell culture and histology.

• Steel and Composite Structures
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• v.49 no.3
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• pp.337-348
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• 2023

Successive wetting and drying cycles of concrete due to weather changes can endanger the safety of engineering structures over time. Considering wetting and drying cycles in concrete tests can lead to a more correct and reliable design of engineering structures. This study aims to provide a model that can be used to estimate the resistance properties of concrete under different wetting and drying cycles. Complex sample preparation methods, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measuring the strength of concrete in the laboratory. To address these problems, in this study, the potential ability of six machine learning techniques, including ANN, SVM, RF, KNN, XGBoost, and NB, to predict the concrete's tensile strength was investigated by applying 240 datasets obtained using the Brazilian test (80% for training and 20% for test). In conducting the test, the effect of additives such as glass and polypropylene, as well as the effect of wetting and drying cycles on the tensile strength of concrete, was investigated. Finally, the statistical analysis results revealed that the XGBoost model was the most robust one with R2 = 0.9155, mean absolute error (MAE) = 0.1080 Mpa, and variance accounted for (VAF) = 91.54% to predict the concrete tensile strength. This work's significance is that it allows civil engineers to accurately estimate the tensile strength of different types of concrete. In this way, the high time and cost required for the laboratory tests can be eliminated.

• Journal of Distribution Science
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• v.22 no.2
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• pp.71-82
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• 2024

Purpose: Despite significant research on decision-making, researchers struggle to comprehend the decision-making process. This paper aims to not only examine the relationship between problem-solving skills, cognitive competency, and decision-making but also develop measurement instruments for cognitive competency and problem-solving skills to better model decision-making. Research Design, Methodology and Approach: A cross-sectional study was conducted by surveying 292 university students in HCM City, Vietnam, via email sent randomly by Google Forms. This study identifies the conceptual framework and tests the hypotheses using a deductive approach. The SPSS program was used to evaluate the scales' reliability, and the SmartPLS program was used to assess the measurement and structural models. Results: The results show that the research model better modelled the relationship between problem-solving skills, cognitive competency, and decision-making. Although thinking ability has no direct impact on decision-making, both creativity and problem-solving skills have a positive impact on decision-making. The mediating role of problem-solving skills is also determined by the positive relationship between cognitive competency and decision-making. Conclusions: This study highlights decision-making efficiency through the cognitive process from low to high levels and provides for policymakers and managers to explain the decision-making process in a variety of sectors, such as distribution chains, marketing, and human resource distribution.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.113-122
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• 2024

This comprehensive study delves into the analysis of user review data across various metaverse platforms, employing advanced text mining techniques such as TF-IDF and Word2Vec to gain insights into user perceptions. The primary objective is to uncover the factors that contribute to user satisfaction and dissatisfaction, thereby providing a nuanced understanding of user experiences in the metaverse. Through TF-IDF analysis, the research identifies key words and phrases frequently mentioned in user reviews, highlighting aspects that resonate positively with users, such as the ability to engage in creative activities and social interactions within these virtual environments. Word2Vec analysis further enriches this understanding by revealing the contextual relationships between words, offering a deeper insight into user sentiments and the specific features that enhance their engagement with the platforms. A significant finding of this study is the identification of common grievances among users, particularly related to the processes of refunds and login, which point to broader issues within payment systems and user interface designs across platforms. These insights are critical for developers and operators of metaverse platforms, suggesting a focused approach towards enhancing user experiences by amplifying positive aspects. The research underscores the importance of continuous improvement in user interface design and the transparency of payment systems to foster a loyal user base. By providing a comprehensive analysis of user reviews, this study offers valuable guidance for the strategic development and optimization of metaverse platforms, ensuring they remain responsive to user needs and continue to evolve as vibrant, engaging virtual environments.

• Journal of Integrative Natural Science
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• v.17 no.2
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• pp.53-58
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• 2024

This study explores the enhancement of mechanical properties in Polymethyl Methacrylate (PMMA) composites through the incorporation of Methyl Methacrylate (MMA) and Ethylene Glycol Dimethacrylate (EGDMA). Utilizing Digital Light Processing (DLP) technology, we conducted a series of experiments to analyze the impact of varying concentrations of MMA and EGDMA on PMMA. The results indicate that while MMA demonstrates non-linear and variable mechanical strength across different PMMA concentrations, EGDMA consistently improves mechanical strength as PMMA concentration increases. This consistent enhancement by EGDMA suggests a stable and predictable reinforcement effect, which is critical for applications requiring high mechanical strength. Our comparative analysis highlights that EGDMA is a more effective additive than MMA for optimizing the mechanical performance of PMMA composites. Specifically, EGDMA's ability to provide uniform reinforcement across various PMMA concentrations makes it ideal for high-strength applications. These findings are significant for material scientists and engineers focused on the design and development of advanced PMMA-based materials. In conclusion, this research underscores the importance of selecting appropriate additives to enhance the mechanical properties of PMMA composites. The superior performance of EGDMA in reinforcing PMMA suggests its potential for broader applications in fields such as automotive, construction, medical devices, and 3D printing. This study provides valuable insights that can guide future research and development in high-performance composite materials, paving the way for innovative applications and improved material efficiency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.657-665
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• 2019

In this study, we conducted a study on the transcranial magnetic electrode, a method for the study of dementia and muscle pain, a neurodegenerative disease caused by an aging society, which is becoming a problem worldwide. In particular, transcranial magnetic electrodes have been studied to improve their ability to be deteriorated by dementia symptoms such as speech, cognitive ability, and memory by outputting magnetism deep into the brain using coils on the head epidermis. In this study, simulation was performed using Maxwell 3D program for the design of coil, the core of transcranial magnetic electrode. As a result of the simulation comparison between the coil designed by the previous research and the coil through the research and development, the output was found to be superior to the conventional designed coil. The graphs of the coil outputs of B-Field and H-Field are found to be symmetrical, but the symmetry between each coil is pseudo-symmetrical and not accurate. Based on these results, an experiment was conducted to confirm whether the output of the head epidermis through both coils is possible. In the magnitude field of the reverse-coil 2-coil analysis, the maximum output was 3.3920e + 004 H [A_per_meter], and the vector field showed the strongest magnetic field around 35 to 165 degrees. It was confirmed that the magnetic output canceled due to the magnetic output. In the case of the forward 2-coil, a maximum of 3.2348e + 004H [A_per_meter] similar to the reverse coil was observed, but in the case of the vector field, the magnetic output regarding the forward output and the head skin output was confirmed. However, when the height change in the output coil, the magnetic output was reduced.

• Korean Journal of Food Science and Technology
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• v.30 no.5
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• pp.1189-1196
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• 1998

Extraction conditions were optimized using response surface methodology for preparing high-quality ethanol extracts from cultivated Chrysanthemum petals. A fractional factorial design was applied to investigate effects of solvent ratio to sample $(X_1)$, ethanol concentration $(X_2)$ and extraction time $(X_3)$ at $60^{\circ}C$ on dependent variables of the extract properties, such as yellow color $(Y_1)$, carotenoids $(Y_2)$, soluble solids $(Y_3)$, phenolic compounds $(Y_4)$, electron donating ability $(Y_5)$, sensory color $(Y_6)$ and sensory aroma $(Y_7)$. Second-order models were employed to generate 3-dimensional response surfaces for dependent variables and their coefficients of determination $(R^2)$ were ranged from 0.8063 to 0.9963. Optimum extraction conditions for each variable were 115 mL/g, 97%, 18 hr in yellow color, 145 mL/g, 50%, 12 hr in carotenoids, 147 mL/g, 48%, 17 hr in soluble solids, 116 mL/g, 68%, 17 hr in phenolic compounds, 110 mL/g, 98%, 14 hr in electron donating ability, 101 mL/g, 48%, 54 hr in organoleptic color and 109 mL/g, 54%, 4 hr in organoleptic aroma, respectively. The range of optimum conditions at 16hr extraction for maximized characteristics of ethanol extracts was $103{\sim}122\;mL/g$ and $64{\sim}78%$. Predicted values at the optimum condition agreed with experimental values.

• Food Engineering Progress
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• v.13 no.1
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• pp.8-15
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• 2009

This study was investigated on optimal conditions of the functional activities of ${\beta}$-glucan which was extracted from rice bran (RB) and rice germ (RG) using response surface methodology. The extraction temperature was varied in the $80-100^{\circ}C$, the extraction time between 2-10 min, and the ethanol concentration was in the interval of 30-70%. A central composite design was applied to investigate the effects of independent variables of extraction temperature ($X_1$), extraction time ($X_2$) and ethanol concentration ($X_3$) on dependent variables such as electron donating ability of RB ($Y_1$), electron donating ability of RG ($Y_2$), total phenolics of RB ($Y_3$), total phenolics of RG ($Y_4$), ${\beta}$-glucan contents of RB ($Y_5$) and ${\beta}$-glucan contents of RG ($Y_6$). As a result, the highest $Y_1$ level was 84.02% at $92.60^{\circ}C$, 2.75 min and 60.41% in saddle point. This value was affected by extraction temperature (P<0.05). The value of $Y_2$ was found to be the highest at $87.52^{\circ}C$, 2.23 min and 54.40% in saddle point. The highest $Y_3$ level was $98.56^{\circ}C$, 6.69 min and 40.26% in saddle point, and this extraction was greatly influenced by extraction temperature (P<0.01) and ethanol concentration (P<0.05). The value of $Y_4$ was found to be highest at $95.73^{\circ}C$, 9.19 min and 53.67% in minimum point. The value of $Y_5$ was found to be the highest at $96.23^{\circ}C$, 7.70 min and 63.69% in saddle point. The value of $Y_6$ was found to be highest at $87.82^{\circ}C$, 2.10 min and 50.03% in minimum point, and this extraction was greatly influenced by extraction time (P<0.01).

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.211-232
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• 1998

It is the purpose of this study to specify contents of Library and Information Science to train information professional to meet environment change of technology and system. Among them. recognizing necessity of present Artificial Intelligence and Export System (AI and ES) required by changing environment of latest Information technology, it is also the purpose of this work to figure out fundamental data and the way of solution how to introduce what contents out of AI and ES to Library and Information Science. The briefed results are as follows. 1. Due to rapid change of high Information technology and computer application it is the most important essential points, In order of Importance, in finding available network source, In indexing on-line data base, in analysing and design information system. and in computer application ability. 2. In contents of AI and ES, most Important training portion for Library and Information Science are : data base treating, thesaurus, natural language processing. and knowledge representation. 3. Library and information science professors recognize It necessary for bigger number of Library and Information Science students to be educated artificial intelligence and expert system. 4. During forthcoming age it shows more important reorganization that artificial intelligence and expert system improves information professional in reference service, cataloging, classification, information retrieval, and documentation delivery 5. According to library and information science professors more important reorganization on the subject of AI and ES, the curricular on AI and ES is, forthcoming, to be Introduced to curricular on library and information science in the nation, In order of importance, (see 1. above).