• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.45-49
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• 2022

The fourth industrial revolution, internet of things, and the expansion of online web services have increased an exponential growth and deployment in the number of cloud data centers (CDC). The cloud is emerging as new paradigm for delivering the Internet-based computing services. Due to the dynamic and non-linear workload and availability of the resources is a critical problem for efficient workload and resource management. In this paper, we propose the particle swarm optimization (PSO) based gated recurrent unit (GRU) neural network for efficient prediction the future value of the CPU and memory usage in the cloud data centers. We investigate the hyper-parameters of the GRU for better model to effectively predict the cloud resources. We use the Google Cluster traces to evaluate the aforementioned PSO-GRU prediction. The experimental shows the effectiveness of the proposed algorithm.

• Journal of the Korean Wood Science and Technology
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• v.49 no.3
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• pp.254-266
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• 2021

Using forest resources involves solving complex and diverse tasks. At the same time, one of the key goals in the field is improving the quality of forest infrastructure. This direction requires adequate mathematical and economic justification. Moreover, creating an effective infrastructure will not only increase the accessibility and usage volumes of wood and other forest resources, but also contribute to the development of continuous and sustainable forest management. The existing practice of making decisions in terms of the organizational and technological aspects of logging, based on the personal experiences of managers or leading specialists in enterprises, hinders the achievement of constant optimal efficiency. The paper presents results that are a continuation of the research cycle of the authors' team in the fields of optimization and algorithmization of various logging processes. The focus of the study lies in the processing and movement of wood resources, the most valuable products of the investigated groups of enterprises. To this end, the paper presents a developed algorithm for determining an effective technological chain of transportation in logging operations, and for improving loading and unloading processing operations under dynamic natural and production conditions. This algorithm serves as the methodological basis for designing logging infrastructure in a dynamically changing environment.

• The Journal of Information Systems
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• v.31 no.4
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• pp.209-232
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• 2022

Purpose In the current environment of online shopping, the cost for consumers to obtain the information they need is decreasing, and the price of products is becoming more transparent, leading to increased price competition among enterprises for similar products. Given the widespread usage of limited-time promotion as a marketing method for enterprises in the context of e-commerce, it is great meaning to study and reveal the internal influence mechanism of limited-time promotion on consumers' impulsive consumption. Design/methodology/approach Based on the S-O-R theory, this study constructs a model of consumers' impulsive consumption in the context of e-commerce from the perspective of perceived price discount, with evoking sense and pleasure as mediating variables and perceived time pressure as moderating variables. Findings The results show that perceived price discount has a significant positive impact on evoking sense and pleasure. Evoking sense has a significant positive impact on pleasure. Both evoking sense and pleasure have a significant positive impact on consumers' impulsive consumption. Meanwhile, perceived time pressure plays a significant moderating role between perceived price discount and evoking sense, between perceived price discount and pleasure, and between evoking sense and consumers' impulsive consumption. Finally, based on the above findings, this study provides effective suggestions for e-commerce participants in the formulation of limited-time promotion strategies.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.201-211
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• 2022

The economic development of most countries in the world has negatively impacted fossil energy resources. Fossil energy sources such as petroleum and coal are increasingly depleted. When energy sources are exhausted, renewable energy sources are growing strongly. Renewable energy development can help to replace diminishing fossil fuels. Furthermore, the usage of renewable energy can contribute to a green economy and sustainable development by protecting the environment. Solar power on the roof is one of the many renewable energy sources available. But at present, the investment in roof voltage systems has not developed strongly in Vietnam. This paper uses the SEM model to evaluate the factors affecting investment in rooftop solar power in some provinces of Vietnam. The article uses the household interview method. The article has given 8 factors affecting the decision to invest in rooftop solar power for households. Research results show that most of the factor variables have a positive impact on the decision to invest in rooftop solar power. Based on assessing the factors affecting the decision to invest in rooftop solar power, the article will provide conclusions and policy suggestions to increase investment in rooftop solar power in Vietnam.

• Journal of Distribution Science
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• v.20 no.11
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• pp.109-120
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• 2022

Purpose: We would like to identify the appropriate size of stores in the commercial district suitable for the era of low growth. In addition, it is intended to present alternatives to prevent gentrification along with measures to revitalize commercial districts according to the selection of appropriate stores. Research design, data and methodology: The importance and commercial district usage patterns were identified through surveys by consumers and sellers. the demand and size of the commercial area were calculated based on the floating population and resident registration population. In addition, based on this, through metric analysis, the importance of the business district activation plan and what important matters can prevent gentrification were analyzed. Result: In this the study, 555 stores are currently operating in the target area, but it is seen as a commercial district with a scale that can operate 136 stores and 938 stores. In addition, it was analyzed that the Commercial Lease Protection Act needs to be strengthened to prevent gentrification. Conclusions: Due to the nature of small and medium-sized cities in Korea, commercial districts that have once lost their resilience must take much effort to find vitality. It is believed that local commercial districts will have resilience when diagnosis and recovery measures are adequately presented.

• Korean Journal of Childcare and Education
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• v.19 no.1
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• pp.43-67
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• 2023

Objective: This study aimed to validate a scale which could measure the correct mediation behavior of parents for their children's smart media use. Methods: The subjects were comprised of 514 parents of 5-year-old children. The collected data were analyzed using Jasp. Results: First, in the primary validation process, a total of 19 items and five factors were extracted through exploratory factor analysis. Through secondary validation process, we found that the scale model satisfies the goodness-of-fit evaluation criteria and is valid through confirmatory factor analysis. The newly constructed parents smart media mediation scale in early childhood emerged as a valid and reliable scale. Second, it was found that the more parents pursue 'active mediation', 'instructive mediation', and 'supervision', and avoid 'co-viewing', and 'technical restrictions', the more they had a positive effect on children's smart media usage capabilities. Third, the total score of smart media mediation for young children's parents was found to significantly differentiate young children's smart media overdependence, and self-regulation. Conclusion/Implications: The final smart media mediation scale for young children's parents was composed of 19 items, with five factors: 'co-viewing', 'instructive mediation', 'technical restrictions', 'active mediation', and 'supervision'.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2734-2741
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• 2023

Brachytherapy is a special case of radiotherapy. It should be arranged according to some principles in medical radiation applications and radiation physics. The primary principle is to use as low as reasonably achievable dose in all ionizing radiation applications for diagnostic and therapeutic treatments. Dosimetric distributions are dependent on radioactive source properties and radiation-matter interactions in an absorber medium such as phantom or tissue. In this consideration, the geometrical structure and material of the seed capsule, which surrounds a radioactive material, are directly responsible for isodose profiles and dosimetric functions. In this study, the radiometric properties of capsule material were investigated on dose distribution in a water phantom by changing its nuclear properties using the EGSnrc Monte Carlo (MC) simulation code. Effective atomic numbers of hypothetic mixtures were calculated by using different elements with several fractions for capsule material. Model 6711 brachytherapy seed was modeled by EGSnrc/Dosrcnrc Code and dosimetric functions were calculated. As a result, dosimetric parameters of hypothetic sources have been acquired in large-scale atomic number. Dosimetric deviations between the data of hypothetic seeds and the original one were analyzed. Unit dose (Gy/Particle) distributions belonging to different types of material in seed capsule have remarkably differed from the original capsule's data. Capsule type is major variable to manage the expected dose profile and isodose distribution around a seed. This study shows us systematically varied scale of material type (cross section or effective atomic number dependent) offers selective material usage in production of seed capsules for the expected isodose profile of a specific source.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.271-291
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• 2023

Settlement estimation in cohesion materials is a crucial topic to tackle because of the complexity of the cohesion soil texture, which could be solved roughly by substituted solutions. The goal of this research was to implement recently developed machine learning features as effective methods to predict settlement (S_m) of shallow foundations over cohesion soil properties. These models include hybridized support vector regression (SVR), random forests (RF), and coot optimization algorithm (COM), and black widow optimization algorithm (BWOA). The results indicate that all created systems accurately simulated the S_m, with an R² of better than 0.979 and 0.9765 for the train and test data phases, respectively. This indicates extraordinary efficiency and a good correlation between the experimental and simulated S_m. The model's results outperformed those of ANFIS - PSO, and COM - RF findings were much outstanding to those of the literature. By analyzing established designs utilizing different analysis aspects, such as various error criteria, Taylor diagrams, uncertainty analyses, and error distribution, it was feasible to arrive at the final result that the recommended COM - RF was the outperformed approach in the forecasting process of S_m of shallow foundation, while other techniques were also reliable.

• Journal of Technologic Dentistry
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• v.45 no.1
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• pp.21-29
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• 2023

Purpose: This study attempted to collect basic data to improve the basic repair ability of university freshmen in a world where the usage of advanced medical devices related to computer programs is now common. Methods: The collected data from 280 university freshmen enrolled in nursing, dental, and health degrees or computer and engineering degrees at K university of Gangwon-do were analyzed using the t-test, ANOVA, correlation analysis, and linear regression analysis using the IBM SPSS Statistics ver. 21.0 (IBM). Results: The mathematical learning status and the detailed factors of basic mathematical ability had a positive (+) correlation. The factors of basic mathematical ability, psychology of learning (p<0.001), method of learning (p<0.001), and propensity to learn (p<0.05) were found to be statistically significant, and the model's explanatory power was 40.0%. Conclusion: As a result of this study and considering that advanced medical devices such as computer-aided design/computer-aided manufacturing and three-dimensional printers are becoming more common and up-to-date in clinical settings, it is determined that nursing and dental health students require education to improve their repair skills.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).