• Title/Summary/Keyword: empirical modeling

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Knowledge from recent investigations on sloshing motion in a liquid pool with solid particles for severe accident analyses of sodium-cooled fast reactor

  • Xu, Ruicong;Cheng, Songbai;Li, Shuo;Cheng, Hui
    • Nuclear Engineering and Technology
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    • v.54 no.2
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    • pp.589-600
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    • 2022
  • Investigations on the molten-pool sloshing behavior are of essential value for improving nuclear safety evaluation of Core Disruptive Accidents (CDA) that would be possibly encountered for Sodium-cooled Fast Reactors (SFR). This paper is aimed at synthesizing the knowledge from our recent studies on molten-pool sloshing behavior with solid particles conducted at the Sun Yat-sen University. To better visualize and clarify the mechanism and characteristics of sloshing induced by local Fuel-Coolant Interaction (FCI), experiments were performed with various parameters by injecting nitrogen gas into a 2-dimensional liquid pool with accumulated solid particles. It was confirmed that under different particle-bed conditions, three representative flow regimes (i.e. the bubble-impulsion dominant, transitional and bed-inertia dominant regimes) are identifiable. Aimed at predicting the regime transitions during sloshing process, a predictive empirical model along with a regime map was proposed on the basis of experiments using single-sized spherical solid particles, and then was extended for covering more complex particle conditions (e.g. non-spherical, mixed-sized and mixed-density spherical particle conditions). To obtain more comprehensive understandings and verify the applicability and reliability of the predictive model under more realistic conditions (e.g. large-scale 3-dimensional condition), further experimental and modeling studies are also being prepared under other more complicated actual conditions.

A hybrid model of regional path loss of wireless signals through the wall

  • Xi, Guangyong;Lin, Shizhen;Zou, Dongyao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.9
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    • pp.3194-3210
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    • 2022
  • Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

Particle loading as a design parameter for composite radiation shielding

  • Baumann, N.;Diaz, K. Marquez;Simmons-Potter, K.;Potter, B.G. Jr.;Bucay, J.
    • Nuclear Engineering and Technology
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    • v.54 no.10
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    • pp.3855-3863
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    • 2022
  • An evaluation of the radiation shielding performance of high-Z-particle-loaded polylactic acid (PLA) composite materials was pursued. Specimens were produced via fused deposition modeling (FDM) using copper-PLA, steel-PLA, and BaSO4-PLA composite filaments containing 82.7, 75.2, and 44.6 wt% particulate phase contents, respectively, and were tested under broad-band flash x-ray conditions at the Sandia National Laboratories HERMES III facility. The experimental results for the mass attenuation coefficients of the composites were found to be in good agreement with GEANT4 simulations carried out using the same exposure conditions and an atomistic mixture as a model for the composite materials. Further simulation studies, focusing on the Cu-PLA composite system, were used to explore a shield design parameter space (in this case, defined by Cu-particle loading and shield areal density) to assess performance under both high-energy photon and electron fluxes over an incident energy range of 0.5-15 MeV. Based on these results, a method is proposed that can assist in the visualization and isolation of shield parameter coordinate sets that optimize performance under targeted radiation characteristics (type, energy). For electron flux shielding, an empirical relationship was found between areal density (AD), electron energy (E), composition and performance. In cases where ${\frac{E}{AD}}{\geq}2MeV{\bullet}cm{\bullet}g^{-1}$, a shield composed of >85 wt% Cu results in optimal performance. In contrast, a shield composed of <10 wt% Cu is anticipated to perform best against electron irradiation when ${\frac{E}{AD}}<2MeV{\bullet}cm{\bullet}g^{-1}$.

Hybrid adaptive neuro fuzzy inference system for optimization mechanical behaviors of nanocomposite reinforced concrete

  • Huang, Yong;Wu, Shengbin
    • Advances in nano research
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    • v.12 no.5
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    • pp.515-527
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    • 2022
  • The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R2), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R2 values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.

A Study on Influence of UN Public Procurement Participation on SMEs Sustainability in Korea (UN 공공 조달 참여가 우리나라 중소기업 지속가능성에 미치는 영향 분석)

  • LEE, Yejin;CHO, Hyuksoo
    • Knowledge Management Research
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    • v.23 no.3
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    • pp.89-109
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    • 2022
  • Many companies are trying to enter into overseas markets to overcome the limited size of domestic markets. However, there are many barriers to enter the overseas markets such as difficulty to find buyers and make contract with them, payment risks, unfriendly foreign policies, and etc. Companies have used to various strategies to get opportunities of overseas markets. One of them is UN public procurement. Despite many advantages, limited number of companies are participating in the procurement. Individual governments are providing policies to support local companies to participate in the UN public procurement. However it is not easy to encourage firms, especially SMEs to participate in the procurement. This study is designed to analyze firm and product determinants of participating in UN public procurement. Based on literature reviews and empirical findings, this study shows social responsibility and global orientation can play an important role regarding the participation. In addition, the positive relationship between UN public procurement participation and sustainability in a given firm could be empirically supported. Last, we suggest combining country- and industry-level data to investigate UN public procurement participation as an interesting topic for future research. This study represents various determinants to encourage UN public procurement participation. They may contribute to enhance firm performance such as sustainability.

User Experience Factors in Connected Car Infotainment Applications : Focusing on Text Mining Analysis in the Android Auto Reviews (커넥티드카 인포테인먼트 애플리케이션의 사용자 경험 요인 : 안드로이드 오토 리뷰의 텍스트마이닝 분석을 중심으로)

  • Jung Yong Kim;Su-Eun Bae;Junho Choi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.4
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    • pp.211-225
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    • 2023
  • In the future, infotainment systems are expected to play a pivotal role in mobility ecosystems connecting users and vehicles. This study draws user-experience factors from reviews of Android Auto, a car infotainment application, and analyzes factors that affect satisfaction. The user-experience factors of infotainment have been redefined based on previous studies. To analyze actual user-experience factors, topics are obtained, applied, and interpreted from user discourse through topic modeling. Sentiment analysis and logistic regression are used to determine positive and negative user-experience factors that affect satisfaction. Results of the empirical analysis show that Ease of Use and Understandability are factors that have the greatest impact on satisfaction, and Flexibility, Safety, and Playfulness are factors that have the most critical effect on dissatisfaction. Therefore, this paper suggests ways to improve the satisfaction level of the infotainment system, and establishes a strategy accordingly.

Exploring Spatial Variations and Factors associated with Walking Practice in Korea: An Empirical Study based on Geographically Weighted Regression (지리적 가중회귀모형을 이용한 지역별 걷기실천율의 지역적 변이 및 영향요인 탐색)

  • Kim, Eunjoo;Lee, Yeongseo;Yoon, Ju Young
    • Journal of Korean Academy of Nursing
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    • v.53 no.4
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    • pp.426-438
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    • 2023
  • Purpose: Walking practice is a representative indicator of the level of physical activity of local residents. Although the world health organization addressed reduction in prevalence of insufficient physical activity as a global target, the rate of walking practice in Korea has not improved and there are large regional disparities. Therefore, this study aimed to explore the spatial variations of walking practice and its associated factors in Korea. Methods: A secondary analysis was conducted using Community Health Outcome and Health Determinants Database 1.3 from Korea Centers for Disease Control and Prevention. A total of 229 districts was included in the analysis. We compared the ordinary least squares (OLS) and the geographically weighted regression (GWR) to explore the associated factors of walking practice. MGWR 2.2.1 software was used to explore the spatial distribution of walking practice and modeling the GWR. Results: Walking practice had spatial variations across the country. The results showed that the GWR model had better accommodation of spatial autocorrelation than the OLS model. The GWR results indicated that different predictors of walking practice across regions of Korea. Conclusion: The findings of this study may provide insight to nursing researchers, health professionals, and policy makers in planning health programs to promote walking practices in their respective communities.

A Study on Experiential Space Consumption Patterns in Urban Parks through Blog Text Analysis - Focusing on Ttukseom Hangang Park - (블로그 텍스트 분석을 통해 살펴본 도시공원의 경험적 공간 소비 양상 - 뚝섬한강공원을 중심으로 -)

  • Kim, Shinsung
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.2
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    • pp.68-80
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    • 2023
  • With the recent changes in society and the introduction of new technologies, the usage patterns of parks have become diverse, leading to increased complexity in park management. As a result, there is a growing demand for flexible and diverse park management that can adapt to these new requirements. However, there is inadequate discussion on these new demands and whether urban park management policies can respond. Therefore, empirical research on how park usage patterns are evolving is critical. To address this, blog data, in which individuals share their experiences, was used to examine the spatial consumption patterns through semantic network and topic analysis. This study also explored whether these spatial consumption patterns exhibit experiential consumption characteristics according to the experience economy theory. The results showed that consumption behaviors, such as renting picnic sets and having food and drinks delivered, were prominent and that emotional experiences were pursued. Furthermore, these findings were consistent with the experiential consumption characteristics of the experience economy theory. This suggests that park planning and maintenance methods need to become more flexible and diverse in response to the changing demands for park usage.

Directed Graph를 이용한 경제 모형의 접근 - Crandall의 탑승자 사망 모형에 관한 수정- ( Directed Graphical Approach for Economic Modeling : A Revision of Crandall's Occupant Death Model )

  • Roh, J.W.
    • Journal of Korean Port Research
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    • v.12 no.1
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    • pp.55-64
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    • 1998
  • Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

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The Impact of SNS Advertisements on Online Purchase Intention of Generation Z: An Empirical Study of TikTok in Vietnam

  • NGO, Thi Thuy An;LE, Thi My Thanh;NGUYEN, Thanh Hieu;LE, Truong Giang;NGO, Gia Thinh;NGUYEN, Tran Duong
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.5
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    • pp.497-506
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    • 2022
  • The study was carried out to investigate the factors affecting the online purchase intention of Vietnamese consumers, focusing on Generation Z (Gen Z), through the information provided on TikTok - a social media network. Besides, the study evaluates the influence of these factors on the intention to purchase online of Gen Z. Most important; the research aims to help businesses better understand the insight of their consumers. The data were collected from 250 people who were born in the 1995 to 2010 period, living in the South of Vietnam. The study was conducted from December 2021 to March 2022 and used two analytical methods, which are exploratory factor analysis and Structural Equation Modeling. Research results show that there are 4 factors of TikTok advertisements that affect the purchase intention of Gen Z consumers, including information, entertainment, trust, and social interaction, and they all have a positive impact on the online purchase intention. In which the information factor has the most significant impact on the online purchase intention of Gen Z consumers. Based on the research results, recommendations are made to help businesses that have sold or intend to sell products via TikTok, improve the effectiveness of advertisement through the TikTok channel.