• Title/Summary/Keyword: data modelling

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Uncertainty assessment caused by GCMs selection on hydrologic studies

  • Ghafouri-Azar, Mona;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.151-151
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    • 2018
  • The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

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Key Factors Affecting Intention to Order Online Food Delivery (OFD)

  • SAN, Sing Su;DASTANE, Omkar
    • The Journal of Industrial Distribution & Business
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    • v.12 no.2
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    • pp.19-27
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    • 2021
  • Purpose: This study investigated the impact of key factors such as service quality, perceived benefit and brand familiarity on a consumer's intention to order online food delivery (OFD). In addition, mediating effect of electronic word of mouth (e-WOM) between relationships among selected key variables and OFD purchase intention is also assessed. Research design, data and methodology: This explanatory, quantitative study employed convenience sampling and collected data through online structured questionnaire from 304 respondents who are users of OFD apps based in greater Klang valley region of Malaysia. The data was then subjected to normality and reliability assessment followed by confirmatory factor analysis, validity assessment and structural equation modelling using IBM SPSS AMOS 24.0. Results: Findings revealed that service quality, perceived benefits and brand familiarity affects purchase intention positively and significantly. Perceived benefits demonstrated highest impact on purchase intention followed by brand familiarity and service quality. Findings also suggest that e-WOM fully mediates relationship between brand familiarity and purchase intention, however, the same was not observed for remaining two variables. Conclusions: The study has enriched OFD literature by investigating impact of selected key factors on purchase intention in the context of OFD. Implications, limitations and future research avenues are then discussed.

Statistical analysis issues for neuroimaging MEG data (뇌영상 MEG 데이터에 대한 통계적 분석 문제)

  • Kim, Jaehee
    • The Korean Journal of Applied Statistics
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    • v.35 no.1
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    • pp.161-175
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    • 2022
  • Oscillatory magnetic fields produced in the brain due to neuronal activity can be measured by the sensor. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution, which gives information about the brain's functional activity. Potential utilization of high spatial resolution in MEG is likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in some diseases under resting state or task state. This review is a comprehensive report to introduce statistical models from MEG data including graphical network modelling. It is also meaningful to note that statisticians should play an important role in the brain science field.

Digital engineering models for prefabricated bridge piers

  • Nguyen, Duy-Cuong;Park, Seong-Jun;Shim, Chang-Su
    • Smart Structures and Systems
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    • v.30 no.1
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    • pp.35-47
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    • 2022
  • Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.

Determining the adjusting bias in reactor pressure vessel embrittlement trend curve using Bayesian multilevel modelling

  • Gyeong-Geun Lee;Bong-Sang Lee;Min-Chul Kim;Jong-Min Kim
    • Nuclear Engineering and Technology
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    • v.55 no.8
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    • pp.2844-2853
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    • 2023
  • A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

The impact of fuel depletion scheme within SCALE code on the criticality of spent fuel pool with RBMK fuel assemblies

  • Andrius Slavickas;Tadas Kaliatka;Raimondas Pabarcius;Sigitas Rimkevicius
    • Nuclear Engineering and Technology
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    • v.54 no.12
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    • pp.4731-4742
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    • 2022
  • RBMK fuel assemblies differ from other LWR FA due to a specific arrangement of the fuel rods, the low enrichment, and the used burnable absorber - erbium. Therefore, there is a challenge to adapt modeling tools, developed for other LWR types, to solve RBMK problems. A set of 10 different depletion simulation schemes were tested to estimate the impact on reactivity and spent fuel composition of possible SCALE code options for the neutron transport modelling and the use of different nuclear data libraries. The simulations were performed using cross-section libraries based on both, VII.0 and VII.1, versions of ENDF/B nuclear data, and assuming continuous energy and multigroup simulation modes, standard and user-defined Dancoff factor values, and employing deterministic and Monte Carlo methods. The criticality analysis with burn-up credit was performed for the SFP loaded with RBMK-1500 FA. Spent fuel compositions were taken from each of 10 performed depletion simulations. The criticality of SFP is found to be overestimated by up to 0.08% in simulation cases using user-defined Dancoff factors comparing the results obtained using the continuous energy library (VII.1 version of ENDF/B nuclear data). It was shown that such discrepancy is determined by the higher U-235 and Pu-239 isotopes concentrations calculated.

The Role of Website Quality, Positive Emotion and Personalized Advertising in Triggering Impulse Buying Behavior: A Study of Online Retailer in Indonesia

  • Agung UTAMA;Hunik Sri Runing SAWITRI;Budhi HARYANTO;Lilik WAHYUDI
    • Journal of Distribution Science
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    • v.22 no.2
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    • pp.11-20
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    • 2024
  • Purpose: The primary objective of this study is to investigate the impact of website quality on impulse buying of the online retailer, which is mediated by positive emotion and moderated by personalized advertising. Research design, data and methodology: The present study used a survey methodology conducted on many user's smartphones. The sample in this study included 409 college students in Indonesia. Purposive sampling was used as the sampling technique. Data was collected by distributing questionnaires to many respondents through the Google Documents online survey. Results: The findings derived from the application of structural equation modelling for data analysis show that 1). Website quality affects impulse buying and positive emotion, and 2). The impact of website quality on impulse buying was mediated by positive emotion and moderated by personalized advertising. Conclusions: The findings presented in this study has significant theoretical implications that contribute to the existing concept on the relationship between website quality, positive emotion, personalized advertising and impulse buying. The findings of the research possess managerial implications. It can be used can as a reference in determining website quality and the appropriate personalized advertising that increases online impulse buying at online retailer In Indonesia.

A Human-Centric Approach for Smart Manufacturing Adoption: An Empirical Study

  • Ying PAN;Aidi AHMI;Raja Haslinda RAJA MOHD ALI
    • Journal of Distribution Science
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    • v.22 no.1
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    • pp.37-46
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    • 2024
  • Purpose: This study aims to address the overlooked micro-level aspects within Smart Manufacturing (SM) research, rectifying the misalignment in manufacturing firms' estimation of their technological adoption capabilities. Drawing upon the Social-Technical Systems (STS) theory, this paper utilises innovation capability as a mediating variable, constructing a human-centric organizational model to bridge this research gap. Research design, data and methodology: This study collected data from 233 Chinese manufacturing firms via online questionnaires. Introducing innovation capability as a mediating variable, it investigates the impact of social-technical system dimensions (work design, social subsystems, and technical subsystems) on SM adoption willingness. Smart PLS 4.0 was employed for data analysis, and Structural Equation Modelling (SEM) validated the theoretical model's assumptions. Results: In direct relationships, social subsystems, technical subsystems, and work design positively influence firms' innovation capabilities, which, in turn, positively impact SM adoption. However, innovation capability does not mediate the relationship between technical subsystems and SM adoption. Conclusions: This study focuses on the internal micro-level of organisational employees, constructing a human-centric framework that emphasises the interaction between organisations and technology. The study fills empirical gaps in Smart Manufacturing adoption, providing organisations with a means to examine the integration of employees and the organisational social-technical system.

A study of OTT consumption based on multilevel modelling: Focusing on OTTgenre and subscription preferences, multihoming, and household environment (다층모형에 기반한 OTT 소비행태 연구: OTT 장르 및 구독 선호도, 멀티호밍 그리고 가구 환경을 중심으로)

  • Jeong, DongA;Lee, Sang Woo
    • The Journal of Information Systems
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    • v.33 no.3
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    • pp.75-104
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    • 2024
  • Purpose The purpose of this study is to analyze the influence of individual characteristics and household environmental factors on OTT consumption, based on the uses and gratifications theory and family systems theory. It seeks to provide strategic and policy insights by incorporating key user attributes and environmental determinants affecting OTT consumption. Design/methodology/approach This research employs multilevel analysis utilizing data from the 2023 Media Panel Survey. The analysis incorporates multilevel data, combining individual and household levels. The Media Panel data, provided by the Korea Information Society Development Institute, encompasses information on households and their members aged six and above. Findings The findings indicate that individual OTT consumption significantly varies based on household environment. Residents of larger cities demonstrated higher OTT expenditure, whereas those in smaller cities exhibited greater OTT usage. A positive correlation was found between the number of OTT services used within a household and individual OTT usage. Interaction effects revealed that residents of smaller cities concentrated more on specific OTT types such as AVOD and AVOD+SVOD,AVOD+SVOD, leading to higher expenditures. While AVOD preference generally resulted in lower OTT expenditure, it increased with higher household OTT service usage. These results underscore the importance of considering both individual preferences and household environments in comprehending OTT consumption, providing a basis for developing customized media policies and content strategies.

A study on the Development of 3D web-map using VRML and java (Web-Map 개발을 위한 VRML과 Java의 적용)

  • 양인태;김동문;박형근
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.21 no.1
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    • pp.81-87
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    • 2003
  • It is very difficult assignment that grasp three-dimensional real life in Web base network environment. But, the recent simulation tools embody third dimension elements within 2 dimensions screen that is limited through third dimension implementation technology. Many GIS tools are offering excellent functions for third dimension data creation. But, research about design of third dimension GIS that use virtual reality technique in Web environment is status that is unprepared. So, in this research embodied third dimension topography map using virtual reality modelling language to produce active third dimension VR map that can supply visual information for direction, visual point that want in World Wide Web without support of expensive Map exclusive use program. And these 3D Web-Map is thought that possibility is enough as next generation map medium.