• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.533-543
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• 2021

This study aims to determine and analyze the effect of social shopping, adventure shopping, value shopping, relaxation shopping, and idea shopping in influencing impulsive online buying behavior moderated by scarcity and serendipity information. The research method used is the quantitative research paradigm using surveys as a medium to obtain primary data. The paper examines the theoretical research model and tested fifteen hypotheses. The questionnaire was developed based on indicators from previous research. A non-probability sampling framework is used in this study. The data collection method uses electronic and online questionnaires to collect primary data with a total sample of 330 taken with the criteria of having made transactions in e-commerce Shopee in the last three months. Data analysis tools using Structural Equation Modelling (SEM) approach. The results showed that 8 out of 15 hypotheses were accepted and supported. The results show that there is a relationship between the value of hedonic shopping, scarcity, and serendipity information on impulsive online buying behavior. Therefore, analyzing the needs of customers, optimizing customer satisfaction, service excellence, website quality, and the ease of use of e-shopping itself especially in the e-commerce industry should be taken seriously nowadays.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3888-3896
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• 2022

Nuclear data is the basis of reactor physics analysis. This paper aim at studying the influence of major evaluated nuclear data libraries, CENDL-3.2, ENDF/B-VIII.0, JEFF-3.3, and JENDL-4.0u, on the neutronics modelling of CEFR start-up tests. Results show these four libraries have a good performance and consistency in the modelling CEFR start-up tests. The JEFF-3.3 results exhibit only an 8 pcm k_eff difference with the measurement. The difference in criticality is decomposed by nuclide, which shows the large overestimation of CENDL-3.2 is mainly from the cross-section of ⁵²Cr. Except for few cases, the calculation results are within 1σ of measurement uncertainty in control rod worth, sodium void reactivity, temperature reactivity, and subassembly swap reactivity. In the evaluation of axial and radial reaction distribution, there are about 65% of relative errors that are less than 5% and 82% of relative errors that are less than 10%.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.246-251
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• 2007

The purpose of this study is to develop a grid based model for calculating the critical nonpoint source (NPS) pollution load (BOD, TN, TP) in Nak-dong area in South Korea. In the last two decades, NPS pollution has become a topic for research that resulted in the development of numerous modeling techniques. Watershed researchers need to be able to emphasis on the characterization of water quality, including NPS pollution loads estimates. Geographic Information System (GIS) has been designed for the assessment of NPS pollution in a watershed. It uses different data such as DEM, precipitation, stream network, discharge, and land use data sets and utilizes a grid representation of a watershed for the approximation of average annual pollution loads and concentrations. The difficulty in traditional NPS modeling is the problem of identifying sources and quantifying the loads. This research is intended to investigate the correlation of NPS pollution concentrations with land uses in a watershed by calculating Expected Mean Concentrations (EMC). This work was accomplished using a grid based modelling technique that encompasses three stages. The first step includes estimating runoff grid by means of the precipitation grid and runoff coefficient. The second step is deriving the gird based model for calculating NPS pollution loads. The last step is validating the gird based model with traditional pollution loads calculation by applying statistical t-test method. The results on real data, illustrate the merits of the grid based modelling approach. Therefore, this model investigates a method of estimating and simulating point loads along with the spatially distributed NPS pollution loads. The pollutant concentration from local runoff is supposed to be directly related to land use in the region and is not considered to vary from event to event or within areas of similar land uses. By consideration of this point, it is anticipated that a single mean estimated pollutant concentration is assigned to all land uses rather than taking into account unique concentrations for different soil types, crops, and so on.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.995-1004
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• 2007

In this paper, we analyse online word-of-mouth and Korean box-office sales data based on kernel regression method. To do this, we consider the regression model with mixed-data and apply the least square cross-validation method proposed by Li and Racine (2004) to the model. We found the box-office sales can be explained by volume of online word-of-mouth and the characteristics of the movies.

• Asia pacific journal of information systems
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• v.4 no.1
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• pp.115-138
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• 1994

Current database systems are based on the assumption that a datum denotes the same meaning; however, in reality, the violation of this assumption is not unusual. Some data are created in such a way that they represent different sets of attribute values. The current research formulates this phenomenon as dissimilarities of derivation rules and defines multi-derived data as ones that are derived by multiple rules. For multi- derived data, this research proposes a new retrieval scheme and analyze its implication with relation to data retrieval.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Earthquakes and Structures
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• v.12 no.3
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• pp.359-374
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• 2017

The seismic events in Northern Italy, May 2012, have revealed the seismic vulnerability of typical Italian precast industrial buildings. The aim of this paper is to present a seismic fragility model for Italian RC precast buildings, to be used in earthquake loss estimation and seismic risk assessment by comparing two building typologies and three different codes: D.M. 3-03-1975, D.M. 16-01-1996 and current Italian building code that has been released in 2008. Based on geometric characteristics and design procedure applied, ten different building classes were identified. A Monte Carlo simulation was performed for each building class in order to generate the building stock used for the development of fragility curves trough analytical method. The probabilistic distributions of geometry were mainly obtained from data collected from 650 field surveys, while the material properties were deduced from the code in place at the time of construction or from expert opinion. The structures were modelled in 2D frameworks; since the past seismic events have identified the beam-column connection as the weakest element of precast buildings, two different modelling solutions were adopted to develop fragility curves: a simple model with post processing required to detect connection collapse and an innovative modelling solution able to reproduce the real behaviour of the connection during the analysis. Fragility curves were derived using both nonlinear static and dynamic analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4759-4780
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• 2017

Full Dimension multiple input multiple output (FD-MIMO) architecture employs a planar array design at the Base Station (BS) to provide high order multi-user MIMO (MU-MIMO) via simultaneous data transmission to large number of users. With FD-MIMO, the BS can also adjust the beam direction in both elevation and azimuth direction to concentrate the energy on the user of interests while minimizing the interference leakage to co-scheduled users in the same cell or users in the neighboring cells. In a typical highly populated macrocell environment, modelling the elevation angular characteristics of three-dimensional (3D) channel is critical to understanding the performance limits of the FD-MIMO system. In this paper, we study the throughput performance of FD-MIMO system with varying elevation angular spread and inter-element spacing using a 3D spatial channel model. Our results show that for a typical urban scenario, horizontal beamforming with correlated antenna spacing achieves optimal performance but by restricting the spread of elevation angles of departure, elevation beamforming achieves high array gain with wide inter-element spacing. We also realize significant gains due to spatial array processing via modelling the elevation domain and varying the inter-element spacing for both the transmitter and receiver.

• Advances in aircraft and spacecraft science
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• v.5 no.2
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• pp.205-223
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• 2018

During launch a spacecraft is subjected to a variety of dynamical loads transmitted through the launcher to spacecraft interface or air-born transmission excitations in the acoustic pressure field inside the fairing. As a result, spacecraft are tested on ground to ensure and demonstrate the global integrity of the structure against these loads, to screen the flight hardware for quality of workmanship and to validate mathematical models. This paper addresses the numerical modelling and simulation of the low frequency sine and random vibration tests performed on electrodynamic shaker facilities to comprise the mechanical-borne transmission loads through the launcher to spacecraft interface. Consequently, the paper reviews techniques and methodologies to derive a reliable and representative coupled virtual vibration testing simulation environment based on experimental data. These technologies are explored with the main objectives to ensure a stable, reliable and accurate control while testing. As a result, the use of the derived simulation models in combination with the added value of improved control and signal processing algorithms can lead to a safer and smoother vibration test control of the entire environmental test campaign.

• Journal of Distribution Science
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• v.14 no.2
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• pp.5-12
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• 2016

Purpose - The present study examines the interrelationship between various components constituting shopping experience in the context of the Indian shopping malls. Research design, data, and methodology - Extracting components of shopping experience from the literature review, the study used Interpretive Structural Modelling (ISM) to propose a conceptual model. The study adopted a mixed methods research involving theoretical constructs from past research, qualitative assessment of relationship between the constructs and imposing definite order and direction to qualitative relations based on mathematical computations. Results - Proposed model indicates that the five components of shopping experience (ambience, physical infrastructure, convenience, marketing focus and safety and security) do not converge directly into shopping experience. Rather, they operate following a hierarchy of influences in which marketing focus plays the role of the initiator. Conclusions - This model points at the order of preference of different components of shopping experience and can be a useful guide for retail industry, especially mall developers and supermarket/hypermarket, may use the findings in key decisions about development of physical infrastructure, which are based on marketing focus.