Search results for: panel data models

Authors: Basma Yassa

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Evidence on cash transfers’ effectiveness in mitigating macro and idiosyncratic shocks’ impacts has been mixed and is mostly concentrated in Latin America, Sub-Saharan Africa, and South Asia with very limited evidence from the MENA region. Yet conditional cash transfers schemes have been continually used, especially in Egypt, as the main social protection tool in response to the recent socioeconomic crises and macro shocks. We use 2 panel datasets and 1 cross-sectional dataset to estimate the effectiveness of cash transfers as a shock-mitigative mechanism in the Egyptian context. In this paper, the results from the different models (Panel Fixed Effects model and the Regression Discontinuity Design (RDD) model) confirm that micro and macro shocks lead to significant decline in several household-level welfare outcomes and that Takaful cash transfers have a significant positive impact in mitigating the negative shock impacts, especially on households’ debt incidence, debt levels, and asset ownership, but not necessarily on food, and non-food expenditure levels. The results indicate large positive significant effects on decreasing household incidence of debt by up to 12.4 percent and lowered the debt size by approximately 18 percent among Takaful beneficiaries compared to non-beneficiaries’. Similar evidence is found on asset ownership levels, as the RDD model shows significant positive effects on total asset ownership and productive asset ownership, but the model failed to detect positive impacts on per capita food and non-food expenditures. Further extensions are still in progress to compare the models’ results with the DID model results when using a nationally representative ELMPS panel data (2018/2024) rounds. Finally, our initial analysis suggests that conditional cash transfers are effective in buffering the negative shock impacts on certain welfare indicators even after successive macro-economic shocks in 2022 and 2023 in the Egyptian Context.

Keywords: cash transfers, fixed effects, household welfare, household debt, micro shocks, regression discontinuity design

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Yuchao Yao

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As two of the main characteristics of Chinese demographic trends, increasing divorce rates and decreasing fertility rates both shaped the population structure in the recent decade. Figuring out to what extent can be having a child make a difference in the divorce rate of a couple will not only draw a picture of Chinese families but also bring about a new perspective to evaluate the Chinese child-breeding policies. Based on China Family Panel Studies (CFPS) Data 2010-2018, this paper provides a systematic evaluation of how children influence a couple’s marital stability through a series of empirical models. Using survival analysis and propensity score matching (PSM) model, this paper finds that the number and age of children that a couple has mattered in consolidating marital relationship, and these effects vary little over time; during the last decade, newly having children can in fact decrease the possibility of divorce for Chinese couples; the such decreasing effect is largely due to the birth of a second child. As this is an inclusive attempt to study and compare not only the effects but also the causality of children on divorce risk in the last decade, the results of this research will do a good summary of the status quo of divorce in China. Furthermore, this paper provides implications for further reforming the current marriage and child-breeding policies.

Keywords: divorce risk, fertility, China, survival analysis, propensity score matching

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Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman

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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.

Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Myoung-Jin Lee, Sung-Jin Lee, Young-Kon Park, Jin-Wook Kim, Bo-Kyoung Kim, Song-Hun Chong, Sun-Ii Kim

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The ability to resist the shear strength arises mainly from the web panel of steel girders and as such, the shear buckling strength of these girders has been extensively investigated. For example, Blaser’s reported that when buckling occurs, the tension field has an effect after the buckling strength of the steel is reached. The findings of these studies have been applied by AASHTO, AISC, and to the European Code that provides guidelines for designs aimed at preventing shear buckling. Steel girders are susceptible to corrosion resulting from exposure to natural elements such as rainfall, humidity, and temperature. This corrosion leads to a reduction in the size of the web panel section, thereby resulting in a decrease in the shear strength. The decrease in the panel section has a significant effect on the maintenance section of the bridge. However, in most conventional designs, the influence of corrosion is overlooked during the calculation of the shear buckling strength and hence over-design is common. Therefore, in this study, a steel girder with an A/D of 1:1, as well as a 6-mm-, 16-mm-, and 12-mm-thick web panel, flange, and intermediate reinforcing material, respectively, were used. The total length was set to that (3200 mm) of the default model. The effect of corrosion shear buckling was investigated by determining the volume amount of corrosion, shape of the erosion patterns, and the angular change in the tensile field of the shear buckling strength. This study provides the basic data that will enable designs that incorporate values closer (than those used in most conventional designs) to the actual shear buckling strength.

Keywords: corrosion, shear buckling strength, steel girder, shear strength

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Authors: Liwiusz Wojciechowski

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Research background: The current knowledge does not give a clear answer to the question of the impact of FDI on productivity. Results of the empirical studies are still inconclusive, no matter how extensive and diverse in terms of research approaches or groups of countries analyzed they are. It should also take into account the possibility that FDI and productivity are linked and that there is a bidirectional relationship between them. This issue is particularly important because on one hand FDI can contribute to changes in productivity in the host country, but on the other hand its level and dynamics may imply that FDI should be undertaken in a given country. As already mentioned, a two-way relationship between the presence of foreign capital and productivity in the host country should be assumed, taking into consideration the endogenous nature of FDI. Purpose of the article: The overall objective of this study is to determine the causality between foreign direct investment and total factor productivity in host county in terms of different relative absorptive capacity across countries. In the classic sense causality among variables is not always obvious and requires for testing, which would facilitate proper specification of FDI models. The aim of this article is to study endogeneity of selected macroeconomic variables commonly being used in FDI models in case of Visegrad countries: main recipients of FDI in CEE. The findings may be helpful in determining the structure of the actual relationship between variables, in appropriate models estimation and in forecasting as well as economic policymaking. Methodology/methods: Panel and time-series data techniques including GMM estimator, VEC models and causality tests were utilized in this study. Findings & Value added: The obtained results allow to confirm the hypothesis states the bi-directional causality between FDI and total factor productivity. Although results differ from among countries and data level of aggregation implications may be useful for policymakers in case of providing foreign capital attracting policy.

Keywords: endogeneity, foreign direct investment, multi-equation models, total factor productivity

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Authors: Jonghae Park, Daesung Kim

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The impact of aggressive and conservative working capital‘s strategies on the value and profitability of the firms has been evaluated by applying the panel data regression analysis. The control variables used in the regression models are natural log of firm size, sales growth, and debt. We collected a panel of 13,988 companies listed on the Korea stock market covering the period 2000-2016. The major findings of this study are as follow: 1) We find a significant negative correlation between firm profitability and the number of days inventory (INV) and days accounts payable (AP). The firm’s profitability can also be improved by reducing the number of days of inventory and days accounts payable. 2) We also find a significant positive correlation between firm profitability and the number of days accounts receivable (AR) and cash ratios (CR). In other words, the cash is associated with high corporate profitability. 3) Tobin's analysis showed that only the number of days accounts receivable (AR) and cash ratios (CR) had a significant relationship. In conclusion, companies can increase profitability by reducing INV and increasing AP, but INV and AP did not affect corporate value. In particular, it is necessary to increase CA and decrease AR in order to increase Firm’s profitability and value.

Keywords: working capital, working capital management, firm value, profitability

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Authors: Balarabe Z. Ahmad, Anne-Lorène Vernay

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The emergence of electricity in Nigeria was dated back to 1896. The power plants have the potential to generate 12,522 MW of electric power. Whereas current dispatch is about 4,000 MW, access to electrification is about 60%, with consumption at 0.14 MWh/capita. The government embarked on energy reforms to mitigate energy poverty. The reform targeted the provision of electricity access to 75% of the population by 2020 and 90% by 2030. Growth of total electricity demand by a factor of 5 by 2035 had been projected. This means that Nigeria will require almost 530 TWh of electricity which can be delivered through generators with a capacity of 65 GW. Analogously, the geographical location of Nigeria has placed it in an advantageous position as the source of solar energy; the availability of a high sunshine belt is obvious in the country. The implication is that the far North, where energy poverty is high, equally has about twice the solar radiation as against southern Nigeria. Hence, the chance of generating solar electricity is 66% possible at 11850 x 103 GWh per year, which is one hundred times the current electricity consumption rate in the country. Harvesting these huge potentials may be a mirage if the entrepreneurs in the solar panel business are left with the conventional business models that are not uncertainty resilient. Currently, business entities in RE in Nigeria are uncertain of; accessing the national grid, purchasing potentials of cooperating organizations, currency fluctuation and interest rate increases. Uncertainties such as the security of projects and government policy are issues entrepreneurs must navigate to remain sustainable in the solar panel industry in Nigeria. The aim of this paper is to identify how entrepreneurial firms consider uncertainties in developing workable business models for commercializing solar energy projects in Nigeria. In an attempt to develop a novel business model, the paper investigated how entrepreneurial firms assess and navigate uncertainties. The roles of key stakeholders in helping entrepreneurs to manage uncertainties in the Nigeria RE sector were probed in the ongoing study. The study explored empirical uncertainties that are peculiar to RE entrepreneurs in Nigeria. A mixed-mode of research was embraced using qualitative data from face-to-face interviews conducted on the Solar Energy Entrepreneurs and the experts drawn from key stakeholders. Content analysis of the interview was done using Atlas. It is a nine qualitative tool. The result suggested that all stakeholders are required to synergize in developing an uncertainty resilient business model. It was opined that the RE entrepreneurs need modifications in the business recommendations encapsulated in the energy policy in Nigeria to strengthen their capability in delivering solar energy solutions to the yawning Nigerians.

Keywords: uncertainties, entrepreneurial, business model, solar-panel

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Authors: Nasiru Inuwa, Haruna Usman Modibbo, Yahya Zakari Abdullahi

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The purpose of this paper is to investigate the effects of foreign direct investment (FDI), economic growth on carbon emissions in context of WAIFEM member countries. The Im-Pesaran-Shin panel unit root test, Kao residual based test panel cointegration technique and panel Granger causality tests over the period 1980-2012 within a multivariate framework were applied. The results of cointegration test revealed a long run equilibrium relationship among CO2 emissions, economic growth and foreign direct investment. The results of Granger causality tests revealed a unidirectional causality running from economic growth to CO2 emissions for the panel of WAIFEM countries at the 5% level. Also, Granger causality runs from economic growth to foreign direct investment without feedback. However, no causality relationship between foreign direct investment and CO2 emissions for the panel of WAIFEM countries was observed. The study therefore, suggest that policy makers from WAIFEM member countries should design policies aim at attracting more foreign direct investments inflow as well the adoption of cleaner production technologies in order to reduce CO2 emissions.

Keywords: economic growth, CO2 emissions, causality, WAIFEM

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Authors: Louati Salma, Louhichi Awatef, Boujelbene Younes

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Analysis of the trade-off between competition and financial stability has been at the center of academic and policy debate for over two decades and especially since the 2007-2008 global financial crises. We use information on 10 OIC countries from 2005 to 2014 to investigate the influence of bank competition on individual bank stability and risk-taking. Alternatively, we explore whether the quality of prudential regulation may affect the nexus between competition and banking stability/risk-taking. We provide a particular attention to the Islamic banking system which principally involves with the Riba-free instruments as compared to the conventional interest-based system. We first run a dynamic panel regression (GMM), and then we apply a panel vector autoregressive (PVAR) methodology to compare both banking business models.

Keywords: Lerner index, Islamic banks, non-performing loans, prudential regulations, z-score

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

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The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

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Authors: S. Raja, K. M. Parammasivam, V. Aghilesh

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Fluid-structure interaction is a crucial consideration in the design of many engineering systems such as flight vehicles and bridges. Aircraft lifting surfaces and turbine blades can fail due to oscillations caused by fluid-structure interaction. Hence, it is focussed to study the fluid-structure interaction in the present research. First, the effect of free vibration over the panel is studied. It is well known that the deformation of a panel and flow induced forces affects one another. The selected panel has a span 300mm, chord 300mm and thickness 2 mm. The project is to study, the effect of cross-sectional area and the stiffener location is carried out for the same panel. The stiffener spacing is varied along both the chordwise and span-wise direction. Then for that optimal location the ideal stiffener length is identified. The effect of stiffener cross-section shapes (T, I, Hat, Z) over flutter velocity has been conducted. The flutter velocities of the selected panel with two rectangular stiffeners of cantilever configuration are estimated using MSC NASTRAN software package. As the flow passes over the panel, deformation takes place which further changes the flow structure over it. With increasing velocity, the deformation goes on increasing, but the stiffness of the system tries to dampen the excitation and maintain equilibrium. But beyond a critical velocity, the system damping suddenly becomes ineffective, so it loses its equilibrium. This estimated in NASTRAN using PK method. The first 10 modal frequencies of a simple panel and stiffened panel are estimated numerically and are validated with open literature. A grid independence study is also carried out and the modal frequency values remain the same for element lengths less than 20 mm. The current investigation concludes that the span-wise stiffener placement is more effective than the chord-wise placement. The maximum flutter velocity achieved for chord-wise placement is 204 m/s while for a span-wise arrangement it is augmented to 963 m/s for the stiffeners location of ¼ and ¾ of the chord from the panel edge (50% of chord from either side of the mid-chord line). The flutter velocity is directly proportional to the stiffener cross-sectional area. A significant increment in flutter velocity from 218m/s to 1024m/s is observed for the stiffener lengths varying from 50% to 60% of the span. The maximum flutter velocity above Mach 3 is achieved. It is also observed that for a stiffened panel, the full effect of stiffener can be achieved only when the stiffener end is clamped. Stiffeners with Z cross section incremented the flutter velocity from 142m/s (Panel with no stiffener) to 328 m/s, which is 2.3 times that of simple panel.

Keywords: stiffener placement, stiffener cross-sectional area, stiffener length, stiffener cross sectional area shape

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Authors: Ozan Kahraman, Hao Feng

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Several models such as Weibull, Modified Gompertz, Biphasic linear, and Log-logistic models have been proposed in order to describe non-linear inactivation kinetics and used to fit non-linear inactivation data of several microorganisms for inactivation by heat, high pressure processing or pulsed electric field. First-order kinetic parameters (D-values and z-values) have often been used in order to identify microbial inactivation by non-thermal processing methods such as ultrasound. Most ultrasonic inactivation studies employed first-order kinetic parameters (D-values and z-values) in order to describe the reduction on microbial survival count. This study was conducted to analyze the E. coli O157:H7 inactivation data by using five microbial survival models (First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic). First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic kinetic models were used for fitting inactivation curves of Escherichia coli O157:H7. The residual sum of squares and the total sum of squares criteria were used to evaluate the models. The statistical indices of the kinetic models were used to fit inactivation data for E. coli O157:H7 by MTS at three temperatures (40, 50, and 60 0C) and three pressures (100, 200, and 300 kPa). Based on the statistical indices and visual observations, the Weibull and Biphasic models were best fitting of the data for MTS treatment as shown by high R2 values. The non-linear kinetic models, including the Modified Gompertz, First-order, and Log-logistic models did not provide any better fit to data from MTS compared the Weibull and Biphasic models. It was observed that the data found in this study did not follow the first-order kinetics. It is possibly because of the cells which are sensitive to ultrasound treatment were inactivated first, resulting in a fast inactivation period, while those resistant to ultrasound were killed slowly. The Weibull and biphasic models were found as more flexible in order to determine the survival curves of E. coli O157:H7 treated by MTS on apple-carrot juice.

Keywords: Weibull, Biphasic, MTS, kinetic models, E.coli O157:H7

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Authors: Avichal Malhotra, Jerome Frisch, Christoph van Treeck

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The utilization of semantic, cadastral and topological data from geographic information systems (GIS) has exponentially increased for building and urban-scale energy performance simulations. Urban planners, simulation scientists, and researchers use virtual 3D city models for energy analysis, algorithms and simulation tools. For dynamic energy simulations at city and district level, this paper provides an overview of the available GIS data models and their levels of detail. Adhering to different norms and standards, these models also intend to describe building and construction industry data. For further investigations, CityGML data models are considered for simulations. Though geographical information modelling has considerably many different implementations, extensions of virtual city data can also be made for domain specific applications. Highlighting the use of the extended CityGML models for energy researches, a brief introduction to the Energy Application Domain Extension (ADE) along with its significance is made. Consequently, addressing specific input simulation data, a workflow using Modelica underlining the usage of GIS information and the quantification of its significance over annual heating energy demand is presented in this paper.

Keywords: CityGML, EnergyADE, energy performance simulation, GIS

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Authors: Barbara Gronostajska

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Currently, housing conditions of buildings executed in large panel technology are deteriorating. The article presents modernization solutions implemented throughout the variety of architectural activities (adding of balconies and staircases, connecting apartments) which guarantee very intriguing results that meet the needs and expectations of the modern society.

Keywords: housing estate, apartments, flats, modernization, plate blocks

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Authors: Mouldi Djelassi, Jamel Boukhatem

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Background: A relation has been established between Islamic banks' activities and interest rates. The aim of this study was to explore the impact of interest rates on the deposits and loans held by Islamic and conventional banks in Saudi Arabia. Methods: A time series data was performed over the period 2008Q1-2020Q2 on eight conventional banks and four Islamic banks. The impacts of interest rate shocks on deposits and loans were identified through panel vector autoregressive models. Results: Impulse response function analysis showed that increasing interest rates reduce loans and conventional deposits. For Islamic banks, deposits are more affected by interest rates than lending. Variance decomposition analysis revealed that deposits contribute to 61% of the Islamic financing variation and only 25% of the conventional loans. Conclusion: Interest rates impacted Islamic banks especially through deposits, which is inconsistent with the theoretical framework. Islamic deposits played an important role in Islamic financing variation and may provide to be a channel for the transmission of the monetary policy in a dual banking system. Monetary policy in Saudi Arabia works in part through “credits” (conventional bank credits) as well as through “money” (conventional and Islamic bank deposits).

Keywords: Islamic banking, interest rates, monetary policy transmission, panel VAR

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Authors: Zahid Ahmad, Nauman Ali

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This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: Haowei Lu, Anaya Aaron

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Understanding historical solar generation and forecasting future solar generation from interconnected Distributed Energy Resources (DER) is crucial for utility planning and interconnection studies. The existing methodology, which relies on solar radiation, weather data, and common inverter models, is becoming less accurate. Rapid advancements in DER technologies have resulted in more diverse project sites, deviating from common patterns due to various factors such as DC/AC ratio, solar panel performance, tilt angle, and the presence of DC-coupled battery energy storage systems. In this paper, the authors review 10,000 DER projects within the system and analyze the Advanced Metering Infrastructure (AMI) data for various types to demonstrate the impact of different parameters. An updated methodology is proposed for redefining historical and future solar generation in distribution feeders.

Keywords: photovoltaic system, solar energy, fluctuations, energy storage, uncertainty

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

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Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel

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Authors: Kashif Nesar Rather, Mantu Kumar Mahalik

Abstract:

The discourse surrounding climate change has gained considerable traction, with a discernible emphasis on its nuanced and consequential impact on gender inequality. Concurrently, escalating global tensions are contributing to heightened uncertainty, potentially exerting influence on gender disparities. Within this framework, this study attempts to empirically investigate the implications of climate change and world uncertainty on the gender inequality for a balanced panel of 100 economies between 1995 to 2021. The estimated models also control for the effects of globalisation, economic growth, and education expenditure. The panel cointegration tests establish a significant long-run relationship between the variables of the study. Furthermore, the PMG-ARDL (Panel mean group-Autoregressive distributed lag model) estimation technique confirms that both climate change and world uncertainty perpetuate the global gender inequalities. Additionally, the results establish that globalisation, economic growth, and education expenditure exert a mitigating influence on gender inequality, signifying their role in diminishing gender disparities. These findings are further confirmed by the FGLS (Feasible Generalized Least Squares) and DKSE (Driscoll-Kraay Standard Errors) regression methods. Potential policy implications for mitigating the detrimental gender ramifications stemming from climate change and rising world uncertainties are also discussed.

Keywords: gender inequality, world uncertainty, climate change, globalisation., ecological footprint

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Authors: Yanqi Yang, Chongshan Liao, Cheuk Hin Ho, Susan Bridges

Abstract:

Aim: To investigate student’s perceptions of using e-models in an inquiry-based curriculum. Approach: 52 second-year dental students completed a pre- and post-test questionnaire relating to their perceptions of e-models and their use in inquiry-based learning. The pre-test occurred prior to any learning with e-models. The follow-up survey was conducted after one year's experience of using e-models. Results: There was no significant difference between the two sets of questionnaires regarding student’s perceptions of the usefulness of e-models and their willingness to use e-models in future inquiry-based learning. Most of the students preferred using both plaster models and e-models in tandem. Conclusion: Students did not change their attitude towards e-models and most of them agreed or were neutral that e-models are useful in inquiry-based learning. Whilst recognizing the utility of 3D models for learning, student's preference for combining these with solid models has implications for the development of haptic sensibility in an operative discipline.

Keywords: e-models, inquiry-based curriculum, education, questionnaire

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Authors: Mina Mortazavi, Hamid Ronagh, Pezhman Sharafi

Abstract:

The new concept of a cold formed-hot rolled hybrid steel wall panel system is introduced to overcome the deficiency in lateral load resisting capacity of cold-formed steel structures. The hybrid system is composed of a cold-formed steel part laterally connected to hot rolled part. The hot rolled steel part is responsible for carrying the whole lateral load; while the cold formed steel part is only required to transfer the lateral load to the hot rolled part without any local failure. The vertical load is beared by both hot rolled, and cold formed steel part, proportionally. In order to investigate the lateral performance of the proposed system, it should be tested under simultaneous lateral and vertical load. The main concern is to deliver the loads to each part during the test to simulate the real load distribution in the structure. In this paper, a detailed description of the proposed wall panel system and the designed testing rig is provided.

Keywords: cold-formed steel, hybrid system, wall panel system, testing rig design

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Authors: Annop Jaewisorn

Abstract:

This study explores the relationship between natural disasters and inequalities -both income and expenditure inequality- at a micro-level of Thailand as the first study of this nature for this country. The analysis uses a unique panel and remote-sensing dataset constructed for the purpose of this research. It contains provincial inequality measures and other economic and social indicators based on the Thailand Household Survey during the period between 1992 and 2019. Meanwhile, the data on natural disasters, which are remote-sensing data, are received from several official geophysical or meteorological databases. Employing a panel fixed effects, the results show that natural disasters significantly reduce household income and expenditure inequality as measured by the Gini index, implying that rich people in Thailand bear a higher cost of natural disasters when compared to poor people. The effect on income inequality is mainly driven by droughts, while the effect on expenditure inequality is mainly driven by flood events. The results are robust across heterogeneity of the samples, lagged effects, outliers, and an alternative inequality measure.

Keywords: inequality, natural disasters, remote-sensing data, Thailand

Procedia PDF Downloads 118