Search results for: general linear regression model

Authors: Rajinder Singh, Ram Valluru

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Chain Ladder (CL) method, Expected Loss Ratio (ELR) method and Bornhuetter-Ferguson (BF) method, in addition to more complex transition-rate modeling, are commonly used actuarial reserving methods in general insurance. There is limited published research about their relative performance in the context of Mortgage Insurance (MI). In our experience, these traditional techniques pose unique challenges and do not provide stable claim estimates for medium to longer term liabilities. The relative strengths and weaknesses among various alternative approaches revolve around: stability in the recent loss development pattern, sufficiency and reliability of loss development data, and agreement/disagreement between reported losses to date and ultimate loss estimate. CL method results in volatile reserve estimates, especially for accident periods with little development experience. The ELR method breaks down especially when ultimate loss ratios are not stable and predictable. While the BF method provides a good tradeoff between the loss development approach (CL) and ELR, the approach generates claim development and ultimate reserves that are disconnected from the ever-to-date (ETD) development experience for some accident years that have more development experience. Further, BF is based on subjective a priori assumption. The fundamental shortcoming of these methods is their inability to model exogenous factors, like the economy, which impact various cohorts at the same chronological time but at staggered points along their life-time development. This paper proposes an alternative approach of parametrizing the loss development curve and using logistic regression to generate the ultimate loss estimate for each homogeneous group (accident year or delinquency period). The methodology was tested on an actual MI claim development dataset where various cohorts followed a sigmoidal trend, but levels varied substantially depending upon the economic and operational conditions during the development period spanning over many years. The proposed approach provides the ability to indirectly incorporate such exogenous factors and produce more stable loss forecasts for reserving purposes as compared to the traditional CL and BF methods.

Keywords: actuarial loss reserving techniques, logistic regression, parametric function, volatility

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Authors: Shlomit Hon-Snir, Sharon Teitler-Regev, Anabel Lifszyc Friedlander

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Tourism, one of the world's largest and fastest growing industries, exerts a major economic influence. The number of international tourists is growing every year, and the relative portion of independent (FIT) tourists is growing as well. The characteristics of independent tourists differ from those of tourists who travel in organized trips. The purpose of the research is to identify the factors that affect the individual tourist's expenses in Israel: total expenses, expenses per day, expenses per tourist, expenses per day per tourist, accommodation expenses, dining expenses and transportation expenses. Most of the research analyzed the total expenses using OLS regression. The determinants influencing expenses were divided into four groups: budget constraints, socio-demographic data, psychological characteristics and travel-related characteristics. Since the effect of each variable may change over different levels of total expenses the quantile regression (QR) theory will be applied. The current research will use data collected by the Israeli Ministry of Tourism in 2015 from individual independent tourists at the end of their visit to Israel. Preliminary results show that: At lower levels of expense, only income has a (positive) effect on total expenses, while at higher levels of expense, both income and length of stay have (positive) effects. -The effect of income on total expenses is higher for higher levels of expenses than for lower level of expenses. -The number of sites visited during the trip has a (negative) effect on tourist accommodation expenses only for tourists with a high level of total expenses. Due to the increasing share of independent tourism in Israel and around the world and due to the importance of tourism to Israel, it is very important to understand the factors that influence the expenses and behavior of independent tourists. Understanding the factors that affect independent tourists' expenses in Israel can help Israeli policymakers in their promotional efforts to attract tourism to Israel.

Keywords: independent tourist, quantile regression theory, tourism expenses, tourism

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Authors: Rashmi Dubey

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The study aims at investigating the onset of thermal convection in an inclined porous layer saturated with a non-Newtonian fluid. The layer is infinitely extended and has a finite width confined between two boundaries with constant pressure conditions, where the lower one is maintained at a higher temperature. Over the years, this area of research has attracted many scientists and researchers, for it has a plethora of applications in the fields of sciences and engineering, such as in civil engineering, geothermal sites, petroleum industries, etc.Considering the possibilities in a practical scenario, an inclined porous layer is considered, which can be used to develop a generalized model applicable to any inclination. Using the isobaric boundaries, the hydrodynamic boundary conditions are derived for the power-law model and are used to obtain the basic state flow. The convection in the basic state flow is driven by the thermal buoyancy in the flow system and is carried away further due to hydrodynamic boundaries. A linear stability analysis followed by a normal-mode analysis is done to investigate the onset of convection in the buoyancy-driven flow. The analysis shows that the convective instability is always initiated by the non-traveling modes for the Newtonian fluid, but prevails in the form of oscillatory modes, for up to a certain inclination of the porous layer. However, different behavior is observed for the dilatant and pseudoplastic fluids.

Keywords: thermal convection, linear stability, porous media flow, Inclined porous layer

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Authors: Mahlet Nigussie Worku

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The main purpose of this study was to examine the effects of different leadership styles on employee engagement in Ethiopian Airlines headquarters located in Addis Ababa. Specific objectives of the study were stated to examine the effects of five leadership styles, namely transformational, transactional, democratic, lassies fair and autocratic leadership styles on employees’ engagement. The study was conducted on 288 sample sizes, and a simple random sampling technique was employed. The quantitative findings were presented and analyzed by table, ANOVA, bivariate correlation and regression model through SPSS software version 23. Out of 288 total distributed questionnaires, 280 were returned, and 8 of the returned were rejected due to missing data, while the remaining 280 responses were used for data analysis. Data was analyzed using the Statistical Package for Social Sciences (SPSS). The study employed both descriptive and explanatory research design. Correlation and regression were used to analyze the relationship and its effect between leadership Style and employee engagement. The regression results showed that transformational, transactional and democratic leadership Styles have significant contributions to employee engagement. Similarly, the transformational, transactional land democratic leadership style had a positive and strong correlation with employee engagement. However, lassies-fair and autocratic leadership styles showed a negative and insignificant effect on employee engagement. Finally, based on the findings, workable recommendations and implications for further studies were forwarded.

Keywords: leadership, autocratic leadership style, democratic leadership style, employee engagement

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

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Thiophene sulfur compounds' removal from diesel oil by batch adsorption process using commercial powdered activated carbon was designed and optimized in two-level factorial design method. This design analysis was used to find out the effects of operating parameters directing the adsorption process, such as amount of adsorbent, temperature and stirring time. The desulfurization efficiency was considered the response or output variable. Results showed that the stirring time had the largest effects on sulfur removal efficiency as compared with other operating parameters and their interactions under the experimental ranges studied. A regression model was generated to observe the closeness between predicted and experimental values. The three-dimensional plots and contour plots of main factors were generated according to the regression results to observe the optimal points.

Keywords: activated carbon, adsorptive desulfurization, factorial design, process optimization

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Authors: Miguel Mariano Rivera Galvan

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The purpose of this research was to create a digital tool by which users can obtain an immediate and accurate solution of the angular characteristics of an irregular quadrilateral. The development of this project arose because of the frequent absence of a polygon’s geometric information in land ownership accreditation documents. The researcher created a mathematical model using a linear approximation iterative method, employing various disciplines and techniques including trigonometry, geometry, algebra, and topography. This mathematical model uses as input data the surface of the quadrilateral, as well as the length of its sides, to obtain its interior angles and make possible its representation in a coordinate system. The results are as accurate and reliable as the user requires, offering the possibility of using this tool as a support to develop future engineering and architecture projects quickly and reliably.

Keywords: digital tool, geometry, mathematical model, quadrilateral, solution

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Authors: Prashant G. Metri

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A numerical model is developed to study nano liquid film flow over an unsteady stretching sheet in the presence of hydromagnetic have been investigated. Similarity transformations are used to convert unsteady boundary layer equations to a system of non-linear ordinary differential equations. The resulting non-linear ordinary differential equations are solved numerically using Runge-Kutta-Fehlberg and Newton-Raphson schemes. A relationship between film thickness β and the unsteadiness parameter S is found, the effect of unsteadiness parameter S, and the hydromagnetic parameter S, on the velocity and temperature distributions are presented. The present analysis shows that the combined effect of magnetic field and viscous dissipation has a significant influence in controlling the dynamics of the considered problem. Comparison with known results for certain particular cases is in excellent agreement.

Keywords: boundary layer flow, nanoliquid, thin film, unsteady stretching sheet

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Authors: Liaquat Ahmad, Muhammad Aslam, Muhammad Azam

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In this article, we propose a control chart based on repetitive group sampling scheme for the location parameter. This charting scheme is based on the regression estimator; an estimator that capitalize the relationship between the variables of interest to provide more sensitive control than the commonly used individual variables. The control limit coefficients have been estimated for different sample sizes for less and highly correlated variables. The monitoring of the production process is constructed by adopting the procedure of the Shewhart’s x-bar control chart. Its performance is verified by the average run length calculations when the shift occurs in the average value of the estimator. It has been observed that the less correlated variables have rapid false alarm rate.

Keywords: average run length, control charts, process shift, regression estimators, repetitive group sampling

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Authors: Aid Abdelkrim

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A method of fatigue damage accumulation based upon application of energy parameters of the fatigue process is proposed in the paper. Using this model is simple, it has no parameter to be determined, it requires only the knowledge of the curve W–N (W: strain energy density N: number of cycles at failure) determined from the experimental Wöhler curve. To examine the performance of nonlinear models proposed in the estimation of fatigue damage and fatigue life of components under random loading, a batch of specimens made of 6082 T 6 aluminium alloy has been studied and some of the results are reported in the present paper. The paper describes an algorithm and suggests a fatigue cumulative damage model, especially when random loading is considered. This work contains the results of uni-axial random load fatigue tests with different mean and amplitude values performed on 6082T6 aluminium alloy specimens. The proposed model has been formulated to take into account the damage evolution at different load levels and it allows the effect of the loading sequence to be included by means of a recurrence formula derived for multilevel loading, considering complex load sequences. It is concluded that a ‘damaged stress interaction damage rule’ proposed here allows a better fatigue damage prediction than the widely used Palmgren–Miner rule, and a formula derived in random fatigue could be used to predict the fatigue damage and fatigue lifetime very easily. The results obtained by the model are compared with the experimental results and those calculated by the most fatigue damage model used in fatigue (Miner’s model). The comparison shows that the proposed model, presents a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner’s model.

Keywords: damage accumulation, energy model, damage indicator, variable loading, random loading

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Authors: Adil A. Mohammed, Seif-Eddeen K. Fateen, Tamer S. Ahmed, Tarek M. Moustafa

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Falling film were widely used for gas-liquid absorption and reaction process. Modeling of falling film for oligomerization of ethylene reaction to linear alpha olefins is developed. Although there are many researchers discuss modeling of falling film in many processes, there has been no publish study the simulation of falling film for the oligomerization of ethylene reaction to produce linear alpha olefins. The Comsol multiphysics software was used to simulate the mass transfer with chemical reaction in falling film absorption process. The effect of concentration profile absorption of the products through falling thickness is discussed. The effect of catalyst concentration, catalyst/co-catalyst ratio, and temperature is also studied. For the effect of the temperature, as it increase the concentration of C4 increase. For catalyst concentration and catalyst/co-catalyst ratio as they increases the concentration of C4 increases, till it reached almost constant value.

Keywords: falling film, oligomerization, comsol mutiphysics, linear alpha olefins

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Authors: Libena Cernohorska

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The goal of this paper is to specify factors influencing the profitability of selected banks. Next, a model will be created to help establish variables that have a demonstrable influence on the development of the selected banks' profitability ratios. Czech banks and their international parent companies were selected for analyzing profitability. Banks categorized as large banks (according to the Czech National Bank's system, which ranks banks according to balance sheet total) were selected to represent the Czech banks. Two ratios, the return on assets ratio (ROA) and the return on equity ratio (ROE) are used to assess bank profitability. Six endogenous and four external indicators were selected from among other factors that influence bank profitability. The data analyzed were for the years 2001 – 2013. First, correlation analysis, which was supposed to eliminate correlated values, was conducted. A large number of correlated values were established on the basis of this analysis. The strongly correlated values were omitted. Despite this, the subsequent regression analysis of profitability for the individual banks that were selected did not confirm that the selected variables influenced their profitability. The studied factors' influence on bank profitability was demonstrated only for Československá Obchodní Banka and Société Générale using regression analysis. For Československá Obchodní Banka, it was demonstrated that inflation level and the amount of the central bank's interest rate influenced the return on assets ratio and that capital adequacy and market concentration influenced the return on equity ratio for Société Générale.

Keywords: banks, profitability, regression analysis, ROA, ROE

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Aminu Hamza

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This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

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Authors: Mahlet Nigussie Worku

Abstract:

The main purpose of this study was to examine the effects of different leadership styles on employee engagement in Ethiopian Airlines head quarter located in Addis Ababa. Specific objectives of the study were stated to examine the effects of five leadership styles namely transformational, transactional, democratic, lassies fair and autocratic leadership styles on employees’ engagement. The study was conducted on 288 sample size and a simple random sampling technique was employed. The quantitative findings were presented and analyzed by table, ANOVA, bivariate correlation and regression model through SPSS software version 23. Out of 288 total distributed questionnaires 280 were returned and 8 of the returned were rejected due to missing data while the remaining 280 responses were used for data analysis. Data was analyzed using the Statistical Package for Social Sciences (SPSS). The study employed both descriptive and explanatory research design. Correlation and regression were used to analyze the relationship and its effect between leadership Style and employee’s engagement. The regression results showed that transformational, transactional and democratic leadership Styles have significant contribution for employee’s engagement. Similarly transformational, transactional land democratic leadership style had a positive and strong correlation with employee’s engagement. However lassies-fair and autocratic leadership style showed negative and insignificant effect on employee engagement. Finally, based on the findings, workable recommendations and implications for further studies were forwarded

Keywords: leadership, leadership style, employee engagement, autocratic leadership styles

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Authors: Devina Aprilia Gunawan, Tasya Aspiranti, Inugrah Ratia Pratiwi

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This research aims to classify the mining sector companies based on Altman’s Z-score model, and providing an analysis based on the Altman’s Z-score model’s financial ratios to provide a picture about the financial condition in mining sector companies in Indonesia and their viability in the future, and to find out the partial and simultaneous impact of each of the financial ratio variables in the Altman’s Z-score model, namely (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), toward the financial condition represented by the Z-score itself. Among 38 mining sector companies listed in Indonesia Stock Exchange (IDX), 28 companies are selected as research sample according to the purposive sampling criteria.The results of this research showed that during 3 years research period at 2010-2012, the amount of the companies that was predicted to be healthy in each year was less than half of the total sample companies and not even reach up to 50%. The multiple regression analysis result showed that all of the research hypotheses are accepted, which means that (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), both partially and simultaneously had an impact towards company’s financial condition.

Keywords: Altman’s Z-score model, financial condition, mining companies, Indonesia

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Saeedeh Ahmadi Basir, Mohammad Mahdavi Mazdeh, Mohammad Namakshenas

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Manufacturers often dispatch jobs in batches to reduce delivery costs. However, sending several jobs in batches can have a negative effect on other scheduling-related objective functions such as minimizing the number of tardy jobs which is often used to rate managers’ performance in many manufacturing environments. This paper aims to minimize the number of weighted tardy jobs and the sum of delivery costs of a two-stage assembly flow-shop problem in a batch delivery system. We present a mixed-integer linear programming (MILP) model to solve the problem. As this is an MILP model, the commercial solver (the CPLEX solver) is not guaranteed to find the optimal solution for large-size problems at a reasonable amount of time. We present several numerical examples to confirm the accuracy of the model.

Keywords: scheduling, two-stage assembly flow-shop, tardy jobs, batched delivery system

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Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

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Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B10’s large neutron capture cross section. The B10 has an effective neutron capture cross section suitable for low energy neutrons ranging from 10-5 to 104 eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm3. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: boron nitride nanotube, radiation shielding, young modulus, atomistic modeling

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Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: Marco Furinghetti, Alberto Pavese, Michele Rinaldi

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Concave Surface Slider devices have been more and more used in real applications for seismic protection of both bridge and building structures. Several research activities have been carried out, in order to investigate the lateral response of such a typology of devices, and a reasonably high level of knowledge has been reached. If radial analysis is performed, the frictional force is always aligned with respect to the restoring force, whereas under bidirectional seismic events, a bi-axial interaction of the directions of motion occurs, due to the step-wise projection of the main frictional force, which is assumed to be aligned to the trajectory of the isolator. Nonetheless, if non-linear time history analyses have to be performed, standard codes provide precise rules for the definition of an averagely spectrum-compatible set of accelerograms in radial conditions, whereas for bidirectional motions different combinations of the single components spectra can be found. Moreover, nowadays software for the adjustment of natural accelerograms are available, which lead to a higher quality of spectrum-compatibility and to a smaller dispersion of results for radial motions. In this endeavor a simplified design procedure is defined, for building structures, base-isolated by means of Concave Surface Slider devices. Different case study structures have been analyzed. In a first stage, the capacity curve has been computed, by means of non-linear static analyses on the fixed-base structures: inelastic fiber elements have been adopted and different direction angles of lateral forces have been studied. Thanks to these results, a linear elastic Finite Element Model has been defined, characterized by the same global stiffness of the linear elastic branch of the non-linear capacity curve. Then, non-linear time history analyses have been performed on the base-isolated structures, by applying seven bidirectional seismic events. The spectrum-compatibility of bidirectional earthquakes has been studied, by considering different combinations of single components and adjusting single records: thanks to the proposed procedure, results have shown a small dispersion and a good agreement in comparison to the assumed design values.

Keywords: concave surface slider, spectrum-compatibility, bidirectional earthquake, base isolation

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Authors: Shanujah Mathuranayagam, William Fuentes, Samanthika Liyanapathirana

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This paper introduces an enhanced version of the coupled hydro-mechanical hypoplastic model. The model is able to simulate volumetric collapse upon wetting and incorporates suction effects on stiffness and strength. Its mechanical constitutive equation links Bishop’s effective stress with strain and suction, featuring a normal consolidation line (NCL) with a compression index (λ) presenting a non-linear dependency with the degree of saturation. The Bulk modulus has been modified to ensure that under rapid volumetric collapse, the stress state remains at the NCL. The coupled model comprises eighteen parameters, with nine for the hydraulic component and nine for the mechanical component. Hydraulic parameters are calibrated with the use of water retention curves (IWRC) across varied soil densities, while mechanical parameters undergo calibration using isotropic and triaxial tests on both unsaturated and saturated samples. The model's performance is analyzed through the back-calculation of two experimental studies: (i) wetting under different vertical stresses for Lower Cromer Till and (ii) isotropic loading and triaxial loading for undisturbed loess. The results confirm that the proposed model is able to predict the hydro-mechanical behavior of unsaturated soils.

Keywords: hypoplastic model, volumetric collapse, normal consolidation line, compression index (λ), degree of saturation, soil suction

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Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

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Authors: Gyula I. Tóth, Shaho Abdalla

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Even though numerical simulations indeed have a significant precursory/supportive role in exploring the disordered phase displaying no long-range order in pattern formation models, studying the stability properties of this phase and determining the order of the ordered-disordered phase transition in these models necessitate an analytical description of the disordered phase. First, we will present the results of a comprehensive statistical analysis of a large number (1,000-10,000) of numerical simulations in the Swift-Hohenberg model, where the bulk disordered (or amorphous) phase is stable. We will show that the average free energy density (over configurations) converges, while the variance of the energy density vanishes with increasing system size in numerical simulations, which suggest that the disordered phase is a thermodynamic phase (i.e., its properties are independent of the configuration in the macroscopic limit). Furthermore, the structural analysis of this phase in the Fourier space suggests that the phase can be modeled by a colored isotropic Gaussian noise, where any instant of the noise describes a possible configuration. Based on these results, we developed the general mathematical framework of finding a pool of solutions to partial differential equations in the sense of continuous probability measure, which we will present briefly. Applying the general idea to the Swift-Hohenberg model we show, that the amorphous phase can be found, and its properties can be determined analytically. As the general mathematical framework is not restricted to continuum theories, we hope that the proposed methodology will open a new chapter in studying disordered phases.

Keywords: fundamental theory, mathematical physics, continuum models, analytical description

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Wondmnew Derebe

Abstract:

Increased adoption of modern beehives improves the livelihood of smallholder farmers whose income largely depends on mixed crop-livestock farming. Improved beehives have been disseminated to farmers in many parts of Ethiopia. However, its impact on income is less investigated. Thus, this study estimates how adopting improved beehives impacts rural households' income. Survey data were collected from 350 randomly selected households' and analyzed using an endogenous switching regression model. The result revealed that the adoption of improved beehives is associated with a higher annual income. On average, improved beehive adopters earned about 6,077 (ETB) more money than their counterparts. However, the impact of adoption would have been larger for actual non-adopters, as reflected in the negative transitional heterogeneity effect of 1792 (ETB). The result also indicated that the decision to adopt or not to adopt improved beehives was subjected to individual self-selection. Improved beehive adoption can increase farmers' income and can be used as an alternative poverty reduction strategy.

Keywords: impact, adoption, endogenous switching regression, income, improved

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Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Joseph Sello Kau, Elias Mashayamombe, Brian Washington Madinkana, Cynthia Ngwane

Abstract:

This paper presents the results for the statistical (stepwise linear regression and multiple regression) analyses, carried out on a number of crops in order to evaluate how the decision for crop choice affect the level of farm income generated by the farmers participating in the High Value Crop production (referred to as the HVC). The goal of the HVC is to encourage farmers cultivate fruit crops. The farmers received planting material from different extension agencies, together with other complementary packages such as fertilizer, garden tools, water tanks etc. During the surveys, it was discovered that a significant number of farmers were cultivating traditional crops even when their plot sizes were small. Traditional crops are competing for resources with high value crops. The results of the analyses show that farmers cultivating fruit crops, maize and potatoes were generating high income than those cultivating spinach and cabbage. High farm income is associated with plot size, access to social grants and gender. Choice for a crop is influenced by the availability of planting material and the market potential for the crop. Extension agencies providing the planting materials stand a good chance of having farmers follow their directives. As a recommendation, for the farmers to cultivate more of the HVCs, the ARC must intensify provision of fruit trees.

Keywords: farm income, nature of extension services, type of crops cultivated, fruit crops, cabbage, maize, potato and spinach

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

Abstract:

The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

Abstract:

The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

Procedia PDF Downloads 117