Search results for: logistic regression model

Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

Procedia PDF Downloads 89

Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

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Authors: Mingyu Xie, Mietek Brdys

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The paper develops a non-linear model predictive control (NMPC) of water quality in drinking water distribution systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives

Procedia PDF Downloads 317

Authors: Juliette Harper, Yu Yang

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Biofuels have gained significant attention recently due to the new regulations and agreements regarding fossil fuels and greenhouse gases being made by countries around the globe. One of the most common types of biofuels is biodiesel, primarily made via the transesterification reaction. We model this nonlinear process in MATLAB using the standard kinetic equations. Then, a nonlinear Model predictive control (NMPC) was developed to regulate this process due to its capability to handle process constraints. The feeding flow uncertainty and kinetic disturbances are further incorporated in the model to capture the real-world operating conditions. The simulation results will show that the proposed NMPC can guarantee the final composition of fatty acid methyl esters (FAME) above the target threshold with a high chance by adjusting the process temperature and flowrate. This research will allow further understanding of NMPC under uncertainties and how to design the computational strategy for larger process with more variables.

Keywords: NMPC, biodiesel, uncertainties, nonlinear, MATLAB

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Authors: Yoko Yamada, Chizumi Yamada

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Narrative psychology is based on the dialogical relationship between self and other. The dialogue can consist of divided, competitive, or opposite communication between self and other. We constructed models of coexistent dialogue in which self and other were positioned side by side and communicated sympathetically. We propose new mediation models for narrative relationships. The mediation models are based on triadic relationships that incorporate a medium or a mediator along with self and other. We constructed three types of mediation model. In the first type, called the “Joint Attention Model”, self and other are positioned side by side and share attention with the medium. In the second type, the “Triangle Model”, an agent mediates between self and other. In the third type, the “Caring Model”, a caregiver stands beside the communication between self and other. We apply the three models to the illness narratives of medical professionals and patients. As these groups have different views and experiences of disease or illness, triadic mediation facilitates the ability to see things from the other person’s perspective and to bridge differences in people’s experiences and feelings. These models would be useful for medical education in various situations, such as in considering the relationships between senior and junior doctors and between old and young patients.

Keywords: illness narrative, mediation, psychology, model, medical education

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 448

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 64

Authors: Bin Li, Mei Liu

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Arrival time information is a crucial component of advanced public transport system (APTS). The advertisement of arrival time at stops can help reduce the waiting time and anxiety of passengers, and improve the quality of service. In this research, an experiment was conducted to compare the performance on prediction accuracy and precision between the link-based and the path-based historical travel time based model with the automatic vehicle location (AVL) data collected from an actual bus route. The research results show that the path-based model is superior to the link-based model, and achieves the best improvement on peak hours.

Keywords: bus transit, arrival time prediction, link-based, path-based

Procedia PDF Downloads 359

Authors: Mai Kaneda, Sarah Feeney

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This study examined the association between adult attachment security and career decision-making self-efficacy (CDMSE) among college students in the United States. Previous studies show that attachment security is associated with levels of CDMSE among college students. Given that a majority of studies examining career development variables have used parental attachment measures, this study adds to understanding of this phenomenon by utilizing a broader measure of attachment. The participants included 269 college students (76% female) between the ages of 19-29. An anonymous survey was distributed online via social media as well as in hard copy format in classrooms. Multiple regression analyses were conducted to determine the relationship between anxious and avoidant attachment and CDMSE. Results revealed anxious attachment was a significant predictor of CDMSE (B = -.13, p = .01), such that greater anxiety in attachment was associated with lower levels of CDMSE. When accounting for anxious attachment, avoidant attachment was no longer significant as a predictor of CDMSE (B = -.12, p = .10). The variance in college CDMSE explained by the model was 7%, F(2,267) = 9.51, p < .001. Results for anxious attachment are consistent with existing literature that finds insecure attachment to be related to lower levels of CDMSE, however the non-significant results for avoidant attachment as a predictor of CDMSE suggest not all types of attachment insecurity are equally related to CDMSE. Future research is needed to explore the nature of the relationship between different dimensions of attachment insecurity and CDMSE.

Keywords: attachment, career decision-making, college students, self-efficacy

Procedia PDF Downloads 221

Authors: Hui-Min Lai, Chin-Pin Chen, Yung-Fu Chang

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The expectation-confirmation model (ECM) is one of the most widely used models for evaluating information system continuance, and this model has been extended to other study backgrounds, or expanded with other theoretical perspectives. However, combining ECM with other theories or investigating the background problem may produce some disparities, thus generating inaccurate conclusions. Habit is considered to be an important factor that influences the user’s continuance behavior. This paper thus critically examines seven pairs of relationships from the original ECM and the habit variable. A meta-analysis was used to tackle the development of ECM research over the last 10 years from a range of journals and conference papers published in 2005–2014. Forty-six journal articles and 19 conference papers were selected for analysis. The results confirm our prediction that a high effect size for the seven pairs of relationships was obtained (ranging from r=0.386 to r=0.588). Furthermore, a meta-analytic structural equation modeling was performed to simultaneously test all relationships. The results show that habit had a significant positive effect on continuance intention at p<=0.05 and that the six other pairs of relationships were significant at p<0.10. Based on the findings, we refined our original research model and an alternative model was proposed for understanding and predicting information system continuance. Some theoretical implications are also discussed.

Keywords: Expectation-confirmation theory, Expectation-confirmation model, Meta-analysis, meta-analytic structural equation modeling.

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The adsorptive ability of different carbon materials, tire char (TC), demineralized tire char (DTC), activated tire char (ATC) and Aldrich supplied commercial activated carbon (CAC) was studied for desulfurization of tire pyrolytic oil (TPO). TPO with an initial sulfur content of 7767.7 ppmw was used in this present study. Preparation of ATC was achieved by chemical treatment of raw TC using a potassium hydroxide (KOH) solution and subsequent activation at 800°C in the presence of nitrogen. The thermal behavior of TC, surface microstructure, and the surface functional groups of the carbon materials was investigated using TGA, SEM, and FTIR, respectively. Adsorptive desulfurization of TPO using the carbon materials was performed and they performed in the order of CAC>ATC>DTC>TC. Adsorption kinetics were studied, and pseudo-first order kinetic model displayed a better fit compared to pseudo-second order model. For isotherm studies, the Freundlich isotherm model fitted to the equilibrium data better than the Langmuir isotherm model.

Keywords: ATC, desulfurization, pyrolysis, tire, TPO

Procedia PDF Downloads 116

Authors: Wanwadee Neamsakul

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VARK learning style is an effective method of learning that could enhance all skills of the students like visual (V), auditory (A), read/write (R), and kinesthetic (K). This learning style benefits the students in terms of professional competencies, critical thinking and lifelong learning which are the desirable characteristics of the nursing students. This study aimed to develop a model of teaching and learning clinical practicum at postpartum ward for nursing students by using VARK learning styles, and evaluate the nursing students’ opinions about the developmental model. A methodology used for this study was research and development (R&D). The model was developed by focus group discussion with five obstetric nursing instructors who have experiences teaching Maternal Newborn and Midwifery I subject. The activities related to practices in the postpartum (PP) ward including all skills of VARK were assigned into the matrix table. The researcher asked the experts to supervise the model and adjusted the model following the supervision. Subsequently, it was brought to be tried out with the nursing students who practiced on the PP ward. Thirty third year nursing students from one of the northern Nursing Colleges, Academic year 2015 were purposive sampling. The opinions about the satisfaction of the model were collected using a questionnaire which was tested for its validity and reliability. Data were analyzed using descriptive statistics. The developed model composed of 27 activities. Seven activities were developed as enhancement of visual skills for the nursing students (25.93%), five activities as auditory skills (18.52%), six activities as read and write skills (22.22%), and nine activities as kinesthetic skills (33.33%). Overall opinions about the model were reported at the highest level of average satisfaction (mean=4.63, S.D=0.45). In the aspects of visual skill (mean=4.80, S.D=0.45) was reported at the highest level of average satisfaction followed by auditory skill (mean=4.62, S.D=0.43), read and write skill (mean=4.57, S.D=0.46), and kinesthetic skill (mean=4.53, S.D=0.45) which were reported at the highest level of average satisfaction, respectively. The nursing students reported that the model could help them employ all of their skills during practicing and taking care of the postpartum women and newborn babies. They could establish self-confidence while providing care and felt proud of themselves by the benefits of the model. It can be said that using VARK learning style to develop the model could enhance both nursing students’ competencies and positive attitude towards the nursing profession. Consequently, they could provide quality care for postpartum women and newborn babies effectively in the long run.

Keywords: model, nursing students, postpartum ward, teaching and learning clinical practicum

Procedia PDF Downloads 150

Authors: Shah Md. Imran Kabir, Md. Mostafa Ali

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Karnafuli is one of the most important rivers of Bangladesh which is playing a vital role in our national economy. The major sea port of Bangladesh is the Chittagong port located on the right bank of Karnafuli River Bangladesh. Karnafuli river port is considered as the lifeline of the economic activities of the country. Therefore, it is always necessary to keep the river active and live in terms of its navigability. Due to man-made intervention, the river flow becomes interrupted and thereby may cause the change in the river morphology. The specific objective of this study is the application of 2D model to assess different hydrodynamic and morphological characteristics of the river due to normal flow condition and sea level rise condition. The model has been set with the recent bathymetry data collected from CPA hydrography division. For model setup, the river reach is selected between Kalurghat and Khal no-18. Time series discharge and water level data are used as boundary condition at upstream and downstream. Calibration and validation have been carried out with the recent water level data at Khal no-10 and Sadarghat. The total reach length of the river has been divided into four parts to determine different hydrodynamic and morphological assessments like variation of velocity, sediment erosion and deposition and bed level changes also have been studied. This model has been used for the assessment of river response due sediment transport and sea level rise. Model result shows slight increase in velocity. It also changes the rate of erosion and deposition at some location of the selected reach. It is hoped that the result of the model simulation will be helpful to suggest the effect of possible future development work to be implemented on this river.

Keywords: CCHE 2D, hydrodynamic, morphology, sea level rise

Procedia PDF Downloads 381

Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

Procedia PDF Downloads 226

Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

Procedia PDF Downloads 137

Authors: Arragaw Alemayehu, Woldeamlak Bewket

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The aim of this study was to understand the influence of current climate variability on crop production in the central highlands of Ethiopia. We used monthly rainfall and temperature data from 132 points each representing a pixel of 10×10 km. The data are reconstructions based on station records and meteorological satellite observations. Production data of the five major crops in the area were collected from the Central Statistical Agency for the period 2004-2013 and for the main cropping season, locally known as Meher. The production data are at the Enumeration Area (EA ) level and hence the best available dataset on crop production. The results show statistically significant decreasing trends in March–May (Belg) rainfall in the area. However, June – September (Kiremt) rainfall showed increasing trends in Efratana Gidim and Menz Gera Meder which the latter is statistically significant. Annual rainfall also showed positive trends in the area except Basona Werana where significant negative trends were observed. On the other hand, maximum and minimum temperatures showed warming trends in the study area. Correlation results have shown that crop production and area of cultivation have positive correlation with rainfall, and negative with temperature. When the trends in crop production are investigated, most crops showed negative trends and below average production was observed. Regression results have shown that rainfall was the most important determinant of crop production in the area. It is concluded that current climate variability has a significant influence on crop production in the area and any unfavorable change in the local climate in the future will have serious implications for household level food security. Efforts to adapt to the ongoing climate change should begin from tackling the current climate variability and take a climate risk management approach.

Keywords: central highlands, climate variability, crop production, Ethiopia, regression, trend

Procedia PDF Downloads 438

Authors: Hossein Shokouhmand, Masoomeh Shadab, Rohallah Torabi

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Turbulent flow inside the seal chamber of a pump operating at nearly high Reynolds number is investigated. A comparison of a 3-D computational model for flow and thermal analysis of a mechanical seal with experimental thermal results is presented. The computational model adequately predicts the flow field in the seal chamber and thermal characteristics with the rotating and stationary rings and the twister flow around the seal parts by solving N-S and energy equations in ANSYS-CFX software. The Reynolds stress model (RSM) is applied as a turbulence model for this purpose. Experimental work is discussed which quantifies the temperature of five different points of the working fluid in chamber, mass flow at inlet and the fluid pressure at inlet and outlet. Experimental measurements are combined with computational modeling to obtain local and average heat transfer characteristics. Numerical results of three cases including different flush rates are reported.

Keywords: mechanical seal, CFD_CFX, reynolds stress model, flow field, heat transfer analysis, stream line, heat transfer coefficient, heat flux, nusselt

Procedia PDF Downloads 440

Authors: J. R. Wang, H. C. Chang, A. L. Ho, J. H. Yang, S. W. Chen, C. Shih

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The purpose of the study is to analyze the load rejection transient of ABWR by using TRACE, PARCS, and SNAP codes. This study has some steps. First, using TRACE, PARCS, and SNAP codes establish the model of ABWR. Second, the key parameters are identified to refine the TRACE/PARCS/SNAP model further in the frame of a steady state analysis. Third, the TRACE/PARCS/SNAP model is used to perform the load rejection transient analysis. Finally, the FSAR data are used to compare with the analysis results. The results of TRACE/PARCS are consistent with the FSAR data for the important parameters. It indicates that the TRACE/PARCS/SNAP model of ABWR has a good accuracy in the load rejection transient.

Keywords: ABWR, TRACE, PARCS, SNAP

Procedia PDF Downloads 197

Authors: Victor Arokia Doss, Kuberapandian Dharaniyambigai, K. Julia Rose Mary

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Advanced Glycation End (AGE) products are the end products due to the reaction between excess reducing sugar present in diabetes and free amino group in protein lipids and nucleic acids. Thus, non-enzymic glycation of molecules such as hemoglobin, collagen, and other structurally and functionally important proteins add to the pathogenic complications such as diabetic retinopathy, neuropathy, nephropathy, vascular changes, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, and chronic heart failure. The most common non-cross linking AGE, carboxymethyl lysine (CML) is formed by the oxidative breakdown of fructosyllysine, which is a product of glucose and lysine. CML is formed in a wide variety of tissues and is an index to assess the extent of glycoxidative damage. Thus we have constructed a mathematical and computational model that predicts the effect of temperature differences in vivo, on the formation of CML, which is now being considered as an important intracellular milieu. This hybrid model that had been tested for its parameter fitting and its sensitivity with available experimental data paves the way for designing novel laboratory experiments that would throw more light on the pathological formation of AGE adducts and in the pathophysiology of diabetic complications.

Keywords: advanced glycation end-products, CML, mathematical model, computational model

Procedia PDF Downloads 129

Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

Procedia PDF Downloads 119

Authors: Mike Tsionas

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The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

Procedia PDF Downloads 349

Authors: Anita Paddy, Millicent Obodai, Lebbaeus Asamani

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The management of sickle cell disease requires a multidisciplinary team for better outcomes. Thus, literature on the application of the biopsychosocial model for the management and explanation of chronic pain in sickle cell disease (SCD) and other chronic diseases abound. However, there is limited research on the use of the biopsychosocial model, together with a spiritual component (biopsychosocial-spiritual model). The study investigated the extent to which healthcare providers utilized the biopsychosocial-spiritual model in the management of chronic pain to improve the quality of life (QoL) of patients with SCD. This study employed the descriptive survey design involving a consecutive sampling of 261 patients with SCD who were between the ages of 18 to 79 years and were accessing hematological services at the Clinical Genetics Department of the Korle Bu Teaching Hospital. These patients willingly consented to participate in the study by appending their signatures. The theory of integrated quality of life, the gate control theory of pain and the biopsychosocial(spiritual) model were tested. An instrument for the biopsychosocial-spiritual model was developed, with a basis from the literature reviewed, while the World Health Organisation Quality of Life BREF (WHOQoLBref) and the spirituality rating scale were adapted and used for data collection. Data were analyzed using descriptive statistics (means, standard deviations, frequencies, and percentages) and partial least square structural equation modeling. The study revealed that healthcare providers had a great leaning toward the biological domain of the model compared to the other domains. Hence, participants’ QoL was not fully improved as suggested by the biopsychosocial(spiritual) model. Again, the QoL and spirituality of patients with SCD were quite high. A significant negative impact of spirituality on QoL was also found. Finally, the biosocial domain of the biopsychosocial-spiritual model was the most significant predictor of QoL. It was recommended that policymakers train healthcare providers to integrate the psychosocial-spiritual component in health services. Also, education on SCD and its resultant impact from the domains of the model should be intensified while health practitioners consider utilizing these components fully in the management of the condition.

Keywords: biopsychosocial (spritual), sickle cell disease, quality of life, healthcare, accra

Procedia PDF Downloads 73

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 115

Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

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Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

Procedia PDF Downloads 266

Authors: Sourour Ramzi, Claudia Sarrico

Abstract:

Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

Procedia PDF Downloads 368

Authors: M. Ndaw, G. Mendy, S. Ouya

Abstract:

Information system risk management helps to reduce or eliminate risk by implementing appropriate controls. In this paper, we propose a quantification model of controls impact on information system risks by automatizing the residual criticality estimation step of FMECA which is based on a inductive reasoning. For this, we defined three equations based on type and maturity of controls. For testing, the values obtained with the model were compared to estimated values given by interlocutors during different working sessions and the result is satisfactory. This model allows an optimal assessment of controls maturity and facilitates risk analysis of information system.

Keywords: information system, risk, control, FMECA method

Procedia PDF Downloads 355

Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

Procedia PDF Downloads 156

Authors: Golden J. Zhang, Dongbao Zhou

Abstract:

Darcy’s law is the fundamental theory in fluid dynamics and engineering applications. Although Darcy linearity was found to be valid for slow, viscous flow, non-linear and non-Darcian flow has been well documented under both small and large velocity fluid flow. Various classical models were proposed and used widely to quantify non-Darcian flow, including the well-known Forchheimer, Izbash, and Swartzendruber models. Applications, however, revealed limitations of these models. Here we propose a general model built upon the Caputo fractional derivative to quantify non-Darcian flow for various flows (laminar to turbulence).Real-world applications and model comparisons showed that the new fractional-derivative model, which extends the fractional model proposed recently by Zhou and Yang (2018), can capture the non-Darcian flow in the relatively small velocity in low-permeability deposits and the relatively high velocity in high-permeability sand. A scale effect was also identified for non-Darcian flow in fractured rocks. Therefore, fractional calculus may provide an efficient tool to improve classical models to quantify fluid dynamics in aquatic environments.

Keywords: fractional derivative, darcy’s law, non-darcian flow, fluid dynamics

Procedia PDF Downloads 126

Authors: Jae Won Shin, Chang Ho Hyun

Abstract:

A disintegration of deuterons by photons (dγ → np) reaction model for GEANT4 is developed in this work. An effective field theory with dibaryon fields Introducing a dibaryon field, we can take into account the effective range contribution to the propagator up to infinite order, and it consequently makes the convergence of the theory better than the pionless effective field theory without dibaryon fields. We develop a hadronic model for GEANT4 which is specialized for the disintegration of the deuteron by photons, dγ → np. For the description of two-nucleon interactions, we employ an effective field theory so called pionless theory with dibaryon fields (dEFT). In spite of its simplicity, the theory has proven very effective and useful in the applications to various two-nucleon systems and processes at low energies. We apply the new model of GEANT4 (G4dEFT) to the calculation of total and differential cross sections in dγ → np, and obtain good agreements to experimental data for a wide range of incoming photon energies.

Keywords: dγ → np, dibaryon fields, effective field theory, GEANT4

Procedia PDF Downloads 378