Search results for: numerical rating score

Authors: Ledi Neçaj

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Introduction: Cardio-respiratory rehabilitation is the set of coordinated interventions needed to provide the best physical, psychological, and social conditions so that patients with chronic or post-acute cardiopulmonary disease, with their efforts, maintain or resume optimal functioning in society through improved health behaviors. Purpose: To study the effectiveness of the application of Cardio-Respiratory Rehabilitation in the typology of patients with chronic or post-acute cardiomyopathy and chronic respiratory diseases in order to facilitate their therapeutic use and to improve the overall quality of life. Material and Method: This is a prospective study including patients with COPD and cardiac disease who were included in the rehabilitation program during the period January 2019 - November 2021. The study was conducted at the University Hospital Center "Mother Teresa" in Tirana, University Hospital "SHEFQET NDROQI", AMERICAN Hospital, HYGEA Hospital, and "Our Lady of Good Counsel, Tirana". An individual chart was used to collect sociodemographic, physical, clinical, and functional examinations for each patient. Results: The study included 253 patients, with a mean age of 62.1 (± 7.9) years, ranging from 48 to 82 years. (67.6%) of the patients were males, and (32.4%) female. Male patients predominated in all age groups, with a statistically significant difference with females (p<0.01). The most common cardiac pathologies are coronary artery bypass (24%), cerebral stroke (9%), myocardial infarction (17%), Stent placement (8%) (p<0.01). Correlation matrix of risk factors found a significant correlation of alcohol consumption with diabetes, smoking, dyslipidemia, sedentary life, obesity, AVC, and hypertension. Functional capacity estimated by change in metabolic equivalents (MET) improved by 46% from 4. ±2.2 to 7.2± .8 METs (p<0.01). Duration of exercise after rehabilitation was increased by 21% compared to baseline (p<0.01). The mean score of all three subscales of the questionnaire: symptoms (p=0.03), activity (p<0.01), and impact (p<0.01) after rehabilitation, was lower compared to pre-rehabilitation. Conclusions: The rehabilitation program has impacted on improving the quality of life, reducing symptoms, reducing the impact of negative factors on daily life, and reducing dyspnea during daily activities.

Keywords: cardio-respiratory rehabilitation, physical exercise, quality of life, diseases

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Rezvan Ravanfar Haghighi, S. Chatterjee, Pratik Kumar, V. C. Vani, Priya Jagia, Sanjiv Sharma, Susama Rani Mandal, R. Lakshmy

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The dual energy computed tomography (DECT) aims at noting the HU(V) values for the sample at two different voltages V=V1, V2 and thus obtain the electron densities (ρe) and effective atomic number (Zeff) of the substance. In the present paper, we aim to obtain a numerical algorithm by which (ρe, Zeff) can be obtained from the HU(100) and HU(140) data, where V=100, 140 kVp. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques.With the idea to develop the inversion algorithm for low Zeff materials, as is the case with non calcified coronary artery plaque, we prepare aqueous samples whose calculated values of (ρe, Zeff) lie in the range (2.65×1023≤ ρe≤ 3.64×1023 per cc ) and (6.80≤ Zeff ≤ 8.90). We fill the phantom with these known samples and experimentally determine HU(100) and HU(140) for the same pixels. Knowing that the HU(V) values are related to the attenuation coefficient of the system, we present an algorithm by which the (ρe, Zeff) is calibrated with respect to (HU(100), HU(140)). The calibration is done with a known set of 20 samples; its accuracy is checked with a different set of 23 known samples. We find that the calibration gives the ρe with an accuracy of ± 4% while Zeff is found within ±1% of the actual value, the confidence being 95%.In this inversion method (ρe, Zeff) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρe, Zeff) does not interfere with each other. It is found that this algorithm can be used for prediction of chemical characteristic (ρe, Zeff) of unknown scanned materials with 95% confidence level, by inversion of the DECT data.

Keywords: chemical composition, dual-energy computed tomography, inversion algorithm

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Akhila Palat, B. Umashankar

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Back-to-back Mechanically Stabilized Earth (MSE) walls are cost-effective soil-retaining structures that can tolerate large settlements compared to conventional gravity retaining walls. They are also an economical way to meet everyday earth retention needs for highway and bridge grade separations, railroads, commercial and residential developments. But, existing design guidelines (FHWA/BS/ IS codes) do not provide a mechanistic approach for the design of back-to-back reinforced retaining walls. The settlement analysis of such structures is limited in the literature. A better understanding of the deformations of this wall system requires an analytical tool that incorporates the properties of backfill material, foundation soil, and geosynthetic reinforcement, and account for the soil–structure interactions in a realistic manner. This study was conducted to investigate the effect of reinforced back-to-back MSE walls on wall settlements and facing deformations. Back-to-back reinforced retaining walls were modeled and compared using commercially available finite difference package FLAC 2D. Parametric studies were carried out for various angles of shearing resistance of backfill material and foundation soil, and the axial stiffness of the reinforcement. A 6m-high wall was modeled, and the facing panels were taken as full-length panels with nominal thickness. Reinforcement was modeled as cable elements (two-dimensional structural elements). Interfaces were considered between soil and wall, and soil and reinforcement.

Keywords: back-to-back walls, numerical modeling, reinforced wall, settlement

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Authors: Zainab Fadil, Mouath Alawadhi, Abdullah Alhusainan, Fahad Alqadiri, Abdulaziz Alqadiri

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This study investigates how lightweight a fire resistance door will perform with under types of insulation materials. Data is initially collected from various websites, scientific books and research papers. Results show that different layers of insulation in a single door can perform better than one insulator. Furthermore, insulation materials that are lightweight, high strength and low thermal conductivity are the most preferred for fire-rated doors. Whereas heavy weight, low strength, and high thermal conductivity are least preferred for fire-resistance doors. Fire-rated doors specifications, theoretical test methodology, structural analysis, and comparison between five different models with diverse layers insulations are presented. Five different door models are being investigated with different insulation materials and arrangements. Model 1 contains an air gap between door layers. Model 2 includes phenolic foam, mild steel and polyurethane. Model 3 includes phenolic foam and glass wool. Model 4 includes polyurethane and glass wool. Model 5 includes only rock wool between the door layers. It is noticed that model 5 is the most efficient model and its design is simple compared to other models. For this model, numerical calculations are performed to check its efficiency and the results are compared to data from experiments for validation. Good agreement was noticed.

Keywords: fire resistance, insulation, strength, thermal conductivity, lightweight, layers

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Authors: Noman Shahzad, Amyn Pardhan, Hasnain Zafar

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Introduction: Though short term survival advantage of damage control laparotomy in management of critically ill trauma patients is established, there is little known about the long-term quality of life of these patients. Facial closure rate after damage control laparotomy is reported to be 20-70 percent. Abdominal wall reconstruction in those who failed to achieve facial closure is challenging and can potentially affect quality of life of these patients. Methodology: We conducted retrospective matched cohort study. Adult patients who underwent damage control laparotomy from Jan 2007 till Jun 2013 were identified through medical record. Patients who had concomitant disabling brain injury or limb injuries requiring amputation were excluded. Age, gender and presentation time matched non exposure group of patients who underwent laparotomy for trauma but no damage control were identified for each damage control laparotomy patient. Quality of life assessment was done via telephonic interview at least one year after the operation, using Urdu version of EuroQol Group Quality of Life (QOL) questionnaire EQ5D after permission. Wilcoxon signed rank test was used to compare QOL scores and McNemar test was used to compare individual parameters of QOL questionnaire. Study was approved by institutional ethical review committee. Results: Out of 32 patients who underwent damage control laparotomy during study period, 20 fulfilled the selection criteria for which 20 matched controls were selected. Median age of patients (IQ Range) was 33 (26-40) years. Facial closure rate in damage control laparotomy group was 40% (8/20). One third of those who did not achieve facial closure (4/12) underwent abdominal wall reconstruction. Self-reported QOL score of damage control laparotomy patients was significantly worse than non-damage control group (p = 0.032). There was no statistically significant difference in two groups regarding individual QOL measures. Significantly, more patients in damage control group were requiring use of abdominal binder, and more patients in damage control group had to either change their job or had limitations in continuing previous job. Our study was not adequately powered to detect factors responsible for worse QOL in damage control group. Conclusion: Quality of life of damage control patients is worse than their age and gender matched patients who underwent trauma laparotomy but not damage control. Adequately powered studies need to be conducted to explore factors responsible for this finding for potential improvement.

Keywords: damage control laparotomy, laparostomy, quality of life

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Authors: Hai Chien Pham, Thi Phuong Anh Vo, Chansik Park

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Risks management in construction projects is important to ensure the positive feasibility of the projects in which financial risks are most concerned while construction projects always run on a credit basis. Credit risks, therefore, require unique and technical tools to be well managed. Underwriting technique in credit risks, in its most basic sense, refers to the process of evaluating the risks and the potential exposure of losses. Risks analysis and underwriting are applied as a must in banks and financial institutions who are supporters for constructions projects when required. Recently, construction organizations, especially contractors, have recognized the significant increasing of credit risks which caused negative impacts to project performance and profit of construction firms. Despite the successful application of underwriting in banks and financial institutions for many years, there are few contractors who are applying this technique to analyze and mitigate the credit risks of their potential owners before signing contracts with them for delivering their performed services. Thus, contractors have taken credit risks during project implementation which might be not materialized due to the bankruptcy and/or protracted default made by their owners. With this regard, this study proposes a model using the underwriting technique for contractors to analyze and assess credit risks of their owners before making final decisions for the potential construction contracts. Contractor’s underwriters are able to analyze and evaluate the subjects such as owner, country, sector, payment terms, financial figures and their related concerns of the credit limit requests in details based on reliable information sources, and then input into the proposed model to have the Overall Assessment Score (OAS). The OAS is as a benchmark for the decision makers to grant the proper limits for the project. The proposed underwriting model is validated by 30 subjects in Asia Pacific region within 5 years to achieve their OAS, and then compare output OAS with their own practical performance in order to evaluate the potential of underwriting model for analyzing and assessing credit risks. The results revealed that the underwriting would be a powerful method to assist contractors in making precise decisions. The contribution of this research is to allow the contractors firstly to develop their own credit risk management model for proactively preventing the credit risks of construction projects and continuously improve and enhance the performance of this function during project implementation.

Keywords: underwriting technique, credit risk, risk management, construction project

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Authors: Liana Claudia Salanță, Anca Corina Fărcaș

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Valorization of agro-industrial by-products offers significant economic and environmental advantages. This study investigates the transformation of tomato processing residues into value-added products, contributing to waste reduction and promoting a circular, sustainable economy. Specifically, the development of sorghum flour-based crackers enriched with tomato waste powder targets the dietary requirements of individuals with celiac disease and diabetes, evaluating their nutritional and sensory properties. Tomato residues were obtained from Roma-Spania tomatoes and processed into powder through drying and grinding. The bioactive compounds, including carotenoids, lycopene, and polyphenols, were quantified using established analytical methods. Formulation of the crackers involved optimizing the incorporation of tomato powder into sorghum flour. Subsequently, their nutritional and sensory attributes were assessed. The tomato waste powder demonstrated considerable bioactive potential, with total carotenoid content measured at 66 mg/100g, lycopene at 52.61 mg/100g, and total polyphenols at 463.60 mg GAE/100g. Additionally, the crackers with a 30% powder addition exhibited the highest concentration of polyphenols. Consequently, this sample also demonstrated a high antioxidant activity of 15.04% inhibition of DPPH radicals. Nutritionally, the crackers showed a 30% increase in fiber content and a 25% increase in protein content compared to standard gluten-free products. Sensory evaluation indicated positive consumer acceptance, with an average score of 8 out of 10 for taste and 7.5 out of 10 for color, attributed to the natural pigments from tomato waste. This innovative approach highlights the potential of tomato by-products in creating nutritionally enhanced gluten-free foods. Future research should explore the long-term stability of these bioactive compounds in finished products and evaluate the scalability of this process for industrial applications. Integrating such sustainable practices can significantly contribute to waste reduction and the development of functional foods.

Keywords: tomato waste, circular economy, bioactive compounds, sustainability, health benefits

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Authors: Qijiao He

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MicroElectrical-Mechanical System (MEMS) is one of the most rapidly developing frontier research field both in theory study and applied technology. Micro-channel is a very important link component of MEMS. With the research and development of MEMS, the size of the micro-devices and the micro-channels becomes further smaller. Compared with the macroscale flow, the flow characteristics of gas in the micro-channel have changed, and the rarefaction effect appears obviously. However, for the rarefied gas and microscale flow, Navier-Stokes-Fourier (NSF) equations are no longer appropriate due to the breakup of the continuum hypothesis. A Nonlinear Coupled Constitutive Model (NCCM) has been derived from the Boltzmann equation to describe the characteristics of both continuum and rarefied gas flows. We apply the present scheme to simulate continuum and rarefied gas flows in a micro-channel structure. And for comparison, we apply other widely used methods which based on particle simulation or direct solution of distribution function, such as Direct simulation of Monte Carlo (DSMC), Unified Gas-Kinetic Scheme (UGKS) and Lattice Boltzmann Method (LBM), to simulate the flows. The results show that the present solution is in better agreement with the experimental data and the DSMC, UGKS and LBM results than the NSF results in rarefied cases but is in good agreement with the NSF results in continuum cases. And some characteristics of both continuum and rarefied gas flows are observed and analyzed.

Keywords: continuum and rarefied gas flows, discontinuous Galerkin method, generalized hydrodynamic equations, numerical simulation

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Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

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Aims: The present study aimed to explore Intensive Care Unit (ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance (ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload, nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

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Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

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With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: electrical market prices, electricity market, energy storage optimization, mixed integer linear programming (MILP) optimization

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Authors: Bartłomiej K. Sołtysik, Agnieszka Guligowska, Łukasz Kroc, Małgorzata Pigłowska, Elizavetta Fife, Tomasz Kostka

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Introduction: Functional capacity is one of the basic determinants of health in older age. Functional capacity may be influenced by multiple disorders, including cardiovascular and metabolic diseases. Nevertheless, there is relatively little evidence regarding the association of functional status and cardiometabolic risk factors. Aim: The aim of this research is to check possible association between functional capacity and cardiovascular risk factor in a group of younger seniors. Materials and Methods: The study group consisted of 300 participants aged 60-65 years (50% were women). Total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), glucose, uric acid, body mass index (BMI), waist-to-height ratio (WHtR) and blood pressure were measured. Smoking status and physical activity level (by Seven Day Physical Activity Recall Questionnaire ) were analysed. Functional status was assessed with the Timed Up and Go (TUG) Test. The data were compared according to gender, and then separately for both sexes regarding prolonged TUG score (>7 s). The limit of significance was set at p≤0.05 for all analyses. Results: Women presented with higher serum lipids and longer TUG. Men had higher blood pressure, glucose, uric acid, the prevalence of hypertension and history of heart infarct. In women group, those with prolonged TUG displayed significantly higher obesity rate (BMI, WHTR), uric acid, hypertension and ischemic heart disease (IHD), but lower physical activity level, TC or LDL-C. Men with prolonged TUG were heavier smokers, had higher TG, lower HDL and presented with higher prevalence of diabetes and IHD. Discussion: This study shows association between functional status and risk profile of cardiometabolic disorders. In women, the relationship of lower functional status to cardiometabolic diseases may be mediated by overweight/obesity. In men, locomotor problems may be related to smoking. Higher education level may be considered as a protective factor regardless of gender.

Keywords: cardiovascular risk factors, functional capacity, TUG test, seniors

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Authors: Georges Jabbour

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Background and aims: This two-year follow-up study explores the long-term sustainability of physical activity (PA) levels in young people with type 1 diabetes, focusing on the relationship between PA, hypoglycemia, and behavioral scores. The literature highlights the importance of PA and its health benefits, as well as the barriers to engaging in PA practices. Studies have shown that individuals with high levels of vigorous physical activity have higher fear of hypoglycemia (FOH) scores and more hypoglycemia episodes. Considering that hypoglycemia episodes are a major barrier to physical activity, and many studies reported a negative association between PA and high FOH scores, it cannot be guaranteed that those experiencing hypoglycemia over a long period will remain active. Building on that, the present work assesses whether high PA levels, despite elevated hypoglycemia risk, can be maintained over time. The study tracks PA levels at one and two years, correlating them with hypoglycemia instances and Fear of Hypoglycemia (FOH) scores. Materials and methods: A self-administered questionnaire was completed by 61 youth with T1D, and their PA was assessed. Hypoglycemia episodes, fear of hypoglycemia scores and HbA1C levels were collected. All assessments were realized at baseline (visit 0: V0), one year (V1) and two years later (V2). For the purpose of the present work, we explore the relationships between PA levels, hypoglycemia episodes, and FOH scores at each time point. We used multiple linear regression to model the mean outcomes for each exposure of interest. Results: Findings indicate no changes in total moderate to vigorous PA (MVPA) and VPA levels among visits, and HbA1c (%) was negatively correlated with the total amount of VPA per day in minutes (β= -0.44; p=0.01, β= -0.37; p=0.04, and β= -0.66; p=0.01 for V0, V1, and V2, respectively). Our linear regression model reported a significant negative correlation between VPA and FOH across the visits (β=-0.59, p=0.01; β= -0.44, p=0.01; and β= -0.34, p=0.03 for V0, V1, and V2, respectively), and HbA1c (%) was influenced by both the number of hypoglycemic episodes and FOH score at V2 (β=0.48; p=0.02 and β=0.38; p=0.03, respectively). Conclusion: The sustainability of PA levels and HbA1c (%) in young individuals with type 1 diabetes is influenced by various factors, including fear of hypoglycemia. Understanding these complex interactions is essential for developing effective interventions to promote sustained PA levels in this population. Our results underline the necessity of a multi-strategic approach to promoting active lifestyles among diabetic youths. This approach should synergize PA enhancement with vigilant glucose monitoring and effective FOH management.

Keywords: physical activity, hypoglycemia, fear of hypoglycemia, youth

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Authors: T. Asefi, J. Faiz, M. A. Khan

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This paper introduces dual rotor axial flux machines with surface mounted and spoke type ferrite permanent magnets with concentrated windings; they are introduced as alternatives to a generator with surface mounted Nd-Fe-B magnets. The output power, voltage, speed and air gap clearance for all the generators are identical. The machine designs are optimized for minimum mass using a population-based algorithm, assuming the same efficiency as the Nd-Fe-B machine. A finite element analysis (FEA) is applied to predict the performance, emf, developed torque, cogging torque, no load losses, leakage flux and efficiency of both ferrite generators and that of the Nd-Fe-B generator. To minimize cogging torque, different rotor pole topologies and different pole arc to pole pitch ratios are investigated by means of 3D FEA. It was found that the surface mounted ferrite generator topology is unable to develop the nominal electromagnetic torque, and has higher torque ripple and is heavier than the spoke type machine. Furthermore, it was shown that the spoke type ferrite permanent magnet generator has favorable performance and could be an alternative to rare-earth permanent magnet generators, particularly in wind energy applications. Finally, the analytical and numerical results are verified using experimental results.

Keywords: axial flux, permanent magnet generator, dual rotor, ferrite permanent magnet generator, finite element analysis, wind turbines, cogging torque, population-based algorithms

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Authors: Ravindra Raju, Vidhu Kampurath

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For smooth transition of the power from the engine to the transmission system, a clutch is used. In agricultural tractors, friction clutches are widely used in power transmission applications. To transmit the maximum torque in friction clutches, selection of materials is one of the important tasks. The present used material for friction disc is Asbestos, Ceramic etc. In this study, analysis is performed using composites materials. The composite materials are considered due to their high strength to weight ratio. Composite materials like kevlar49, kevlar 29U were used in the study. The paper presents a systematic approach to optimize the structural and thermal characteristics of the clutch friction pad. A single plate clutch is modeled using Creo 2.0 software and analyzed using ANSYS. Thermal analysis considers the reduction of heat generated between the friction surfaces and reducing the temperature rise during the steady state period. Structural analysis is done to minimize the stresses developed as a result of the loading contact between friction surfaces. Also, modal analysis is done to optimize the natural frequency of the friction plate to avoid being in resonance with the engine frequency range. The analysis carried out on ANSYS workbench to get the foremost appropriate friction material for clutch. From the analyzed results stress, strain / total deformation values and natural frequency of the materials were compared for all the composite materials and the best one was taken out. For the study purpose, specifications of the clutch are obtained from the MF1035 (47KW) Tractor model.

Keywords: ANSYS, clutch, composite materials, creo

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Authors: Dhiraj Biswas, Chaitali Ray

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A modified refined higher order zigzag theory has been developed in this paper in order to compute the accurate interlaminar stresses within hybrid laminates. Warping has significant effect on the mechanical behaviour of the laminates. To the best of author(s)’ knowledge the stress analysis of hybrid laminates is not reported in the published literature. The present paper aims to develop a new C0 continuous element based on the refined higher order zigzag theories considering warping effect in the formulation of hybrid laminates. The eight noded isoparametric plate bending element is used for the flexural analysis of laminated composite plates to study the performance of the proposed model. The transverse shear stresses are computed by using the differential equations of stress equilibrium in a simplified manner. A computer code has been developed using MATLAB software package. Several numerical examples are solved to assess the performance of the present finite element model based on the proposed higher order zigzag theory by comparing the present results with three-dimensional elasticity solutions. The present formulation is validated by comparing the results obtained from the relevant literature. An extensive parametric study has been carried out on the hybrid laminates with varying percentage of materials and angle of orientation of fibre content.

Keywords: hybrid laminate, Interlaminar stress, refined higher order zigzag theory, warping effect

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Authors: Alireza Gholipour, Mergen H. Ghayesh, Anthony Zander, Stephen J. Nicholls, Peter J. Psaltis

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A three-dimensional numerical model of an atherosclerotic coronary ‎artery is developed for the determination of high-risk situation and ‎hence heart attack prediction. Employing the finite element method ‎‎(FEM) using ANSYS, fluid-structure interaction (FSI) model of the ‎artery is constructed to determine the shear stress distribution as well ‎as the von Mises stress field. A flexible model for an atherosclerotic ‎coronary artery conveying pulsatile blood is developed incorporating ‎three-dimensionality, artery’s tapered shape via a linear function for ‎artery wall distribution, motion of the artery, blood viscosity via the ‎non-Newtonian flow theory, blood pulsation via use of one-period ‎heartbeat, hyperelasticity via the Mooney-Rivlin model, viscoelasticity ‎via the Prony series shear relaxation scheme, and micro-calcification ‎inside the plaque. The material properties used to relate the stress field ‎to the strain field have been extracted from clinical data from previous ‎in-vitro studies. The determined stress fields has potential to be used as ‎a predictive tool for plaque rupture and dissection.‎ The results show that stress concentration due to micro-calcification ‎increases the von Mises stress significantly; chance of developing a ‎crack inside the plaque increases. Moreover, the blood pulsation varies ‎the stress distribution substantially for some cases.‎

Keywords: atherosclerosis, fluid-structure interaction‎, coronary arteries‎, pulsatile flow

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Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

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In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: amelioration, deterioration, small sized poultry farmers, optimal price

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Authors: Abhishek Saha, Serene Tay, Gerard Pijcke

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The availability of high-resolution topography and rainfall information in urban areas has made it necessary to revise modeling approaches used for simulating flood risk assessments. Lidar derived elevation models that have 1m or lower resolutions are becoming widely accessible. The classical approaches of 1D-2D flow models where channel flow is simulated and coupled with a coarse resolution 2D overland flow models may not fully utilize the information provided by high-resolution data. In this context, a study was undertaken to compare three different modeling approaches to simulate flooding in an urban area. The first model used is the base model used is Sobek, which uses 1D model formulation together with hydrologic boundary conditions and couples with an overland flow model in 2D. The second model uses a full 2D model for the entire area with shallow water equations at the resolution of the digital elevation model (DEM). These models are compared against another shallow water equation solver in 2D, which uses a subgrid method for grid refinement. These models are simulated for different horizontal resolutions of DEM varying between 1m to 5m. The results show a significant difference in inundation extents and water levels for different DEMs. They are also sensitive to the different numerical models with the same physical parameters, such as friction. The study shows the importance of having reliable field observations of inundation extents and levels before a choice of model and data can be made for spatial flood risk assessments.

Keywords: flooding, DEM, shallow water equations, subgrid

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Authors: Florian Monetti, Brett Beamsley, Peter McComb, Simon Weppe

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Land reclamation from the ocean has considerably increased over past decades to support worldwide rapid urban growth. Reshaping the coastline, however, inevitably affects coastal systems. One of the main challenges for coastal oceanographers is to predict the physical and morphological responses for nearshore systems to man-made changes over multiple time-scales. Fully-coupled numerical models are powerful tools for simulating the wide range of interactions between flow field and bedform morphology. Restricted and inconsistent measurements, combined with limited computational resources, typically make this exercise complex and uncertain. In the present study, we investigate the impact of proposed land reclamation within a wave-dominated bay in New Zealand. For this purpose, we first calibrated our morphological model based on the long-term evolution of the bay resulting from land reclamation carried out in the 1950s. This included the application of sedimentological spin-up and reduction techniques based on historical bathymetry datasets. The updated bathymetry, including the proposed modifications of the bay, was then used to predict the effect of the proposed land reclamation on the wave climate and morphology of the bay after one decade. We show that reshaping the bay induces a distinct symmetrical response of the shoreline which likely will modify the nearshore wave patterns and consequently recreational activities in the area.

Keywords: coastal waves, impact of land reclamation, long-term coastal evolution, morphodynamic modeling

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Authors: Lucy Patricia Onundo, Wilfred Njoroge Mwema

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The tidal power potential available for electricity generation from Mombasa and Lamu sites in Kenya will be examined. Several African countries in the Western Indian Ocean endure insufficiencies in the power sector, including both generation and distribution. One important step towards increasing energy security and availability is to intensify the use of renewable energy sources. The access to cost-efficient hydropower is low in Mombasa and Lamu hence Ocean energy will play an important role. Global-Level resource assessments and oceanographic literature and data have been compiled in an analysis between technology-specific requirements for ocean energy technologies (salinity, tide, tidal current, wave, Ocean thermal energy conversion, wind and solar) and the physical resources in Lamu and Mombasa. The potential for tide and tidal current power is more restricted but may be of interest at some locations. The theoretical maximum power produced over a tidal cycle is determined by the product of the forcing tide and the undisturbed volumetric flow-rate. The extraction of the maximum power reduces the flow-rate, but a significant portion of the maximum power can be extracted with little change to the tidal dynamics. Two-dimensional finite-element, numerical simulations designed and developed agree with the theory. Temporal variations in resource intensity, as well as the differences between small-scale and large-scale applications, are considered.

Keywords: energy assessment, marine tidal power, renewable energy, tidal dynamics

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Authors: Madhu Aneja, Sapna Sharma

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The water-based bioconvection of a nanofluid containing motile gyrotactic micro-organisms over nonlinear inclined stretching sheet has been investigated. The governing nonlinear boundary layer equations of the model are reduced to a system of ordinary differential equations via Oberbeck-Boussinesq approximation and similarity transformations. Further, the modified set of equations with associated boundary conditions are solved using Finite Element Method. The impact of various pertinent parameters on the velocity, temperature, nanoparticles concentration, density of motile micro-organisms profiles are obtained and analyzed in details. The results show that with the increase in angle of inclination δ, velocity decreases while temperature, nanoparticles concentration, a density of motile micro-organisms increases. Additionally, the skin friction coefficient, Nusselt number, Sherwood number, density number are computed for various thermophysical parameters. It is noticed that increasing Brownian motion and thermophoresis parameter leads to an increase in temperature of fluid which results in a reduction in Nusselt number. On the contrary, Sherwood number rises with an increase in Brownian motion and thermophoresis parameter. The findings have been validated by comparing the results of special cases with existing studies.

Keywords: bioconvection, finite element method, gyrotactic micro-organisms, inclined stretching sheet, nanofluid

Procedia PDF Downloads 183

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Predicting the risk of diabetic retinopathy (DR) in Indian type 2 diabetes patients is immensely necessary. India, being the second largest country after China in terms of a number of diabetic patients, to the best of our knowledge not a single risk score for complications has ever been investigated. Diabetic retinopathy is a serious complication and is the topmost reason for visual impairment across countries. Any type or form of DR has been taken as the event of interest, be it mild, back, grade I, II, III, and IV DR. A sample was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of DR. Cox proportional hazard regression is used to design risk scores for the prediction of retinopathy. Model calibration and discrimination are assessed from Hosmer Lemeshow and area under receiver operating characteristic curve (ROC). Overfitting and underfitting of the model are checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Optimal cut off point is chosen by Youden’s index. Five-year probability of DR is predicted by both survival function, and Markov chain two state model and the better technique is concluded. The risk scores developed can be applied by doctors and patients themselves for self evaluation. Furthermore, the five-year probabilities can be applied as well to forecast and maintain the condition of patients. This provides immense benefit in real application of DR prediction in T2DM.

Keywords: Cox proportional hazard regression, diabetic retinopathy, ROC curve, type 2 diabetes mellitus

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Authors: Md Monoarul Haque

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Nutritional status is a sensitive indicator of community health and nutrition among preschool children, especially the prevalence of undernutrition that affects all dimensions of human development and leads to growth faltering in early life. The present study is an attempt to assess the food intake pattern and nutritional status of pre-school Chakma tribe children. It was a cross-sectional community based study. The subjects were selected purposively. This study was conducted at Savar Upazilla of Rangamati. Rangamati is located in the Chittagong Division. Anthropometric data height and weight of the study subjects were collected by standard techniques. Nutritional status was measured using Z score according WHO classification. χ2 test, independent t-test, Pearson’s correlation, multiple regression and logistic regression was performed as P<0.05 level of significance. Statistical analyses were performed by appropriate univariate and multivariate techniques using SPSS windows 11.5. Moderate (-3SD to <-2SD) to severe underweight (<-3SD) were 23.8% and 76.2% study subjects had normal weight for their age. Moderate (-3SD to <-2SD) to severe (<-3SD) stunted children were only 25.6% and 74.4% children were normal and moderate to severe wasting were 14.7% whereas normal child was 85.3%. Significant association had been found between child nutritional status and monthly family income, mother education and occupation of father and mother. Age, sex and incomes of the family, education of mother and occupation of father were significantly associated with WAZ and HAZ of the study subjects (P=0.0001, P=0.025, P=0.001 and P=0.0001, P=0.003, P=0.031, P=0.092, P=0.008). Maximum study subjects took local small fish and some traditional tribal food like bashrool, jhijhipoka and pork very much popular food among tribal children. Energy, carbohydrate and fat intake was significantly associated with HAZ, WAZ, BAZ and MUACZ. This study demonstrates that malnutrition among tribal children in Bangladesh is much better than national scenario in Bangladesh. Significant association was found between child nutritional status and family monthly income, mother education and occupation of father and mother. Most of the study subjects took local small fish and some traditional tribal food. Significant association was also found between child nutritional status and dietary intake of energy, carbohydrate and fat.

Keywords: food intake pattern, nutritional status, preschool children, Chakma ethnic community

Procedia PDF Downloads 494

Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

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One of the important concerns within the field of geotechnical engineering is the presence of cavities in soils. This present work is an attempt to understand the behaviour of strip footing subjected to inclined load and constructed on cavitied soil. The failure mechanism of strip footing located above such soils was studied analytically. The capability of analytical model to correctly expect the system behaviour is assessed by carrying out verification analysis on available studies. The study was prepared by finite element software (PLAXIS) in which an elastic-perfectly plastic soil model was used. It was indicated, from the results of the study, that the load carrying capacity of foundation constructed on cavity can be analysed well using such analysis. The research covered many foundation cases, and in each foundation case, there occurs a critical depth under which the presence of cavities has shown minimum impact on the foundation performance. When cavities are found above this critical depth, the load carrying capacity of the foundation differs with many influences, such as the location and size of the cavity and footing depth. Figures involving the load carrying capacity with the affecting factors studied are presented. These figures offer information beneficial for the design of strip footings rested on underground cavities. Moreover, the results might be used to design a shallow foundation constructed on cavitied soil, whereas the obtained failure mechanisms may be employed to improve numerical solutions for this kind of problems.

Keywords: axial load, cavity, inclined load, strip footing

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Authors: Zhuoneng Li, Zeeshan A. Rana, Karl W. Jenkins

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In industry, to validate a case, often a multitude of simulation are required and in order to demonstrate confidence in the process where users tend to use a coarser mesh. Therefore, it is imperative to establish the coarsest mesh that could be used while keeping reasonable simulation accuracy. To date, the two most reliable, affordable and broadly used advanced simulations are the hybrid RANS (Reynolds Averaged Navier Stokes)/LES (Large Eddy Simulation) and wall modelled LES. The potentials in these two simulations will still be developed in the next decades mainly because the unaffordable computational cost of a DNS (Direct Numerical Simulation). In the wall modelled LES, the turbulence model is applied as a sub-grid scale model in the most inner layer near the wall. The RANS turbulence models cover the entire boundary layer region in a hybrid RANS/LES (Detached Eddy Simulation) and its variants, therefore, the RANS still has a very important role in the state of art simulations. This research focuses on the turbulence model mesh sensitivity analysis where various turbulence models such as the S-A (Spalart-Allmaras), SSG (Speziale-Sarkar-Gatski), K-Omega transitional SST (Shear Stress Transport), K-kl-Omega, γ-Reθ transitional model, v2f are evaluated within the OpenFOAM. The simulations are conducted on a fully developed turbulent flow over a flat plate where the skin friction coefficient as well as velocity profiles are obtained to compare against experimental values and DNS results. A concrete conclusion is made to clarify the mesh sensitivity for different turbulence models.

Keywords: mesh sensitivity, turbulence models, OpenFOAM, RANS

Procedia PDF Downloads 249

Authors: Habtamu Ayenew Asegie

Abstract:

Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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