Search results for: models error comparison

Authors: Ahmad R. Zamani, Luigi Sanguigno, Angelo R. Maligno

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A 3D woven composite, designed for automotive applications, is studied using Abaqus Finite Element (FE) software suite. Python scripts were developed to build FE models of the woven composite in Complete Abaqus Environment (CAE). They can read TexGen or WiseTex files and automatically generate consistent meshes of the fabric and the matrix. A user menu is provided to help define parameters for the FE models, such as type and size of the elements in fabric and matrix as well as the type of matrix-fabric interaction. Node-to-node constraints were imposed to guarantee periodicity of the deformed shapes at the boundaries of the representative volume element of the composite. Tensile loads in three axes and biaxial loads in x-y directions have been applied at different Fibre Volume Fractions (FVFs). A simple damage model was implemented via an Abaqus user material (UMAT) subroutine. Existing tools for homogenization were also used, including voxel mesh generation from TexGen as well as Abaqus Micromechanics plugin. Linear relations between homogenised elastic properties and the FVFs are given. The FE models of composite exhibited balanced behaviour with respect to warp and weft directions in terms of both stiffness and strength.

Keywords: 3D woven composite (3DWC), meso-scale finite element model, homogenisation of elastic material properties, Abaqus Python scripting

Procedia PDF Downloads 146

Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

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Authors: Mahesh K. Chudasama, Harit K. Raval

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3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper, bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.

Keywords: analytical modeling, cone frustum, dynamic bending, static bending

Procedia PDF Downloads 307

Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

Procedia PDF Downloads 102

Authors: Mustapha Babatunde, Bassam Tawabini, Ole John Nielson

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Air dispersion (AD) models such as AERMOD are important tools for estimating the environmental impacts of air pollutant emissions into the atmosphere from anthropogenic sources. The outcome of these models is significantly linked to the climate condition like air temperature, which is expected to differ in the future due to the global warming phenomenon. With projections from scientific sources of impending changes to the future climate of Saudi Arabia, especially anticipated temperature rise, there is a potential direct impact on the dispersion patterns of air pollutants results from AD models. To our knowledge, no similar studies were carried out in Saudi Arabia to investigate such impact. Therefore, this research investigates the effects of climate temperature change on air quality in the Dammam Metropolitan area, Saudi Arabia, using AERMOD coupled with Station data using Sulphur dioxide (SO₂) – as a model air pollutant. The research uses AERMOD model to predict the SO₂ dispersion trends in the surrounding area. Emissions from five (5) industrial stacks on twenty-eight (28) receptors in the study area were considered for the climate period (2010-2019) and future period of mid-century (2040-2060) under different scenarios of elevated temperature profiles (+1ᵒC, + 3ᵒC and + 5ᵒC) across averaging time periods of 1hr, 4hr and 8hr. Results showed that levels of SO₂ at the receiving sites under current and simulated future climactic condition fall within the allowable limit of WHO and KSA air quality standards. Results also revealed that the projected rise in temperature would only have mild increment on the SO₂ concentration levels. The average increase of SO₂ levels was 0.04%, 0.14%, and 0.23% due to the temperature increase of 1, 3, and 5 degrees, respectively. In conclusion, the outcome of this work elucidates the degree of the effects of global warming and climate changes phenomena on air quality and can help the policymakers in their decision-making, given the significant health challenges associated with ambient air pollution in Saudi Arabia.

Keywords: air quality, sulfur dioxide, dispersion models, global warming, KSA

Procedia PDF Downloads 82

Authors: Sharon Li, Zhonghang Xia

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Post-database search is an essential phase in peptide identification using tandem mass spectrometry (MS/MS) to refine peptide-spectrum matches (PSMs) produced by database search engines. These engines frequently face difficulty differentiating between correct and incorrect peptide assignments. Despite advances in statistical and machine learning methods aimed at improving the accuracy of peptide identification, challenges remain in selecting critical features for these models. In this study, two machine learning models—a random forest tree and a support vector machine—were applied to three datasets to enhance PSMs. SHAP values were utilized to determine the significance of each feature within the models. The experimental results indicate that the random forest model consistently outperformed the SVM across all datasets. Further analysis of SHAP values revealed that the importance of features varies depending on the dataset, indicating that a feature's role in model predictions can differ significantly. This variability in feature selection can lead to substantial differences in model performance, with false discovery rate (FDR) differences exceeding 50% between different feature combinations. Through SHAP value analysis, the most effective feature combinations were identified, significantly enhancing model performance.

Keywords: peptide identification, SHAP value, feature selection, random forest tree, support vector machine

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Authors: Chinmayee Choudhury

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Human Melanocortin 4 Receptor (HMC4R) is one of the most potential drug targets for the treatment of obesity which controls the appetite. A deletion of the residues 88-92 in HMC4R is sometimes the cause of severe obesity in the humans. In this study, two homology models are constructed for the normal as well as mutated HMC4Rs and some phytochemicals present in Green Tea, Honey and Cinnamon have been docked to them to study their differential binding to the normal and mutated HMC4R as compared to the natural agonist α- MSH. Two homology models have been constructed for the normal as well as mutated HMC4Rs using the Modeller9v7. Some of the phytochemicals present in Green Tea, Honey, and Cinnamon, which have appetite suppressant activities are constructed, minimized and docked to these normal and mutated HMC4R models using ArgusLab 4.0.1. The mode of binding of the phytochemicals with the Normal and Mutated HMC4Rs have been compared. Further, the mode of binding of these phytochemicals with that of the natural agonist α- Melanocyte Stimulating Hormone(α-MSH) to both normal and mutated HMC4Rs have also been studied. It is observed that the phytochemicals Kaempherol, Epigallocatechin-3-gallate (EGCG) present in Green Tea and Honey, Isorhamnetin, Chlorogenic acid, Chrysin, Galangin, Pinocambrin present in Honey, Cinnamaldehyde, Cinnamyl acetate and Cinnamyl alcohol present in Cinnamon have capacity to form more stable complexes with the Mutated HMC4R as compared to α- MSH. So they may be potential agonists of HMC4R to suppress the appetite.

Keywords: HMC4R, α-MSH, docking, photochemical, appetite suppressant, homology modelling

Procedia PDF Downloads 195

Authors: Yaghoubi N., Moore Z., Van Der Veen S. M., Pidcoe P. E., Thomas J. S., Dexheimer B.

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Optoelectronic 3D motion capture systems, such as the Vicon kinematic system, are widely utilized in biomedical research to track joint motion. These systems are considered powerful and accurate measurement tools with <2 mm average error. However, these systems are costly and may be difficult to implement and utilize in a clinical setting. 3D virtual reality (VR) is gaining popularity as an affordable and accessible tool to investigate motor control and perception in a controlled, immersive environment. The HTC Vive VR system includes puck-style trackers that seamlessly integrate into its VR environments. These affordable, wireless, lightweight trackers may be more feasible for clinical kinematic data collection. However, the accuracy of HTC Vive Trackers (3.0), when compared to optoelectronic 3D motion capture systems, remains unclear. In this preliminary study, we compared the HTC Vive Tracker system to a Vicon kinematic system in a simulated lumbar flexion task. A 6-DOF robot arm (SCORBOT ER VII, Eshed Robotec/RoboGroup, Rosh Ha’Ayin, Israel) completed various reaching movements to mimic increasing levels of hip flexion (15°, 30°, 45°). Light reflective markers, along with one HTC Vive Tracker (3.0), were placed on the rigid segment separating the elbow and shoulder of the robot. We compared position measures simultaneously collected from both systems. Our preliminary analysis shows no significant differences between the Vicon motion capture system and the HTC Vive tracker in the Z axis, regardless of hip flexion. In the X axis, we found no significant differences between the two systems at 15 degrees of hip flexion but minimal differences at 30 and 45 degrees, ranging from .047 cm ± .02 SE (p = .03) at 30 degrees hip flexion to .194 cm ± .024 SE (p < .0001) at 45 degrees of hip flexion. In the Y axis, we found a minimal difference for 15 degrees of hip flexion only (.743 cm ± .275 SE; p = .007). This preliminary analysis shows that the HTC Vive Tracker may be an appropriate, affordable option for gross motor motion capture when the Vicon system is not available, such as in clinical settings. Further research is needed to compare these two motion capture systems in different body poses and for different body segments.

Keywords: lumbar, vivetracker, viconsystem, 3dmotion, ROM

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

Procedia PDF Downloads 349

Authors: Abdolghader Pourali, Mohammad V. Malakooti, Muhammad Hussein Yektaie

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A mobile payment system in mobile e-commerce generally have high security so that the user can trust it for doing business deals, sales, paying financial transactions, etc. in the mobile payment system. Since an architecture or payment model in e-commerce only shows the way of interaction and collaboration among users and mortgagers and does not present any evaluation of effectiveness and confidence about financial transactions to stakeholders. In this paper, we try to present a detailed assessment of the reliability of a mobile payment model in the mobile e-commerce using formal models and colored Petri nets. Finally, we demonstrate that the reliability of this system has high value (case study: a secure payment model in mobile commerce.

Keywords: reliability, colored Petri net, assessment, payment models, m-commerce

Procedia PDF Downloads 537

Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

Procedia PDF Downloads 385

Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

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We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models for Generative Named Entity Recognition (GNER). Alongside Retrieval Augmented Generation (RAG), and supported by task-specific prompting, our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self-verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

Procedia PDF Downloads 49

Authors: Pavel E. Mikriukov

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The demand for natural gas (NG) is increasing every year around the world, so it is necessary to produce and transport NG in large quantities. To solve this problem, liquefied natural gas (LNG) plants are used, using different equipment and different technologies to achieve the required LNG quality. To determine the best efficiency of the LNG liquefaction plant, it is necessary to analyze the equipment used in this process and identify other technological solutions for LNG production using more productive and energy-efficient equipment. Based on this, mathematical models of the technological process of the LNG plant were created, which are based on a two-circuit system of heat exchange equipment and a nitrogen isolated cycle for NG cooling. The final liquefaction of natural gas is performed on the construction of the basic principle of the Joule-Thompson effect. The pressure and temperature drop are considered on different types of equipment such as throttle valve, which was used in the basic scheme; turbo expander and supersonic separator, which act as new equipment, to be compared with the efficiency of the basic scheme of the unit. New configurations of LNG plants are suggested, which can be used in almost all LNG facilities. As a result of the analysis, it turned out that the turbo expander and the supersonic separator have comparatively equal potential in comparison with the baseline scheme execution on the throttle valve. A more rational method of selecting the technology and the equipment used for natural gas liquefaction can improve the efficiency of low-tonnage plants and reduce the cost of gas for own needs.

Keywords: gas liquefaction, gas, Joule-Thompson effect, LNG, low-tonnage LNG, supersonic separator, Throttle valve, turbo expander

Procedia PDF Downloads 111

Authors: Thamer Kubat, Riadh Al Mahiadi, Ahmad Shayan

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The alkali-aggregate reaction (AAR) in concrete has a negative influence on the mechanical properties and durability of concrete. Confinement by carbon fiber reinforced polymer (CFRP) is an effective method of treatment for some AAR-affected elements. Eighteen reinforced columns affected by different levels of expansion due to AAR were confined using CFRP to evaluate the effect of expansion level on confinement efficiency. Strength and strain capacities (axial and circumferential) were measured using photogrammetry under uniaxial compressive loading to evaluate the efficiency of CFRP wrapping for the rehabilitation of affected columns. In relation to uniaxial compression capacity, the results indicated that the confinement of AAR-affected columns by one layer of CFRP is sufficient to reach and exceed the load capacity of unaffected sound columns. Parallel to the experimental study, finite element (FE) modeling using ATENA software was employed to predict the behavior of CFRP-confined damaged concrete and determine the possibility of using the model in a parametric study by simulating the number of CFRP layers. A comparison of the experimental results with the results of the theoretical models showed that FE modeling could be used for the prediction of the behavior of confined AAR-damaged concrete.

Keywords: ATENA, carbon fiber reinforced polymer (CFRP), confinement efficiency, finite element (FE)

Procedia PDF Downloads 76

Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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This paper will focus on the suitability of a trapped vortex combustor as a candidate for gas turbine combustor objectives to minimize pressure drop across the combustor and investigate aerodynamic performance. Non-reacting simulation of axisymmetric cavity trapped vortex combustors were simulated to investigate the pressure drop for various cavity aspect ratios of 0.3, 0.6, and 1 and for air mass flow rates of 14 m/s, 28 m/s, and 42 m/s. A numerical study of an axisymmetric trapped vortex combustor was carried out by using two-dimensional and three-dimensional computational domains. A comparison study was conducted between Reynolds Averaged Navier Stokes (RANS) k-ε Realizable with enhanced wall treatment and RANS k-ω Shear Stress Transport (SST) models to find the most suitable turbulence model. It was found that the k-ω SST model gives relatively close results to experimental outcomes. The numerical results were validated and showed good agreement with the experimental data. Pressure drop rises with increasing air mass flow rate, and the lowest pressure drop was observed at 0.6 cavity aspect ratio for all air mass flow rates tested, which agrees with the experimental outcome. A mixing enhancement study showed that 30-degree angle air injectors provide improved fuel-air mixing.

Keywords: aerodynamic, computational fluid dynamics, propulsion, trapped vortex combustor

Procedia PDF Downloads 86

Authors: R. Nandhini, Gaurab Mudbhari

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Ranging from the field of health care to self-driving cars, machine learning and deep learning algorithms have revolutionized the field with the proper utilization of images and visual-oriented data. Segmentation, regression, classification, clustering, dimensionality reduction, etc., are some of the Machine Learning tasks that helped Machine Learning and Deep Learning models to become state-of-the-art models for the field where images are key datasets. Among these tasks, classification and clustering are essential but difficult because of the intricate and high-dimensional characteristics of image data. This finding examines and assesses advanced techniques in supervised classification and unsupervised clustering for image datasets, emphasizing the relative efficiency of Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Deep Embedded Clustering (DEC), and self-supervised learning approaches. Due to the distinctive structural attributes present in images, conventional methods often fail to effectively capture spatial patterns, resulting in the development of models that utilize more advanced architectures and attention mechanisms. In image classification, we investigated both CNNs and ViTs. One of the most promising models, which is very much known for its ability to detect spatial hierarchies, is CNN, and it serves as a core model in our study. On the other hand, ViT is another model that also serves as a core model, reflecting a modern classification method that uses a self-attention mechanism which makes them more robust as this self-attention mechanism allows them to lean global dependencies in images without relying on convolutional layers. This paper evaluates the performance of these two architectures based on accuracy, precision, recall, and F1-score across different image datasets, analyzing their appropriateness for various categories of images. In the domain of clustering, we assess DEC, Variational Autoencoders (VAEs), and conventional clustering techniques like k-means, which are used on embeddings derived from CNN models. DEC, a prominent model in the field of clustering, has gained the attention of many ML engineers because of its ability to combine feature learning and clustering into a single framework and its main goal is to improve clustering quality through better feature representation. VAEs, on the other hand, are pretty well known for using latent embeddings for grouping similar images without requiring for prior label by utilizing the probabilistic clustering method.

Keywords: machine learning, deep learning, image classification, image clustering

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Authors: Andrew J. Zacharias

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The forest garden approach (FGA) was established by Trees for the Future (TREES) over the organization’s 30 years of agroforestry projects in Sub-Saharan Africa. This method transforms traditional agricultural systems into highly managed gardens that produce food and marketable products year-round. The effects of the FGA on food security, dietary diversity, and economic resilience have been measured closely, and TREES has begun to closely monitor the environmental impacts through the use of sensors mounted on unmanned aerial vehicles, commonly known as 'drones'. These drones collect thousands of pictures to create 3-D models in both the visible and the near-infrared wavelengths. Analysis of these models provides TREES with quantitative and qualitative evidence of improvements to the annual above-ground biomass and leaf area indices, as measured in-situ using NDVI calculations.

Keywords: agroforestry, biomass, drones, NDVI

Procedia PDF Downloads 157

Authors: Yasemin Kaya, Ahmet N. Eraslan

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In this study, the thermoelastic behavior of a long tube is studied by taking into account the temperature dependency of all mechanical and thermal properties. As the tube is heated slowly, an uncoupled solution procedure is adopted under free and radially constrained boundary conditions. The nonlinear heat conduction equation is solved by a finite element collocation procedure and the corresponding distributions of stress and strain are computed by shooting iterations. The computational model is verified in comparison to the analytical solution by shutting down the temperature dependency of physical properties. In the analysis, experimental data available in the literature is used to describe the coefficient of thermal expansion $\alpha$, the thermal conductivity $k$, the modulus of rigidity $G$, the yield strength $\sigma_{0}$, and the Poisson's ratio $\nu$ of Nickel. Results of the analysis are presented in comparison to those having constant physical properties. As a result of the calculations, the temperature dependency of the material properties should be taken into account at higher temperature ranges.

Keywords: thermoelasticity, long tube, temperature-dependent properties, internal heating

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Authors: Neha Bhardwaj

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In this paper, we consider positive linear operators and study the Voronovskaya type result of the operator then obtain an error estimate in terms of the higher order modulus of continuity of the function being approximated and its A-statistical convergence. Also, we compute the corresponding rate of A-statistical convergence for the linear positive operators.

Keywords: Poisson distribution, Voronovskaya, modulus of continuity, a-statistical convergence

Procedia PDF Downloads 333

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

Procedia PDF Downloads 567

Authors: Asmae Tafraouti, Yasmina Layouni, Pascal Kleimann

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The growing market for Microsystems (MST) and Micro-Electromechanical Systems (MEMS) is driving the research for alternative manufacturing techniques to microelectronics-based technologies, which are generally expensive and time-consuming. Hot-embossing and micro-injection modeling of thermoplastics appear to be industrially viable processes. However, both require the use of master models, usually made in hard materials such as steel. These master models cannot be fabricated using standard microelectronics processes. Thus, other micromachining processes are used, such as laser machining or micro-electrical discharge machining (µEDM). In this work, µEDM has been used. The principle of µEDM is based on the use of a thin cylindrical micro-tool that erodes the workpiece surface. The two electrodes are immersed in a dielectric with a distance of a few micrometers (gap). When an electrical voltage is applied between the two electrodes, electrical discharges are generated, which cause material machining. In order to produce master models with high resolution and smooth surfaces, it is necessary to well control the discharge mechanism. However, several problems are encountered, such as a random electrical discharge process, the fluctuation of the discharge energy, the electrodes' polarity inversion, and the wear of the micro-tool. The effect of different parameters, such as the applied voltage, the working capacitor, the micro-tool diameter, and the initial gap, has been studied. This analysis helps to improve the machining performances, such as the workpiece surface condition and the lateral crater's gap.

Keywords: craters, electrical discharges, micro-electrical discharge machining, microsystems

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Authors: Bader Alkandari, Jamal Y. Madouh, Ahmad M. Alkandari, Anwar A. Alnaqi

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A new formulation of fuzzy linear estimation problem is presented. It is formulated as a linear programming problem. The objective is to minimize the spread of the data points, taking into consideration the type of the membership function of the fuzzy parameters to satisfy the constraints on each measurement point and to insure that the original membership is included in the estimated membership. Different models are developed for a fuzzy triangular membership. The proposed models are applied to different examples from the area of fuzzy linear regression and finally to different examples for estimating the electrical load on a busbar. It had been found that the proposed technique is more suited for electrical load estimation, since the nature of the load is characterized by the uncertainty and vagueness.

Keywords: fuzzy regression, load estimation, fuzzy linear parameters, electrical load estimation

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Authors: N. P. Bhandary, R. C. Tiwari, R. Yatabe

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The research employs finite element method to evaluate the stability of roadside settlements slopes from Barpak to Yamagaon through Laprak village of Gorkha, Nepal after the 7.8Mw 2015 Barpak, Gorkha, Nepal earthquake. It includes three major villages of Gorkha, i.e., Barpak, Laprak and Yamagaun that were devastated by 2015 Gorkhas’ earthquake. The road head distance from the Barpak to Laprak and Laprak to Yamagaun are about 14 and 29km respectively. The epicentral distance of main shock of magnitude 7.8 and aftershock of magnitude 6.6 were respectively 7 and 11 kilometers (South-East) far from the Barpak village nearer to Laprak and Yamagaon. It is also believed that the epicenter of the main shock as said until now was not in the Barpak village, it was somewhere near to the Yamagaun village. The chaos that they had experienced during the earthquake in the Yamagaun was much more higher than the Barpak. In this context, we have carried out a detailed study to investigate the stability of Yamagaun settlements slope as a case study, where ground fissures, ground settlement, multiple cracks and toe failures are the most severe. In this regard, the stability issues of existing settlements and proposed road alignment, on the Yamagaon village slope are addressed, which is surrounded by many newly activated landslides. Looking at the importance of this issue, field survey is carried out to understand the behavior of ground fissures and multiple failure characteristics of the slopes. The results suggest that the Yamgaun slope in Profile 2-2, 3-3 and 4-4 are not safe enough for infrastructure development even in the normal soil slope conditions as per 2, 3 and 4 material models; however, the slope seems quite safe for at Profile 1-1 for all 4 material models. The result also indicates that the first three profiles are marginally safe for 2, 3 and 4 material models respectively. The Profile 4-4 is not safe enough for all 4 material models. Thus, Profile 4-4 needs a special care to make the slope stable.

Keywords: earthquake, finite element method, landslide, stability

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Authors: Anahita Yarahmadi, Nazanin Mahboobi, Nahid Sadat Rahmatpour Nori, Mohammad Hossein Bijeh Keshavarzi, Mohammad Javad Shakori

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This research aimed at considering biological fertilizer effect and chemical fertilizer on the quantitative characteristics of Sweet wormwood (Artemisia annua L.), an experiment was carried out in factorial design in completely randomized design with 4 replications in an experimental greenhouse which was located in Tehran. Experimental treatment involved chemical fertilizers (Nitrogen, Phosphorus) in4 levels and biological fertilizers in 4 levels (control, Nitroxin, Bio-phosphorus and Vemricompost). Results showed that using biological fertilizers and increasing different levels of chemical fertilizers (N, P) had significant effects on all the characteristics. Considering means comparison showed that biological fertilizers lead to significant enhancement on all the characteristics and among biological fertilizers, Vermicompost treatment has the most effect. Considering means comparison tables of different levels of chemical fertilizer have been found that (N80P80) had the most increase on characteristics.

Keywords: Artemisia annua L, bio-fertilizer, chemical fertilizer, vermicompost

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Authors: Nabil A. A. Mohamed, Alaa A. A. Balbaa, Khaled E. Ayad

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Osteoarthritis (OA) of the knee is the most common form of arthritis and leads to more activity limitations (e.g., disability in walking and stair climbing) than any other disease, especially in the elderly. Recently, impaired proprioceptive accuracy of the knee has been proposed as a local factor in the onset and progression of radiographic knee OA (ROA). Purpose: To compare the clinical and radiological findings in healthy with that of knee OA. Also, to determine if there is a correlation between the clinical and radiological findings in patients with knee OA. Subjects: Fifty one patients diagnosed as unilateral or bilateral knee OA with age ranged between 35-70 years, from both gender without any previous history of knee trauma or surgery, and twenty one normal subjects with age ranged from 35 - 68 years. METHODS: peak torque/body weight (PT/BW) was recorded from knee extensors at isokinetic isometric mode at angle of 45 degree. Also, the Absolute Angular Error was recorded at 45O and 30O to measure joint position sense (JPS). They made anteroposterior (AP) plain X-rays from standing semiflexed knee position and their average score of Timed Up and Go test(TUG) and WOMAC were recorded as a measure of knee pain, stiffness and function. Comparison between the mean values of different variables in the two groups was performed using unpaired student t test. The P value less or equal to 0.05 was considered significant. Results: There were significant differences between the studied variables between the experimental and control groups except the values of AAE at 30O. Also, there were no significant correlation between the clinical findings (pain, function, muscle strength and proprioception) and the severity of arthritic changes in X-rays. CONCLUSION: From the finding of the current study we can conclude that there were a significant difference between the both groups in all studied parameters (the WOMAC, functional level, quadriceps muscle strength and the joint proprioception). Also this study did not support the dependency on radiological findings in management of knee OA as the radiological features did not necessarily indicate the level of structural damage of patients with knee OA and we should consider the clinical features in our treatment plan.

Keywords: joint position sense, peak torque, proprioception, radiological knee osteoarthritis

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Authors: Pumela Msweli, Dexter L. Ryneveldt

Abstract:

This paper seeks to shed light on institutional logics and institutionalization processes that influence the successful implementation of financial sector regulations. We use the neo-institutional theory lens to interrogate how the newly promulgated Financial Sector Regulations Act (FSRA) provides for the institutionalisation of the Twin Peaks Model. With the enactment of FSRA, previous financial regulatory institutions were dismantled, and new financial regulators established. In point, the Financial Services Conduct Authority (FSCA) replaced the Financial Services Board (FSB), and accordingly, the Prudential Authority (PA) was established. FSRA is layered with complexities that make it mandatory to co-exist, cooperate, and collaborate with other institutions to fulfill FSRA’s overall financial stability objective. We use content analysis of the financial regulations that established the Twin Peaks Models (TPM) in South Africa and in the Netherlands, to map out the three-stage institutionalization processes: (1) habitualisation, (2) objectification and (3) sedimentation. This allowed for a comparison of how South Africa, as a developing country and Netherlands as a developed country, have institutionalized the Twin Peak model. We provide valuable insights into how differences in the institutional and societal logics of the developing and developed contexts shape the institutionalization of financial regulations.

Keywords: financial industry, financial regulation, financial stability, institutionalisation, habitualization, objectification, sedimentation, twin peaks model

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Authors: Sajeesh Sulaiman, Gomathisankar A., Aravind Devaraj, Aswin R., Vijay Kumar G., Rachana Raj

Abstract:

Wind turbines are the next big answer to the emerging and ever-growing demand for electricity, and this need is increasing day by day. These high mast structures, whether on land or on the sea, has also become one of the big sources of electromagnetic interferences (EMI) in the not so distant past. With the emergence of the AC-AC converter and drawing of large power cables through the wind turbine towers has made this clean and efficient source of renewable energy to become one of the culprits in creating electromagnetic interference. This paper will present the sources of such EMIs, a comparison of radiated emissions (both electric and magnetic field) patterns in wind turbine towers for both onshore and offshore wind turbines and close look into the IEC 61400-40 (new standard for EMC design on wind turbine). At present, offshore wind turbines are tested in onshore facilities. This paper will present the anomaly in results for offshore wind turbines when tested in onshore, which the existing standards and the upcoming standards have failed to address.

Keywords: emissions, electric field, magnetic field, wind turbine, tower, standards and regulations

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

Abstract:

Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor

Procedia PDF Downloads 338

Authors: R. Stoyanova, R. Dimova, M. Tarnovska, T. Boeva, R. Dimov, I. Doykov

Abstract:

Patient safety culture (PSC) is an essential component of quality of healthcare. Improving PSC is considered a priority in many developed countries. Specialized software platform for registration and evaluation of hospital patient safety culture has been developed with the support of the Medical University Plovdiv Project №11/2017. The aim of the study is to assess the status of PSC in Bulgarian hospitals and to compare it to that in USA and Croatian hospitals. Methods: The study was conducted from June 01 to July 31, 2018 using the web-based Bulgarian Version of the Hospital Survey on Patient Safety Culture Questionnaire (B-HSOPSC). Two hundred and forty-eight medical professionals from different hospitals in Bulgaria participated in the study. To quantify the differences of positive scores distributions for each of the 42 HSOPSC items between Bulgarian, Croatian and USA samples, the x²-test was applied. The research hypothesis assumed that there are no significant differences between the Bulgarian, Croatian and US PSCs. Results: The results revealed 14 significant differences in the positive scores between the Bulgarian and Croatian PSCs and 15 between the Bulgarian and the USA PSC, respectively. Bulgarian medical professionals provided less positive responses to 12 items compared with Croatian and USA respondents. The Bulgarian respondents were more positive compared to Croatians on the feedback and communication of medical errors (Items - C1, C4, C5) as well as on the employment of locum staff (A7) and the frequency of reported mistakes (D1). Bulgarian medical professionals were more positive compared with their USA colleagues on the communication of information at shift handover and across hospital units (F5, F7). The distribution of positive scores on items: ‘Staff worries that their mistakes are kept in their personnel file’ (RA16), ‘Things ‘fall between the cracks’ when transferring patients from one unit to another’ (RF3) and ‘Shift handovers are problematic for patients in this hospital’ (RF11) were significantly higher among Bulgarian respondents compared with Croatian and US respondents. Conclusions: Significant differences of positive scores distribution were found between Bulgarian and USA PSC on one hand and between Bulgarian and Croatian on the other. The study reveals that distribution of positive responses could be explained by the cultural, organizational and healthcare system differences.

Keywords: patient safety culture, healthcare, HSOPSC, medical error

Procedia PDF Downloads 136