Search results for: parameter selection

Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Additive manufacturing gains the popularity in recent times, due to its capability to create prototype as well functional as end use product directly from CAD data without any specific requirement of tooling. Fused deposition modeling (FDM) is one of the widely used additive manufacturing techniques that are used to create functional end use part of polymer that is comparable with the injection-molded parts. FDM printed part has an application in various fields such as automobile, aerospace, medical, electronic, etc. However, application of FDM part is greatly affected by poor mechanical properties. Proper selection of the process parameter could enhance the mechanical performance of the printed part. In the present study, experimental investigation has been carried out to study the behavior of the mechanical performance of the printed part with respect to process variables. Three process variables viz. raster angle, raster width and layer height have been varied to understand its effect on tensile strength. Further, effect of process variables on fractured surface has been also investigated.

Keywords: 3D Printing, fused deposition modeling, layer height, raster angle, raster width, tensile strength

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Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

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Authors: Maram Elkady

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Purpose: The purpose behind this study is to determine the impact of some factors on achieving successful accounting information systems (AIS) outsourcing in Egypt, taking into account two factors: the selection of an effective accounting service provider and the quality relationships between the client firm and the accounting service provider. The researcher measured outsourcing success through the perceived benefits, including (strategic, technological, and economic benefits). Design/Methodology/Approach: A survey was carried out by means of questionnaires answered by 152 small and medium Egyptian firms outsourcing their accounting activities. The researcher targeted the personnel in the client firms who were in direct contact with the accounting outsourcer. The hypotheses were tested through multiple regression analysis using SPSS 24 and AMOS 22. Findings: Building a quality relationship with the provider is found to have more impact than the effective selection of the AIS provider on the success of the AIS outsourcing process. Originality/Value: The researcher found that some proxies of each success determinant can be more influential than others based on type of benefits perceived from AIS outsourcing (strategic, technological, and economic).

Keywords: accounting information system, AIS, outsourcing, successful outsourcing, AIS service provider selection, relationship with the accounting service provider

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Authors: G. N. Sekhar, P. G. Siddheshwar, G. Jayalatha, R. Prakash

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The problem of thermal convection in temperature and magnetic field sensitive Newtonian ferromagnetic liquid is studied in the presence of uniform vertical magnetic field and throughflow. Using a combination of Galerkin and shooting techniques the critical eigenvalues are obtained for stationary mode. The effect of Prandtl number (Pr > 1) on onset is insignificant and nonlinearity of non-buoyancy magnetic parameter M3 is found to have no influence on the onset of ferroconvection. The magnetic buoyancy number, M1 and variable viscosity parameter, V have destabilizing influences on the system. The effect of throughflow Peclet number, Pe is to delay the onset of ferroconvection and this effect is independent of the direction of flow.

Keywords: ferroconvection, magnetic field dependent viscosity, temperature dependent viscosity, throughflow

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Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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Authors: Yue Huang, Yiheng Feng

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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

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Authors: Al Omari Mohammed Ahmed

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This paper focuses on Maximum Likelihood Estimator with Covariate. Covariates are incorporated into the Weibull model. Under this regression model with regards to maximum likelihood estimator, the parameters of the covariate, shape parameter, survival function and hazard rate of the Weibull regression distribution with right censored data are estimated. The mean square error (MSE) and absolute bias are used to compare the performance of Weibull regression distribution. For the simulation comparison, the study used various sample sizes and several specific values of the Weibull shape parameter.

Keywords: weibull regression distribution, maximum likelihood estimator, survival function, hazard rate, right censoring

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Ayodele Oluwole Alejo

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Wall finishes are the term to describe an application over a wall surface to provide a suitable surface. Wall finishes are smelt, touched and seen by building occupiers even colour and design affects the user psychology and the atmosphere of our building. Building users/owners seem not to recognize the function of various wall finishes in building and factors to be considered in selecting them suitable for the type and purpose of proposed buildings. Therefore, defects such as deterioration, dampness, and stain may occur when comparisons of wall finishes are not made before the selection of appropriate materials at the design stage with knowledge of the various factors that may hinder the performance or maintenance culture of proposed building of a particular location. This research work investigates and compares various wall finishes in building. Buildings in Ondo state, Nigeria were used as the target area to conduct the research works. The factors bearing on various wall finishes were analyzed to find out their individual and collective impact using suitable analytical tools. The findings revealed that paint with high percentage score was the most preferred wall finishes, whereas wall paper was ranked the least by the respondent findings, Factors considered most in the selection of wall finishes was durability with the highest ranking percentage and least was the cost. The study recommends that skilled worker should carry out operations, quality product should be used and all of wall finishes and materials should be considered before selection.

Keywords: building, construction, design, finishes, wall

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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Authors: Mukesh Kumar Shah, Tushar Gupta

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An Upgraded Cuckoo Search Algorithm is proposed here to solve optimization problems based on the improvements made in the earlier versions of Cuckoo Search Algorithm. Short comings of the earlier versions like slow convergence, trap in local optima improved in the proposed version by random initialization of solution by suggesting an Improved Lambda Iteration Relaxation method, Random Gaussian Distribution Walk to improve local search and further proposing Greedy Selection to accelerate to optimized solution quickly and by “Study Nearby Strategy” to improve global search performance by avoiding trapping to local optima. It is further proposed to generate better solution by Crossover Operation. The proposed strategy used in algorithm shows superiority in terms of high convergence speed over several classical algorithms. Three standard algorithms were tested on a 6-generator standard test system and the results are presented which clearly demonstrate its superiority over other established algorithms. The algorithm is also capable of handling higher unit systems.

Keywords: economic dispatch, gaussian selection operator, prohibited operating zones, ramp rate limits

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Authors: Habtamu Garoma Debela, Gemechis File Duressa

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In this work, our primary interest is to provide ε-uniformly convergent numerical techniques for solving singularly perturbed semilinear boundary value problems with non-local boundary condition. These singular perturbation problems are described by differential equations in which the highest-order derivative is multiplied by an arbitrarily small parameter ε (say) known as singular perturbation parameter. This leads to the existence of boundary layers, which are basically narrow regions in the neighborhood of the boundary of the domain, where the gradient of the solution becomes steep as the perturbation parameter tends to zero. Due to the appearance of the layer phenomena, it is a challenging task to provide ε-uniform numerical methods. The term 'ε-uniform' refers to identify those numerical methods in which the approximate solution converges to the corresponding exact solution (measured to the supremum norm) independently with respect to the perturbation parameter ε. Thus, the purpose of this work is to develop, analyze, and improve the ε-uniform numerical methods for solving singularly perturbed problems. These methods are based on nonstandard fitted finite difference method. The basic idea behind the fitted operator, finite difference method, is to replace the denominator functions of the classical derivatives with positive functions derived in such a way that they capture some notable properties of the governing differential equation. A uniformly convergent numerical method is constructed via nonstandard fitted operator numerical method and numerical integration methods to solve the problem. The non-local boundary condition is treated using numerical integration techniques. Additionally, Richardson extrapolation technique, which improves the first-order accuracy of the standard scheme to second-order convergence, is applied for singularly perturbed convection-diffusion problems using the proposed numerical method. Maximum absolute errors and rates of convergence for different values of perturbation parameter and mesh sizes are tabulated for the numerical example considered. The method is shown to be ε-uniformly convergent. Finally, extensive numerical experiments are conducted which support all of our theoretical findings. A concise conclusion is provided at the end of this work.

Keywords: nonlocal boundary condition, nonstandard fitted operator, semilinear problem, singular perturbation, uniformly convergent

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Authors: Hamidoddin Yousife

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Drilling optimization requires a prediction of drilling rate of penetration (ROP) since it provides a significant reduction in drilling costs. There are several factors that can have an impact on the ROP, both controllable and uncontrollable. Numerous drilling penetration rate models have been considered based on drilling parameters. This papers considered the effect of proper drilling parameter selection such as bit, Mud Type, applied weight on bit (WOB), Revolution per minutes (RPM), and flow rate on drilling optimization and drilling cost reduction. A predicted analysis is used in real-time drilling performance to determine the optimal drilling operation. As a result of these modeling studies, the real data collected from three directional wells at Azadegan oil fields, Iran, was verified and adjusted to determine the drillability of a specific formation. Simulation results and actual drilling results show significant improvements in inaccuracy. Once simulations had been validated, optimum drilling parameters and equipment specifications were determined by varying weight on bit (WOB), rotary speed (RPM), hydraulics (hydraulic pressure), and bit specification for each well until the highest drilling rate was achieved. To evaluate the potential operational and economic benefits of optimizing results, a qualitative and quantitative analysis of the data was performed.

Keywords: drlling, cost, optimization, parameters

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Authors: Ebtesam. E. Ateia, L. M. Salah, A. H. El-Bassuony

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The aim of the presented study was the possibility of developing a nanosized material with enhanced structural properties that was suitable for many applications. Nanostructure ferrite of composition Ni0.5 Zn0.5 Cr0.1 Fe1.9 O4 were prepared by sol–gel, co-precipitation, citrate-gel, flash and oxalate precursor methods. The Structural and micro structural analysis of the investigated samples were carried out. It was observed that the lattice parameter of cubic spinel was constant, and the positions of both tetrahedral and the octahedral bands had a fixed position. The values of the lattice parameter had a significant role in determining the stoichiometric cation distribution of the composition.The average crystalline sizes of the investigated samples were from 16.4 to 69 nm. Discussion was made on the basis of a comparison of average crystallite size of the investigated samples, indicating that the co-precipitation method was the the effective one in producing small crystallite sized samples.

Keywords: chemical preparation, ferrite, grain size, nanocomposites, sol-gel

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Authors: Polycarp Igbojekwe

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The main objective of this study was to determine if emotional labour has become a criterion in performance appraisal, job description, selection, and training schemes in the hotel industry in Nigeria. Our main assumption was that majority of hotel organizations have not built emotional labour into their human resources management schemes. Data were gathered by the use of structured questionnaires designed in Likert format, and interviews. The focus group was managers of the selected hotels. Analyses revealed that majority of the hotels have not built emotional labour into their human resources schemes particularly in the 1, 2, and 3-star hotels. It was observed that service employees of 1, 2, and 3-star hotels have not been adequately trained to perform emotional labour; a critical factor in quality service delivery. Managers of 1, 2, and 3-star hotels have not given serious thought to emotional labour as a critical factor in quality service delivery. The study revealed that suitability of an individual’s characteristics is not being considered as a criterion for selection and performance appraisal for service employees. The implication of this is that, person-job-fit is not seriously considered. It was observed that there has been a disconnect between required emotional competency, its recognition, evaluation, and training. Based on the findings of this study, it is concluded that selection, training, job description and performance appraisal instruments in use in hotels in Nigeria are inadequate. Human resource implications of the findings in this study are presented. It is recommended that hotel organizations should re-design and plan the emotional content and context of their human resources practices to reflect the emotional demands of front line jobs in the hotel industry and the crucial role emotional labour plays during service encounters.

Keywords: emotional labour, employee selection, job description, performance appraisal, person-job-fit, employee compensation

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Authors: Khaled M. Alqahtani

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Copy number alterations (CNA) are variations in the structure of the genome, where certain regions deviate from the typical two chromosomal copies. These alterations are pivotal in understanding tumor progression and are indicative of patients' survival outcomes. However, effectively modeling patients' survival based on their genomic CNA profiles while identifying relevant genomic regions remains a statistical challenge. Various methods, such as the Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties, have been proposed but often overlook the inherent dependencies between genomic regions, leading to results that are hard to interpret. In this study, we enhance the elastic net penalty by incorporating an additional penalty that accounts for these dependencies. This approach yields smooth parameter estimates and facilitates variable selection, resulting in a sparse solution. Our findings demonstrate that this method outperforms other models in predicting survival outcomes, as evidenced by our simulation study. Moreover, it allows for a more meaningful interpretation of genomic regions associated with patients' survival. We demonstrate the efficacy of our approach using both real data from a lung cancer cohort and simulated datasets.

Keywords: copy number alterations, cox proportional hazard, lung cancer, regression, sparse solution

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Aman Sharma, Sonali Sengupta

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The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

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Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar

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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.

Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry

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Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

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One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

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Authors: C. J. Coetzee, E. Horn

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One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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Authors: Sheikh Samsuzzhan Alam

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The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Richard E. Miller

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12.7-mm thick plates of 6061-T6511 aluminum alloy and high hardness steel (528 HV) were successfully joined by a friction stir bonding process using a tungsten-rhenium stir tool. Process parameter variation experiments, which included tool design geometry, plunge and traverse rates, tool offset, spindle tilt, and rotation speed, were conducted to develop a parameter set which yielded a defect free joint. Laboratory tensile tests exhibited yield stresses which exceed the strengths of comparable AA6061-to-AA6061 fusion and friction stir weld joints. Scanning electron microscopy and energy dispersive X-ray spectroscopy analysis also show atomic diffusion at the material interface region.

Keywords: dissimilar materials, friction stir, welding, materials science

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Authors: Kamel Hachour, Lydia Sadeg, Djamel Sersab, Tassadit Bellahcen

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The hydrostatic stress is, for polymers, a significant parameter which affects the yield behavior of these materials. In this work, we investigate the influence of this parameter on yield behavior of the high density polyethylene (hdpe). Some tests on specimens with diverse geometries are described in this paper. Uniaxial tests: tensile on notched round bar specimens with different curvature radii, compression on cylindrical specimens and simple shear on parallelepiped specimens were performed. Biaxial tests with various combinations of tensile/compressive and shear loading on butterfly specimens were also realized in order to determine the hydrostatic stress for different states of solicitation. The experimental results show that the yield stress is very affected by the hydrostatic stress developed in the material during solicitations.

Keywords: biaxial tests, hdpe, Hydrostatic stress, yield behavior

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Authors: Sangeeta Yadav, Mantosh Biswas

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In this paper, we proposed an improved color based K-mean algorithm for clustering of satellite Image (SAR). Our method comprises of two stages. The first step is an interactive selection process where users are required to input the number of colors (ncolor), number of clusters, and then they are prompted to select the points in each color cluster. In the second step these points are given as input to K-mean clustering algorithm that clusters the image based on color and Minimum Square Euclidean distance. The proposed method reduces the mixed pixel problem to a great extent.

Keywords: cluster, ncolor method, K-mean method, interactive selection process

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

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Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

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Authors: Yinwei Lin, Cha'o-Kuang Chen

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In this article, the Laplace Adomian transform method (LADM) and double decomposition method (DDM) are used to solve the annular hyperbolic profile fins with variable thermal conductivity. As the thermal conductivity parameter ε is relatively large, the numerical solution using DDM become incorrect. Moreover, when the terms of DDM are more than seven, the numerical solution using DDM is very complicated. However, the present method can be easily calculated as terms are over seven and has more precisely numerical solutions. As the thermal conductivity parameter ε is relatively large, LADM also has better accuracy than DDM.

Keywords: fins, thermal conductivity, Laplace transform, Adomian, nonlinear

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Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

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Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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Authors: Motahar Reza, Rajni Chahal, Neha Sharma

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This article addresses the boundary layer flow and heat transfer of Casson fluid over a nonlinearly permeable stretching surface with chemical reaction in the presence of variable magnetic field. The effect of thermal radiation is considered to control the rate of heat transfer at the surface. Using similarity transformations, the governing partial differential equations of this problem are reduced into a set of non-linear ordinary differential equations which are solved by finite difference method. It is observed that the velocity at fixed point decreases with increasing the nonlinear stretching parameter but the temperature increases with nonlinear stretching parameter.

Keywords: boundary layer flow, nonlinear stretching, Casson fluid, heat transfer, radiation

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