Search results for: variable reduction

Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control

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Authors: Bougema Theodore Ntenkeh, Chi-bikom Barbara Kyien

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The reduction of poverty and hunger sits at the heart of the United Nations 2030 Agenda for Sustainable Development, and are the first two of the Sustainable Development Goals. The World Food Day celebrated on the 16th of October every year, highlights the need for people to have physical and economic access at all times to enough nutritious and safe food to live a healthy and active life; while the world poverty day celebrated on the 17th of October is an opportunity to acknowledge the struggle of people living in poverty, a chance for them to make their concerns heard, and for the community to recognize and support poor people in their fight against poverty. The association between household food security and poverty reduction is not only sparse in Cameroon but mostly qualitative. The paper therefore investigates the effect of household food security on poverty reduction in Cameroon quantitatively using data from the Cameroon Household Consumption Survey collected by the Government Statistics Office. The methodology employed five indicators of household food security using the Multiple Correspondence Analysis and poverty is captured as a dummy variable. Using a control function technique, with pre and post estimation test for robustness, the study postulates that household food security has a positive and significant effect on poverty reduction in Cameroon. A unit increase in the food security score reduces the probability of the household being poor by 31.8%, and this effect is statistically significant at 1%. The result further illustrates that the age of the household head and household size increases household poverty while households residing in urban areas are significantly less poor. The paper therefore recommends that households should diversify their food intake to enhance an effective supply of labour in the job market as a strategy to reduce household poverty. Furthermore, family planning methods should be encouraged as a strategy to reduce birth rate for an equitable distribution of household resources including food while the government of Cameroon should also develop the rural areas given that trend in urbanization are associated with the concentration of productive economic activities, leading to increase household income, increased household food security and poverty reduction.

Keywords: food security, poverty reduction, SDGs, Cameroon

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Authors: Khaled A. Madi, Abdulalhakim O. Naji, Hassouna A. Aalaoh, Elmahdi Eldeeb

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Solar energy is one of the cleanest energy sources with no environmental impact. Due to rapid increase in industrial as well as domestic needs, solar energy becomes a good candidate for safe and easy to handle energy source, especially after it becomes available due to reduction of manufacturing price. The main part of the solar inverter system is the inverter where the DC is inverted to AC, where we try to minimize the loss of power to the minimum possible level by the use of microcontroller. In this work, a deep investigation is made experimentally as well as theoretically for a microcontroller based variable frequency power inverter. The microcontroller will provide the variable frequency Pulse Width Modulation (PWM) signal that will control the switching of the gate of the Insulating Gate Bipolar Transistor (IGBT) with less harmonics at the output of power inverter which can be fed to the public grid at high quality. The proposed work for single phase as well as three phases is also simulated using Matlab/Simulink where we found a good agreement between the simulated and the practical results, even though the experimental work were done in the laboratory of the academy.

Keywords: solar, inverter, PV, solar inverter system

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Authors: Edris Rawashdeh, I. Abu-Falahah, H. M. Jaradat

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The variable-coefficient non-linear dispersive wave equation is investigated with the aid of symbolic computation. By virtue of a newly developed simplified bilinear method, multi-soliton solutions for such an equation have been derived. Effects of the inhomogeneities of media and nonuniformities of boundaries, depicted by the variable coefficients, on the soliton behavior are discussed with the aid of the characteristic curve method and graphical analysis.

Keywords: dispersive wave equations, multiple soliton solution, Hirota Bilinear Method, symbolic computation

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Authors: Xiuqin Ma, Hongwu Qin

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A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.

Keywords: soft sets, parameter reduction, normal parameter reduction, online shopping

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Authors: Adewale Oladapo, C. A. Afolami

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The study analyzed the effect of micro credit access on poverty reduction among small scale women entrepreneurs in Ondo state, Nigeria. Primary data were collected in a cross-sectional survey of 100 randomly selected woman entrepreneurs. These were drawn in multistage sampling process covering four local government areas (LGAS). Data collected include socio economics characteristics of respondents, access to micro credit, sources of micro credit, and constraints faced by the entrepreneur in sourcing for micro credit. Data were analyzed using descriptive statistics, Foster, Greer and Thorbecke (FGT) index of poverty measure, Gini coefficients and probit regression analysis. The study found that respondents sampled for the survey were within the age range of 31-40 years with mean age 38.6%. Mostly (56.0%) of the respondents were educated to the tune of primary school. Majority (87.0%) of the respondents were married with fairly large household size of (4-5). The poverty index analysis revealed that most (67%) of the sample respondents were poor. The result of the Probit regression analyzed showed that income was a significant variable in micro credit access, while the result of the Gini coefficient revealed a very high income inequality among the respondents. The study concluded that most of the respondents were poor and return on investment (income) was an important variable that increased the chance of respondents in sourcing for micro-credit loan and recommended that income realized by entrepreneur should be properly documented to facilitate loan accessibility.

Keywords: entrepreneurs, income, micro-credit, poverty

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Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

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Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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Authors: Farhana Arzu, Roslan Hashim

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Renewable energy is the only alternative sources of energy to meet the current energy demand, healthy environment and future growth which is considered essential for essential sustainable development. Marine renewable energy is one of the major means to meet this demand. Turbines (both horizontal and vertical) play a vital role for extraction of tidal energy. The influence of swept area on the performance improvement of tidal turbine is a vital factor to study for the reduction of relatively high power generation cost in marine industry. This study concentrates on performance investigation of variable length blade tidal turbine concept that has already been proved as an efficient way to improve energy extraction in the wind industry. The concept of variable blade length utilizes the idea of increasing swept area through the turbine blade extension when the tidal stream velocity falls below the rated condition to maximize energy capture while blade retracts above rated condition. A three bladed horizontal axis variable length blade horizontal axis tidal turbine was modelled by modifying a standard fixed length blade turbine. Classical blade element momentum theory based numerical investigation has been carried out using QBlade software to predict performance. The results obtained from QBlade were compared with the available published results and found very good agreement. Three major performance parameters (i.e., thrust, moment, and power coefficients) and power output for different blade extensions were studied and compared with a standard fixed bladed baseline turbine at certain operational conditions. Substantial improvement in performance coefficient is observed with the increase in swept area of the turbine rotor. Power generation is found to increase in great extent when operating at below rated tidal stream velocity reducing the associated cost per unit electric power generation.

Keywords: variable length blade, performance, tidal turbine, power generation

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Authors: Manojkumar Sabanayagam

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The Riemann hypothesis is an unsolved millennium problem and the search for a solution to the Riemann hypothesis is to study the pattern of prime number distribution. The scope of this paper is to identify the solution for the critical strip and the critical line axis, which has the non-trivial zero solutions using complex plane functions. The Riemann graphical plot is constructed using a linear complex variable function (X+iY) and is applicable only when X>1. But the investigation shows that complex variable behavior has two zones. The first zone is the transformation zone, where the definition of the complex plane should be a non-linear variable which is the critical strip zone in the graph (X=0 to 1). The second zone is the transformed zone (X>1) defined using linear variables conventionally. This paper deals with the Non-linear function in the transformation zone derived using cosine and sinusoidal time lag w.r.t imaginary number ‘i’. The alternate complex variable (Cosθ+i Sinθ) is used to understand the variables in the critical strip zone. It is concluded that the non-trivial zeros present in the Real part 0.5 are because the linear function is not the correct approach in the critical strip. This paper provides the solution to Reimann's hypothesis.

Keywords: Reimann hypothesis, critical strip, complex plane, transformation zone

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Authors: Minho Kwak, Suhwan Yun, Choonsoo Park

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Nose shape optimizations of high-speed train are performed for the improvement of aerodynamic characteristics. Based on the commercial train, KTX-Sancheon, multi-objective optimizations are conducted for the improvement of the side wind stability and the micro-pressure wave following the optimization for the reduction of aerodynamic drag. 3D nose shapes are modelled by the Vehicle Modeling Function. Aerodynamic drag and side wind stability are calculated by three-dimensional compressible Navier-Stokes solver, and micro pressure wave is done by axi-symmetric compressible Navier-Stokes solver. The Maxi-min Latin Hypercube Sampling method is used to extract sampling points to construct the approximation model. The kriging model is constructed for the approximation model and the NSGA-II algorithm was used as the multi-objective optimization algorithm. Nose length, nose tip height, and lower surface curvature are design variables. Because nose length is a dominant variable for aerodynamic characteristics of train nose, two optimization processes are progressed respectively with and without the design variable, nose length. Each pareto set was obtained and each optimized nose shape is selected respectively considering Honam high-speed rail line infrastructure in South Korea. Through the optimization process with the nose length, when compared to KTX Sancheon, aerodynamic drag was reduced by 9.0%, side wind stability was improved by 4.5%, micro-pressure wave was reduced by 5.4% whereas aerodynamic drag by 7.3%, side wind stability by 3.9%, micro-pressure wave by 3.9%, without the nose length. As a result of comparison between two optimized shapes, similar shapes are extracted other than the effect of nose length.

Keywords: aerodynamic characteristics, design variable, multi-objective optimization, train nose shape

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Authors: Mohammad Reza Ghaani, Michele Catti

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The reduction of CoO/Fe₂O₃ oxides supported on carbon xerogels was studied to elucidate the effect of nano-size distribution of the catalyst in carbon matrices. Resorcinol formaldehyde xerogels were synthesized, impregnated with iron and cobalt nitrates, and subsequently heated to obtain the oxides. The mechanism of oxide reduction to metal was investigated by in-situ synchrotron X-ray diffraction in dynamic, non-isothermal conditions. Kinetic profiles of the reactions were obtained by plotting the diffraction intensities of selected Bragg peaks vs. temperature. The extracted Temperature-Programmed-Reduction (TPR) diagrams were analyzed by appropriate kinetic models, leading to best results with the Avrami-Erofeev model for all reduction reactions considered. The activation energies for the two-step reduction of iron oxide were 65 and 37 kJmol⁻¹, respectively. The average value for the reduction of CoO to Co was found to be around 21 kJ mol⁻¹. Such results may contribute to develop efficient and inexpensive non-noble metal-based catalysts in element form, e.g., Fe, Co, via heterogenization of metal complexes on mesoporous supports.

Keywords: non-isothermal kinetics, carbon aerogel, in-situ synchrotron X-ray diffraction, reduction mechanisms

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

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Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Ian Phil Canlas, Mageswary Karpudewan, Joyce Magtolis, Rosario Canlas

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This study reported the development and validation of the Awareness to Disaster Risk Reduction Questionnaire for Teachers (ADRRQT). The questionnaire is a combination of Likert scale and open-ended questions that were grouped into two parts. The first part included questions relating to the general awareness on disaster risk reduction. Whereas, the second part comprised questions regarding the integration of disaster risk reduction in the teaching process. The entire process of developing and validating of the ADRRQT was described in this study. Statistical and qualitative findings revealed that the ADRRQT is significantly valid and reliable and has the potential of measuring awareness to disaster risk reduction of stakeholders in the field of teaching. Moreover, it also shows the potential to be adopted in other fields.

Keywords: awareness, development, disaster risk reduction, questionnaire, validation

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Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: M. Y. Malik, Farzana Khan

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In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: Auliya Adzillatin Uzhma, M. Adrian Rizky, Puri Diah Santyarini

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Bekasi Industrial Area in Kab. Bekasi and SEZ (Special Economic Zone) Sei Mangkei in Kab. Simalungun are two areas whose have the same main economic activity that are manufacturing industrial. Manufacturing industry in Bekasi Industrial Area contributes more than 70% of Kab. Bekasi’s GDP, while manufacturing industry in SEZ Sei Mangkei contributes less than 20% of Kab. Simalungun’s GDP. The dependent variable in the research is labor productivity, while the independent variable is the amount of labor, the level of labor education, the length of work and salary. This research used linear regression method to find the model for represent actual condition of productivity in two industrial area, then the equalization using dummy variable on labor education level variable. The initial hypothesis (Ho) in this research is that labor productivity in Bekasi Industrial Area will be higher than the productivity of labor in SEZ Sei Mangkei. The variable that supporting the accepted hypothesis are more labor, higher education, longer work and higher salary in Bekasi Industrial Area.

Keywords: labor, industrial city, linear regression, productivity

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Authors: Thomas S. Abia II, Citlali Garcia-Saucedo

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A continuous copper precipitation treatment (CCPT) system was conceived at Intel Chandler Site to serve as a first-of-kind (FOK) facility-scale waste copper (Cu), nickel (Ni), and manganese (Mn) co-precipitation facility. The process was designed to treat highly variable wastewater discharged from a substrate packaging research factory. The paper discusses metals co-precipitation induced by internal changes for manufacturing facilities that lack the capacity for hardware expansion due to real estate restrictions, aggressive schedules, or budgetary constraints. Herein, operating parameters such as pH and oxidation reduction potential (ORP) were examined to analyze the ability of the CCPT System to immobilize various waste metals. Additionally, influential factors such as influent concentrations and retention times were investigated to quantify the environmental variability against system performance. A total of 2,027 samples were analyzed and statistically evaluated to measure the performance of CCPT that was internally retrofitted for Mn abatement to meet environmental regulations. In order to enhance the consistency of the influent, a separate holding tank was cannibalized from another system to collect and slow-feed the segregated Mn wastewater from the factory into CCPT. As a result, the baseline influent Mn decreased from 17.2+18.7 mg¹L^-1 at pre-pilot to 5.15+8.11 mg¹L^-1 post-pilot (70.1% reduction). Likewise, the pre-trial and post-trial average influent Cu values to CCPT were 52.0+54.6 mg¹L^-1 and 33.9+12.7 mg¹L^-1, respectively (34.8% reduction). However, the raw Ni content of 0.97+0.39 mg¹L^-1 at pre-pilot increased to 1.06+0.17 mg¹L^-1 at post-pilot. The average Mn output declined from 10.9+11.7 mg¹L^-1 at pre-pilot to 0.44+1.33 mg¹L^-1 at post-pilot (96.0% reduction) as a result of the pH and ORP operating setpoint changes. In similar fashion, the output Cu quality improved from 1.60+5.38 mg¹L^-1 to 0.55+1.02 mg¹L^-1 (65.6% reduction) while the Ni output sustained a 50% enhancement during the pilot study (0.22+0.19 mg¹L^-1 reduced to 0.11+0.06 mg¹L^-1). pH and ORP were shown to be significantly instrumental to the precipitative versatility of the CCPT System.

Keywords: copper, co-precipitation, industrial wastewater treatment, manganese, optimization, pilot study

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Authors: Gülçin Tekin, Fethi Kadıoğlu

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In this study, the dynamic analysis of viscoelastic plates with variable thickness is examined. The solutions of dynamic response of viscoelastic thin plates with variable thickness have been obtained by using the functional analysis method in the conjunction with the Gâteaux differential. The four-node serendipity element with four degrees of freedom such as deflection, bending, and twisting moments at each node is used. Additionally, boundary condition terms are included in the functional by using a systematic way. In viscoelastic modeling, Three-parameter Kelvin solid model is employed. The solutions obtained in the Laplace-Carson domain are transformed to the real time domain by using MDOP, Dubner & Abate, and Durbin inverse transform techniques. To test the performance of the proposed mixed finite element formulation, numerical examples are treated.

Keywords: dynamic analysis, inverse laplace transform techniques, mixed finite element formulation, viscoelastic plate with variable thickness

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Authors: Itiola Kehinde Adeniran

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This paper investigated the influence of harnessing entrepreneurial opportunities on the national security in Nigeria with a specific focus on the security situation of the post-amnesty programmes of the Federal Government in Ondo State. The self-administered structured questionnaire was employed to collect data from one hundred and twenty participants through purposive sampling method. Inferential statistics was used to analyze the data, specifically; ordinary least squares linear regression method was employed with the aid of statistical package for social science (SPSS) version 20 in order to determine the influence of independent variable (entrepreneurial opportunities) on dependent variable (national security). The result showed that business opportunities have a significant influence on the rate of criminal activities. The study also revealed that entrepreneurial opportunity creation and discovery as well as providing a model on how these entrepreneurial opportunities could be effectively and efficiently utilized jointly predict better national security, which counted for 69% variance of crime rate reduction. The paper, therefore, recommended that citizens should be encouraged to develop an interest in the skill-based activities in order to change their mindset towards self-employment which can motivate them in identify entrepreneurial opportunities.

Keywords: entrepreneurship, entrepreneurial opportunities, national security, unemployment

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Authors: Syed Ali Taqi, Muhammad Ismail

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A comparative study of estimators of population means in two phase sampling in the presence of non-response when Unknown population means of the auxiliary variable(s) and incomplete information of study variable y as well as of auxiliary variable(s) is made. Three real data sets of University students, hospital and unemployment are used for comparison of all the available techniques in two phase sampling in the presence of non-response with the newly generalized ratio estimators.

Keywords: two-phase sampling, ratio estimator, product estimator, generalized estimators

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Authors: Haniye Dehestani, Yadollah Ordokhani

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In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Roli Saini, Pradeep Kumar

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A coagulation/flocculation process was adopted for the reduction of carbamate insecticide (carbofuran) from aqueous solution. Ferric chloride (FeCl₃) was used as a coagulant to treat the carbofuran. To exploit the reduction efficiency of pesticide concentration and COD, the jar-test experiments were carried out and process was optimized through response surface methodology (RSM). The effects of two independent factors; i.e., FeCl₃ dosage and pH on the reduction efficiency were estimated by using central composite design (CCD). The initial COD of the 30 mg/L concentrated solution was found to be 510 mg/L. Results exposed that the maximum reduction occurred at an optimal condition of FeCl₃ = 80 mg/L, and pH = 5.0, from which the reduction of concentration and COD 75.13% and 65.34%, respectively. The present study also predicted that the obtained regression equations could be helpful as the theoretical basis for the coagulation process of pesticide wastewater.

Keywords: carbofuran, coagulation, optimization, response surface methodology

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Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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Authors: Kaouther Selmi, Alaeddine Sridi, Mohamed Bouallegue, Kais Bouallegue

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Neurons are the fundamental units of the brain and the nervous system. The variable structure model of neurons consists of a system of differential equations with various parameters. By optimizing these parameters, we can create a unique model that describes the dynamic behavior of a single neuron. We introduce a neural network based on neurons with multiple dendrites employing an activation function with a variable structure. In this paper, we present a model for heart behavior. Finally, we showcase our successful simulation of the heart's ECG diagram using our Variable Structure Neuron Model (VSMN). This result could provide valuable insights into cardiology.

Keywords: neural networks, neuron, dendrites, heart behavior, ECG

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Authors: Seok Hong Min, Tae Kwon Ha

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With increasing demands for high performance materials, intensive interest on the Ti has been focused. Especially, low cost production process of Ti has been extremely necessitated from wide parts and various industries. Tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock and used as an intermediate product for the production of metal titanium sponge. Reduction of TiCl₄ is usually conducted by Kroll process using magnesium as a reduction reagent, producing metallic Ti in the shape of sponge. The process is batch type and takes very long time including post processes treating sponge. As an alternative reduction reagent, hydrogen in the state of plasma has long been strongly recommended. Experimental confirmation has not been completely reported yet and more strict analysis is required. In the present study, hydrogen plasma reduction process has been thermodynamically analyzed focusing the effects of temperature, pressure and concentration. All thermodynamic calculations were performed using the FactSage® thermodynamical software.

Keywords: TiCl₄, titanium, hydrogen, plasma, reduction, thermodynamic calculation

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Authors: Mustafa Sahin, İlkay Yavrucuk

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This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control

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Authors: Kirill Trapezon, Alexandr Trapezon

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A problem is formulated for the natural oscillations of a circular plate of linearly variable thickness on the basis of the symmetry method. The equations of natural frequencies and forms for a plate are obtained, providing that it is rigidly fixed along the inner contour. The first three eigenfrequencies are calculated, and the eigenmodes of the oscillations of the acoustic element are constructed. An algorithm for applying the symmetry method and the factorization method for solving problems in the theory of oscillations for plates of variable thickness is shown. The effectiveness of the approach is demonstrated on the basis of comparison of known results and those obtained in the article. It is shown that the results are more accurate and reliable.

Keywords: vibrations, plate, method of symmetries, differential equation, factorization, approximation

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Authors: Yong-Heng Shi, Peng Hao, Bai-Chen Xie

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Solar prosumers are playing increasingly prominent roles in the power system. However, its uncertainty affects the outcomes and functions of the power market, especially in the asymmetric information environment. Therefore, an important issue is how to take effective measures to reduce the impact of uncertainty on market equilibrium. We propose a two-level stochastic differential game model to explore the Cournot decision problem of prosumers. In particular, we study the impact of punishment and cooperation mechanisms on the efficiency of the Cournot game in which prosumers face uncertainty. The results show that under the penalty mechanism of fixed and variable rates, producers and consumers tend to take conservative actions to hedge risks, and the variable rates mechanism is more reasonable. Compared with non-cooperative situations, prosumers can improve the efficiency of the game through cooperation, which we attribute to the superposition of market power and uncertainty reduction. In addition, the market environment of asymmetric information intensifies the role of uncertainty. It reduces social welfare but increases the income of prosumers. For regulators, promoting alliances is an effective measure to realize the integration, optimization, and stable grid connection of producers and consumers.

Keywords: Cournot games, power market, uncertainty, prosumer cooperation

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Authors: Ercan Yilmaz, Ali Murat Sünbül

Abstract:

The aim of the study is to investigate teachers’ self-efficacy with regards to their emotional intelligence. The relational model was used in the study. The participant of the study included 194 teachers from secondary schools in Konya, Turkey. In order to assess teachers’ emotional intelligence, “Trait Emotional Intelligence Questionnaire-short Form was implemented. For teachers’ self-efficacy, “Teachers’ Sense of Self-Efficacy Scale” was used. As a result of the study, a significant relationship is available between teachers’ sense of self-efficacy and their emotional intelligence. Teachers’ emotional intelligence enucleates approximate eighteen percent of the variable in dimension named teachers’ self-efficacy for the students’ involvement. About nineteen percent of the variable in dimension “self-efficacy for teaching strategies is represented through emotional intelligence. Teachers’ emotional intelligence demonstrates about seventeen percent of variable aimed at classroom management.

Keywords: teachers, self-efficacy, emotional intelligence, education

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