Search results for: variable coefficient Jacobian elliptic function method

Authors: Ramish, Farhan Khalique Awan

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Kinematic redundancy within the manipulators presents extended dexterity and manipulability to the manipulators. Redundant serial robotic manipulators are very popular in industries due to its competencies to keep away from singularities during normal operation and fault tolerance because of failure of one or more joints. Such fault tolerant manipulators are extraordinarily beneficial in applications where human interference for repair and overhaul is both impossible or tough; like in case of robotic arms for space programs, nuclear applications and so on. The design of this sort of fault tolerant serial 3 DoF manipulator is presented in this paper. This work was the extension of the author’s previous work of designing the simple 3R serial manipulator. This work is the realization of the previous design with optimizing the link lengths for incorporating the feature of fault tolerance. Various measures have been followed by the researchers to quantify the fault tolerance of such redundant manipulators. The fault tolerance in this work has been described in terms of the worst-case measure of relative manipulability that is, in fact, a local measure of optimization that works properly for certain configuration of the manipulators. An optimum fault tolerant Jacobian matrix has been determined first based on prescribed null space properties after which the link parameters have been described to meet the given Jacobian matrix. A solid model of the manipulator was then developed to realize the mathematically rigorous design. Further work was executed on determining the dynamic properties of the fault tolerant design and simulations of the movement for various trajectories have been carried out to evaluate the joint torques. The mathematical model of the system was derived via the Euler-Lagrange approach after which the same has been tested using the RoboAnalyzer© software. The results have been quite in agreement. From the CAD model and dynamic simulation data, the manipulator was fabricated in the workshop and Advanced Machining lab of NED University of Engineering and Technology.

Keywords: fault tolerant, Graham matrix, Jacobian, kinematics, Lagrange-Euler

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Authors: Le Linh, Truong Nguyen Luan Vu, Le Hieu Giang

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In this work, the IMC-PID controller cascaded filter based on Internal Model Control (IMC) scheme is systematically proposed for the simplified decoupling control system. The simplified decoupling is firstly introduced for multivariable processes by using coefficient matching to obtain a stable, proper, and causal simplified decoupler. Accordingly, transfer functions of decoupled apparent processes can be expressed as a set of n equivalent independent processes and then derived as a ratio of the original open-loop transfer function to the diagonal element of the dynamic relative gain array. The IMC-PID controller in series with filter is then directly employed to enhance the overall performance of the decoupling control system while avoiding difficulties arising from properties inherent to simplified decoupling. Some simulation studies are considered to demonstrate the simplicity and effectiveness of the proposed method. Simulations were conducted by tuning various controllers of the multivariate processes with multiple time delays. The results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.

Keywords: coefficient matching method, internal model control (IMC) scheme, PID controller cascaded filter, simplified decoupler

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Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

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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: Esmat Mohammadinasab

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The aim of this paper is to investigate theoretically and establish a predictive model for determination LogP of armchair polyhex BN nanotubes by using simple descriptors. The relationship between the octanol-water partition coefficient (LogP) and quantum chemical descriptors, electric moments, and topological indices of some armchair polyhex BN nanotubes with various lengths and fixed circumference are represented. Based on density functional theory (DFT) electric moments and physico-chemical properties of those nanotubes are calculated. The DFT method performed based on the Becke’s 3-parameter formulation with the Lee-Yang-Parr functional (B3LYP) method and 3-21G standard basis sets. For the first time, the relationship between partition coefficient and different properties of polyhex BN nanotubes is investigated.

Keywords: topological indices, quantum descriptors, DFT method, nanotubes

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Authors: Golamhassan Ghahramani Aghdam, Pedram Bavili Tabrizi

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The aim of this research is to investigate the relationship between accounting information and the value of the companies accepted in Tehran Exchange Market. The dependent variable in this research is the value of a company that is measured by price coefficients, and the independent variables are balance sheet information, profit and loss information, cash flow state information, and profit quality characteristics. The profit quality characteristic index is to be related and to be on-time. This research is an application research, and the research population includes all companies that are active in Tehran exchange market. The number of 194 companies was selected by the systematic method as the statistics sample in the period of 2018-2019. The multi-variable linear regression model was used for the hypotheses test. The results show that there is no relationship between accounting information and companies’ value (stock value) that can be due to the lack of efficiency of the investment market and the inability to use the accounting information by investment market activists.

Keywords: accounting information, company value, profit quality characteristics, price coefficient

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Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

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Elliptic curve discrete logarithm problem (ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard's rho method to evaluate the security of ECDLP on Barreto-Naehrig (BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard's rho method, BN curve, Montgomery multiplication

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Authors: Song Ni, Junxiang Xu

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This paper concerns quasi-periodic perturbations with parameters of 2-dimensional degenerate systems. If the equilibrium point of the unperturbed system is elliptic-type degenerate. Assume that the perturbation is real analytic quasi-periodic with diophantine frequency. Without imposing any assumption on the perturbation, we can use a path of equilibrium points to tackle with the Melnikov non-resonance condition, then by the Leray-Schauder Continuation Theorem and the Kolmogorov-Arnold-Moser technique, it is proved that the equation has a small response solution for many sufficiently small parameters.

Keywords: quasi-periodic systems, KAM-iteration, degenerate equilibrium point, response solution

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Authors: Ali Dehgan Moroozeh, B. Farhadi Bansouleh

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Evapotranspiration is one of the most important components of the hydrological cycle. Evapotranspiration (ETo) is an important variable in water and energy balances on the earth’s surface, and knowledge of the distribution of ET is a key factor in hydrology, climatology, agronomy and ecology studies. Many researchers have a valid relationship, which is a function of climate factors, to estimate the potential evapotranspiration presented to the plant water stress or water loss, prevent. The FAO-Penman method (PM) had been recommended as a standard method. This method requires many data and these data are not available in every area of world. So, other methods should be evaluated for these conditions. When sufficient or reliable data to solve the PM equation are not available then Hargreaves equation can be used. The Hargreaves equation (HG) requires only daily mean, maximum and minimum air temperature extraterrestrial radiation .In this study, Hargreaves method (HG) were evaluated in 12 stations in the North West region of Iran. Results of HG and M.HG methods were compared with results of PM method. Statistical analysis of this comparison showed that calibration process has had significant effect on efficiency of Hargreaves method.

Keywords: evapotranspiration, hargreaves, equation, FAO-Penman method

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

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Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: Valerii Dashuk

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The usage of the confidence intervals in economics and econometrics is widespread. To be able to investigate a random variable more thoroughly, joint tests are applied. One of such examples is joint mean-variance test. A new approach for testing such hypotheses and constructing confidence sets is introduced. Exploring both the value of the random variable and its deviation with the help of this technique allows checking simultaneously the shift and the probability of that shift (i.e., portfolio risks). Another application is based on the normal distribution, which is fully defined by mean and variance, therefore could be tested using the introduced approach. This method is based on the difference of probability density functions. The starting point is two sets of normal distribution parameters that should be compared (whether they may be considered as identical with given significance level). Then the absolute difference in probabilities at each 'point' of the domain of these distributions is calculated. This measure is transformed to a function of cumulative distribution functions and compared to the critical values. Critical values table was designed from the simulations. The approach was compared with the other techniques for the univariate case. It differs qualitatively and quantitatively in easiness of implementation, computation speed, accuracy of the critical region (theoretical vs. real significance level). Stable results when working with outliers and non-normal distributions, as well as scaling possibilities, are also strong sides of the method. The main advantage of this approach is the possibility to extend it to infinite-dimension case, which was not possible in the most of the previous works. At the moment expansion to 2-dimensional state is done and it allows to test jointly up to 5 parameters. Therefore the derived technique is equivalent to classic tests in standard situations but gives more efficient alternatives in nonstandard problems and on big amounts of data.

Keywords: confidence set, cumulative distribution function, hypotheses testing, normal distribution, probability density function

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Authors: Maha Zouaoui Khalifa, Hakim Ben Othman, Hussaney Khaled

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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Authors: Khalifa Maha, Ben Othman Hakim, Khaled Hussainey

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren

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Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.

Keywords: flywheel energy storage, fuzzy, optimization, stress analysis

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Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

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Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: Suparat Niwitpong, Sa-aat Niwitpong

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Statistical inference of normal mean with known coefficient of variation has been investigated recently. This phenomenon occurs normally in environment and agriculture experiments when the scientist knows the coefficient of variation of their experiments. In this paper, we constructed new confidence intervals for the normal population mean with known coefficient of variation. We also derived analytic expressions for the coverage probability of each confidence interval. To confirm our theoretical results, Monte Carlo simulation will be used to assess the performance of these intervals based on their coverage probabilities.

Keywords: confidence interval, coverage probability, expected length, known coefficient of variation

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Authors: Noboru Wakamoto, Kiyotaka Obunai, Kazuya Okubo, Toru Fujii

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The aim of this study is to moderate the dependence of counter frictional coefficient on temperature between counter surfaces and to reduce the wear of C/C composites at low temperature. To modify the C/C composites, Silica (SiO₂) powders were added into phenolic resin for carbon precursor. The preform plate of the precursor of C/C composites was prepared by conventional filament winding method. The C/C composites plates were obtained by carbonizing preform plate at 2200 °C under an argon atmosphere. At that time, the silicon carbides (SiC) were synthesized around the surfaces and the internal vacancies of the C/C composites. The frictional coefficient on the counter surfaces and specific wear volumes of the C/C composites were measured by our developed frictional test machine like pin-on disk type. The XRD indicated that SiC was synthesized in the body of C/C composite fabricated by current method. The results of friction test showed that coefficient of friction of unmodified C/C composites have temperature dependence when the test condition was changed. In contrast, frictional coefficient of the C/C composite modified with SiO₂ powders was almost constant at about 0.27 when the temperature condition was changed from Room Temperature (RT) to 300 °C. The specific wear rate decreased from 25×10^-6 mm²/N to 0.1×10^-6 mm²/N. The observations of the surfaces after friction tests showed that the frictional surface of the modified C/C composites was covered with a film produced by the friction. This study found that synthesizing SiC around surface and internal vacancies of C/C composites was effective to moderate the dependence on the frictional coefficient and reduce to the abrasion of C/C composites.

Keywords: C/C composites, friction coefficient, wear, SiC

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Authors: M. G. M. Khan, V. D. Prasad, D. K. Rao

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In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.

Keywords: auxiliary variable, dynamic programming technique, nonlinear programming problem, optimum stratification, uniform distribution

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Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: edge effect, scale optimization, small crack locating, spatial wavelet

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Authors: Ahmad Alhawarat, Mustafa Mamat, Mohd Rivaie, Ismail Mohd

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Conjugate gradient method has been enormously used to solve large scale unconstrained optimization problems due to the number of iteration, memory, CPU time, and convergence property, in this paper we find a new class of nonlinear conjugate gradient coefficient with global convergence properties proved by exact line search. The numerical results for our new βK give a good result when it compared with well-known formulas.

Keywords: conjugate gradient method, conjugate gradient coefficient, global convergence

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Authors: Safa Saoudi, Souheib Yousfi, Riadh Robbana

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E-passport is a relatively new electronic document which maintains the passport features and provides better security. It deploys new technologies such as biometrics and Radio Frequency identification (RFID). The international civil aviation organization (ICAO) and the European union define mechanisms and protocols to provide security but their solutions present many threats. In this paper, a new mechanism is presented to strengthen e-passport security and authentication process. We propose a new protocol based on Elliptic curve, identity based encryption and shared secret between entities. Authentication in our contribution is formally proved with BAN Logic verification language. This proposal aims to provide a secure data storage and authentication.

Keywords: e-passport, elliptic curve cryptography, identity based encryption, shared secret, BAN Logic

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Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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Authors: Ping-Ben Liu, Chien-Chou Tseng

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The objective of this study is to investigate the relationship between the lift coefficient and dynamic behaviors of cavitating flow around a two-dimensional Clark Y hydrofoil at 8° angle of attack, cavitation number of 0.8, and Reynolds number of 7.10⁵. The flow field is investigated numerically by using a vapor transfer equation and a modified turbulence model which applies the filter and local density correction. The results including time-averaged lift/drag coefficient and shedding frequency agree well with experimental observations, which confirmed the reliability of this simulation. According to the variation of lift coefficient, the cycle which consists of growth and shedding of cavitation can be divided into three stages, and the lift coefficient at each stage behaves similarly due to the formation and shedding of the cavity around the trailing edge.

Keywords: Computational Fluid Dynamics, cavitation, turbulence, lift coefficient

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Authors: Wang Guangda, Ma Jun, Zhao Caiqi, Pan Rui

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Wind load is the main control load of large statue structures. Due to the irregular plane and elevation and uneven outer contour, statues’ shape coefficient can not pick up from the current code. Currently a common practice is based on wind tunnel test. But this method is time-consuming and high cost. In this paper, based on the fundamental theory of CFD, using fluid dynamics software of Fluent 15.0, a few large statue structure of 40 to 70m high, which are located in china , including large fairy statues and large Buddha statues, are analyzed by numerical wind tunnel. The results are contrasted with the recommended values in load code and the wind tunnel test results respectively. Results show that the shape coefficient has a good reliability by the numerical wind tunnel method of this kind of building. This will has a certain reference value of wind load values for large statues’ structure.

Keywords: large statue structure, shape coefficient, irregular structure, wind tunnel test, numerical wind tunnel simulation

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Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Lucy Novianti

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The purpose of this study is to determine the effect of corporate governance, ownership structure, and cash holdings on firm value, either direct or indirect through profitability as an intervening variable for non-financial companies listed on the Indonesia Stock Exchange during 2006 to 2014. Samples of 176 firms are chosen based on purposive sampling method. The results of this study conclude that profitability, the size of Audit Committee, audit quality, and cash flow have positive effects on firm value. This study also shows that the meeting frequency of the Board of Directors and free cash flow have negative effects on firm value. In addition, this study finds that the size of the Board of Directors, Independent Commissioner, and ownership structure do not have significant effects on firm value. In this study, the function of profitability as an intervening variable can only be done on the impact of the meeting frequency of the Board of Directors and cash flow on firm value. This study provides a reference for management in decision making concerning the application of corporate governance, cash holdings, and financial performance. Moreover, it can be used as additional information for investors in assessing the feasibility of an investment. Finally, it provides a suggestion for the government regarding the regulation of corporate governance.

Keywords: cash holdings, corporate governance, firm value, ownership structure, profitability

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Authors: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

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