Search results for: linear operators

Authors: Yngvar Berg, Mehdi Azadmehr

Abstract:

In this paper we present a linear autozeroing ultra lowvoltage amplifier. The autozeroing performed by all ULV circuits is important to reduce the impact of noise and especially avoid power supply noise in mixed signal low-voltage CMOS circuits. The simulated data presented is relevant for a 90nm TSMC CMOS process.

Keywords: Low-voltage, trans conductance amplifier, linearity, floating-gate.

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Authors: Mohsen Ziaee

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In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.

Keywords: Scheduling, flexible job shop, makespan, mixed integer linear programming.

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Authors: N. F. Jamaluddin, N. A. H. Aizam

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This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed.

Keywords: Demands, educational timetabling, integer linear programming, scheduling, university examination timetabling problem.

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Authors: Tomoaki Hashimoto

Abstract:

Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: Optimal control, stochastic systems, discrete-time systems, probabilistic constraints, random dither quantization.

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Authors: Deepthi P.P., P.S. Sathidevi

Abstract:

Proposal for a secure stream cipher based on Linear Feedback Shift Registers (LFSR) is presented here. In this method, shift register structure used for polynomial modular division is combined with LFSR keystream generator to yield a new keystream generator with much higher periodicity. Security is brought into this structure by using the Boolean function to combine state bits of the LFSR keystream generator and taking the output through the Boolean function. This introduces non-linearity and security into the structure in a way similar to the Non-linear filter generator. The security and throughput of the suggested stream cipher is found to be much greater than the known LFSR based structures for the same key length.

Keywords: Linear Feedback Shift Register, Stream Cipher, Filter generator, Keystream generator, Modular division circuit

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Authors: Pierre Kenfack

Abstract:

In this paper we present a contribution for the modelling and control of the inverter voltage of a permanent magnet linear generator with multi air-gap structure. The time domain control method is based on instant comparison of reference signals, in the form of current or voltage, with actual or measured signals. The reference current or voltage must be kept close to the actual signal with a reasonable tolerance. In this work, the time domain control method is used to control tracking signals. The performance evaluation concerns the continuation of reference signal. Simulations validate very well the tracking of reference variables (current, voltage) by measured or actual signals. All is simulated and presented under PSIM Software to show the performance and robustness of the proposed controller.

Keywords: Control, permanent magnet, linear machine, multi air-gap structure.

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Authors: Kazuyoshi MORI

Abstract:

The two-stage compensator designs of linear system are investigated in the framework of the factorization approach. First, we give “full feedback" two-stage compensator design. Based on this result, various types of the two-stage compensator designs with partial feedbacks are derived.

Keywords: Linear System, Factorization Approach, Two-Stage Compensator Design, Parametrization of Stabilizing Controllers.

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Authors: Jiashang Jiang, Hao Liu, Yongxin Yuan

Abstract:

In this paper the gradient based iterative algorithms are presented to solve the following four types linear matrix equations: (a) AXB = F; (b) AXB = F, CXD = G; (c) AXB = F s. t. X = XT ; (d) AXB+CYD = F, where X and Y are unknown matrices, A,B,C,D, F,G are the given constant matrices. It is proved that if the equation considered has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. The numerical results show that the proposed method is reliable and attractive.

Keywords: Matrix equation, iterative algorithm, parameter estimation, minimum norm solution.

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Authors: C. Ardil

Abstract:

This paper introduces a new method for multiplecriteria decision making (MCDM) that avoids order reversal and ensures consistency in decision-making. The proposed method involves range targeting of benefit and cost criteria vectors for range normalization of the initial decision matrix. The Reference Linear Combination (RLC) is used to avoid the rank reversal problem. The preference order generated from the target score matrix does not require relative comparisons between alternatives but relies on a chosen reference solution point after transforming the original decision matrix into an MCDM problem by specifying the minimum and maximum bounds of each criterion. The efficiency and applicability of the proposed RLC method were demonstrated in the selection of commercial passenger aircraft. 

Keywords: Aircraft selection, reference linear combination (RLC), multiple criteria decision-making, MCDM

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Authors: Ehab Mourtaga, Ahmad Sharieh, Mousa Abdallah

Abstract:

An automatic speech recognition system for the formal Arabic language is needed. The Quran is the most formal spoken book in Arabic, it is spoken all over the world. In this research, an automatic speech recognizer for Quranic based speakerindependent was developed and tested. The system was developed based on the tri-phone Hidden Markov Model and Maximum Likelihood Linear Regression (MLLR). The MLLR computes a set of transformations which reduces the mismatch between an initial model set and the adaptation data. It uses the regression class tree, as well as, estimates a set of linear transformations for the mean and variance parameters of a Gaussian mixture HMM system. The 30th Chapter of the Quran, with five of the most famous readers of the Quran, was used for the training and testing of the data. The chapter includes about 2000 distinct words. The advantages of using the Quranic verses as the database in this developed recognizer are the uniqueness of the words and the high level of orderliness between verses. The level of accuracy from the tested data ranged 68 to 85%.

Keywords: Hidden Markov Model (HMM), MaximumLikelihood Linear Regression (MLLR), Quran, Regression ClassTree, Speech Recognition, Speaker-independent.

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Authors: Nicholas D. Assimakis

Abstract:

In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: Discrete time, linear estimation, Kalman filter, Kalman filter gain.

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Authors: Chompunut Jantarasorn, Chutima Prommak

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The important issue considered in the widespread deployment of Wireless Sensor Networks (WSNs) is an efficiency of the energy consumption. In this paper, we present a study of the optimal relay station planning problems using Binary Integer Linear Programming (BILP) model to minimize the energy consumption in WSNs. Our key contribution is that the proposed model not only ensures the required network lifetime but also guarantees the radio connectivity at high level of communication quality. Specially, we take into account effects of noise, signal quality limitation and bit error rate characteristics. Numerical experiments were conducted in various network scenarios. We analyzed the effects of different sensor node densities and distribution on the energy consumption.

Keywords: Binary Integer Linear Programming, BILP, Energy consumption, Optimal node placement and Wireless sensor networks.

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Authors: M. B. Meenavathi, K. Rajesh

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In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider both the Gaussian and mixed Gaussian-impulse noise to test the robustness of the filter. Image enhancement and restoration results using the proposed Volterra filter are found to be superior to those obtained with standard linear and nonlinear filters.

Keywords: Gaussian noise, Image enhancement, Imagerestoration, Linear filters, Nonlinear filters, Volterra series.

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

Abstract:

In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: Optimal linear quadratic tracker, proportional plus integral observer, state estimator, disturbance estimator.

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Authors: Moulay A. Akhloufi, Abdelhakim Bendada

Abstract:

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Keywords: Face recognition, biometrics, probabilistic imageprocessing, infrared imaging.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: J. Cheeneebash, V. Beeharry, A. Gopaul

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The aim of this paper is to express the input-output matrix as a linear ordering problem which is classified as an NP-hard problem. We then use a Tabu search algorithm to find the best permutation among sectors in the input-output matrix that will give an optimal solution. This optimal permutation can be useful in designing policies and strategies for economists and government in their goal of maximizing the gross domestic product.

Keywords: Input-Output matrix, linear ordering problem, Tabusearch.

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Authors: F. Soleymani, M. Sharifi

Abstract:

Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which is to some extent like the secant method, is accompanied with some numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically iterative schemes.

Keywords: Non-linear equation, iterative methods, derivative-free, convergence.

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Authors: Soo-young Ye, Jun-mo Park, Jae-hyung Kim, Jae-hee Jung, Ah-young Jeon, In-cheol Kim, Jung-man Son, Ki-gon Nam, Seong-wan Baik, Jung-hoon Ro, Gye-rok Jeon

Abstract:

The linear SEF (Spectral Edge Frequency) parameter and spectrum analysis method can not reflect the non-linear of EEG. This method can not contribute to acquire real time analysis and obtain a high confidence in the clinic due to low discrimination. To solve the problems, the development of a new index is carried out using the bispectrum analyzing the EEG(electroencephalogram) including the non-linear characteristic. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. New index could afford to effectively discriminate the awake and anesthesia state.

Keywords: Bispectrum, anesthesia depth, EEG, SEF.

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Authors: O. M. Bamigbola, A. A. Ibrahim

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Analysis of real life problems often results in linear systems of equations for which solutions are sought. The method to employ depends, to some extent, on the properties of the coefficient matrix. It is not always feasible to solve linear systems of equations by direct methods, as such the need to use an iterative method becomes imperative. Before an iterative method can be employed to solve a linear system of equations there must be a guaranty that the process of solution will converge. This guaranty, which must be determined apriori, involve the use of some criterion expressible in terms of the entries of the coefficient matrix. It is, therefore, logical that the convergence criterion should depend implicitly on the algebraic structure of such a method. However, in deference to this view is the practice of conducting convergence analysis for Gauss- Seidel iteration on a criterion formulated based on the algebraic structure of Jacobi iteration. To remedy this anomaly, the Gauss- Seidel iteration was studied for its algebraic structure and contrary to the usual assumption, it was discovered that some property of the iteration matrix of Gauss-Seidel method is only diagonally dominant in its first row while the other rows do not satisfy diagonal dominance. With the aid of this structure we herein fashion out an improved version of Gauss-Seidel iteration with the prospect of enhancing convergence and robustness of the method. A numerical section is included to demonstrate the validity of the theoretical results obtained for the improved Gauss-Seidel method.

Keywords: Linear system of equations, Gauss-Seidel iteration, algebraic structure, convergence.

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Authors: E. Aruchunan, J. Sulaiman

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The objective of this paper is to analyse the application of the Half-Sweep Gauss-Seidel (HSGS) method by using the Half-sweep approximation equation based on central difference (CD) and repeated trapezoidal (RT) formulas to solve linear fredholm integro-differential equations of first order. The formulation and implementation of the Full-Sweep Gauss-Seidel (FSGS) and Half- Sweep Gauss-Seidel (HSGS) methods are also presented. The HSGS method has been shown to rapid compared to the FSGS methods. Some numerical tests were illustrated to show that the HSGS method is superior to the FSGS method.

Keywords: Integro-differential equations, Linear fredholm equations, Finite difference, Quadrature formulas, Half-Sweep iteration.

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Authors: Chaimongkol Limpianchob

Abstract:

This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: Aromatic coconut, supply chain management, production planning, mixed-integer linear programming.

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Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic kidney disease, microfluidics, linear regression, VITROS analyzer, urinary albumin.

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Authors: Tejeet Singh, Harmanjit Singh

Abstract:

Creep behavior of thick-walled functionally graded cylinder consisting of AlSiC and subjected to internal pressure and high temperature has been analyzed. The functional relationship between strain rate with stress can be described by the well known threshold stress based creep law with a stress exponent of five. The effect of imposing non-linear particle gradient on the distribution of creep stresses in the thick-walled functionally graded composite cylinder has been investigated. The study revealed that for the assumed non-linear particle distribution, the radial stress decreases throughout the cylinder, whereas the tangential, axial and effective stresses have averaging effect. The strain rates in the functionally graded composite cylinder could be reduced to significant extent by employing non-linear gradient in the distribution of reinforcement.

Keywords: Functionally Graded Material, Pressure, Steady State Creep, Thick-Cylinder.

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Authors: Guangbin Wang, Deyu Sun, Fuping Tan

Abstract:

In this paper, we present new preconditioned modified accelerated overrelaxation (MAOR) method for solving linear systems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned MAOR method converges faster than the MAOR method whenever the MAOR method is convergent. Finally, we give one numerical example to confirm our theoretical results.

Keywords: preconditioned, MAOR method, linear system, convergence, comparison.

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Authors: Yananda Siraphatthada

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The current study was the succession of a previous study on value added of recycling business management. Its aims are to 1) explore conditions on how to increasing value add of Thai recycling business, and 2) exam the implementation of the 3-staged plan (short, medium, and long term), suggested by the former study, to increase value added of the recycling business as immediate mechanisms to accelerate government operation. Quantitative and qualitative methods were utilized in this research. A qualitative research consisted of in-depth interviews and focus group discussions. Responses were obtained from owners of the waste separation plants, and recycle shops, as well as officers in relevant governmental agencies. They were randomly selected via Quota Sampling. Data was analyzed via content analysis. The sample used for quantitative method consisted of 1,274 licensed recycling operators in eight provinces. The operators were randomly stratified via sampling method. Data were analyzed via descriptive statistics frequency, percentage, average (Mean) and standard deviation.The study recommended three-staged plan: short, medium, and long terms. The plan included the development of logistics, the provision of quality market/plants, the amendment of recycling rules/regulation, the restructuring recycling business, the establishment of green-purchasing recycling center, support for the campaigns run by the International Green Purchasing Network (IGPN), conferences/workshops as a public forum to share insights among experts/concern people.

Keywords: Strategies, Value Added, Recycle Business.

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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Authors: D.N. Zheng, J.X. Wang, Y.N. Zhao, Z.H. Yang

Abstract:

The Linear discriminant analysis (LDA) can be generalized into a nonlinear form - kernel LDA (KLDA) expediently by using the kernel functions. But KLDA is often referred to a general eigenvalue problem in singular case. To avoid this complication, this paper proposes an iterative algorithm for the two-class KLDA. The proposed KLDA is used as a nonlinear discriminant classifier, and the experiments show that it has a comparable performance with SVM.

Keywords: Linear discriminant analysis (LDA), kernel LDA (KLDA), conjugate gradient algorithm, nonlinear discriminant classifier.

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Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó

Abstract:

Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate a FEM model which is accurate and competitive for a future shape optimization task.

Keywords: Rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model.

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Authors: Hassan Zarei, Ali Vahidian Kamyad, Sohrab Effati

Abstract:

In this paper, a mathematical model of human immunodeficiency virus (HIV) is utilized and an optimization problem is proposed, with the final goal of implementing an optimal 900-day structured treatment interruption (STI) protocol. Two type of commonly used drugs in highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are considered. In order to solving the proposed optimization problem an adaptive memetic algorithm with population management (AMAPM) is proposed. The AMAPM uses a distance measure to control the diversity of population in genotype space and thus preventing the stagnation and premature convergence. Moreover, the AMAPM uses diversity parameter in phenotype space to dynamically set the population size and the number of crossovers during the search process. Three crossover operators diversify the population, simultaneously. The progresses of crossover operators are utilized to set the number of each crossover per generation. In order to escaping the local optima and introducing the new search directions toward the global optima, two local searchers assist the evolutionary process. In contrast to traditional memetic algorithms, the activation of these local searchers is not random and depends on both the diversity parameters in genotype space and phenotype space. The capability of AMAPM in finding optimal solutions compared with three popular metaheurestics is introduced.

Keywords: HIV therapy design, memetic algorithms, adaptivealgorithms, nonlinear integer programming.

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