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 Subjects -> ENGINEERING (Total: 2052 journals)     - CHEMICAL ENGINEERING (169 journals)    - CIVIL ENGINEERING (159 journals)    - ELECTRICAL ENGINEERING (87 journals)    - ENGINEERING (1142 journals)    - ENGINEERING MECHANICS AND MATERIALS (318 journals)    - HYDRAULIC ENGINEERING (49 journals)    - INDUSTRIAL ENGINEERING (52 journals)    - MECHANICAL ENGINEERING (76 journals) ENGINEERING (1142 journals)            First | 3 4 5 6 7 8 9 10 | Last
 Journal of Analytical Sciences, Methods and Instrumentation       (Followers: 1) Journal of Applied Analysis Journal of Applied and Industrial Sciences Journal of Applied Logic Journal of Applied Physics       (Followers: 201) Journal of Applied Probability       (Followers: 6) Journal of Applied Research and Technology Journal of Applied Science and Technology Journal of Applied Sciences       (Followers: 5) Journal of Architectural Engineering       (Followers: 6) Journal of ASTM International       (Followers: 3) Journal of Automation and Control Journal of Aviation Technology and Engineering       (Followers: 6) Journal of Biological Dynamics       (Followers: 1) Journal of Biomedical Science       (Followers: 2) Journal of Biomolecular NMR       (Followers: 4) Journal of Biosciences Journal of Catalysis       (Followers: 6) Journal of Catalyst & Catalysis Journal of Central South University Journal of China Universities of Posts and Telecommunications       (Followers: 2) Journal of China University of Mining and Technology Journal of Cleaner Production       (Followers: 16) Journal of Coal Science and Engineering (China) Journal of Cold Regions Engineering       (Followers: 3) Journal of Combinatorial Designs       (Followers: 3) Journal of Combustion       (Followers: 6) Journal of Communications       (Followers: 17) Journal of Complex Systems Journal of Computational and Nonlinear Dynamics       (Followers: 5) Journal of Computational and Theoretical Nanoscience       (Followers: 1) Journal of Computational Biology       (Followers: 6) Journal of Computational Electronics       (Followers: 1) Journal of Computational Engineering Journal of Computing and Information Science in Engineering       (Followers: 2) Journal of Dairy Science       (Followers: 15) Journal of Display Technology       (Followers: 2) Journal of Dynamic Systems, Measurement, and Control       (Followers: 8) Journal of Dynamical and Control Systems       (Followers: 3) Journal of Earthquake Engineering       (Followers: 8) Journal of Elasticity       (Followers: 2) Journal of Electroceramics Journal of Electromagnetic Waves and Applications       (Followers: 2) Journal of Electronic Imaging       (Followers: 2) Journal of Electronic Testing       (Followers: 1) Journal of Electronics Cooling and Thermal Control       (Followers: 1) Journal of Electrostatics Journal of Energy Engineering       (Followers: 7) Journal of Energy Resources Technology       (Followers: 6) Journal of Engineering Journal of Engineering and Computer Innovations Journal of Engineering and Technology       (Followers: 5) Journal of Engineering and Technology Research Journal of Engineering Design       (Followers: 15) Journal of Engineering Education Journal of Engineering Entrepreneurship, The       (Followers: 3) Journal of Engineering for Gas Turbines and Power       (Followers: 11) Journal of Engineering Mathematics Journal of Engineering Mechanics       (Followers: 12) Journal of Engineering Physics and Thermophysics Journal of Engineering Thermophysics Journal of Engineering, Computers and Applied Sciences Journal of Engineering, Design and Technology       (Followers: 15) Journal of Environmental & Engineering Geophysics Journal of Environmental Engineering       (Followers: 28) Journal of Environmental Engineering and Landscape Management       (Followers: 7) Journal of Experimental Nanoscience       (Followers: 3) Journal of Fire Sciences       (Followers: 2) Journal of Flood Risk Management       (Followers: 7) Journal of Fluids Engineering       (Followers: 14) Journal of Fourier Analysis and Applications Journal of Fuel Cell Science and Technology       (Followers: 2) Journal of Functional Analysis       (Followers: 1) Journal of Fundamental and Applied Sciences Journal of Geological Research       (Followers: 1) Journal of Geotechnical and Geoenvironmental Engineering       (Followers: 18) Journal of Global Optimization       (Followers: 4) Journal of Guidance, Control, and Dynamics       (Followers: 62) Journal of Healthcare Engineering       (Followers: 2) Journal of Heat Transfer       (Followers: 26) Journal of Humanitarian Engineering       (Followers: 1) Journal of Hydraulic Engineering       (Followers: 14) Journal of Hyperspectral Remote Sensing       (Followers: 1) Journal of Imaging Science and Technology Journal of Industrial and Production Engineering       (Followers: 2) Journal of Industrial Engineering and Management       (Followers: 4) Journal of Inequalities and Applications Journal of Infrared, Millimeter and Terahertz Waves       (Followers: 1) Journal of Integrated Design and Process Science       (Followers: 1) Journal of Intelligent and Fuzzy Systems       (Followers: 9) Journal of Inverse and Ill-posed Problems       (Followers: 1) Journal of Irrigation and Drainage Engineering       (Followers: 10) Journal of K-Theory       (Followers: 1) Journal of King Saud University - Engineering Sciences Journal of Konbin Journal of Liquid Chromatography & Related Technologies       (Followers: 9) Journal of Management in Engineering       (Followers: 10) Journal of Manufacturing Science and Engineering       (Followers: 10) Journal of Manufacturing Systems       (Followers: 6) Journal of Manufacturing Technology Management       (Followers: 4)
 Journal of Mathematical Modelling and Algorithms     [SJR: 0.264]   [H-I: 15]    [4 followers]  Follow        Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1570-1166 - ISSN (Online) 1572-9214    Published by Springer-Verlag  [2210 journals]
• Balking and Reneging Multiple Working Vacations Queue with Heterogeneous
Servers
• Abstract: Abstract This paper presents the analysis of a renewal input multiple working vacations queue with balking, reneging and heterogeneous servers. Whenever the system becomes empty the second server leaves for a working vacation whereas the first server remains idle in the system. During a working vacation the second server provides service at a slower rate rather than completely stopping service. The steady-state probabilities of the model are obtained using supplementary variable and recursive techniques. Various performance measures of the model such as expected system length, expected balking rate, etc., have been discussed. Finally, some numerical results have been presented to show the effect of model parameters on the system performance measures.
PubDate: 2015-01-23

• Multi-objective Compromise Allocation in Multivariate Stratified Sampling
Using Extended Lexicographic Goal Programming with Gamma Cost Function
• Abstract: Abstract In the present paper, a new Gamma cost function is proposed for an optimum allocation in multivariate stratified random sampling with linear regression estimator. Extended lexicographic goal programming is used for solution of multi-objective non-linear integer allocation problem. A real data set is used to illustrate the application.
PubDate: 2014-12-18

• Efficiency Improvement Strategy Under Constant Sum of Inputs
• Abstract: Abstract In this paper, we have formulated Data Envelopment Analysis (DEA) models to reduce the inputs in an inefficient Decision Making Unit (DMU) when the specific inputs are under the constant sum constraint. We have also extended the models to reallocate the excess input without any reduction in efficiency of other DMUs. These DEA models and methods developed in this work will help decision makers in developing an optimal strategy to transfer excess input to other DMUs. Theoretical results have been illustrated with the help of a case study.
PubDate: 2014-12-01

• Sea SAR Images Analysis to Detect Oil Slicks in Algerian Coasts
• Abstract: Abstract In this paper, we investigate the performance of partition features derived from histogram analysis to isolate dark spots which are candidates to be oil spills in SAR images. The first partition is carried out to obtain preliminary clusters of the pixels on the basis of their grey level intensities and threshold values deduced from the histogram. The detection process is achieved by a contextual partition where the conflict pixels are attributed to their region involving local information about pre-etiqueted pixels neighbouring the pixel in question. For pixel’s assignment, we propose two decision criteria: the first based on Local Probability Maximization (LPM) while the second uses a Chi-squared test (χ 2). We considered variable context in order to characterize the sea texture and dark spots. This method is tested on ERS-2 SAR Precision Image (PRI) covering Algerian coasts and gave promising results which are useful for the identification process.
PubDate: 2014-12-01

• Generalized Multiobjective Evolutionary Algorithm Guided by Descent
Directions
• Abstract: Abstract This paper proposes a generalized descent directions-guided multiobjective algorithm (DDMOA2). DDMOA2 uses the scalarizing fitness assignment in its parent and environmental selection procedures. The population consists of leader and non-leader individuals. Each individual in the population is represented by a tuple containing its genotype as well as the set of strategy parameters. The main novelty and the primary strength of our algorithm is its reproduction operator, which combines the traditional local search and stochastic search techniques. To improve efficiency, when the number of objective is increased, descent directions are found only for two randomly chosen objectives. Furthermore, in order to increase the search pressure in high-dimensional objective space, we impose an additional condition for the acceptance of descent directions found for leaders during local search. The performance of the proposed approach is compared with those produced by representative state-of-the-art multiobjective evolutionary algorithms on a set of problems with up to 8 objectives. The experimental results reveal that our algorithm is able to produce highly competitive results with well-established multiobjective optimizers on all tested problems. Moreover, due to its hybrid reproduction operator, DDMOA2 demonstrates superior performance on multimodal problems.
PubDate: 2014-12-01

• Wolfe Type Higher Order Multiple Objective Nondifferentiable Symmetric
Dual Programming with Generalized Invex Function
• Abstract: Abstract In this paper, a new class of higher order (ϕ, ρ)-invex function is introduced with an example, in which the sublinearity and convexity assumption on ϕ with respect to third argument is relaxed. A pair of higher order Wolfe type multiobjective symmetric dual for a class of nondifferentiable multiobjective programming involving square root term is presented and the weak duality, strong duality and converse duality theorems are established with their proofs under higher order (ϕ, ρ)-invexity and (ϕ, ρ)-incavity assumption. Self duality theorem is proved for the proposed dual program. These results are used to discuss Wolfe type higher-order symmetric minimax mixed integer dual problems. A numerical example is developed where the results of weak and strong duality theorems can be applied. Discussion on some particular cases shows that our results generalize earlier results in related domain.
PubDate: 2014-12-01

• Web Page Textual Color Contrast Compensation for CVD Users Using
Optimization Methods
• Abstract: Abstract With this paper, we propose two methods for color contrast compensation of the textual information contained in a web page using numerical optimization. The optimization process can be reduced to the minimization of a single objective function which aims to achieve an on-the-fly compensation inducing a small amount of change in the original colors. Mass-spring system based optimization and CMA-ES metaheuristics are compared with the problem in order to assess their efficiency for compensating the loss. Experiments conducted on real and artificial datasets, prove the methods efficiency even with a small number of evaluations. Also, the methods behaviour is bound to the amount of compensation needed.
PubDate: 2014-12-01

• A PTAS for a Particular Case of the Two-machine Flow Shop with Limited
Machine Availability
• Abstract: Abstract In this paper we develop a polynomial-time approximation scheme for a particular case of the two-machine flow shop scheduling problem with several availability constraints on the second machine under the resumable scenario.
PubDate: 2014-12-01

• A Graphical Approach to Solve an Investment Optimization Problem
• Abstract: Abstract We consider a project investment problem, where a set of projects and an overall budget are given. For each project, a piecewise linear profit function is known which describes the profit obtained if a specific amount is invested into this project. The objective is to determine the amount invested into each project such that the overall budget is not exceeded and the total profit is maximized. For this problem, a graphical algorithm (GrA) is presented which is based on the same Bellman equations as the best known dynamic programming algorithm (DPA) but the GrA has several advantages in comparison with the DPA. Based on this GrA, a fully-polynomial time approximation scheme is proposed having the best known running time. The idea of the GrA presented can also be used to solve some similar scheduling or lot-sizing problems in a more effective way, e.g., the related problem of finding lot-sizes and sequencing several products on a single imperfect machine.
PubDate: 2014-12-01

• Goal Directed Programming for Determining Process Efficiency Using Data
Envelopment Analysis
• Abstract: Abstract There are numerous measurement methods for process performance control. One of which, widely used in quality control programs, is process capability (C p ) index. The advantage of this index is due to the high amount of information extracted from it. Since C p is independent from a particular measurement unit it can be used to compare several quite different processes. While the relative efficiency of the process performance based on the C p for a period is satisfying, the process may lose efficiency in the next period for variety of reasons and could not keep up with the standard limits. The objective of this paper is to develop a new approach for measuring the relative efficiency of peer decision making units (DMUs) based upon process capability indices. A case study demonstrates the applicability of the proposed approach.
PubDate: 2014-12-01

• On Compromise Mixed Allocation in Multivariate Stratified Sampling with
Random Parameters
• Abstract: Abstract For estimating the population mean Clark and Steel (Stat. 49, 1970–207 2000) worked out the optimum allocation of sample sizes to strata and stages with simple additional constraints to use different type of allocations in different strata. Ahsan et al. (Aligarh J. Statist. 25, 87–97 2005) used the same idea to work out optimum allocation in univariate stratified sampling and called it a ‘Mixed Allocation’. Later on Varshney and Ahsan (J. Indian Soc. Agr. Stat. 65(3), 291–296, 2011) extended this work for multivariate stratified sampling and called it a compromise mixed allocation. This article presents a more realistic approach to the compromise mixed allocation by formulating the problem as a Stochastic Nonlinear Programming Problem in which the stratum-wise measurement costs and the sample stratum standard deviations are independent random variables with known probability distributions. The application of this approach is exhibited through a numerical example with normal distributions of the random parameters. The proposed compromise mixed allocation is compared with some other well known compromise allocations available in multivariate stratified sampling literature. It is found that the author’s proposed compromise mixed allocation is the most efficient allocation among the discussed allocations. A simulation study is also carried out to support the claim made by the authors on the basis of the results of the numerical example.
PubDate: 2014-12-01

• A Generic Interior-point Algorithm for Monotone Symmetric Cone Linear
Complementarity Problems Based on a New Kernel Function
• Abstract: Abstract Kernel functions play an important role in defining new search directions for interior-point algorithms for solving monotone linear complementarity problems. In this paper we present a new kernel function which yields the complexity bounds $${\mathcal O}(\sqrt{r}\log r\log\frac{r}{\epsilon})$$ and $${\mathcal O}(\sqrt{r}\log\frac{r}{\epsilon})$$ for large-and small-update methods, respectively, which are currently the best known bounds for such methods.
PubDate: 2014-12-01

• Optimal SVM Classification for Compact Polarimetric Data Using Stokes
Parameters
• Abstract: Abstract In this paper, our objective is twofold: first, to assess the potential of the new compact polarimetry imaging radar system called hybrid-polarimetry (CL-pol): circular transmitted polarization and coherent dual linear receive polarizations for full characterization and exploitation of the backscattered field. Useful characteristics that are unique to the hybrid-polarity architecture are invariance to geometrical orientations and minimizing on-board resource requirements. Second, to develop a classification polarimetric method based on the support vector machine (SVM) which uses full- and the compact-pol modes. We present a study of the polarimetric information content derived from the decomposition for the CL-mode using Stokes parameter data products and from Freeman-Durden-decomposition derived from the full-pol imaging mode. We compare SVM classification both among the partial polarimetric datasets and against the full quad-pol dataset. We illustrate our results by using the polarimetric SAR images of Algiers city in Algeria acquired by the RadarSAT2 (FQ19) in C-band.
PubDate: 2014-12-01

• Preface
• PubDate: 2014-12-01

• A Large-Update Interior-Point Method for Cartesian P ∗ ( κ
)-LCP Over Symmetric Cones
• Abstract: Abstract In this paper, we propose a new large-update interior point algorithm for the Cartesian P ∗(κ) linear complementarity problem over symmetric cones (SCLCP) based on a parametric kernel function, which determines both search directions and the proximity measure between the iterate and the μ-center. Using Euclidean Jordan algebras, we derive the iteration bound that match the currently best known iteration bound for large update methods.
PubDate: 2014-12-01

• Multi-period Possibilistic Mean Semivariance Portfolio Selection with
Cardinality Constraints and its Algorithm
• Abstract: Abstract In this paper, we consider a multi-period portfolio selection problem in a fuzzy investment environment, in which the return and risk of assets are characterized by possibilistic mean value and possibilistic semivariance, respectively. Based on the theories of possibility, a new multi-period possibislistic portfolio selection model is proposed, which contains risk control, transaction costs, borrowing constraints, threshold constraints and cardinality constraints. the proposed model can be transformed into a crisp nonlinear dynamic optimization problem by using fuzzy programming approach. Because of the transaction costs and cardinality constraints, the multi-period portfolio selection is a mix integer dynamic optimization problem with path dependence A forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, a comparison analysis of the different cardinality constraints is provided to illustrate the efficiency of the proposed approaches and the designed algorithm.
PubDate: 2014-11-28

• CUBLAS-aided Long Vector Algorithms
• Abstract: Abstract The paper propose vector methods that allow you to use GPU-processors more rationally. The approach is based on using long vectors of arguments instead of short matrix rows. Efficiency of the method is verified by comparisons with a library OpenCurrent.
PubDate: 2014-11-25

• Reducing the Structure Space of Bayesian Classifiers Using Some General
Algorithms
• Abstract: Abstract The use of Bayesian Networks (BNs) as classifiers in different application fields has recently witnessed a noticeable growth. Yet, using the Naïve Bayes application, and even the augmented Naïve Bayes, to classifier-structure learning, has been vulnerable to some extent, which accounts for the resort of experts to other more sophisticated types of algorithms. Consequently, the use of such algorithms has paved the way for raising the problem of super-exponential increase in computational complexity of the Bayesian classifier learning structure, with the increasing number of descriptive variables. In this context, the main objective of our present work lies in trying to conceive further solutions to solve the problem of the intricate algorithmic complexity imposed during the learning of Bayesian classifiers structure through the use of sophisticated algorithms. Our results revealed that the newly suggested approach allows us to considerably reduce the execution time of the Bayesian classifier structure learning without any information loss.
PubDate: 2014-10-31

• A new Hybrid Projection Algorithm for Solving the Split Generalized
Equilibrium Problems and the System of Variational Inequality Problems
• Abstract: Abstract In this paper, we introduced modified Mann iterative algorithms by the new hybrid projection method for finding a common element of the set of fixed points of a countable family of nonexpansive mappings, the set of the split generalized equilibrium problem and the set of solutions of the general system of the variational inequality problem for two-inverse strongly monotone mappings in real Hilbert spaces. The strong convergence theorem of the iterative algorithm in Hilbert spaces under certain mild conditions are provided.
PubDate: 2014-10-03

• Image-Filtering and Optimization of Rainy Cells
• Abstract: Abstract This paper deals with the identification and elimination of ground echoes in radar images using their textural features. The images collected in Setif (Algeria) by a non Doppler radar, are processed. Two kinds of texture-based techniques have been considered, consisting in calculating either the histograms of their sum and difference or the pattern recognition. Energy and local homogeneity are found to be the textural parameters that clearly separate the precipitation and ground echoes. To get only the rainfall echoes, the resulting template is applied to each of the raw radar images and the filtering is improved by removing the residual clutter with pattern recognition. This method allows as to completely removing the ground clutter with minimal alterations of the rain echoes with reduced calculation time. It has the advantages of effectiveness and simplicity. However, when there is overlap of precipitation echoes with the ground echoes, significant small cells may occur. In this case, these cells are restored by interpolating from neighboring pixels with a regularization function. The application of this optimization algorithm of filtered images can effectively reproduce true structure of clouds. The radar images can be processed in real-time because the computation time needed by these techniques is small.
PubDate: 2014-06-10

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