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Investment decision is difficult to be determined as the investors need to earn highest possible return in generating profit and protecting capital. Mathematical model which can provide the ranking and proportion of the investment alternatives will benefit investors as selection guideline. This paper aims to investigate in ranking and allocating proportion of asset funds using fuzzy preference relation and weighting algorithm. The evaluation of asset fund is expressed in trapezoidal fuzzy number. The data used for this study is 30 asset funds that listed in the Bursa Malaysia. This study found that 14 asset funds are suggested based on ranking and proportion allocation obtained from this model. As a conclusion, this study can assist investors in making decision in terms of ranking and allocating asset funds. [ABSTRACT FROM AUTHOR]

In this paper, a new multi-agent genetic algorithm based on orthogonal experiment is proposed, which is based on multi-agent system, genetic algorithm and orthogonal experimental design. The design of neighborhood competition operator, orthogonal crossover operator, Son and self-learning operator. The new algorithm is applied to mobile tower defense game, according to the characteristics of the game, the establishment of mathematical models, and finally increases the value of the game’s monster. [ABSTRACT FROM AUTHOR]

The emerging growth of edge devices and the expansion of IoT systems produced the demand to enhance their security algorithms to run on diverse applications and appliances. Lightweight cipher algorithms are mainly designed for IoT-constrained devices. Thus, due to the new services and applications of IoT that require extensive networks and devices, the need for efficient lightweight cipher algorithm implementations is a critical issue. In this paper, an enhanced cipher LED-128 algorithm based on Galois Fields (GF) operations is presented. The mathematical model of the LED algorithm simply requires a slight execution time for encryption-decryption processing. The Enhanced LED algorithm is applied with 64 bits of block plaintext and 128 bits of the key size which turn out 64 bits block size of ciphertext. The proposed algorithm is presented to advance the randomness of cipher text by enhancing the key schedule based on GF operations. The developed key schedule is enhanced to generate a robust key for the proposed algorithm. The NIST statistical tests have been examined and experimented for the proposed enhanced algorithm by utilizing diverse keys with distinct cipher text, which passed the randomness for each test. The proposed algorithm demonstrated a high confusion and diffusion based on the correlation coefficient analysis. The executed time for the encryption and decryption processes of the proposed enhanced LED algorithm is concentrated at minimum compared to the original LED-128 cipher algorithm. Hence, the proposed enhanced algorithm can be implemented for diverse IoT systems and can reach the trade-off between cost and performance as an efficient lightweight algorithm. The results of the enhanced algorithm are benchmarked with the current LED 64/128 algorithms and presented significant improvements in the performance compared to original design of the LED cipher algorithm. [ABSTRACT FROM AUTHOR]

The paper presents the problem of calculating the remaining oil reserves and determining the forecast production rate of wells. The mathematical model for the calculation of this problem. Created computational algorithm and software for mathematical model. Forecast production rate was determined and calculated residual reserves the example of the well-birth Umid place to use to create a program. Show amenities, calculated using established task program. [ABSTRACT FROM AUTHOR]

In this paper, the systematization of numerical (implemented on a computer) randomized functional algorithms for approximation of a solution of Fredholm integral equation of the second kind is carried out. Wherein, three types of such algorithms are distinguished: the projection, the mesh and the projection-mesh methods. The possibilities for usage of these algorithms for solution of practically important problems is investigated in detail. The disadvantages of the mesh algorithms, related to the necessity of calculation values of the kernels of integral equations in fixed points, are identified. On practice, these kernels have integrated singularities, and calculation of their values is impossible. Thus, for applied problems, related to solving Fredholm integral equation of the second kind, it is expedient to use not mesh, but the projection and the projection-mesh randomized algorithms. [ABSTRACT FROM AUTHOR]

Mathematical modeling of the heat transfer during the pyrolysis process used for the treatment of the Endof-Lifetires (EOLT) is presented in this paper. The pyrolysis process is 3D and non-stationary and because of this it is very complicated for modeling and studying. To simplify the modeling here a hierarchy of 2D models for the temperature which describe the non-stationary heat transfer in such a pyrolysis station is created. An algorithm for solving the model equations, based on MATLAB software is developed. The results for the temperature for some characteristic periods of operation of pyrolysis station are presented and commented in the paper. The results from this modeling can be used in the real pyrolysis station for more precise displacement of measurement devices and for designing of automated management of the process. [ABSTRACT FROM AUTHOR]

In this paper we will revisit the modification of the piecewise constant policy timestepping (PCPT) method for solving Hamilton-Jacobi-Bellman (HJB) equations. This modification is called piecewise predicted policy timestepping (PPPT) method and if properly used, it may be significantly faster. We will quickly recapitulate the algorithms of PCPT, PPPT methods and of the classical implicit method and apply them on a passport option pricing problem with non-standard payoff. We will present modifications needed to solve this problem effectively with the PPPT method and compare the performance with the PCPT method and the classical implicit method. [ABSTRACT FROM AUTHOR]

In this paper we discuss a general problem related to spurious conservation laws for discrete velocity models (DVMs) of the classical (elastic) Boltzmann equation. Models with spurious conservation laws appeared already at the early stage of the development of discrete kinetic theory. The well-known theorem of uniqueness of collision invariants for the continuous velocity space very often does not hold for a set of discrete velocities. In our previous works we considered the general problem of the construction of normal DVMs, we found a general algorithm for the construction of all such models and presented a complete classification of normal DVMs with small number n of velocities (n<11). Even if we have a general method to classify all normal discrete kinetic models (and in particular DVMs), the existing method is relatively slow and the amount of possible cases to check increases rapidly with n. We remarked that many of our normal DVMs appear to be axially symmetric. In this paper we consider a connection between symmetric transformations and normal DVMs. We first develop a new inductive method that, starting with a given normal DVM, leads by symmetric extensions to a new normal DVM. This method can produce very fast many new normal DVMs with larger number of velocities, showing that the class of normal DVMs contains a large subclass of symmetric models. We finally apply the method to several normal DVMs and construct new models that are not only normal, but also symmetric relatively to more and more axes. We hope that such symmetric velocity sets can be used for DSMC methods of solving Boltzmann equation. [ABSTRACT FROM AUTHOR]

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper. [ABSTRACT FROM AUTHOR]

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm that is able to solve optimal control problems in which the modelling of the system contains variable parameters, with the added complication that, in certain cases, these parameters can lead to control problems governed by quasi-linear equations. Combining the techniques of Pontryagin's Maximum Principle and the shooting method, an algorithm has been developed that is not affected by the values of the parameters, being able to solve conventional problems as well as cases in which the optimal solution is shown to be bang-bang with singular arcs. [ABSTRACT FROM AUTHOR]

The paper deals with an algorithm of translation of RTCP-nets' (real-time coloured Petri nets) coverability graphs into nuXmv state machines. The approach enables users to verify RTCP-nets with model checking techniques provided by the nuXmv tool. Full details of the algorithm are presented and an illustrative example of the approach usefulness is provided. [ABSTRACT FROM AUTHOR]

The paper presents an RTCP-nets' (real-time coloured Petri nets) coverability graphs into Aldebaran format translation algorithm. The approach provides the possibility of automatic RTCP-nets verification using model checking techniques provided by the CADP toolbox. An actual fire alarm control panel system has been modelled and several of its crucial properties have been verified to demonstrate the usability of the approach. [ABSTRACT FROM AUTHOR]

The paper deals with an algorithm of translation of RTCP-nets' (real-time coloured Petri nets) coverability graphs into nuXmv state machines. The approach enables users to verify RTCP-nets with model checking techniques provided by the nuXmv tool. Full details of the algorithm are presented and an illustrative example of the approach usefulness is provided. [ABSTRACT FROM AUTHOR]

A shortest path based algorithm is proposed in this paper to find splitting lines for touching cells. Firstly, an initial splitting line is obtained through the distance transform of a marker image and the watershed algorithm. Then, the initial splitting line is separated into different line segments if necessary, and the start and end points of these line segments act as the start and end points of shortest path. Finally, the shortest path algorithm is used to find the splitting line between the start and end points, and the final result of touching cells splitting can be formed by the contour of the touching cells and the splitting lines. Experimental results show that the proposed algorithm is efficient for different types of touching cells. [ABSTRACT FROM AUTHOR]

This paper proposes a novel parallelization of ABC Algorithm to solve Short-term Hydro-Thermal Scheduling (SHTS) problem. Parallelization is a novel way of improving the convergence of the algorithm. In case of normal ABC algorithms accelerating operation or modification can be used for better convergence and diversity. But with large number of variables the non-linearity of the search space increases and these modifications are not sufficient to give enough diversity in the crowds of swarms for finding better solutions. However, parallelization of the algorithm increases the diversity in solutions and the search capability. The performance of the proposed algorithm is experimented on two short term multi reservoir cascaded hydrothermal systems. First test case is moderately large while the second test case is a considerably large one. Experimental results demonstrate the superior performance of the proposed algorithm as compared to other recently reported ones in terms of convergence and better quality of solutions. [ABSTRACT FROM AUTHOR]

According to the two challenges in the prediction of cross-project software defects, the distribution differences between the source project and the target project dataset and the class imbalance in the dataset, proposing a cross-project software defect prediction method based on transfer learning, named NTrA. Firstly, solving the source project data’s class imbalance based on the Augmented Neighborhood Cleaning Algorithm. Secondly, the data gravity method is used to give different weights on the basis of the attribute similarity of source project and target project data. Finally, a defect prediction model is constructed by using Trad boost algorithm. Experiments were conducted using data, come from NASA and SOFTLAB respectively, from a published PROMISE dataset. The results show that the method has achieved good values of recall and F-measure, and achieved good prediction results. [ABSTRACT FROM AUTHOR]

This paper discusses an extension of the looping algorithm for 3-D triangular or quadrilateral surface mesh generation. The triangulation of the model surface is input by the neutral STL file, and the topology of triangular facets is established. The triangular facets are grouped based on the angles of adjacent facets, and each group forms a feature region. The common boundary of the adjacent feature regions constitutes a feature curve. The nodes are generated on each feature curve based on the mesh density distribution. The boundary of each feature region is represented by the nodes list. For each feature region, an appropriate splitting plane is chose to split it into two sub-regions, the spatial shape of the splitting line is calculated and the nodes are generated on it. The nodes list is determined for each sub-region and each sub-region is recursively subdivided until all sub-regions are not reducible. After mesh generation on each region, the smoothing of the nodes is performed. The proposal algorithm is reliable and efficient for surface mesh generation with high quality. The examples of surface mesh generation are also given to demonstrate the feasibility of the algorithm. [ABSTRACT FROM AUTHOR]

Numerical models serve an important role in eddy current non-destructive evaluation applications. The results of computational models provide meaningful insight into the underlying physics, help theoretically visualize the field/sample interaction and help optimize sensor design and assist algorithms developing for interpreting the measured signals. However, three dimensional computational models can be time consuming. This paper presents a fast and efficient GPU based numerical model for simulating eddy current testing techniques. The model, based on boundary integral method, uses novel matrix compression techniques to optimize the solver performance on GPU architectures. Validation results of model predictions for a number of sample geometries are presented. [ABSTRACT FROM AUTHOR]

Computational aerodynamics is a key technology in aircraft design which is ahead of physical experiment and complements it. Of course all three components of computational modeling are actively developed: mathematical models of real aerodynamic processes, numerical algorithms, and high-performance computing. The most impressive progress has been made in the field of computing, though with a considerable complication of computer architecture. Numerical algorithms are developed more conservative. More precisely, they are offered and theoretically justified for more simple mathematical problems. Nevertheless, computational mathematics now has amassed a whole palette of numerical algorithms that can provide acceptable accuracy and interface between modern mathematical models in aerodynamics and high-performance computers. A significant step in this direction was the European Project ADIGMA whose positive experience will be used in International Project TRISTAM for further movement in the field of computational technologies for aerodynamics. This paper gives a general overview of objectives and approaches intended to use and a description of the recommended four-stage computer technology. [ABSTRACT FROM AUTHOR]

In the paper we test robustness of particular dynamic systems in a compact regions of a plane and a weak structural stability of one dynamic system of high order in a compact region of its phase space. The test was carried out based on the fundamental theory of dynamical systems on a plane and based on the conditions for weak structural stability of high order dynamic systems. A numerical algorithm for testing the weak structural stability of high order dynamic systems has been proposed. Based on this algorithm we assess the weak structural stability of one computable general equilibrium model. [ABSTRACT FROM AUTHOR]

Model reduction is an approach for fast and cost-efficient modelling of large-scale systems governed by Ordinary Differential Equations (ODEs). Multi-dimensional model reduction has been suggested for reduction of the linear systems simultaneously with respect to frequency and any other parameter of interest. Multi-dimensional model reduction is also used to reduce the weakly nonlinear systems based on Volterra theory. Multiple dimensions degrade the efficiency of reduction by increasing the size of the projection matrix. In this paper a new methodology is proposed to efficiently build the reduced model based on regression analysis. A numerical example confirms the validity of the proposed regression algorithm for model reduction. [ABSTRACT FROM AUTHOR]

Integer goal programming problems arise quite naturally in many real-world applications. In this paper, we propose a reference direction approach and interactive algorithm to solve integer goal programming problem. We use analytic hierarchy process (AHP) to get the reference direction. At each iteration, only one integer linear programming problem is solved to get an efficient solution. Through analytic hierarchy process the decision maker has to provide the preference point such that the original problem has been transformed into linear integer programming model. [ABSTRACT FROM AUTHOR]

Ductile damage mechanics is essential to predict failure during cold metal forming applications. Several damage models can be found in the literature. These damage models are coupled with the mechanical behavior so as to model the progressive softening of the material due to damage growth. However, the identification of damage parameters remains an issue. In this paper, an inverse analysis approach is set-up to identify ductile damage parameters, based on different kind of mechanical tests and observables. The Lemaitre damage model is used and damage is coupled with the material behavior. The Efficient Global Optimization (EGO) method is used in a parallel environment. This global algorithm based on kriging meta-model enables the identification of a set of damage parameters based on experimental observables. Global and local observables are used to identify these parameters and a special attention is paid to the computation of the cost function. Finally, an identification procedure based on displacement field measurements is presented and applied for damage parameters identification. [ABSTRACT FROM AUTHOR]

Gaussian beam tracing methods have emerged as a standard approach for modeling sound propagation in the ocean. The first implementations were developed in the 1970's by Bucker and evolved significantly. Today there are actually some four different types of Gaussian beam algorithms. They are quite different in terms of both the beam characteristics and their performance. This paper will review the development of the methods and their application to typical ocean acoustic problems. [ABSTRACT FROM AUTHOR]

In present paper, a two-dimensional numerical study on a standing-wave thermoacoustic engine was performed with compressible SIMPLE algorithm based on a pressure-correction method. First, the simulation model was developed, and the time-dependent compressible thermoacoustic engine system was chosen through substantive numerical tests. Appropriate governing equations for mass, momentum and energy were introduced. Then, the computational results of the onset of the self-excited oscillations across the entire evolution process and the acoustical characteristics of the pressure and velocity wave were presented and analyzed. In addition, the standing-wave of the pressure and velocity along the center of the two stacks are investigated. The crucial nonlinear phenomenon that cannot be captured by the existing linear theory, like high harmonic frequencies, is also revealed in present paper. It is concluded that compressible SIMPLE algorithm could be employed in our future work to simulate and optimize thermoacoustic system. The present result is an important step toward development to predict the high-amplitude thermoacoustic systems and optimize thermoacoustic engine performance. [ABSTRACT FROM AUTHOR]

This paper details findings from the research work targeted at economic communications investigation with agent-based models usage. The agent-based model set was engineered to simulate economic communications. Money in the form of internal and external currencies was introduced into the models to support exchanges in communications. Every model, being based on the general concept, has its own peculiarities in algorithm and input data set since it was engineered to solve the specific problem. Several and different origin data sets were used in experiments: theoretic sets were estimated on the basis of static Leontief's equilibrium equation and the real set was constructed on the basis of statistical data. While simulation experiments, communication process was observed in dynamics, and system macroparameters were estimated. This research approved that combination of an agent-based and mathematical model can cause a synergetic effect. [ABSTRACT FROM AUTHOR]

The paper deals with the development of algorithms for solving nonlinear problems of heat conduction in bodies consisting of layered metal composites. The nonlinearity of the problems is governed by the temperature dependence of the heat conductivity coefficients of the composite layer materials. Mathematical models and solution algorithms based on the boundary element method have been constructed for one-dimensional cases of heat distribution. [ABSTRACT FROM AUTHOR]

In the paper, a mathematical model and a numerical algorithm are proposed for modeling the complex of phenomena which accompany the passage of a friable asteroid-comet body through the Earth's atmosphere: the material ablation, the dissociation of molecules, and the radiation. The proposed model is constructed on the basis of the Navier-Stokes equations for viscous heat-conducting gas with an additional equation for the motion and propagation of a friable lumpy-dust material in air. The energy equation is modified for the relation between two its kinds: the usual energy of the translation of molecules (which defines the temperature and pressure) and the combined energy of their rotation, oscillation, electronic excitation, dissociation, and radiation. For the mathematical model of atmosphere, the distribution of density, pressure, and temperature in height is taken as for the standard atmosphere. An asteroid-comet body is taken initially as a round body consisting of a friable lumpy-dust material with corresponding density and significant viscosity which far exceed those for the atmosphere gas. A numerical algorithm is proposed for solving the initial-boundary problem for the extended system of Navier-Stokes equations. The algorithm is the combination of the semi-Lagrangian approximation for Lagrange transport derivatives and the conforming finite element method for other terms. The implementation of these approaches is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

In the paper, a mathematical model and a numerical algorithm are proposed for modeling the complex of phenomena which accompany the passage of a friable asteroid-comet body through the Earth's atmosphere: the material ablation, the dissociation of molecules, and the radiation. The proposed model is constructed on the basis of the Navier-Stokes equations for viscous heat-conducting gas with an additional equation for the motion and propagation of a friable lumpy-dust material in air. The energy equation is modified for the relation between two its kinds: the usual energy of the translation of molecules (which defines the temperature and pressure) and the combined energy of their rotation, oscillation, electronic excitation, dissociation, and radiation. For the mathematical model of atmosphere, the distribution of density, pressure, and temperature in height is taken as for the standard atmosphere. An asteroid-comet body is taken initially as a round body consisting of a friable lumpy-dust material with corresponding density and significant viscosity which far exceed those for the atmosphere gas. A numerical algorithm is proposed for solving the initial-boundary problem for the extended system of Navier-Stokes equations. The algorithm is the combination of the semi-Lagrangian approximation for Lagrange transport derivatives and the conforming finite element method for other terms. The implementation of these approaches is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

In this paper a hybrid algorithm is proposed to find the optimal solution for any instance of the bin packing problem one-dimensional. The hybrid algorithm considers the use of a heuristic method and a mathematical model based on flow arcs technique to find the optimal solution for an instance of 1D-BPP. The hybrid algorithm makes use of the lower bound of an instance as an element that allows it to identify if it have found the optimum or starting from this value it must find the optimal solution. The experiments were performed using the instances of the hard28 set, finding it the optimal solutions for all instances. The results show that the developed algorithm, called AHR, used 75% less time than using the Valerio model. [ABSTRACT FROM AUTHOR]

This paper presents new mathematical models and algorithms of optimal control of multiple parallel FIFO-queues in the memory of one level, where the queues are moving consecutive and one after another in a circle. As mathematical models we propose random walks on the integer lattice in different areas on the plane and in 3-dimensional space. The optimality criterion is the minimum average portion of lost elements on infinite working time. [ABSTRACT FROM AUTHOR]

This paper presents mathematical models and algorithms of optimal control of 2 FIFO-queues in the memory of one level where the queues are moving one after another in a circle. As mathematical models we propose random walks on the integer lattice in different areas in 3-dimensional space. Optimality criterions are the average working time. [ABSTRACT FROM AUTHOR]

The inverse problem associated with reconstruction of Poisson blurred images has attracted attention in recent years. In this paper, we propose an alternative unified approach to blind image deconvolution problem using fuzzy median filter as Gibbs prior to model the nature of inter pixel interaction for better edge preserving reconstruction. The performance of the algorithm at various SNR levels has been studied quantitatively using PSNR, RMSE and universal quality index (UQI). Comparative analysis with existing methods has also been carried out. [ABSTRACT FROM AUTHOR]

Pseudo electrocardiogram (pseudo-ECG) is a virtual ECG signal that is computed using 1D mathematical models of the myocardium. This signal has the QRS-complex and T wave similar to that of real ECG. In this paper, we used pseudo-ECG as a tool to develop an algorithm for the estimation of electrophysiological properties of the myocardium or single cardiomyocytes based on electrogram recordings. Here, we analyzed the relationship between pseudo-ECG produced by a 1D myocardial model and characteristics of the cellular action potential and parameters of an ionic cardiomyocyte model. We showed that in the noise-free conditions the action potential morphology and cardiomyocyte model parameters can be identified from pseudo-ECG using a linear transformation. [ABSTRACT FROM AUTHOR]

The tomogram deformation method, previously proposed by the author for fan-beam tomography problems, has been extended here to a number of simple curved rays that allow one-to-one transitions to parallel straight lines. The transition from straight lines to curvilinear lines expands the range of possible statements of problems of tomographic diagnostics of objects, in particular, for cases of weak refraction in the medium under study, when it is possible to analytically describe the equation of the ray path in a first approximation. The software implementation of the algorithm is performed using the example of a family of trajectories described by a sinusoid with a controlled period and amplitude. A numerical simulation on a number of mathematical models showed the possibility of geometric implementation of the Generalized Radon Transform inversion based on the direct and inverse tomogram deformation procedures. In the two- dimensional statement of the problem, it is shown that artifacts of fan-beam and wave few-view tomography largely repeat the form of the trajectories themselves: for fan-beam tomography, the image of artifacts is close to weak hyperbolic disturbances, for wave tomography, characteristic wave structures appear in the polar coordinate system - in radius and in angle. These artifacts arise at the stage of backprojection, during the transition from rectilinear projections to projections along the initial trajectories, with the inverse deformation being carried out. [ABSTRACT FROM AUTHOR]

In this paper, we steady natural convection in a discrete heat transfer and the effect of Rayleigh number in a two- dimensional square enclosure with an inner square block. The present problem taken by three different cases were containing on the partially heated which left vertical wall maintained at high temperature Th(Th > Tc). The right vertical wall considered at Tc and other horizontal walls and the inner square block should be thermally insulated. The mathematical model considered as mass, momentum and energy equation solved to using the simple algorithm by Finite Volume Method (FVM) on a flounder grid system consisting of modified Alternating Direction Implicit Method (ADIM) which are used to solve vorticity-stream function formulation.This result found that the streamlines and isotherms achieved a maximum for the distribution of partial heater and also increasing Rayleigh number. [ABSTRACT FROM AUTHOR]

Variation in illumination has a drastic effect on the appearance of a face image. This may hinder the automatic face recognition process. This paper presents a novel approach for face recognition under varying lighting conditions. The proposed algorithm uses adaptive retina modeling based illumination normalization. In the proposed approach, retina modeling is employed along with histogram remapping following normal distribution. Retina modeling is an approach that combines two adaptive nonlinear equations and a difference of Gaussians filter. Two databases: extended Yale B database and CMU PIE database are used to verify the proposed algorithm. For face recognition Gabor Kernel Fisher Analysis method is used. Experimental results show that the recognition rate for the face images with different illumination conditions has improved by the proposed approach. Average recognition rate for Extended Yale B database is 99.16%. Whereas, the recognition rate for CMU-PIE database is 99.64%. [ABSTRACT FROM AUTHOR]

The discrete element method has been increasingly used to model granular processes of increasing complexity, from dry to wet to multiphase systems. Whilst DEM has been shown to produce qualitatively many of the complex phenomena observed in these complex granular systems, establishing the extent of the predictive capability of DEM model is still in its infancy. This summary paper discusses the need to develop verification and validation methodologies with regard to DEM computations. It proposes the need to first verify that a DEM code with its implemented mathematical model and computation algorithm is accurately reproducing the conceptual model and its solution, before validating to determine the degree to which the computational model accurately represent the physics being modelled. It also discusses the associated issue of data analysis to extract the parameters of interest from DEM particle scale data. [ABSTRACT FROM AUTHOR]

The paper presents a set of Monte Carlo algorithms, based on the Kac's stohastic gas model for simulation of the binary collision process in a homogenous rarefied gas. These collision algorithms avoid the repeat collisions and can be used for simualtion of the collsions in grid cells with small average number of particles, when the DSMC method is applied and the simulation requires computational resources of very large proportions. [ABSTRACT FROM AUTHOR]

The objective of this research is to build a nested generalized linear mixed model using an ordinal response variable with some covariates. There are three main jobs in this paper, i.e. parameters estimation procedure, simulation, and implementation of the model for the real data. At the part of parameters estimation procedure, concepts of threshold, nested random effect, and computational algorithm are described. The simulations data are built for 3 conditions to know the effect of different parameter values of random effect distributions. The last job is the implementation of the model for the data about poverty in 9 districts of Java Island. The districts are Kuningan, Karawang, and Majalengka chose randomly in West Java; Temanggung, Boyolali, and Cilacap from Central Java; and Blitar, Ngawi, and Jember from East Java. The covariates in this model are province, number of bad nutrition cases, number of farmer families, and number of health personnel. In this modeling, all covariates are grouped as ordinal scale. Unit observation in this research is sub-district (kecamatan) nested in district, and districts (kabupaten) are nested in province. For the result of simulation, ARB (Absolute Relative Bias) and RRMSE (Relative Root of mean square errors) scale is used. They show that prov parameters have the highest bias, but more stable RRMSE in all conditions. The simulation design needs to be improved by adding other condition, such as higher correlation between covariates. Furthermore, as the result of the model implementation for the data, only number of farmer family and number of medical personnel have significant contributions to the level of poverty in Central Java and East Java province, and only district 2 (Karawang) of province 1 (West Java) has different random effect from the others. The source of the data is PODES (Potensi Desa) 2008 from BPS (Badan Pusat Statistik). [ABSTRACT FROM AUTHOR]

This paper presents a new calibration procedure to identify the geometric parameters which improve the kinematic model accuracy of a mechanism. This procedure has been applied to a 2-DOF spatial parallel mechanism, obtaining the identified parameters by means of the direct kinematic model and reducing the position error of the moving platform. Data acquisition is performed by measuring three standard spheres, fixed to the moving platform, by means of a coordinate measuring machine. The method implemented defines an objective function which is optimized though a numerical method based on the Levenberg-Marquardt algorithm. This function compares the measured and calculated moving platform coordinates and minimizes this difference. Results show that in both cases, identification and test position, the position error is reduced considerably. The method developed can be easily generalized to other parallel mechanism. [ABSTRACT FROM AUTHOR]

This paper analyzes the effectiveness of various monotonic discretizations of an ODE in a parameter range reduction algorithm by considering the resulting ranges for the parameter λ obtained from the simple model x′ = λx. [ABSTRACT FROM AUTHOR]

This paper presents the formulation of an axi-symmetric element based on an efficient method called 'Inverse Approach' (I.A.) for the numerical modeling of cold forging process. In contrast to the classical incremental methods, the Inverse Approach exploits the known shape of the final part and executes the calculation from the final part to the initial billet. The assumptions of the proportional loading and the simplified tool actions make the I.A. calculation very fast. The metal's incompressibility is ensured by the penalty method. The comparison with ABAQUS® and FORGE® shows the efficiency and limitations of the I.A. This simplified method will be a good tool for the preliminary preform design. [ABSTRACT FROM AUTHOR]

Aim of this paper is to develop an adaptive technique for modeling an ammunition trajectory fired from gun to hit a desired aerial target (Surface-to-Air) accurately. The proposed technique for fire control system would follow the estimated trajectory based on ballistic data provided. The essential components of a modern fire control system of a gun required for computational modeling, their connectivity and requirements have also been discussed. The ballistic data of gun ammunition has been exploited in four parameters to get the ballistic solution by modeling. These four parameters are: azimuth angle, elevation angle, initial velocity and miss distance. The target interception depends upon proposed miss-distance concept, hence, the mathematical model computes future position of the target on the basis of present position of target. [ABSTRACT FROM AUTHOR]

Methods which provide good conditioning of model identification task in immune inspired, steady-state controller SILO (Stochastic Immune Layer Optimizer) are presented in this paper. These methods are implemented in a model based optimization algorithm. The first method uses a safe model to assure that gains of the process’s model can be estimated. The second method is responsible for elimination of potential linear dependences between columns of observation matrix. Moreover new results from one of SILO implementation in polish power plant are presented. They confirm high efficiency of the presented solution in solving technical problems. [ABSTRACT FROM AUTHOR]

In this paper a computational method and numerical algorithm is developed for finding the optimal control policy for a partially observable system subject to random failure. The condition of the system is modeled by an unobservable continuous-time homogeneous Markov chain. Multivariate data stochastically related to the system state is collected at equidistant sampling times. The system is controlled by a multivariate Bayesian control chart, i.e. full inspection followed by maintenance is performed when the posterior probability that the system is in the warning state exceeds a control limit. A statistical constraint is considered which bounds the probability of a true alarm given by the control chart. The objective is to minimize the long-run expected average cost per unit time by determining the optimal values of the control limit and sampling interval subject to the statistical constraint. The stochastic evolution of the posterior probability process is analyzed and computational algorithm is developed in the semi-Markov decision process framework. Numerical examples are provided which illustrate the effect of the statistical constraint and the performance of the Bayesian control chart is compared with the traditional multivariate χ2 control chart. [ABSTRACT FROM AUTHOR]

A simple algorithm finds the partition of a data interval optimizing the fitness of a model that represents the underlying signal as constant over the elements of the partition. Using dynamic programming the exponentially large space of partitions of N data points is implicitly but exhaustively searched in time O(N2). This paper also describes an extension to optimal partitions of higher dimensional data spaces, with application to multivariate signal processing, image processing, cluster analysis, density estimation in 3-dimensional redshift surveys, etc. The algorithm finds the exact global optimum, automatically determines the model order (the number of segments), and has a convenient real-time mode. © 2005 American Institute of Physics [ABSTRACT FROM AUTHOR]

To better predict the polycrystalline behavior at large deformations, a robust time integration algorithm at the single crystal level is of vital importance. The present paper analyzes often-used integration approaches for rate-dependent single crystal plasticity in the area and classifies them into three representative approaches. Three different formulations are grouped into the first approach, which is based up the deformation gradient. The second approach is defined in terms of the slip rates. A modification is proposed to alleviate the numerical stabilities to the second approach upon analyzing the Jacobian. Comparisons between these two approaches show that they demonstrate very similar phenomenology in terms of kinematics and kinetics. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]

In this paper, we present results from an experimental evaluation of centroiding algorithms, simple center of gravity (CoG) and weighted center of gravity (WCoG) in a Shack Hartmann wavefront sensor at different light levels and background noise conditions. CoG performs better than WCoG at good light conditions. WCoG performs better than CoG algorithm at low light level conditions and in cases of high intensity. [ABSTRACT FROM AUTHOR]