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Modal-free optimization algorithms do not require specific mathematical models, and they, along with their other benefits, have great application potential in adaptive optics. In this study, two different algorithms, the single-dimensional perturbation descent algorithm (SDPD) and the second-order stochastic parallel gradient descent algorithm (2SPGD), are proposed for wavefront sensorless adaptive optics, and a theoretical analysis of the algorithms' convergence rates is presented. The results demonstrate that the single-dimensional perturbation descent algorithm outperforms the stochastic parallel gradient descent (SPGD) and 2SPGD algorithms in terms of convergence speed. Then, a 32-unit deformable mirror is constructed as the wavefront corrector, and the SPGD, single-dimensional perturbation descent, and 2SPSA algorithms are used in an adaptive optics numerical simulation model of the wavefront controller. Similarly, a 39-unit deformable mirror is constructed as the wavefront controller, and the SPGD and single-dimensional perturbation descent algorithms are used in an adaptive optics experimental verification device of the wavefront controller. The outcomes demonstrate that the convergence speed of the algorithm developed in this paper is more than twice as fast as that of the SPGD and 2SPGD algorithms, and the convergence accuracy of the algorithm is 4% better than that of the SPGD algorithm. [ABSTRACT FROM AUTHOR]

Objective: Bioinformatics analyses have been becoming important research tools in the field of life science since 2000. New tools have been developed for the detection of allergens in food sources. This study investigated potential allergen proteins similar to the endochitinase class 1(Pers a 1) protein found in avocado using bioinformatics analysis tools. Materials and Methods: The potential allergens were examined with four different in silico tools: Clustal W for multiple sequence comparison, Swiss-MODEL for homology modeling, ProtParam for comparing protein parameters, and AlgPred for allergen prediction. Results: In silico analyses revealed high rates of similarities in protein sequences among the studied species. The highest percent identity was found in Cinnamomum micranthum f. kanehirae as 97.55 while the lowest percent identity was found in Diospyros kaki as 70.23. It is very important to note that 9 of the 10 potential allergen species investigated are plats consumed in daily life and these species were identified as allergens. According to the algorithm of BLAST search on allergen representative peptides (ARPs), ARPs were found in eight potential allergen proteins except for Prunus avium and Citrus unshiu. The ARP sequence related to Persea americana is LQLTWNYNYGAAGNSIGFNGLSNP. Conclusion: People who are allergic to avocado (Persea americana) may be advised to be careful while consuming foods such as Phoenix dactylifera, Allium sativum, Citrus unshiu, Diospyros kaki, and Spinacia oleracea. The present paper can be considered as a model study for understanding allergens in foods by using in silico tools. [ABSTRACT FROM AUTHOR]

The thermodynamic stability of a folded RNA is intricately tied to the counterions and the free energy of this interaction must be accounted for in any realistic RNA simulations. Extending a tight-binding model published previously, in this paper we investigate the fundamental structure of charges arising from the interaction between small functional RNA molecules and divalent ions such as Mg2+ that are especially conducive to stabilizing folded conformations. The characteristic nature of these charges is utilized to construct a discretely connected energy landscape that is then traversed via a novel application of a deterministic graph search technique. This search method can be incorporated into larger simulations of small RNA molecules and provides a fast and accurate way to calculate the free energy arising from the interactions between an RNA and divalent counterions. The utility of this algorithm is demonstrated within a fully atomistic Monte Carlo simulation of the P4-P6 domain of the Tetrahymena group I intron, in which it is shown that the counterionmediated free energy conclusively directs folding into a compact structure. [ABSTRACT FROM AUTHOR]

In clustering problems, to model the intrinsic structure of unlabeled data, the latent variable models are frequently used. These model-based clustering methods often provide a clustering rule minimizing the total false assignment error. However, in many clustering applications, it is desirable to treat false assignment errors for a certain cluster differently. In this paper, we introduce the false assignment rate for clustering and estimate it by using the extended likelihood approach. We propose VRclust, a novel clustering rule that controls various errors differently across clusters. Real data examples illustrate the usage of estimation of false assignment rate and a simulation study shows that error controls are consistent as the sample size increases. [ABSTRACT FROM AUTHOR]

Using computer simulations to model the folding of proteins into their native states is computationally expensive due to the extraordinarily low degeneracy of the ground state. In this paper, we develop an efficient way to sample these folded conformations using Wang Landau sampling coupled with the configurational bias method (which uses an unphysical 'temperature' that lies between the collapse and folding transition temperatures of the protein). This method speeds up the folding process by roughly an order of magnitude over existing algorithms for the sequences studied. We apply this method to study the adsorption of intrinsically disordered hydrophobic polar protein fragments on a hydrophobic surface. We find that these fragments, which are unstructured in the bulk, acquire secondary structure upon adsorption onto a strong hydrophobic surface. Apparently, the presence of a hydrophobic surface allows these random coil fragments to fold by providing hydrophobic contacts that were lost in protein fragmentation. [ABSTRACT FROM AUTHOR]

Improving tractive effort is a very complex task in locomotive design. It requires the development of not only mechanical systems but also power systems, traction machines and traction algorithms. At the initial design stage, traction algorithms can be verified by means of a simulation approach. A simple single wheelset simulation approach is not sufficient because all locomotive dynamics are not fully taken into consideration. Given that many traction control strategies exist, the best solution is to use more advanced approaches for such studies. This paper describes the modelling of a locomotive with a bogie traction control strategy based on a co-simulation approach in order to deliver more accurate results. The simplified and advanced modelling approaches of a locomotive electric power system are compared in this paper in order to answer a fundamental question. What level of modelling complexity is necessary for the investigation of the dynamic behaviours of a heavy-haul locomotive running under traction? The simulation results obtained provide some recommendations on simulation processes and the further implementation of advanced and simplified modelling approaches. [ABSTRACT FROM AUTHOR]

In this paper, a method for numerical simulation of the shape of a ferrofluid under external magnetic fields and the gravitational field is presented. The final shape is determined by an equilibrium condition of energy in a coupled system of electromagnetic fields and ferrofluid in the presence of gravity. The shape of the ferrofluid is captured by using the level set technique. The velocity field is calculated using continuum shape sensitivity analysis based on the material derivative concept. The numerical algorithm is implemented with a standard finite element procedure and tested on a shaping problem of ferrofluid located under an electromagnet. The numerical results showed that the proposed algorithm and numerical techniques are feasible and effective means of calculating ferrofluid shape variation under magnetic fields and the gravitational force. [ABSTRACT FROM AUTHOR]

Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant. In such a scenario, it is required that different loops oscillating due to a common cause and hence similar frequency may be grouped together. In this paper an adaptive method for plant-wide oscillation detection based on multivariate empirical mode decomposition (MEMD) along with a grouping algorithm is proposed. The method can identify multiple oscillation groups among different variables as well as variables with random noise only. The proposed method is also applicable to both non-linear and non-stationary time series where the techniques based on the conventional Fourier analysis are prone to errors. Within each group that oscillate due to a common cause, the method can also indicate the location of the probable root cause of oscillations. The efficacy of the proposed method is established with the help of both simulation and industrial case studies. [ABSTRACT FROM AUTHOR]

The block inverse iteration and block Newton’s methods proposed by the authors of this paper for computing invariant pairs of regular linear matrix pencils are generalized to the case of regular nonlinear matrix pencils. Numerical properties of the proposed methods are demonstrated with a typical quadratic eigenproblem. [ABSTRACT FROM AUTHOR]

Objective: Dynamic ambulance redeployment policies tend to introduce much more flexibilities in improving ambulance resource allocation by capitalizing on the definite geospatial-temporal variations in ambulance demand patterns over the time-of-the-day and day-of-the-week effects. A novel modelling framework based on the Approximate Dynamic Programming (ADP) approach leveraging on a Discrete Events Simulation (DES) model for dynamic ambulance redeployment in Singapore is proposed in this paper.Methods: The study was based on the Singapore's national Emergency Medical Services (EMS) system. Based on a dataset comprising 216,973 valid incidents over a continuous two-years study period from 1 January 2011-31 December 2012, a DES model for the EMS system was developed. An ADP model based on linear value function approximations was then evaluated using the DES model via the temporal difference (TD) learning family of algorithms. The objective of the ADP model is to derive approximate optimal dynamic redeployment policies based on the primary outcome of ambulance coverage.Results: Considering an 8min response time threshold, an estimated 5% reduction in the proportion of calls that cannot be reached within the threshold (equivalent to approximately 8000 dispatches) was observed from the computational experiments. The study also revealed that the redeployment policies which are restricted within the same operational division could potentially result in a more promising response time performance. Furthermore, the best policy involved the combination of redeploying ambulances whenever they are released from service and that of relocating ambulances that are idle in bases.Conclusion: This study demonstrated the successful application of an approximate modelling framework based on ADP that leverages upon a detailed DES model of the Singapore's EMS system to generate approximate optimal dynamic redeployment plans. Various policies and scenarios relevant to the Singapore EMS system were evaluated. [ABSTRACT FROM AUTHOR]

This paper deals with the stability problem of selected induction motor speed estimators in the case of the regenerating mode operation. Two effective solutions are taken into consideration: adaptive full-order observer and model reference adaptive system-type estimator based on the current flux model and stator current estimation. The two estimation algorithms are compared in detail, namely their mathematical models, theoretical stability analysis, unstable operation areas, and stability improvement methods. The speed adaptation mechanism is extended with an additional shift angle in both cases. The theoretical analysis and simulation test results are validated by wide experimental tests. [ABSTRACT FROM PUBLISHER]

Energy optimisation is one of the important issues in the research of wireless sensor networks (WSNs). In the application of monitoring, a large number of sensors are scattered uniformly to cover a collection of points of interest (PoIs) distributed randomly in the monitored area. Since the energy of battery-powered sensor is limited in WSNs, sensors are scheduled to wake up in a large-scale sensor network application. In this paper, we consider how to reduce the energy consumption and prolong the lifetime of WSNs through wake-up scheduling with probabilistic sensing model in the large-scale application of monitoring. To extend the lifetime of sensor network, we need to balance the energy consumption of sensors so that there will not be too much redundant energy in some sensors before the WSN terminates. The detection probability and false alarm probability are taken into consideration to achieve a better performance and reveal the real sensing process which is characterised in the probabilistic sensing model. Data fusion is also introduced to utilise information of sensors so that a PoI in the monitored area may be covered by multiple sensors collaboratively, which will decrease the number of sensors that cover the monitored region. Based on the probabilistic model and data fusion, minimum weight probabilistic coverage problem is formulated in this paper. We also propose a greedy method and modified genetic algorithm based on the greedy method to address the problem. Simulation experiments are conducted to demonstrate the advantages of our proposed algorithms over existing work. [ABSTRACT FROM AUTHOR]

Abstract: Motion is a common phenomenon in the real world so the consistence of virtual and real motion is one of hot focuses in augmented reality system. This paper mainly analyzes virtual and real motion blur consistence in augmented reality system, and mainly do improvement in two aspects, one is how to get the motion blur parameters, the other is how to render motion blur. From the available literature it can be seen that, most achieved methods to get motion blur parameters are based on machine vision. But this paper first acquires the motion trajectory by magnetic tracking, and then gets motion blur parameters. Considering the available literature on motion blur rendering methods, they mainly contain convolution and accumulator caching and so on. Due to rotation translation compound motion blur, this paper does rendering in advance based on improved mathematical model, and then render virtual object through looking up table in augmented reality system. Experimental results show that the new virtual and real motion blur consistence render algorithm has low time complexity and achieve the desired effect in simulation environment and real scenes. [Copyright &y& Elsevier]

Abstract: This paper presents a detailed experimental and numerical investigation for a turbine cascade with different trailing edge ejection. The numerical simulation is based on Three-Dimensional Navier–Stokes equations coupled with an effective ejection model, where a high resolution non-oscillatory scheme, LU-SGS implicit algorithm and Baldwin-Lomax turbulence model are employed. The experiments presented in this paper focused on a transonic turbine cascade performance with different ejection to validate the numerical simulation results. The results show that the blowing ratio has a small effect on the Mach number distribution and exit flow angle with two slot types. However the energy loss coefficient increases initially, and subsequently has a decrease tendency with the increasing of blowing ratio. The ejection from the symmetry slot blows away the vortex at the blade trailing edge and strengthens the mixing between the wake and main flow. The ejection from the pressure side cutback only clears up the vortex near the slot surface, and has small effect on the flow field near the trailing edge. [Copyright &y& Elsevier]

Abstract: The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm. If the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross randomdec signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions, which is of the same form as the free-vibration decay or impulse response of the original system. The practical problem of insufficient data samples available for evaluating nonstationary randomdec signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. However, the error involved in the approximate free-decay response would generally lead to a distortion in the modal identification. In the present paper, we also further propose that, if the ambient excitation can be modeled as a zero-mean nonstationary process, without any additional treatment of transforming the original nonstationary responses, the nonstationary cross randomdec signatures of structural response are shown in the same mathematical form as that of free vibration of a structure, from which modal parameters of the original system can thus be identified. Numerical simulations, including one example of using the practical excitation data, confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data only. [Copyright &y& Elsevier]

Abstract: In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management. [Copyright &y& Elsevier]

The use of RFID technology in complex and distributed environments often leads to a multi-domain RFID system, in which trust establishment among entities from heterogeneous domains without past interaction or prior agreed policy, is a challenge. The current trust management mechanisms in the literature do not meet the specific requirements in multi-domain RFID systems. Therefore, this paper analyzes the special challenges on trust management in multi-domain RFID systems, and identifies the implications and the requirements of the challenges on the solutions to the trust management of multi-domain RFID systems. A multi-domain trust management model is proposed, which provides a hierarchical trust management framework include a diversity of trust evaluation and establishment approaches. The simulation results and analysis show that the proposed method has excellent ability to deal with the trust relationships, better security, and higher accuracy rate. [ABSTRACT FROM AUTHOR]

Discrete hard fault is always tested in existing node selection methods for analog circuit diagnosis. Actually, analog component parameter changes continuously and output node voltages distribute in a continuous voltage interval. In this paper, an novel test node selection method is proposed for continuous parameter shifting (CPS) fault. Firstly, CPS faults are sampled by parameter scan simulation in a single test frequency. Collected node voltages are seen as a data set in a statistical distribution. Secondly, ambiguous faults are identified according to the independent distributions of all CPS faults. The independence of CPS fault sample is deduced by Kruskal-Wallis non-parametric testing. Then, new fault dictionaries are generated for each test node according to ambiguous interval. The proposed fault dictionary represents the mutual independence of each pair of CPS faults. Finally, as fault dictionaries are considered as connected graphs, the optimal test nodes are selected based on an improved depth first search (DFS) algorithm. The effectiveness of method is verified by testing linear and nonlinear circuits. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model of steady-state reaction-diffusion (RD) model for estimating the concentration of species is discussed. We have applied a new wavelet-based operational matrix of derivative method to obtain the approximate solutions for nonlinear RDEs. The proposed method is a powerful and easy-to-use analytical tool for linear and nonlinear problems. Some illustrative examples are given to validate our results with exact solutions. Satisfactory agreement with the exact solution is noticed. Moreover, the use of Legendre wavelets is found to be simple, accurate, efficient and requires small computation costs. [ABSTRACT FROM AUTHOR]

Background: Bivariate random-effects models represent a widely accepted and recommended approach for meta-analysis of test accuracy studies. Standard likelihood methods routinely used for inference are prone to several drawbacks. Small sample size can give rise to unreliable inferential conclusions and convergence issues make the approach unappealing. This paper suggests a different methodology to address such difficulties.Methods: A SIMEX methodology is proposed. The method is a simulation-based technique originally developed as a correction strategy within the measurement error literature. It suits the meta-analysis framework as the diagnostic accuracy measures provided by each study are prone to measurement error. SIMEX can be straightforwardly adapted to cover different measurement error structures and to deal with covariates. The effortless implementation with standard software is an interesting feature of the method.Results: Extensive simulation studies highlight the improvement provided by SIMEX over likelihood approach in terms of empirical coverage probabilities of confidence intervals under different scenarios, independently of the sample size and the values of the correlation between sensitivity and specificity. A remarkable amelioration is obtained in case of deviations from the normality assumption for the random-effects distribution. From a computational point of view, the application of SIMEX is shown to be neither involved nor subject to the convergence issues affecting likelihood-based alternatives. Application of the method to a diagnostic review of the performance of transesophageal echocardiography for assessing ascending aorta atherosclerosis enables overcoming limitations of the likelihood procedure.Conclusions: The SIMEX methodology represents an interesting alternative to likelihood-based procedures for inference in meta-analysis of diagnostic accuracy studies. The approach can provide more accurate inferential conclusions, while avoiding convergence failure and numerical instabilities. The application of the method in the R programming language is possible through the code which is made available and illustrated using the real data example. [ABSTRACT FROM AUTHOR]

This paper is concerned with numerical simulations for the GBrownian motion (defined by S. Peng in Stochastic Analysis and Applications, 2007, 541-567). By the definition of the G-normal distribution, we first show that the G-Brownian motions can be simulated by solving a certain kind of Hamilton-Jacobi-Bellman (HJB) equations. Then, some finite difference methods are designed for the corresponding HJB equations. Numerical simulation results of the G-normal distribution, the G-Brownian motion, and the corresponding quadratic variation process are provided, which characterize basic properties of the G-Brownian motion. We believe that the algorithms in this work serve as a fundamental tool for future studies, e.g., for solving stochastic differential equations (SDEs)/stochastic partial differential equations (SPDEs) driven by the G-Brownian motions. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used. [Copyright &y& Elsevier]

This paper is a review of the use of particulate discrete element modeling (DEM) in geomechanics. The overall objective of the paper is to serve as an introduction to researchers and practitioners in geomechanics who are considering adopting DEM in their work or using the results of DEM simulations to guide other studies, for example, the development of constitutive models for continuum-based numerical analysis. It is hoped that prior converts to the use of DEM will also benefit from a relatively objective overview of current DEM use in geomechanics. The introductory sections present the background to the method and give an overview of the evolution of the use of particulate DEM in recent geotechnical research. The general principals of the algorithm are then presented, considering the types of particles typically used, the calculation of contact forces, and formulation of simulation boundary conditions. Some techniques available to interpret and postprocess of DEM results and provide the information to link the particle scale and overall response are outlined. Approaches used to validate and calibrate DEM models to verify that DEM simulation results representative of physical reality are discussed. An overview of the application of DEM modeling to field-scale problems is then presented. Finally the conclusions consider future developments in the area and emphasize the need to maintain quality in DEM simulations. [ABSTRACT FROM AUTHOR]

Abstract: Computer simulation is an increasingly popular tool for determining the most suitable hybrid energy system type, design and control for an isolated community or a cluster of villages. This paper presents the development of the optimum control algorithm based on combined dispatch strategies, to achieve the optimal cost of battery incorporated hybrid energy system for electricity generation, during a period of time by solving the mathematical model, which was developed in Part I of this tri-series paper. The main purpose of the control system proposed here is to reduce, as much as possible, the participation of the diesel generator in the electricity generation process, taking the maximum advantage of the renewable energy resources available. The overall load dispatch scenario is controlled by the availability of renewable power, total system load demand, diesel generator operational constraints and the proper management of the battery bank. The incorporation of a battery bank makes the control operation more practical and relatively easier. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we give the details of the numerical solution of a three-dimensional multispecies diffuse interface model of tumor growth, which was derived in [S.M. Wise, J.S. Lowengrub, H.B. Frieboes, V. Cristini, Three-dimensional multispecies nonlinear tumor growth–I: model and numerical method, J. Theoret. Biol. 253 (2008) 524–543] and used to study the development of glioma in [H.B. Frieboes, J.S. Lowengrub, S.M. Wise, X. Zheng, P. Macklin, E.L. Bearer, V. Cristini, Computer simulation of glioma growth and morphology, NeuroImage 37 (2007) S59–S70] and tumor invasion in [E.L. Bearer, J.S. Lowengrub, Y.L. Chuang, H.B. Frieboes, F. Jin, S.M. Wise, M. Ferrari, D.B. Agus, V. Cristini, Multiparameter computational modeling of tumor invasion, Cancer Res. 69 (2009) 4493–4501; H.B. Frieboes, F. Jin, Y.L. Chuang, S.M. Wise, J.S. Lowengrub, V. Cristini, Three-dimensional multispecies nonlinear tumor growth—II: tissue invasion and angiogenesis, J. Theoret. Biol. 264 (2010) 1254–1278]. The model has a thermodynamic basis, is related to recently developed mixture models, and is capable of providing a detailed description of tumor progression. It utilizes a diffuse interface approach, whereby sharp tumor boundaries are replaced by narrow transition layers that arise due to differential adhesive forces among the cell-species. The model consists of fourth-order nonlinear advection–reaction–diffusion equations (of Cahn–Hilliard-type) for the cell-species coupled with reaction–diffusion equations for the substrate components. Computing numerical solutions of the model is challenging because the equations are coupled, highly nonlinear, and numerically stiff. In this paper we describe a fully adaptive, nonlinear multigrid/finite difference method for efficiently solving the equations. We demonstrate the convergence of the algorithm and we present simulations of tumor growth in 2D and 3D that demonstrate the capabilities of the algorithm in accurately and efficiently simulating the progression of tumors with complex morphologies. [Copyright &y& Elsevier]

Abstract: The focus of this paper is to propose a hybrid neural network model for associative recall of analog and digital patterns. This hybrid model consists of self-feedback neural network structures (SFNN) in parallel with generalized regression neural networks (GRNN). Using a new one-shot learning algorithm developed in the paper, pattern representations are first stored as the asymptotically stable fixed points of the SFNN. Then in the retrieving process, each pattern is applied to the GRNN to make the corresponding initial condition and to initiate the dynamical equations of the SFNN that should in turn output the corresponding representation. In this way, the corresponding stored patterns are retrieved even under high noise degradation. Moreover, contrary to many associative memories, the proposed hybrid model is without any spurious attractors and can store both binary and real-value patterns without any preprocessing. Several simulations confirm the theoretical analyses of the model. Results indicate that the performance of the hybrid model is better than that of recurrent associative memory and competitive with other classes of networks. [Copyright &y& Elsevier]

Abstract: This paper presents a nonlinear piecewise smooth dynamical system of the trajectory of deviated wells according to engineering background. An optimal control model is established and the necessary conditions for optimality are proved via maximum principle. The optimal control problem is solved by a revised Hooke–Jeeves algorithm. The uniform design technique has been incorporated into the revised Hooke–Jeeves algorithm to handle the multimodal function. Computer simulation is used for this paper, and the numerical example illustrates the validity and efficiency of the algorithm. The procedure demonstrates its advantages in practical applications in Liaohe Oil Field. [Copyright &y& Elsevier]

This paper presents a way to access both the multiple-order and parameters of a multidimensional complex number autoregressive (AR) model through matrix factorization. The principle of this technique consists of the transformation of the multidimensional model to a pseudo simple-input simple-output AR model, then performing factorization of the covariance matrix of the data. This factorization then leads- to a recursive form of the parameter and order estimation. This paper makes two principal contributions. The first is a generalization of one dimensional factored form algorithm, and the second is that it makes it possible to access all the possible different orders and parameters of a multidimensional complex number AR model of any dimension, whereas classical approaches are limited to at most four-dimensional models. Computer simulation results are provided to illustrate the behavior of this method. [ABSTRACT FROM AUTHOR]

We are witnessing the emergence of a new paradigm in the modeling of material structures . It stems from the digitization of manufacturing and is fueled by advances in additive manufacturing and material science. This paper strives to provide a critical examination of this new paradigm in a historical and technological context and to show that it requires non-trivial extensions and generalizations of the classical theoretical foundation and algorithmic solutions originally developed for solid modeling. Specifically, it requires new models and data-intensive representations for materials, physical behavior, and manufacturing processes across multiple scales. In particular, we argue that most computational tasks that support traditional and emerging manufacturing may be formulated systematically and addressed in terms of relations ( conversions , synthesis , change propagation updates , verification , and other harmonization activities) among four views (manifestations) of an engineered artifact: Functional , which captures the design constraints and tolerances on shape, properties, and behavior; Designed , which represents a toleranced design that satisfies these constraints; Planned , which defines a manufacturing process plan; Simulated , which models the expected outcome of the process plan; and a Real sample set of physical artifacts produced by executing the process plan on a particular manufacturing technology. Based on this formulation, we outline important directions for a research agenda aimed at enabling, driving, and amplifying further advances in digital design and manufacturing. [ABSTRACT FROM AUTHOR]

Wheeled mobile robots (WMRs) are often used for maintenance of round pipes or ducts, which can typically be represented as a cylindrical workspace. Working in round pipes or ducts, kinematic models of WMRs are different from those applying on a plane and thus pose significant challenges in terms of kinematic analysis and motion control. To address these challenges, the kinematic properties of WMRs in a cylindrical workspace are analyzed in this paper. First, we discuss the kinematic properties of a single wheel in a cylindrical workspace. Then, we analyze the geometric constraints of WMRs in round pipes or ducts with analytical geometry. Based on these analyses, kinematic properties of WMRs in cylindrical workspaces are discussed with screw theory. A control law based on biaxial clinometer information is proposed, and it enables the robot to move horizontally in round pipes or ducts. Finally, the motion of a single wheel purely rolling in a cylindrical workspace is simulated. Experiments using a car-like mobile robot moving in round ducts are carried out to show the feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) model by analyzing the limitations of existing localization algorithm is proposed in this paper. Specifically, neither the anchor nor the ID is required in the proposed model, and the node function is limited. The hardware function of the node in our model is independent of the MAC protocol. Moreover, based on the proposed WSN model, we design an energy efficient anchor-free localization algorithm for no-identity WSN. Instead of multiple measurements, mathematical calculation is adopted to acquire the position information. Subsequently, the effectiveness of the algorithm is confirmed by rigid theory. The simulation results show that the proposed algorithm can improve the performance of localization and energy efficiency in WSN significantly. [ABSTRACT FROM AUTHOR]

Based on the proposed higher order gradient quasi-continuum model, the numerical investigations of the basic mechanical properties and deformation behaviors of human red blood cell (RBC) membrane under large deformation at room temperature (i.e., 300 K) are carried out in the present paper. The results show that RBC membrane is a nonlinear hyperelastic material. The mechanical properties of RBC membrane is dominated by isotropic nature at the stage of initial deformation, however, its anisotropic material properties emerge clearly with the loading increasing. The out-of-plane wrinkling of RBC membrane upon shear loading can be reproduced numerically. With the use of the so-called higher order Cauchy-Born rule as the kinematic description, the bending stiffness of RBC membrane can be considered conveniently. [ABSTRACT FROM AUTHOR]

The investigation reported in this paper looks into the application of a number of system-identification techniques to problems of earthquake engineering. A number of techniques for structural-system identification have been developed over the past few years. Many of these techniques have been successful at identifying properties of linearized and time-invariant equivalent structural systems. Most of these techniques were verified using mathematical models simulated on the computer. In this paper, a number of structural-identification algorithms are reviewed and applied to the identification of structural systems subjected to earthquake excitations. The algorithms are applied to experimental data obtained in controlled laboratory conditions. The data pertain to the acceleration records from two building models subjected to various loading conditions. The performance of the various identification algorithms is critically assessed, and guidelines are obtained regarding their suitability to various engineering applications. [ABSTRACT FROM AUTHOR]

gggggAssume that an n × n dot matrix is stored in consecutive n words of a computer with one word being n bit. This paper discusses eight operations to rotate or transpose the dot matrix in horizontal/vertical! slant direction. As is well known, such operations form a group. This paper presents a unified description of the algorithms, and it is shown that all eight algorithms can be derived by suit- ably setting the constants in the unified algorithm. Then it is shown that the algorithms can be transformed to each other by simple transformation rules for the constants, and those transformation rules are shown to form a group. The foregoing algorithms for the dot matrix are not unique, and there can be different descriptions for the algorithm producing the same result. Consequently, there can be various versions of the eight algorithms as well as versions of transformation rules. This paper shows that one of the two groups formed by the transformation rules is isomorphic to the group of algorithms, but the other is not isomorphic. [ABSTRACT FROM AUTHOR]

Background: Although Pneumatic Artificial Muscle (PAM) has a promising future in rehabilitation robots, it's difficult to realize accurate position control due to its highly nonlinear properties.Objective: This paper deals with position control of PAM.Methods: To describe the hysteresis inside PAM, a polynomial based phenomenological function is developed. Based on the phenomenological model for PAM and analysis of pressure dynamics within PAM, an adaptive cascade controller is proposed. Both outer loop and inner loop employ BP Neural Network tuned PID algorithm. The outer loop is to handle high nonlinearities and unmodeled dynamics of PAM, while the inner loop is responsible for nonlinearities caused by pressure dynamics.Results: Experimental results show high tracking accuracy as compared with a convention PID controller.Conclusion: The proposed controller is effective in improving performance of PAM and will be implemented in a rehabilitation robot. [ABSTRACT FROM AUTHOR]

A systematic approach to I / Q mismatch calibration in image-reject receivers is presented in this paper. A new error detection algorithm is proposed, which automatically calibrates for phase and gain mismatches limiting the performance of image-reject receivers. A dual-loop feedback is employed which looks for the minimum phase/gain error using a 2-dimensional analog-based search algorithm and then finds the minimum value for the error. An experimental CMOS prototype RF front-end for cognitive radio applications operating at 400–800 MHz is proposed and simulated in the 0.18 μm CMOS technology, achieving an image rejection ratio (IRR) better than 55-dB in post-layout simulation. The comprehensive mathematical model of this analog algorithm is thoroughly studied in the appendix and the convergence is verified theoretically. [ABSTRACT FROM AUTHOR]

This paper reports the performance of particle swarm optimization (PSO) for the assignment of blood to meet patients’ blood transfusion requests for blood transfusion. While the drive for blood donation lingers, there is need for effective and efficient management of available blood in blood banking systems. Moreover, inherent danger of transfusing wrong blood types to patients, unnecessary importation of blood units from external sources, and wastage of blood products due to nonusage necessitate the development of mathematical models and techniques for effective handling of blood distribution among available blood types in order to minimize wastages and importation from external sources. This gives rise to the blood assignment problem (BAP) introduced recently in literature. We propose a queue and multiple knapsack models with PSO-based solution to address this challenge. Simulation is based on sets of randomly generated data that mimic real-world population distribution of blood types. Results obtained show the efficiency of the proposed algorithm for BAP with no blood units wasted and very low importation, where necessary, from outside the blood bank. The result therefore can serve as a benchmark and basis for decision support tools for real-life deployment. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel parallel 3D Delaunay triangulation algorithm for large-scale simulations on parallel computers. Our method keeps the 3D boundary representation model information during the whole parallel 3D Delaunay triangulation process running on parallel computers so that the solid model information can be accessed dynamically and the meshing results can be very approaching to the model boundary with the increase of meshing scale. The model is coarsely meshed at first and distributed on CPUs with consistent partitioned shared interfaces and partitioned model boundary meshes across processors. The domain partition aims at minimizing the edge-cuts across different processors for minimum communication cost and distributing roughly equal number of mesh vertices for load balance. Then a parallel multi-scale surface mesh refinement phase is iteratively performed to meet the mesh density criteria followed by a parallel surface mesh optimization phase moving vertices to the model boundary so as to fit model geometry feature dynamically. A dynamic load balancing algorithm is performed to change the partition interfaces if necessary. A 3D local non-Delaunay mesh repair algorithm is finally done on the shared interfaces across processors and model boundaries. The experimental results demonstrate our method can achieve high parallel performance and perfect scalability, at the same time preserve model boundary feature and generate high quality 3D Delaunay mesh as well. [ABSTRACT FROM AUTHOR]

This paper deals with the computational modeling and numerical simulation of contact problems at finite deformations using the finite element method. Quasi-static and dynamic problems are considered and two particular frictional conditions, full stick friction and frictionless cases, are addressed. Lagrange multipliers and regularized formulations of the contact problem, such as penalty or augmented Lagrangian methods, are avoided and a new direct elimination method is proposed. Conserving algorithms are also introduced for the proposed formulation for dynamic contact problems. An assessment of the performance of the resulting formulation is shown in a number of selected benchmark tests and numerical examples, including both quasi-static and dynamic contact problems under full stick friction and frictionless contact conditions. Conservation of key discrete properties exhibited by the time stepping algorithm used for dynamic contact problems is also shown in an example. [ABSTRACT FROM AUTHOR]

This paper investigates the computational performance of S-CLAY1S constitutive model by varying its yield function equation. S-CLAY1S is an advanced anisotropic elasto-plastic model that has been developed based on the extension of conventional critical state theory. In addition to modified Cam-Clay׳s hardening law, S-CLAY1S also accounts for inherent and evolving plastic anisotropy, interparticle bonding and degradation of bonds during plastic straining. A modified Newton–Raphson stress update algorithm has been adopted for the implementation of the model and it was found that the algorithm׳s convergence performance is sensitive to the expression of the yield function. It is shown that for an elasto-plastic model which is developed based on the critical state theory, it is possible to improve the performance of the numerical implementation by changing the form of the yield function. The results of this work can provide a new perspective for computationally cost-effective implementation of complex constitutive models in finite element analysis that can yield in more efficient boundary value level simulations. [ABSTRACT FROM AUTHOR]

The paper introduces methods of dynamic games for automation of ship control in the collision situation, the game control processes in marine navigation and the fundamental mathematical model of the game ship control. First, state equations, control and state constraints and then control goal function in the form of payments: the integral payment and the final one, have been defined. Multi-stage positional, and multi-step matrix, non-cooperative and cooperative, game and optimum control algorithms for a collision situation, have been presented. Te considerations have been illustrated with an exemplary computer simulation of algorithms to determine a safe own ship's trajectory in the process of passing the ships encountered in Kattegat Strait. [ABSTRACT FROM AUTHOR]

Magnetic tracking technology is emerging to provide an occlusion-free tracking scheme for the estimation of full pose (position and orientation) of various instruments. This brings substantial benefits for intracorporeal applications, such as for tracking of flexible or wireless endoscopic devices, and thus is significant for further computer-assisted diagnosis, interventions, and surgeries. Toward efficient magnetic tracking, a 6-D magnetic localization and orientation method is proposed in this paper. An annular permanent magnet is mounted on the exterior surface of a capsule. With a magnetic sensor array, the magnetic field can be measured and the capsule’s 3-D location and 3-D orientation information can be estimated based on proposed closed-form analytical model of annular magnet and particle swarm optimization algorithm. Magnetic dipole model and Levenberg–Marquardt algorithm are used to improve the speed and accuracy of estimation. Extensive simulation experiments show that the localization and orientation method works well with good position and orientation accuracy. [ABSTRACT FROM AUTHOR]

In this paper a method for the development of a static VAR compensator (SVC) control algorithm is presented. The proposed algorithm has been designed with the objective of eliminating the negative impact of electric arc furnaces on the power system. First, a mathematical model of the proposed SVC controller in the d-q synchronous rotating coordinate system is developed. An analysis under dynamic and steady state conditions is also carried out. The efficiency of the presented controller is demonstrated by means of computer simulations of an actual steel-factory network model. The major advantages of the proposed controller are better flicker compensation, increased ability to regulate voltage and the need for only one-point network measurements. [ABSTRACT FROM AUTHOR]

A modified fuzzy relational modeling structure is presented in this paper by proposing a fuzzy relational inner composition. This leads to an integrated framework for representing multilevel fuzzy relational equations which is able to provide multi-dimensional models of complex systems very effectively. A potentially online derivative-based identification algorithm is also presented for the proposed model. The identification procedure is based on the special t-norm-based and t-conorm-based operations leading to an easy and fast implementation of the proposed algorithm. The proposed modeling structure is customized and used for two different applications. The simulation results show high modeling capability of the proposed fuzzy relational model. [ABSTRACT FROM AUTHOR]