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When synchronization phenomena are analyzed, the phase equations are known to often provide useful qualitative and quantitative information [1]. The target of this paper is to examine through comparisons of the derivation algorithm of the phase equations a realistic system including the case where the equations are not necessarily given explicitly. In other words, the equivalence of two different conventional algorithms [1, 4] is shown, and the advantages and cautions when specific phenomena use both in an example are each explained. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(12): 1– 9, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20284 [ABSTRACT FROM AUTHOR]

In this paper, we propose a unified approach for video summarization based on the analysis of video structures, and video highlights. Two major components in our approach are scene modeling and highlight detection. Scene modeling Is achieved by normalized cut algorithm and temporal graph analysis, while high-light detection is accomplished by motion attention modeling. In our proposed approach, a video is represented as a complete undirected graph and the normalized cut algorithm is carried out to globally and optimally partition the graph into video clusters. The resulting clusters form a directed temporal graph and a Shortest path algorithm is proposed to efficiently detect video scenes. The attention values are then computed and attached to the scenes, clusters, shots, and subshots in a temporal graph. As a result, the temporal graph can inherently describe the evolution and perceptual importance of a video. In our application, video summaries that emphasize both content balance and perceptual quality can be generated directly from a temporal graph that embeds both the structure and attention information. [ABSTRACT FROM AUTHOR]

Abstract-Subspace-based estimation of multiple real-valued sine wave frequencies is considered in this paper. A novel data covariance model is proposed. In the proposed model, the dimension of the signal subspace equals the number of frequencies present in the data, which is half of the signal. subspace dimension for the conventional model. Consequently, an ESPRIT-like algorithm using the proposed data model is presented. The proposed algorithm is then extended for the case of complex-valued sine waves. Performance analysis of the proposed algorithms are also carried out. The algorithms are tested in numerical simulations. When compared with ESPRIT, the newly proposed algorithm results in a significant reduction in computational burden without any compromise in the accuracy. [ABSTRACT FROM AUTHOR]

Loopholes exist in nearly every regime, which leads to invalidity and instability in the running process of a regime. In this paper, we propose a new framework based on agent method and game theory to find loopholes in a regime, which contains two players with their clear payoffs. Following the principle of "winners stay, losers change", agents make their own choices among strategies, and their choices can affect the payoffs of other players, resulting in a dynamic equilibrium that has obvious features in decision path, which can be easily found in the final figures after simulation. We further exploit typical cases, such as prisoner's dilemma, anti-coordination game, coordination game and harmony, of which the results have been mathematical proved, to illustrate the validity of our method. Finally, we make some regimes in this paper based on the classical case, "Boxed Pigs", and find the loopholes in these regimes. By utilizing the framework proposed in this paper, managers are able to detect possible problems in advance at the time when they make regimes, which helps reduce the loss of costs caused by management and improve team relations. [ABSTRACT FROM AUTHOR]

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]

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]

Copyright of INFOR is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the process of k-coverage of the target node, there will be a lot of data redundancy forcing the phenomenon of congestion which reduces network communication capability and coverage, and accelerates network energy consumption. Therefore, this paper proposes a novel energy balanced k-coverage control algorithm based on probability model (EBKCCA). The algorithm constructs the coverage network model by using the positional relationship between the nodes. By analyzing the network model, the coverage expected value of nodes and the minimum number of nodes in the monitoring area are given. In terms of energy consumption, this paper gives the proportion of energy conversion functions between working nodes and neighboring nodes. By using the function proportional to schedule low energy nodes, we achieve the energy balance of the whole network and optimizing network resources. The last simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but also completely inhibit the rapid energy consumption of node, and extend the network lifetime. [ABSTRACT FROM AUTHOR]

When conducting recurrent event data analysis, it is common to assume that the covariate processes are observed throughout the follow-up period. In most applications, however, the values of time-varying covariates are only observed periodically rather than continuously. A popular ad-hoc approach is to carry forward the last observed covariate value until it is measured again. This simple approach, however, usually leads to biased estimation. To tackle this problem, we propose to model the covariate effect on the risk of the recurrent events through jointly modeling the recurrent event process and the longitudinal measures. Despite its popularity, estimation of the joint model with binary longitudinal measurements remains a challenge, because the standard linear mixed effects model approach is not appropriate for binary measures. In this paper, we postulate a Markov model for the binary covariate process and a random-effect proportional intensity model for the recurrent event process. We use a Markov chain Monte Carlo algorithm to estimate all the unknown parameters. The performance of the proposed estimator is evaluated via simulations. The methodology is applied to an observational study designed to evaluate the effect of Group A streptococcus on pharyngitis among school children in India. [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]

As peer-to-peer networks gather and share large sets of computing resources, their aggregate energy consumption is an important problem to be addressed, given the economic and environmental impact of energy production and use. This is particularly true for file sharing peer-to-peer networks, considered the vast number of nodes participating to these systems. To address such problem, this paper proposes a peer-to-peer file sharing model organized in two logical layers. The lower layer is composed of a set of peers providing the files to be shared. The upper layer includes a set of super peers organized to form a distributed hash table, whose purpose is indexing files and peers, including their availability status. Following a sleep-and-wake approach, energy saving is achieved by letting peers cyclically switch between normal and sleep modes, where the time passed in normal mode by a peer depends on the number of files it provides. An energy-saving algorithm and an associated file search and retrieval strategy are proposed within this model. Simulation results show that more than 50% of energy can be saved using the proposed model and that more than 80% of file downloads start with no additional delay compared with a network in which all peers are always powered on. Copyright © 2014 John Wiley & Sons, Ltd. [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]

Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute — without learning an explicit model — a schedule of them for solving a given Constraint Satisfaction Problem (CSP). Motivated by the performance reached by SUNNY vs. different simulations of other state of the art approaches, we developed sunny-csp, an effective portfolio solver that exploits the underlying SUNNY algorithm in order to solve a given CSP. Empirical tests conducted on exhaustive benchmarks of MiniZinc models show that the actual performance of sunny-csp conforms to the predictions. This is encouraging both for improving the power of CSP portfolio solvers and for trying to export them to fields such as Answer Set Programming and Constraint Logic Programming. [ABSTRACT FROM AUTHOR]

Intercell interference coordination (ICIC) techniques not only help improve cellular data coverage but allow more efficient use of a valuable wireless spectrum as well. This paper investigates soft frequency reuse (SFR), which is a form of ICIC, for long-term evolution (LTE) systems. By analyzing the throughput of the SFR scheme, we find that classifying cell-edge users and cell-center users is critical. Thus, we develop low-complexity decentralized SFR scheduling algorithms that include optimal user classification and balance throughput and fairness among multiusers. We also propose suboptimal methods to reduce computational complexity. Computer simulation demonstrates that gains of the proposed SFR algorithm can improve the fifth percentile user throughput by 26% while maintaining the same cell average throughput, compared with a non-ICIC system. [ABSTRACT FROM PUBLISHER]

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]

This paper proposes to use a state feedback method to control the Hopf bifurcation for a novel congestion control model, i.e. the exponential random early detection (RED) algorithm with a single link and a single source. The gain parameter of the congestion control model is chosen as the bifurcation parameter. The analysis shows that in the absence of the state feedback controller, the model loses stability via the Hopf bifurcation early, and can maintain a stationary sending rate only in a certain domain of the gain parameter. When applying the state feedback controller to the model, the onset of the undesirable Hopf bifurcation is postponed. Thus, the stability domain is extended, and the model possesses a stable sending rate in a larger parameter range. Furthermore, explicit formulae to determine the properties of the Hopf bifurcation are obtained. Numerical simulations are given to justify the validity of the state feedback controller in bifurcation control. [ABSTRACT FROM AUTHOR]

The wind generator system is a large inertia system, so the use of the PI controller in pitch control will lead to the system instability. The theory of variable pitch wind turbines is analyzed in this paper. The mathematical model of the aerodynamic part, the drive part, the operative part and the whole unit are established. An algorithm is proposed to allow the generator to track the maximum power points of the wind turbine system by PD controller. The proposed algorithm is verified by simulation re-sult, and good control results are achieved. [ABSTRACT FROM AUTHOR]

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]

Bayesian modeling requires the specification of prior and likelihood models. In reservoir characterization, it is common practice to estimate the prior from a training image. This paper considers a multi-grid approach for the construction of prior models for binary variables. On each grid level we adopt a Markov random field (MRF) conditioned on values in previous levels. Parameter estimation in MRFs is complicated by a computationally intractable normalizing constant. To cope with this problem, we generate a partially ordered Markov model (POMM) approximation to the MRF and use this in the model fitting procedure. Approximate unconditional simulation from the fitted model can easily be done by again adopting the POMM approximation to the fitted MRF. Approximate conditional simulation, for a given and easy to compute likelihood function, can also be performed either by the Metropolis-Hastings algorithm based on an approximation to the fitted MRF or by constructing a new POMM approximation to this approximate conditional distribution. The proposed methods are illustrated using three frequently used binary training images. [ABSTRACT FROM AUTHOR]

Due to the massive spread of distributed computing systems their effective use has become an urgent issue. Therefore it is necessary to analyze the algorithms of such systems. This paper attempts to examine the coverage area with the specified reliability indices. A proposed method based on selection of the redundancy rate. Methods of analytical modeling and multivariate optimization were used to solve the problem. [ABSTRACT FROM AUTHOR]

If humanoid robots are to be used in society, they should be able to maintain their balance. Knowing where to step is crucially important. In this paper we contribute an algorithm that can compute the foot step location such that bipedal balance is maintained for planar bipeds with point feet and an arbitrary number of non-massless links on a horizontal and flat ground. The algorithm is called the foot placement indicator (FPI) and it extends the foot placement estimator (FPE). The FPE uses an inverted pendulum model to capture the dynamics of a humanoid robot, whereas the FPI deals with multi-body models with distributed masses. This paper analyses equilibrium sets and the stability of planar bipeds with point feet. The algorithm uses conservation of energy throughout the step, taking into account the instantaneous impact dynamics at foot strike. A simulation case study on a five-link planar biped shows the effectiveness of the FPI. [ABSTRACT FROM AUTHOR]

Copyright of Mechanika is the property of Mechanika and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Purpose: The purpose of this paper is to propose a heuristic for the inventory management of smart vending machine systems with product substitution under the replenishment point, order-up-to level policy and to evaluate its performance. Design/methodology/approach: The heuristic is developed on the basis of the decoupled approach. An integer linear mathematical model is built to determine the number of product storage compartments and replenishment threshold for each smart vending machine in the system and the Clarke and Wright's savings algorithm is applied to route vehicles for inventory replenishments of smart vending machines that share the same delivery days. Computational experiments are conducted on several small-size test problems to compare the proposed heuristic with the integrated optimization mathematical model with respect to system profit. Furthermore, a sensitivity analysis is carried out on a medium-size test problem to evaluate the effect of the customer service level on system profit using a computer simulation. Findings: The results show that the proposed heuristic yielded pretty good solutions with 5.7% error rate on average compared to the optimal solutions. The proposed heuristic took about 3 CPU minutes on average in the test problems being consisted of 10 five-product smart vending machines. It was confirmed that the system profit is significantly affected by the customer service level. Originality/value: The inventory management of smart vending machine systems is newly treated. Product substitutions are explicitly considered in the model. The proposed heuristic is effective as well as efficient. It can be easily modified for application to various retail vending settings under a vendor-managed inventory scheme with POS system. [ABSTRACT FROM AUTHOR]

The new systems which assess the nutritive value and determine the nutrient requirement triggered changes in the manner of formulation and development of optimized poultry diets. The purpose of this paper is to present a viewpoint on a possible solution for diet optimization. We considered the determination of a possible "common denominator" between the nutritional requirements, mathematical algorithms that can be applied to the stated problem and the economic aspects assimilated as purpose functions in formulating the mathematical models that are used. [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]

In this paper, small signal analysis of power systems is investigated using Subspace System Identification (SSI) methods. Classical small signal analysis methods for power systems are based on mathematical modeling and linearized model of power system in an especial operating point. There are some difficulties when such a classical method is applied, specially, in the case of large power systems. In this paper, such difficulties and their bases are investigated and in order to avoid them, it is suggested to use SSI algorithms for small signal analysis of power systems. The paper discusses extracting of small signal properties of power systems and presents some new suggestions for application of subspace system identification methods. Different types of subspace system identification algorithms were applied to different power system case studies using the presented propositions. The benefits and drawbacks of subspace system identification methods and the presented suggestions are studied for small signal analysis of power systems and power system monitoring. Several comparisons were investigated using computer simulations. The results express the usefulness and easiness of proposed methods. [ABSTRACT FROM AUTHOR]

A family of the block matching 3-D (BM3D) algorithms for various imaging problems has been recently proposed within the framework of nonlocal patchwise image modeling refid="ref1"/, refid="ref2"/. In this paper, we construct analysis and synthesis frames, formalizing BM3D image modeling, and use these frames to develop novel iterative deblurring algorithms. We consider two different formulations of the deblurring problem, i.e., one given by the minimization of the single-objective function and another based on the generalized Nash equilibrium (GNE) balance of two objective functions. The latter results in the algorithm where deblurring and denoising operations are decoupled. The convergence of the developed algorithms is proved. Simulation experiments show that the decoupled algorithm derived from the GNE formulation demonstrates the best numerical and visual results and shows superiority with respect to the state of the art in the field, confirming a valuable potential of BM3D-frames as an advanced image modeling tool. [ABSTRACT FROM AUTHOR]

A channel simulator is an essential component in the development and accurate performance evaluation of wireless systems. A key technique for producing statistically accurate fading variates is to shape the flat spectrum of Gaussian variates using digital filters. This paper addresses various challenges when designing real and complex spectrum shaping filters with quantized coefficients for efficient realization of both isotropic and nonisotropic fading channels. An iterative algorithm for designing stable complex infinite impulse response (IIR) filters with fixed-point coefficients is presented. The performance of the proposed filter design algorithm is verified with 16-bit fixed-point simulations of two example fading filters. [ABSTRACT FROM AUTHOR]

The paper suggests a new approach to determine the intensity of failures and restorations of complex technical systems of arbitrary nature, based on the application of probability theory, mathematical statistics, simulation and function approximation. Finding failure rates and restorations in the form of functional dependencies allows model the function of readiness. [ABSTRACT FROM AUTHOR]

System identification provides many convenient and useful methods for engineering modelling. This study targets the parameter identification problems for multivariable equation-error autoregressive moving average systems. To reduce the influence of the coloured noises on the parameter estimation, the data filtering technique is adopted to filter the input and output data, and to transform the original system into a filtered system with white noises. Then the filtered system is decomposed into several subsystems and a filtering-based partially-coupled generalised extended stochastic gradient algorithm is developed via the coupling concept. In contrast to the multivariable generalised extended stochastic gradient algorithm, the proposed algorithm can give more accurate parameter estimates. Finally, the effectiveness of the proposed algorithm is well demonstrated by simulation examples. [ABSTRACT FROM AUTHOR]

Objective: With the overall goal to harmonize prospective effectiveness assessment of active safety systems, the specific objective of this study is to identify and evaluate sources of variation in virtual precrash simulations and to suggest topics for harmonization resulting in increased comparability and thus trustworthiness of virtual simulation-based prospective effectiveness assessment. Methods: A round-robin assessment of the effectiveness of advanced driver assistance systems was performed using an array of state-of-the-art virtual simulation tools on a set of standard test cases. The results were analyzed to examine reasons for deviations in order to identify and assess aspects that need to be harmonized and standardized. Deviations between results calculated by independent engineering teams using their own tools should be minimized if the research question is precisely formulated regarding input data, models, and postprocessing steps. Results: Two groups of sources of variations were identified; one group (mostly related to the implementation of the system under test) can be eliminated by using a more accurately formulated research question, whereas the other group highlights further harmonization needs because it addresses specific differences in simulation tool setups. Time-to-collision calculations, vehicle dynamics, especially braking behavior, and hit-point position specification were found to be the main sources of variation. Conclusions: The study identified variations that can arise from the use of different simulation setups in assessment of the effectiveness of active safety systems. The research presented is a first of its kind and provides significant input to the overall goal of harmonization by identifying specific items for standardization. Future activities aim at further specification of methods for prospective assessments of the effectiveness of active safety, which will enhance comparability and trustworthiness in this kind of studies and thus contribute to increased traffic safety. [ABSTRACT FROM AUTHOR]

Mock circulatory loops (MCLs) have been widely used to test left ventricular assist devices. The hydraulic properties of the mock systemic arterial system are usually described by two alternative four-element windkessel (W4) models. Compared with three-element windkessel model, their parameters, especially the inertial term, are much more difficult to estimate. In this paper, an estimator based on the iterated unscented Kalman filter (IUKF) algorithm is proposed to identify model parameters. Identifiability of these parameters for different measurements is described. Performance of the estimator for different model structures is first evaluated using numerical simulation data contaminated with artificial noise. An MCL is developed to test the proposed algorithm. Parameter estimates for different models are compared with the calculated values derived from the mechanical and hydraulic properties of the MCL to validate model structures. In conclusion, the W4 model with an inertance and an aortic characteristic resistance arranged in series is proposed to represent the mock systemic arterial system. Once model structure is appropriately selected, IUKF can provide reasonable estimation accuracy in a limited time and may be helpful for future clinical applications. [ABSTRACT FROM PUBLISHER]

For many practical applications of ASP, for instance data integration or planning, query answering is important, and therefore query optimization techniques for ASP are of great interest. Magic Sets are one of these techniques, originally defined for Datalog queries (ASP without disjunction and negation). Dynamic Magic Sets (DMS) are an extension of this technique, which has been proved to be sound and complete for query answering over ASP programs with stratified negation. A distinguishing feature of DMS is that the optimization can be exploited also during the non-deterministic phase of ASP engines. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query under these assumptions. This allows for dynamic pruning of the search space, which may result in exponential performance gains. In this paper, the correctness of DMS is formally established and proved for brave and cautious reasoning over the class of super-coherent ASP programs (ASPsc programs). ASPsc programs guarantee consistency (i.e., have answer sets) when an arbitrary set of facts is added to them. This result generalizes the applicability of DMS, since the class of ASPsc programs is richer than ASP programs with stratified negation, and in particular includes all odd-cycle-free programs. DMS has been implemented as an extension of DLV, and the effectiveness of DMS for ASPsc programs is empirically confirmed by experimental results with this system. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm using binary trees is developed to detect the change points of a data set in which the data are assumed to be normally distributed. Usual BIC-type criteria are considered in the binary searching procedures when the number of change points is unknown. The algorithm is also extended to the switching regression models. Simulation study confirms that our algorithm is efficient compared with the ML-method. A real data example also verifies that the proposed procedure is appropriate. [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]

This paper describes a block-latency insertion method (LIM) for the fast transient simulation of the large networks with many coupling elements. First, the basic formulation of LIM is reviewed. Next, the block-LIM formulation for the network with many coupling elements, such as the mutual inductance, the mutual capacitance, and controlled sources is described. Then, the block-LIM algorithm is applied to the tightly coupled transmission lines, which are connected to each other by a number of mutual inductors and capacitors. Finally, some numerical results are shown, and it is confirmed that the proposed technique is useful and efficient for the simulation of the tightly coupled transmission lines. [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]

An output constrained control with input delay is proposed for a central heating system. Due to the delay of signal transmission and valves opening time, an input delay is considered into the system and an auxiliary system is employed to handle this issue by converting the delayed input into a delay-free one. Moreover, to ensure the output supply water temperature within a limited range, Barrier Lyapunov algorithm is involved to achieve desired control accuracy. Finally, external disturbance and model uncertainty are incorporated into the dynamic system and neural networks (NN) are trained in an online fashion for the compensation. The stability of the control system is guaranteed through rigorous Lyapunov analysis and the excellent control performance over traditional PID control is demonstrated via numerical simulation study. [ABSTRACT FROM AUTHOR]

The leader-follower consensus problem of second-order multiagent systems with both absent velocity measurement and time delay is considered. First of all, the consensus protocol is designed by introducing an auxiliary system to compensate for the unavailability of the velocity information. Then, time delay is incorporated into the consensus protocol and two cases with, respectively, constant time delay and time-varying delay are investigated. For the case of constant time delay, Lyapunov-Razumikhin theorem is deployed to obtain the sufficient conditions that guarantee the stability of the consensus algorithm. For the case of time-varying delay, the sufficient conditions are also derived by resorting to the Lyapunov-Razumkhin theorem and linear matrix inequalities (LMIs). Various numerical simulations demonstrate the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract The estimation of a hazardous contaminant unknown source characteristics (i.e., rate and location) in a complex urban environment using efficient inverse modelling techniques is a challenging problem that involves advanced computational fluid dynamics combined with appropriate mathematical algorithms. In this paper we further assess our recently proposed inverse source term estimation method (Efthimiou et al., 2017, Atmos. Environ., 170, 118–129) by applying it in two wind tunnel experiments simulating atmospheric flow and tracer dispersion following a stationary release in realistic urban settings, namely Michelstadt and Complex Urban Terrain Experiment (CUTE). The method appears to be robust and to predict with encouraging accuracy the source location and emission rate for both wind tunnel experiments. Highlights • Evaluation of an inverse source term identification method. • Variational, 2-steps method: (1) source coordinates (2) emission rate estimation. • Successful validation through simulations of Michelstadt and CUTE wind tunnel experiments. • The performance of the method varies with the examined scenario. [ABSTRACT FROM AUTHOR]

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]

In this paper we investigate a numerical algorithm for the pricing of swing options, relying on the so-called optimal quantization method. The numerical procedure is described in detail and numerous simulations are provided to assert its efficiency. In particular, we carry out a comparison with the Longstaff-Schwartz algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new robust congestion- control strategy for a differentiated-services (DiffServ) network. A sliding-mode-based variable structure control technique is utilized to design a congestion controller on the basis of a fluid flow model. The performance of our proposed scheme is then demonstrated on a DiffServ network. Our proposed algorithm is developed for an interconnected network as a hop-by-hop distributed-control approach. A formal analysis of the controlled network is conducted, where it is shown that the error dynamics of the overall time-delay-dependent system is ℒ∞ stable. Numerical simulations are provided to demonstrate the capabilities of our proposed methodology. [ABSTRACT FROM AUTHOR]