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This study introduces a novel approach for integrating a compact mechanism into the Marine Predator Algorithm (MPA), subsequently proposing innovative parallel and communication strategies. The synergistic combination of these methodologies substantially augments the global search efficiency and accelerates the convergence rate of the original MPA. The paper culminates in presenting an enhanced version of the Marine Predator Algorithm, termed PCMPA, which leverages compact parallel technology. The performance of PCMPA, alongside a range of comparative algorithms, is rigorously evaluated using the CEC2013 benchmark test functions. These comparative algorithms encompass recent variants of MPA, PSO, DE, and other newly developed algorithms. Evaluation results reveal that PCMPA outperforms its counterparts in a more extensive array of test functions. To corroborate PCMPA's efficacy in real-world scenarios, the algorithm is applied to parameter optimization in Backpropagation neural network (BNN) and targeted engineering optimization challenges. This application demonstrates that PCMPA consistently achieves enhanced performance in practical implementations. • The study presents a novel variant of the Marine Predators Algorithm, dubbed PCMPA. • The paper benchmarks PCMPA against other Marine Predators Algorithm variants and other Algorithms. • The research applies PCMPA to optimize parameters of BNNs and to tackle engineering optimization challenges. [ABSTRACT FROM AUTHOR]

Solving differential equations over extended temporal domains is pivotal for many scientific and engineering endeavors. The progression of numerous phenomena in the natural world occurs over prolonged durations, necessitating a comprehensive understanding of their temporal dynamics to facilitate precise prognostications and judicious decision-making. Existing methodologies such as homotopy perturbation, Adomian decomposition, and homotopy analysis are noted for their precision within limited temporal scopes. An optimized decomposition method proposed by Odibat extends this accuracy over a longer term, yet its solutions become untenable over substantial timeframes. This paper proposes a novel semi-analytical method to yield solutions over greater temporal extents. Moreover, this work integrates a convergence control parameter to bolster the proposed method's accuracy and operational efficiency. A rigorous theoretical convergence analysis is delineated, substantiating the method's validity. Three illustrative examples are numerically examined and discussed to validate the proposed approaches empirically. [ABSTRACT FROM AUTHOR]

The slowly forced Duffing system has been found to exhibit unique fast–slow behaviors in descending frequency switching scheme, the typical of which is the sliding bursting, which is instructive for understanding the dynamics of ubiquitous frequency switching systems in scientific research and practical engineering. This paper is devoted to further refining the fast–slow dynamics of the slowly forced Duffing system with another commonly encountered frequency switching scheme, i.e., the ascending frequency switching, characterized by switching the frequency synchronously according to the increase or decrease of state variable values. Taking the forcing amplitude as an example, this paper provides a theoretical way to fully summarize the fast–slow behaviors in frequency switching systems with the variation of parameter values based on the proposed superposition analysis of one- and two-parameter bifurcations of subsystems. As a result, two typical bifurcation structures and eight threshold windows with distinct switching vector fields therein are identified, inducing up to ten different bursting patterns. Among them, several novel fast–slow dynamics, such as multiple jumps hysteresis loop formed by boundary equilibrium bifurcations and the switching failure phenomena, are presented and investigated. In particular, the underlying mechanism of threshold modulation, i.e., the evolution of unconventional bifurcations, is also found. These findings contribute to complementing and contrasting the existing studies on the fast–slow dynamics of frequency switching systems. • Theoretical way for identifying threshold windows under different parameter values. • Novel bursting patterns induced by several novel multi-jump hysteresis loops. • Underlying mechanisms of the threshold modulating the dynamical behaviors. • Effect of frequency switching scheme and system parameters on the fast–slow dynamics. [ABSTRACT FROM AUTHOR]

The macroscopic behaviors of materials are determined by interactions that occur at multiple lengths and time scales. Depending on the application, describing, predicting, and understanding these behaviors may require models that rely on insights from atomic and electronic scales. In such cases, classical simplified approximations at those scales are insufficient, and quantum-based modeling is required. In this paper, we study how quantum effects can modify the mechanical properties of systems relevant to materials engineering. We base our study on a high-fidelity modeling framework that combines two computationally efficient models rooted in quantum first principles: Density Functional Tight Binding (DFTB) and many-body dispersion (MBD). The MBD model is applied to accurately describe non-covalent van der Waals interactions. Through various benchmark applications, we demonstrate the capabilities of this framework and the limitations of simplified modeling. We provide an open-source repository containing all codes, datasets, and examples presented in this work. This repository serves as a practical toolkit that we hope will support the development of future research in effective large-scale and multiscale modeling with quantum-mechanical fidelity. [ABSTRACT FROM AUTHOR]

Memristor has been universally accepted as the perfect device for simulating neuromorphic synapse, sparking recent and widespread interest in the study of memristive neural networks (MNNs). This paper reports an interesting multi-scroll memristive neural network (MMNN) by configuring newly designed memristor with scalable memductance as the only self-excited synapse to chain-loop Hopfield neural network (HNN). The remarkable feature of the proposed MMNN is that it can yield controllable multi-scroll chaotic attractors, initial-boosting coexisting attractors and large-scale amplitude modulation. As parameter conditions change, the multiscroll chaotic attractors can be split into different numbers of single-scroll chaotic and periodic attractors with initial-boosting along the internal variable of memristive synapse. The comprehensive study of the MMNN on dynamic behaviors, circuit implementation and NIST test is presented. An image encryption algorithm with pixel-level minimal matrix permutation and diffusion processes that shows high security and strong resistance to attacks is constructed by recurring to the MMNN for partially illustrating its availability and superiority in engineering applications. • A new multi-scroll chain-loop memristive neural network model is designed. • Interesting dynamics and circuit realization of the proposed network are studied. • An encryption scheme based on the proposed network is designed and evaluated. [ABSTRACT FROM AUTHOR]

Due to their good approximation accuracy and local fitting characteristics, the moving least squares (MLS) and moving total least squares (MTLS) methods are widely used in various engineering fields. However, neither of these two methods is robust and they cannot effectively deal with outliers in measurement data. To eliminate the negative influence of outliers and achieve robust reconstruction, a novel MTLS method is proposed in this paper, which introduces local Bayesian estimation combined with clustering using representatives (CURE) algorithm. In the support domain, this method adopts a two-step process to remove the abnormal points and adjust the weights of discrete points through compound weighting. Bayesian estimation is first performed on discrete points to derive the reference model, and the residuals are calculated as the input of CURE clustering. The points with large residuals are classified into one cluster and removed. The remaining points undergo repeated processing until the iteration concludes. A gradient weight function based on the residuals and a compact support weight function are combined to determine the final estimated value using weighted Bayesian estimation. The simulations and experiments demonstrate that the proposed reconstruction method achieves excellent accuracy and robustness, surpassing several existing methods when handling highly contaminated datasets. [ABSTRACT FROM AUTHOR]

Owing to their computational efficiency and generative potential, discrete neural models have been gaining interest, both theoretically and towards engineering applications. In this paper, we propose a discrete map endowed with neuron-like dynamics and two distinguishing properties. Namely, the attractor has a spiral topology, and it has a cavity. The size of this cavity shows a non-monotonic relationship to a control parameter, delineating a pulsating behavior. The map shows a multitude of qualitatively-different periodic, chaotic, and hyperchaotic behaviors as a function of the control parameter settings, and its jump points restrict the internal and external size of the attractor. The oscillation frequency is also controllable and also shows a non-monotonic effect. In preparation for future work realizing neural-like networks, we demonstrate the synchronizability by coupling two nodes through a quadratic discrete memristor as the synapse. Finally, the analog circuit realizing this map is implemented and its dynamics are studied experimentally via a comprehensive set of measurements. As the control parameter is varied, the dynamic contraction and expansion of the attractor are observed alongside its well-developed spiral structure. [ABSTRACT FROM AUTHOR]

The nature of the real-world problem is multi-modal and multidimensional. This paper proposes a novel metaheuristic algorithm based on social behaviors of people acquiring favorable information, which is the society-based metaheuristic optimization mechanism, called the Information-Decision Search Algorithm (IDSE), aiming to provide a new optimization technology for solving real-world optimization problems. This optimization technology proposes special searching mechanisms of delivery behavior, approaching behavior, inheritance behavior, mutation behavior, interaction, and learning behavior, establishing corresponding mathematical models to develop an efficient optimization framework for solving constrained optimization. The performance of the proposed algorithm and 10 state-of-the-art optimizers is evaluated on 46 benchmarks, including convergence, solution accuracy, robustness, diversity, significance, and the dimensional-scalability on CEC 2017 benchmarks (50 Dim and 100 Dim). The statistical results suggest, with the dimensionality of the problem variable increasing, the computing efficiency of the proposed optimization technology keeps on the highest level at all times. The low-rank feature for IDSE on 46 benchmarks emphasizes the selective priority in solving the same optimization problem. In addition, IDSE also considers 7 real-world engineering problems. The comparison results suggest that IDSE is superior to competitive algorithms in improving solution accuracy and reducing optimization costs, indicating the significant performance for solving constraint optimization. [ABSTRACT FROM AUTHOR]

This paper studies the exponential input-to-state stability under events (called as exponential ISS under events) for hybrid dynamical networks (HDNs) with coupling time-delays. Notions of input-to-state exponent, exponential ISS under events, and uniform exponential ISS under events are proposed. The exponential ISS under events and the uniform case are studied according to whether the flow gain is a small-gain or not. When the flow gain is a small-gain, Halanay-type ISS Lemmas are firstly established and used to derive criteria of exponential ISS under events and uniform exponential ISS under events. And the minimal dwell time between two consecutive events required for HDNs to achieve uniform exponential ISS under events is estimated. When the flow gain may be not a small-gain, by the method of Lyapunov–Krasovskii functional and M -matrix theory, criteria of exponential ISS under events and uniform exponential ISS under events are also established. And the maximal dwell time between two consecutive events is given for the uniform case. All conditions and results on the uniform case are easily checkable. Examples are given through the paper to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: Since the fundamental solutions (FS) are smooth, the method of FS (MFS) is poor in accuracy for singularity problems, except for some techniques, such as local refinements or adding singular particular solutions (SPS). To better deal with singularity problems, in this paper, we combine the FS and the SPS in the Trefftz methods (TM), explore efficient coupling techniques, and derive error bounds. Moreover, we also combine the MFS with the popular finite element method (FEM), as error bounds are provided. Numerical experiments are reported for Motz''s problem by the TM with both FS and SPS. It is due to the algorithms and the error analysis in this paper that the MFS can be combined with other numerical methods, to greatly extend its application for engineering problems. [Copyright &y& Elsevier]

Summary: Sediment materials play an important role on the dynamic response of large structures where fluid–soil-structure interaction is relevant and materials of that kind are present. Dam-reservoir systems and harbor structures are examples of civil engineering constructions where those effects are significant. In those cases the dynamic response is determined by hydrodynamic water pressure, which depends on the absorption effects of bottom sediments. Sediments of very different mechanical properties may exist on the bottom. A three-dimensional BE model for the analysis of sediment effects on dynamic response of those structures is presented in this paper. One of the most extended models for sediment materials corresponds to Biot''s fluid-filled poroelastic solid. The BE formulation for dynamics of poroelastic solids is reviewed including a weighted residual formulation more general and concise than those previously existing in literature. Systems consisting of water, other pressure wave propagating materials, viscoelastic solids and fluid-filled poroelastic zones, are studied. Coupling conditions at interfaces are taken into account in a rigorous way. A simple geometry coupled problem is first studied to asses the effects of sediments on its dynamic response and to determine the influence of parameters such as sediment depth, consolidation, compressibility and permeability. A fully 3D arch dam-reservoir-foundation system where sediments and radiation damping play an important role is also studied in this paper. Obtained results show the importance of a realistic representation of sediments and the influence of their consolidation degree, compressibility and permeability on the system dynamic response. [Copyright &y& Elsevier]

Abstract In this paper, a novel robust control strategy based on disturbance-compensation-gain (DCG) construction approach is proposed for small-scale unmanned helicopters in the presence of high-order mismatched disturbances. The overall control structure consists of two hierarchical layers. The inner-loop controller is to guarantee the stability of the unmanned helicopters subject to high-order mismatched disturbances. With the estimation of the disturbances and their successive derivatives via finite-time disturbance observer (FTDO), by properly designing some disturbance compensation gains, a novel robust controller is developed to remove the high-order mismatched disturbances from the output channels. The outer-loop controller is to produce flight commands for inner-loop system, as well as to track the reference trajectory, which is carried out with the dynamic inversion technique. The simulation results demonstrate that the unmanned helicopters are capable to perform flight missions autonomously with the proposed control strategy. [ABSTRACT FROM AUTHOR]

Abstract This paper studies the global asymptotic stability of a class of interval fractional-order (FO) nonlinear systems with time-delay. First, a new lemma for the Caputo fractional derivative is presented. It extends the FO Lyapunov direct method allowing the stability analysis and synthesis of FO nonlinear systems with time-delay. Second, by employing FO Razumikhin theorem, a new delay-independent stability criterion, in the form of linear matrix inequality is established for ensuring that a system is globally asymptotically stable. It is shown that the new criterion is simple, easy to use and valid for the FO or integer-order interval neural networks with time-delay. Finally, the feasibility and effectiveness of the proposed scheme are tested with a numerical example. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new algebraic approach to the on-line signal derivatives estimation is proposed. The proposed approach is based on the conversion of the truncated Taylor series expansion to the set of linearly independent equations regarding the signal derivatives. The nonhomogeneous parts of the obtained set of equations are convolution integrals, which can be transformed to the stable linear state-space filter realization. The proposed algebraic estimator provides stable convergence without the need for periodic re-initialization, as in the case of the conventional algebraic estimators. In contrast to the Taylor series-based tracking differentiators, the proposed estimator also provides an estimation of the arbitrary number of the higher-order signal derivatives. In addition, the tuning of the estimator parameters does not depends on the filter dimension. The efficiency of the proposed estimator is illustrated by the simulation examples and experimental results related to the monitoring of the surgical drilling process. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate the incremental H ∞ performance problem for a class of stochastic switched nonlinear systems by using a state-dependent switching law and the maximum and minimum dwell time approach. By resorting to the state-dependent switching law, some sufficient conditions are provided to cope with the incremental H ∞ performance problem, which can be applied even if all subsystems are unstable. Then, based on the maximum and minimum dwell time scheme, the incremental H ∞ performance problem to be solvable is derived for two cases: one is all subsystems are incrementally globally asymptotically stable in the mean(IGASiM), another is both IGASiM subsystems and unstable subsystems coexist. When all subsystems are IGASiM, the stochastic switched nonlinear system is IGASiM and possesses a incremental L 2 -gain under given conditions. When both IGASiM subsystems and unstable subsystems coexist, if the activation time ratio between IGASiM subsystems and unstable ones is not less than a specified constant, the sufficient conditions for the incremental H ∞ performance of the stochastic switched nonlinear system are given. Two numerical examples are given to illustrate the validity of methods proposed. [ABSTRACT FROM AUTHOR]

Abstract The paper is dedicated to solving the generalized periodic discrete-time coupled Sylvester matrix equation, which is frequently encountered in control theory and applied mathematics. The solvable condition and a iterative algorithm for this equation are presented. The proposed method is developed from a point of least squares method. The rationality of the method is testified by theoretical analysis, which shows that the algorithm can solve the problem within finite number of iterations. The presented approach is numerically reliable and requires less computation. A numerical example illustrates the effectiveness of the raised result. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on the parameter estimation problem of multivariate output-error autoregressive systems. Based on the decomposition technique and the auxiliary model identification idea, we derive a decomposition based auxiliary model recursive generalized least squares algorithm. The key is to divide the system into two fictitious subsystems, the one including a parameter vector and the other including a parameter matrix, and to estimate the two subsystems using the recursive least squares method, respectively. Compared with the auxiliary model based recursive generalized least squares algorithm, the proposed algorithm has less computational burden. Finally, an illustrative example is provided to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate the asymptotic stability of fractional-order fuzzy neural networks with fixed-time impulse and time delay. According to the fractional Barbalat's lemma, Riemann–Liouville operator and Lyapunov stability theorem, some sufficient conditions are obtained to ensure the asymptotic stability of the fractional-order fuzzy neural networks. Two numerical examples are also given to illustrate the feasibility and effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a practical technology or solution of quality-related fault diagnosis is provided for nonlinear and dynamic process. Unlike traditional data-based fault diagnosis methods, the alternative approach is focused more on identifying the propagation path that combines diagnostic information and process knowledge. The new method addresses the quality-related fault detection issue with developed nonlinear dynamic latent variable model for extracting nonlinear latent variables that exhibit dynamic correlations, then the advantage of relative reconstruction based contribution approach is followed to analyze the potential root-cause variables. Meanwhile, a new partitioned Bayesian network methodology is proposed for propagation path identification of quality-related faults. Finally, the whole proposed framework is applied to a real hot strip mill process, where the effectiveness is further demonstrated from real industrial data. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the problem of finite-horizon H ∞ state estimation is investigated for a class of discrete time-varying complex networks with multiplicative noises and random coupling strengths. The network nodes and estimators are connected via a constrained communication network which allows only one node to send measurement data at each transmission instant. The Round-Robin protocol is introduced to determine which node obtains the access to the network at certain transmission instant. The aim of the addressed problem is to design a set of time-varying estimator parameters such that the prescribed H ∞ performance is guaranteed over a finite horizon. By using the stochastic analysis approach and completing-the-square method, sufficient conditions are derived for the existence of the desired estimators in terms of the solution to backward recursive Riccati difference equations. Finally, a numerical example is provided to validate the feasibility and effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the positive filter design problem for a class of continuous-discrete Roesser model in Takagi-Sugeno fuzzy form. Both the observer-based and the general form of filters are designed with l 1 performance constraint. By utilizing the co-positive Lyapunov function approach, sufficient criteria are derived in the form of linear programming, which not only guarantee the existence of the positive lower-bounding/upper-bounding filters but also assure the resulting filtering error system to be asymptotically stable and having a prescribed l 1 -gain performance index. In addition, the explicit design schemes for the corresponding filter parameters are also presented. Finally, two numerical examples are provided to illustrate effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new reaching law based sliding mode control strategy for discrete time systems is introduced. Contrary to most existing approaches, the new strategy uses a sliding variable with relative degree two. It is demonstrated that the new reaching law drives the sliding variable to a narrower quasi-sliding mode band than its relative degree one equivalent, while simultaneously ensuring the desired dynamic properties of the system. Furthermore, it is shown that the smaller quasi-sliding mode band width is reflected in reduced magnitude of all state variables in the sliding mode. [ABSTRACT FROM AUTHOR]

In this paper, we present a distance-based framework for DL-Lite based on the notion of features. Within this framework, we propose a distance-based paraconsistent semantics for DL-Lite where meaningful conclusions can be rationally drawn even from an inconsistent knowledge base and we develop a distance-based inconsistency measurement for DL-Lite to provide more informative metrics which can tell the differences between axioms causing inconsistency and among inconsistent knowledge. Furthermore, we investigate several important logical properties (e.g., consistency preservation, closure consistency, splitting property etc.) of the entailment relation based on the new semantics and show its advantages in non-monotonic reasoning for DL-Lite. Finally, we show that our two distance-based inconsistency measures are basic inconsistency measures where some good properties hold such as Free Axiom Independence and Dominance of inconsistency etc. [ABSTRACT FROM AUTHOR]

Sport is one of the activities of human being where cooperative, competitive, self-learning and interactive environment helps in the overall improvement of the performance. These learning processes are very effective to regulate the players in a good direction as well as to enhance their capability of exploring the new techniques. Particle Swarm Optimization (PSO) is a popular stochastic optimization algorithm, used for solving real-world engineering problems. However, it usually suffers from local confinement and easily loses its diversity. In this paper, we have integrated the properties of sports with PSO algorithm and proposed an efficient player selection strategy based diversified PSO (EPS-dPSO), which improves the fitness and robustness of the technique without compromising the computational complexity of the algorithm. The properties of player selection is adopted to enhance the diversity within the search phase as well as to incorporate intense searching of the space. We have comprehensively evaluated the performance of proposed EPS-dPSO by applying it on standard benchmark problems. Experimental result shows that it not only tracks the global optimum within the small search interval but also able to obtain good result for large and asymmetrical search space and also insensitive to initialization of the problems. Further, tests are carried out on the benchmark functions from CEC2005, the large dimensional problems of CEC2008 and some real world problems from CEC2011. All the experimental results indicate the effectiveness and efficiency of the proposed EPS-dPSO compared to other traditional algorithms. [ABSTRACT FROM AUTHOR]

Multi-objective optimization (MOO) is an important research topic in both science and engineering. This paper proposes a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA). We combine the memory of the best states of individual particles and their population in their evolution paths and the gravitational rules to construct a new search strategy. Under this strategy, the position and mass states of each particle are updated based on the memory associated with it and the current states of all particles in the current population in terms of their gravitational forces on it. A novel diversity-enhancement mechanism is also employed to control the velocity of each particle for traveling to a new position. Experiments were conducted on 12 well-known benchmark functions, and for each function the results of DMMOGSA were compared with those of SPEA2, NSGA-II and MOPSO. Our results show that DMMOGSA can reduce the effect of premature convergence and achieve more reliable performance on most of the tested cases. [ABSTRACT FROM AUTHOR]

Bloch theorem is useful for analyzing wave propagation in periodic systems. It has been widely used to determine the energy bands of various translationally-periodic crystals and with the advent of nanoscale structures like nanotubes, it has been extended to account for additional symmetries using group theory. However, this extension is restricted to Hamiltonian systems with analytical potentials. For complex problems, as for engineering structures, the periodic unit cells are often discretized and the Bloch method is restricted to translational periodicity. The goal of this paper is to generalize the direct and transfer-matrix propagation Bloch method to structures with glide and screw symmetries by deriving appropriate boundary conditions. Dispersion relations for a set of reduced problems are compared to results from the classical method, when available. It is found that (i) the dispersion curves are easier to interpret, (ii) the computational cost and error are reduced, and (iii) revisited Bloch method is applicable to structures as the Boerdijk–Coxeter helix that do not possess purely-translational symmetries for which the classical method is not applicable. [ABSTRACT FROM AUTHOR]

Probabilistic causal interaction models have become quite popular among Bayesian-network engineers as elicitation of all probabilities required often proves the main bottleneck in building a real-world network with domain experts. The best-known interaction models are the noisy-OR model and its generalisations. These models in essence are parameterised conditional probability tables for which just a limited number of parameter probabilities are required. The models assume specific properties of intercausal interaction and cannot be applied uncritically. Given their clear engineering advantages however, they are subject to ill-considered use. This paper demonstrates that such ill-considered use can result in poorly calibrated output probabilities from a Bayesian network. By studying, in an analytical way, the propagation effects of noisy-OR calculated probability values, we identify conditions under which use of the model can be harmful for a network's performance. These conditions demonstrate that use of the noisy-OR model for mere pragmatic reasons is sometimes warranted, even when the model's underlying assumptions are not met in reality. [ABSTRACT FROM AUTHOR]

In this paper we show that an enriched continuum model of the micromorphic type (Relaxed Micromorphic Model) can be used to model metamaterials' response in view of their use for meta-structural design. We focus on the fact that the reduced model's structure, coupled with the introduction of well-posed interface conditions, allows us to easily test different combinations of metamaterials' and classical-materials bricks, so that we can eventually end-up with the conception of a meta-structure acting as a mechanical diode for low/medium frequencies and as a total screen for higher frequencies. Thanks to the reduced model's structure, we are also able to optimize this meta-structure so that the diode-behaviour is enhanced for both "pressure" and "shear" incident waves and for all possible angles of incidence. • The importance of disposing of a reduced model to enable the effective use of metamaterials in meta-structural design. • An enriched continuum model of the micromorphic type can be effectively used to model metamaterials' response, even for specimens of finite size. • The reduced model's structure, coupled with the introduction of well-posed interface conditions allows us to unveil the response of meta-structures combining metamaterials and classical-materials bricks. • The conception of a simple metamaterial/classical-material structure that acts as a mechanical diode for low/medium frequencies and as a total screen for higher frequencies. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the in-plane and out-of-plane flexural vibrations of microscale pipes conveying fluid with clamped–clamped ends are examined theoretically, by modifying the classical equations of motion with consideration of the size effects of micro-flow and micro-structure. The theoretical model including an additional parameter associated with the flow velocity profile and another material length scale parameter representing the size effect of micro-structure is valid for both straight and curved pipe systems. The results of calculating the evolution of natural frequencies for straight pipes with increasing mean flow velocity show that the material length scale parameter tends to stiffer the microscale pipe and hence increases the critical flow velocity while the parameter describing the effect of flow velocity profile would decrease the critical flow velocity. For curved pipes, however, the modified inextensible theory predicts that the effect of micro-flow on the in-plane and out-of-plane natural frequencies may be not visible. [Copyright &y& Elsevier]

Abstract: This paper is concerned with the study of reflection of longitudinal displacement waves from the flat boundary of an elastic half-space containing a distribution of void pores. The half space is under the action of a uniform magnetic field and the magnetic field is applied in such a direction that the problem can be considered as a two dimensional one. The critical value of the frequency has been detected. Amplitude ratios have been presented. The effects of magnetic field on various subjects of interest are discussed and shown graphically. [Copyright &y& Elsevier]

In this paper we describe an algorithm and a Fortran 90 module (Conical) for the computation of the conical function for , , . These functions appear in the solution of Dirichlet problems for domains bounded by cones; because of this, they are involved in a large number of applications in engineering and physics. In the Fortran 90 module, the admissible parameter ranges for computing the conical functions in standard IEEE double precision arithmetic are restricted to and . Based on tests of the three-term recurrence relation satisfied by these functions and direct comparison with Maple, we claim a relative accuracy close to in the full parameter range, although a mild loss of accuracy can be found at some points of the oscillatory region of the conical functions. The relative accuracy increases to in the region of the monotonic regime of the functions where integral representations are computed (). Program summary: Program title: Conical Catalogue identifier: AELD_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AELD_v1_0.html Program obtainable from: CPC Program Library, Queenʼs University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5387 No. of bytes in distributed program, including test data, etc.: 49 615 Distribution format: tar.gz Programming language: Fortran 90 Computer: Any supporting a FORTRAN compiler Operating system: Any supporting a FORTRAN compiler RAM: A few MB Classification: 4.7 Nature of problem: Conical functions appear in a large number of applications because these functions are the natural function basis for solving Dirichlet problems bounded by conical domains. Also, they are the Kernel of the Mehler–Fock transform. Solution method: The algorithm uses different methods of computation depending on the range of parameters: asymptotic expansions, quadrature methods and recurrence relations. Restrictions: In order to avoid underflow/overflow problems, the admissible parameter ranges for computing the conical functions in standard IEEE double precision arithmetic are restricted to and . Additional comments: The module Conical uses a Fortran 90 version of the routine dkia (developed by the authors) for computing the modified Bessel functions and its derivative. This routine is included in the distribution file and is also available at http://toms.calgo.org. Running time: Depending on the parameter range: when numerical quadrature is used (for ), the algorithm is 10–20 times slower than the computations made using asymptotic expansions+recurrence relations. [ABSTRACT FROM AUTHOR]

Abstract: The transport equation has many applications in various fields of science and engineering. In this paper we shown that we can transform a transport equation in two-dimensional case into a Fredholm integral equation of the second kind with a compact integral operator for the angular flux by using the Sumudu transform. [Copyright &y& Elsevier]

Abstract: Particle-in-cell (PIC) simulation is widely used in many branches of physics and engineering. In this paper, we give an analysis of the particle-field decomposition method and the domain decomposition method in parallel particle-in-cell beam dynamics simulation. The parallel performance of the two decomposition methods was studied on the Cray XT4 and the IBM Blue Gene/P Computers. The domain decomposition method shows better scalability but is slower than the particle-field decomposition in most cases (up to a few thousand processors) for macroparticle dominant applications. The particle-field decomposition method also shows less memory usage than the domain decomposition method due to its use of perfect static load balance. For applications with a smaller ratio of macroparticles to grid points, the domain decomposition method exhibits better scalability and faster speed. Application of the particle-field decomposition scheme to high-resolution macroparticle-dominant parallel beam dynamics simulation for a future light source linear accelerator is presented as an example. [ABSTRACT FROM AUTHOR]

Abstract: The next development in building Bayesian networks will most likely entail constructing multi-purpose models that can be employed for varying tasks and by different types of user. In this position paper, we argue that the development of a special type of ontology to organize the knowledge involved in such a multi-purpose model is crucial for the management of the model’s content. This ontology should preserve all knowledge elicited for the construction of the model and be accessible to domain experts and knowledge engineers alike. Based on the different ways in which people learn and gain expertise, we further argue that knowledge elicitation will result in task-specific knowledge mostly, which is best stored in the format in which it is elicited. To support varying model views for different tasks and different types of user, we propose that the elicited knowledge be organized in a library-style ontology of separate modules. [Copyright &y& Elsevier]

Abstract: Features of power flow of an undamped beam at resonance are studied in the present paper. It is found that when an undamped beam undergoes free vibration at one of its natural frequencies, the active component of the power flow becomes zero while the reactive component is of modal pattern, whose characteristic frequency is twice of the natural frequency. The power flow in this case can thus be termed as modal power flow. The instantaneous energy density associated with the vibration mode consists of a static component and a dynamic component, related to the mean total and Lagrangian energy densities, respectively. The modal power flow is relevant to the latter but independent of the former. Potential application of modal power flow to structural damage detection is investigated. Two typical damages, transverse cracks and delaminations, are considered. A damage index based on the modal power flow is proposed, and compared with the damage indices based on the slope, the bending strain, and the strain energy through numerical examples. The imperfection of boundary conditions is also considered. It is shown that the proposed damage index is sensitive to both types of damage, thus can be used as an universal damage indicator. [Copyright &y& Elsevier]

Abstract: In this paper we propose a perturbation method to investigate the propagation of the ordinary waves in second-order elastic, isotropic, incompressible, and homogeneous materials. This method allows us to determine the first-order terms of the speeds and the amplitudes both of the principal waves and the waves in any propagation direction, when the undisturbed region is subjected to an arbitrary isochoric deformation. Another application of this method is presented when the undisturbed region is subjected to a simple shear. Finally, some numerical results are presented in Mooney–Rivlin materials. [Copyright &y& Elsevier]

Abstract: There have been many approaches used to discover useful information patterns from databases, such as concept description, associations, sequential patterns, classification, clustering, and deviation detection. This paper proposes a new type of information pattern, called a typical pattern, which is a small subset of objects selected from a large dataset that provides a compact and suitable representation of the original dataset. The Typical Patterns Mining (TPM) algorithm is developed to mine typical patterns from databases. Extensive experiments are carried out using a real dataset to demonstrate the usefulness of typical patterns in practical situations. The experimental results indicate that TPM is a computationally efficient method and that typical patterns can provide a compact and suitable representation of the original dataset. [Copyright &y& Elsevier]

Abstract: The problem of robust stability for a class of uncertain neutral system with time-varying delay and nonlinear uncertainties is studied in this paper. A new delay-dependent stability criteria is presented by using Lyapunov method. The criteria is given in terms of linear matrix inequalities (LMIs) which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the developed techniques. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to report old and new results in the theory of multivalued fractals. We show that the dynamics of an iterated multifunctions system are given by the dynamics of a unique suitable operator. Moreover, some topological properties of the fixed point set of a multivalued operator can be obtained from the properties of the multivalued fractal. [Copyright &y& Elsevier]

Abstract: Within the acoustic approximation, the paper provides the transient reflected and transmitted waves produced by a plane wave, obliquely incident on the plane interface of a layer which is sandwiched between two homogeneous half spaces. First, the unknown waves are investigated in the Fourier transform domain and Snell’s law is applied. Next, attention is restricted to incidence beyond the critical angle and the solution to the reflection–transmission problem is shown to be unique. The reflected and transmitted waves and the waves in the layer are eventually obtained in the time domain. The transient waves turn out to be expressed as convolutions of the incident wave with appropriate solutions to the wave equation. Such solutions, which are parameterized by the mass density, the speed and the width of the layer, express the pertinent effects of multiple reflections within the layer. [Copyright &y& Elsevier]

Abstract: Nonparametric smoothings are useful tool to model longitudinal data. In this paper we study the estimating problem of longitudinal nonparametric additive regression models. A two-stage efficient approach is developed to estimate the unknown additive components. We show the resulted estimators have some advantages over the existed ones. For example, they are asymptotically more efficient than those neglecting the dependence of repeated observations over time within the same subject, have an oracle property, that is the asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty, and can be naturally extended to deal with generalized longitudinal nonparametric additive regression model. The asymptotic normality is established for the underlying additive components. Some simulation studies are conducted to illustrate the finite sample performance of the proposed procedure. Applying the proposed procedure to a real data set is also made. [Copyright &y& Elsevier]

A lot of meshless methods were built and published in last years. They became an effective tool for solving problems from engineering practice. Their advantage is that they do not require any explicit mesh in computation. In this paper we deal with one of this methods—RKHPUM. [Copyright &y& Elsevier]

Abstract: Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example. [Copyright &y& Elsevier]

Abstract: Before selecting a design for a large engineering system several design proposals are evaluated studying different key aspects. In such a design assessment process, different criteria need to be evaluated, which can be of both of a quantitative and qualitative nature, and the knowledge provided by experts may be vague and/or incomplete. Consequently, the assessment problems may include different types of information (numerical, linguistic, interval-valued). Experts are usually forced to provide knowledge in the same domain and scale, resulting in higher levels of uncertainty. In this paper, we propose a flexible framework that can be used to model the assessment problems in different domains and scales. A fuzzy evaluation process in the proposed framework is investigated to deal with uncertainty and manage heterogeneous information in engineering evaluation processes. [Copyright &y& Elsevier]

Abstract: Fluid–structure interaction (FSI) problems are of great relevance to many fields in engineering and applied sciences. One wide spread and complex FSI-subclass is the category that studies the instationary behavior of incompressible viscous flows and thin-walled structures exhibiting large deformations. Free surfaces often present an essential additional challenge for this class of problems. Prominent application areas are fluid sloshing in tanks and numerable problems in offshore engineering and naval architecture. Especially when partitioned strong coupling schemes are used in order to solve the coupled FSI problem the design of an appropriate overall computational approach including free surface effects is not trivial. In this paper a new so-called partitioned implicit free surface approach is introduced and embedded into a strong coupling FSI solver. For complex problem classes this approach is combined with the general elevation equation that is closed through a dimensionally reduced pseudo-structural approach. The presented approach shows the same stability properties as a full implicit approach but is by far more efficient—especially in the partitioned coupled case. [Copyright &y& Elsevier]

Abstract: Bandpass sigma delta modulators (SDMs) have applications in areas such as digital radio demodulation. It is well known that bandpass SDMs with single bit quantizers can exhibit nonlinear and complex state space dynamics like elliptical fractal patterns. These fractal patterns are usually confined in trapezoidal regions. In this paper, we consider bandpass SDMs with multi-bit quantizers. Their nonlinear dynamics is studied. [Copyright &y& Elsevier]

Abstract: The meshless methods for solving boundary value problems have been extensively popularised owing to their flexibility in engineering applications. In the present paper, a meshless method based on a new combination between thin plate and multiquadraic radial basis functions is developed. The new form of the radial basis function contains a parameter ε, which named a control parameter, . Starting the proposed method by the classical Θ–weight implicit finite difference approximation, then fellow up the same procedure as thin plate or multiquadraic but with the new form of the radial basis function. The parameter, ε will take zero when evaluating the diagonal elements for the coefficients matrix resulted. Two different examples were solved with different dimensionality and the present results were compared with the analytical results and gave a good agreement. [Copyright &y& Elsevier]

Abstract: In this paper a generalized KdV–Burger type equationincorporating the effect of absorption is studied using the symmetry method [Steinberg S, Technical Report No. 367, University of New Mexico, USA, 1979]. Besides for the general equation, symmetry reductions and exact solutions are reported for the porous medium equation, corresponding to the case a =0, β =0, and also for the dispersive equation, resulting when α =0 and g(x)=0. [Copyright &y& Elsevier]

Abstract: The relationship between Finite Parts (FPs) and Cauchy Principal Values (CPVs) (when they exist) of certain integrals has been previously studied by Toh and Mukherjee [Toh K-C, Mukherjee S. Hypersingular and finite part integrals in the boundary element method. Int J Solids Struct 1994;31:2299–2312] and Mukherjee [Mukherjee S. CPV and HFP integrals and their applications in the boundary element method. Int J Solids Struct 2000;37:6623–6634, Mukherjee S. Finite parts of singular and hypersingular integrals with irregular boundary source points. Engrg Anal Bound Elem 2000;24:767–776]. This paper continues this study and presents and proves an interesting new relationship between the CPV and FP of certain boundary integrals (on closed boundaries) that occur in Boundary Integral Equation (BIE) formulations of some common Boundary Value Problems (BVPs) in science and engineering. [Copyright &y& Elsevier]

Engineering problems, such as those dealing with boundary element methods (BEM), usually involve high computational costs. Previous works have proposed effective parallel implementations of BEM. These works have proved the benefit of using parallel computers to solve large civil engineering problems. Despite the profits of the parallel implementation in the discretization step of these methods, the drawback remains the solution of the systems of equations obtained. Because of their fully populated coefficient matrices, direct methods are usually preferable to solve these linear systems. However, parallel implementations of iterative methods achieve higher efficiency, but need suitable preconditioners in order to speed up their convergence. The aim of this work is the research into parallel Sparse Approximate Inverse Preconditioners (SPAI) for the iterative solution of dense systems of equations arising from the boundary element codes. Different heuristics for the construction of SPAI preconditioners suitable for this kind of systems are proposed. Some experiments and numerical results, on distributed-memory computers, are presented in this paper. [Copyright &y& Elsevier]