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This study proposes an improved interferogram filtering method with mathematical morphology. The algorithm firstly converts the interferogram in cosine and sine parts to preserve the continuity of phases, then adopts the improved adaptive line structure elements to run reconstruction process on two parts based on grey scale morphological opening and closing operations. In addition combine the two filtered parts to get the wrapped phases. Simulated and real-data experiments show that the proposed algorithm is more robust in filtering compared with other algorithms referred in this study. [ABSTRACT FROM AUTHOR]

The simulation of two‐dimensional human locomotion in a bird's eye perspective is a key technology for various domains to realistically predict walk paths. The generated trajectories, however, are frequently deviating from reality due to the usage of simplifying assumptions. For instance, common deterministic motion planning algorithms predominantly utilize a set of static steering parameters (e.g. maximum acceleration or velocity of the agent) to simulate the walking behaviour of a person. This procedure neglects important influence factors, which have a significant impact on the spatio‐temporal characteristics of the finally resulting motion—such as the operator's physical conditions or the probabilistic nature of the human locomotor system. In overcome this drawback, this paper presents an approach to derive probabilistic motion models from a database of captured human motions. Although being initially designed for industrial purposes, this method can be applied to a wide range of use cases while considering an arbitrary number of dependencies (input) and steering parameters (output). To underline its applicability, a probabilistic steering parameter model is implemented, which models velocity, angular velocity and acceleration as a function of the travel distances, path curvature and height of a respective person. Finally, the technical performance and advantages of this model are demonstrated within an evaluation. The simulation of two‐dimensional human locomotion in a bird's eye perspective is a key technology for various domains to realistically predict walk paths. The generated trajectories, however, are frequently deviating from reality due to the usage of simplifying assumptions. For instance, common deterministic motion planning algorithms predominantly utilize a set of static steering parameters (e.g. maximum acceleration or velocity of the agent) to simulate the walking behaviour of a person. This procedure neglects important influence factors, which have a significant impact on the spatio‐temporal characteristics of the finally resulting motion—such as the operator's physical conditions or the probabilistic nature of the human locomotor system. In overcome this drawback, this paper presents an approach to derive probabilistic motion models from a database of captured human motions. Although being initially designed for industrial purposes, this method can be applied to a wide range of use cases while considering an arbitrary number of dependencies (input) and steering parameters (output). [ABSTRACT FROM AUTHOR]

The paper focuses on the numerical approximation of discrete fractional order systems with the conditions of nonzero initial instant and nonzero initial state. First, the inverse nabla Laplace transform is developed and the equivalent infinite dimensional frequency distributed model of discrete fractional order system is introduced. Then, resorting the nabla discrete Laplace transform, the rationality of the finite dimensional frequency distributed model approaching the infinite one is illuminated. Based on this, an original algorithm to estimate the parameters of the approximate model is proposed with the help of vector fitting method. Additionally, the applicable object is extended from a sum operator to a general system. Three numerical examples are performed to illustrate the applicability and flexibility of the introduced methodology. [ABSTRACT FROM AUTHOR]

Summary: One of the most important steps in designing a model predictive control strategy is selecting appropriate parameters for the relative weights of the objective function. Typically, these are selected through trial and error to meet the desired performance. In this paper, a reinforcement learning technique called learning automata is used to select appropriate parameters for the controller of a differential drive robot through a simulation process. Results of the simulation show that the parameters always converge, although to different values. A controller chosen by the learning process is then ported to a real platform. The selected controller is shown to control the robot better than a standard model predictive control. [ABSTRACT FROM AUTHOR]

In this paper, we provide a smooth extension of the energy aware Gauss‐Seidel iteration to the Position‐Based Dynamics (PBD) method. This extension is inspired by the kinetic and potential energy changes equalization and uses the foundations of the recent extended version of PBD algorithm (XPBD). The proposed method is not meant to conserve the total energy of the system and modifies each position constraint based on the equality of the kinetic and potential energy changes within the Gauss‐Seidel process of the XPBD algorithm. Our extension provides an implicit solution for relatively better stiffness during the simulation of elastic objects. We apply our solution directly within each Gauss‐Seidel iteration and it is independent of both simulation step‐size and integration methods. To demonstrate the benefits of our proposed extension with higher frame rates, we develop an efficient and practical mesh coloring algorithm for the XPBD method which provides parallel processing on a GPU. During the initialization phase, all mesh primitives are grouped according to their connectivity. Afterwards, all these groups are computed simultaneously on a GPU during the simulation phase. We demonstrate the benefits of our method with many spring potential and strain‐based continuous material constraints. Our proposed algorithm is easy to implement and seamlessly fits into the existing position‐based frameworks. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study the problem of adaptive trajectory tracking control for a class of nonlinear systems with structured parametric uncertainties. We propose to use an iterative modular approach: we first design a robust nonlinear state feedback that renders the closed‐loop input‐to‐state stable (ISS). Here, the input is considered to be the estimation error of the uncertain parameters, and the state is considered to be the closed‐loop output tracking error. Next, we propose an iterative adaptive algorithm, where we augment this robust ISS controller with an iterative data‐driven learning algorithm to estimate online the parametric uncertainties of the model. We implement this method with two different learning approaches. The first one is a data‐driven multiparametric extremum seeking method, which guarantees local convergence results, and the second is a Bayesian optimization‐based method called Gaussian Process Upper Confidence Bound, which guarantees global results in a compact search set. The combination of the ISS feedback and the data‐driven learning algorithms gives a learning‐based modular indirect adaptive controller. We show the efficiency of this approach on a two‐link robot manipulator numerical example. [ABSTRACT FROM AUTHOR]

In the field of radar reconnaissance, unsupervised recognition of radar signals is a particularly important method for classifying different signals and estimating signal parameters. For untagged signals, a new unsupervised recognition method based on the time‐frequency (TF) analysis and Multi‐view Low‐Rank Sparse Subspace Clustering (MLRSSC) is proposed. Specifically, the authors use image wavelet decomposition to create four views for TF images (TFIs), which introduces the concept of multi‐view subspace clustering into radar signal recognition. Compared with other advanced clustering algorithms, the authors' algorithm pays more attention to combining the inherent properties of TFIs. Aiming at the unique ridgeline distribution phenomenon of TFI, a multi‐block technology capable of robustly distributing TFIs subspaces is proposed. Then, Multi‐block and MLRSSC are combined to propose the Multi‐block Joint Multi‐view Subspace Clustering (M‐MLRSSC). The simulation shows that in the TFIs data set with a certain signal‐to‐noise ratio, M‐MLRSSC has obtained superior results, which is better than a variety of advanced subspace clustering algorithms. [ABSTRACT FROM AUTHOR]

ABSTRACT The paper proposes hybrid cloud service selection optimization scheme. Hybrid cloud service selection optimization is distributed to and performed at two levels: hybrid cloud user agent- hybrid cloud service agent at hybrid cloud service layer and hybrid cloud service agent- hybrid cloud agent at hybrid cloud resource layer. Interactions among hybrid cloud user agent, hybrid cloud service agent, public cloud agents and private cloud agents are mediated by means of market mechanisms. Two level hybrid cloud service selection optimization maximizes the interests of hybrid cloud user agents, hybrid cloud service agent, public cloud agents and private cloud agents. Hybrid cloud service selection process includes two parts: hybrid cloud service provisioning and cloud resource allocation. The paper presents a two-level hybrid cloud service selection algorithm used to perform service provisioning and resource allocation. In the simulations, compared with other related algorithm, our proposed hybrid cloud service selection algorithms achieve the better performance with acceptable overhead. © 2015 Wiley Periodicals, Inc. Comput. Appl. Eng. Educ. Comput Appl Eng Educ 23:645-657, 2015; View this article online at ; DOI [ABSTRACT FROM AUTHOR]

SUMMARY This paper proposes an adaptive notch filter that automatically adjusts the notch frequency and notch gain, where they are the null frequency and the depth of the null, respectively. The proposed notch filter consists of an inverse notch filter and a linear prediction filter, and gives an appropriate filter gain which can eliminate a sinusoidal noise and extract only a wide-band signal even if they share the same frequency. We compare the capability of the proposed notch filter with traditional methods. Simulation results show that the proposed system improves the SNR in comparison to the conventional methods. [ABSTRACT FROM AUTHOR]

Distribution-free (nonparametric) control charts are helpful in applications where we do not have enough information about the underlying distribution. The Shewhart precedence charts is a class of Phase I nonparametric charts for location. One of these charts, called the median precedence chart (Med chart hereafter), uses the median of the test sample as the charting statistic, whereas another chart, called the minimum precedence chart (Min chart hereafter), uses the minimum. In this paper, we first study the comparative performance of the Min and the Med charts, respectively, in terms of their in-control and out-of-control run-length properties in an extensive simulation study. It is seen that neither chart is best as each has its strength in certain situations. Next, we consider enhancing their performance by adding some supplementary runs-rules. It is seen that the new charts present very attractive run-length properties, that is, they outperform their competitors in many situations. A summary and some concluding remarks are given. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In practice, many systems exhibit load‐sharing behavior, where the surviving components share the total load imposed on the system. Different from general systems, the components of load‐sharing systems are interdependent in nature, in such a way that when one component fails, the system load has to be shared by the remaining components, which increases the failure rate or degradation rate of the remaining components. Because of the load‐sharing mechanism among components, parameter estimation and reliability assessment are usually complicated for load‐sharing systems. Although load‐sharing systems with components subject to sudden failures have been intensely studied in literatures with detailed estimation and analysis approaches, those with components subject to degradation are rarely investigated. In this paper, we propose the parameter estimation method for load‐sharing systems subject to continuous degradation with a constant load. Likelihood function based on the degradation data of components is established as a first step. The maximum likelihood estimators for unknown parameters are deduced and obtained via expectation‐maximization (EM) algorithm considering the nonclosed form of the likelihood function. Numerical examples are used to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Profile monitoring is a vast area of research underneath the statistical process monitoring (SPM). Several methods for univariate and multivariate process control are found in literature to monitor the profile data, including parametric, nonparametric, and some semiparametric methods. The main idea behind monitoring the linear profiles in mixed effects is to model the possible individual differences between similar set of profiles for future monitoring. In this paper, nonparametric and semiparametric approaches are proposed to model the profile data in a linear mixed effect setting by considering the residuals from a parametric model. A simulation study was carried out to compare the efficiency of the proposed methods. At first step, the residuals from a parametric linear mixed model are obtained. A nonparametric approach (NPR) is then used to model these residuals. Finally, a semiparametric method (MMRRPM) is proposed as a convex combination of the parametric (P) and nonparametric estimations based on the residuals (NPR) to model the profile data in mix effects. Two Hoteling's T2 statistics were computed for each technique based on fitted values and the estimated random effects. The results show that the proposed methods are most effective to monitor the autocorrelated profile data compared with the state‐of‐the‐art. [ABSTRACT FROM AUTHOR]

This paper discusses an alternative approach to the estimation procedure presented in a recently published paper. The authors developed a model-based clustering approach for regression time series and proposed the APECM procedure as an acceleration method for the expectation-maximization algorithm. The process of the estimation of model parameters was discussed in great detail. In this paper, we show how the proposed procedure can be modified to achieve substantial acceleration and better stability. In particular, numerical maximization suggested for the estimation of parameters can be replaced with analytical closed-form expressions, and inverting high dimensional matrices can be avoided entirely. A convenient approach for assessing variability in parameter estimates is also provided. The results of conducted experiments are very promising. © 2012 Wiley Periodicals, Inc. Statistical Analysis and Data Mining, 2012 [ABSTRACT FROM AUTHOR]

For the current generation of cellular communication systems, long-term evolution (LTE) has been the major protocol to support high-speed data transmission. It is critical to allocate downlink spectral resource in LTE, namely, resource blocks (RBs), but the issue is not well addressed in the standard. Therefore, the paper develops an efficient RB allocation algorithm with 4 mechanisms to improve both fairness and throughput in LTE. For fairness concern, our RB allocation algorithm uses a resource-reservation mechanism to prevent cell-edge user equipments from starvation, and a credit-driven mechanism to keep track of the amount of resource given to each user equipment. For throughput concern, it adopts both weight-assignment and RB-matching mechanisms to allocate each RB to a packet according to its flow type and length. Through simulations, we demonstrate that the proposed RB allocation algorithm can significantly increase both throughput and fairness while reducing packet dropping and delays of real-time flows, as compared with previous methods. [ABSTRACT FROM AUTHOR]

This paper has proposed a new pre-processing stage algorithm to enhance the overall performance of current simplification algorithms in analog circuits. This pre-process stage takes place after the calculation of symbolic transfer function and before the main core of the simplification algorithm. The detailed stages of this pre-process are completely independent of the main simplification and symbolic transfer function algorithm. As such, the pre-process algorithm can be easily added to any simplification algorithm to improve the total simplification performance. The use of this command, which is based on the stack decision method, helps the pre-process algorithm to obtain a high-process speed. Based on the CPU time simulation results for a transfer function with 139 terms, it is expected to have a total CPU time in the simplification of a 9820 term of about 28 to 30 seconds pulse and 1.2 to 4.9 seconds for the pre-process algorithm. Finally, a total method, which involves the combination of this pre-process algorithm with the main simplification algorithm is proposed in, and a CPU time of about 30 to 35 seconds is needed for simplifying a huge transfer function with 9820 terms. The addition of extra pre-process algorithm to the main simplification algorithm will reduce the total CPU time of simulation from 820 to 35 seconds, indicating a reduction of 95% in the total needed simulation time. [ABSTRACT FROM AUTHOR]

Computer experiments are often used as inexpensive alternatives to real‐world experiments. Statistical metamodels of the computer model's input‐output behavior can be constructed to serve as approximations of the response surface of the real‐world system. The suitability of a metamodel depends in part on its intended use. While decision makers may want to understand the entire response surface, they may be particularly keen on finding interesting regions of the design space, such as where the gradient is steep. We present an adaptive, value‐enhanced batch sequential algorithm that samples more heavily in such areas while still providing an understanding of the entire surface. The design points within each batch can be run in parallel to leverage modern multi‐core computing assets. We illustrate our approach for deterministic computer models, but it has potential for stochastic simulation models as well. [ABSTRACT FROM AUTHOR]

This article proposes a distributed model‐free adaptive consensus tracking control (DMFACTC) approach for a class of unknown heterogeneous nonlinear discrete‐time multi‐agent systems (MASs) with sensor saturation and measurement disturbance to perform consensus tracking tasks. Meanwhile, both fixed and switching topologies are considered, where only a subset of agents can acquire the desired trajectory information in each topology. A time‐varying linear data model for each agent is first established by utilizing the dynamic linearization method to formulate this algorithm. Merely, the input data and the saturated output data with measurement disturbance of each agent are applied to construct the DMFACTC algorithm without employing any dynamics model information of MASs. The convergence of the designed scheme is strictly proved. It illustrates that the output saturation and switching topologies do not affect the stability of MASs. Moreover, even if the sensor saturation, measurement disturbance, and switching topologies happen simultaneously, the DMFACTC also guarantees that the tracking errors of MASs converge to a small range around the origin. Furthermore, two numerical simulations and a realistic filling system simulation further verify the correctness and effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper reviews the Bayesian melding approach while a companion technical report cited in the paper gives technical details about the Gibbs sampling algorithm used to implement the model and software developed for the research reported in this paper and available online can enable the method's use in other applications. This paper critically assesses the use of melding for mapping ozone concentration fields for possible future use in setting regulatory standards. This assessment has two stages. First a simulation study validates the computer code and goes on to investigate properties of the melding approach in situation where the 'truth' is known. Then it is critically tested on a ozone mapping application using ozone data from the air quality system (AQS) database and simulated data from the multiscale air quality simulation platform (MAQSIP) chemical transportation model for ozone. In all cases, the melding is testing against Kriging, a simpler and more traditional way of mapping spatial fields. Conclusions and recommendations for future work are provided. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The post‐silicon validation and debug is the most important task in the contemporary integrated circuit design methodology. The vital problem prevailing in this system is that it has limited observability and controllability due to the minimum number of storage space in the trace buffer. This tends to select the signals prudently in order to maximize state reconstruction. In the reported works, to select and to restore the signals efficiently it is categorized into two types like low simulation with high‐quality technique and high simulation with low‐quality technique. In this work, a node‐based combinational gate signal selection algorithm is proposed based on machine learning method that maximizes the state restoration capability. A significant improvement (80%) has made to achieve adequate simulation time with the high‐quality associated with the state‐of‐the‐art of supplementary methods. [ABSTRACT FROM AUTHOR]

A dimensionality-reduction-augmented non-linear state-space representation has been proposed to reduce the optimisation space for maximum-likelihood estimation. Based on the above representation, an expectation-maximisation algorithm has been derived to realise joint estimation of states and parameters. During the expectation step, the system state was estimated via the use of a fifth-order cubature Kalman filter and Rauch-Tung-Striebel smoother based on the stateaugmented method. During the maximisation step, unknown parameters within iterations were estimated using the Newton method. Subsequently, two joint-estimation methods - one containing all measurements and the other involving a sliding window - were developed to estimate the invariants and step parameters, respectively. An example concerning manoeuvringtarget tracking has been discussed to demonstrate the performance of proposed algorithms. [ABSTRACT FROM AUTHOR]

To investigate highly squinted spotlight synthetic aperture radar (SAR) images of an electrically large ship target over a rough sea surface, this work focuses on the simulation analysis of SAR images from such a composite scene. For this problem, there are two key issues need to be considered, namely the simulation and the processing of SAR echoes. Considering the first issue, an efficient facet scattering model based on capillary wave modification facet scattering model and geometrical optics and physical optics hybrid method is applied to calculate the electromagnetic (EM) scattering characteristics from a real ship-ocean scene, based on which SAR echoes can be obtained. For the second issue, a non-linear frequency scaling algorithm (NFSA) is employed to efficiently process the highly squinted SAR echoes. Compared with the traditional frequency scaling algorithm, the NFSA extends the frequency scaling operation to the cubic order and makes a more accurate secondary range compression. With the solutions to the two issues, SAR images of a complicated ship-ocean scene under different incident and squint angles are presented and analysed. The reasonable results demonstrate the validity of the simulation approach and the practicability of the model for highly squinted spotlight SAR images. [ABSTRACT FROM AUTHOR]

In this paper, we propose a sensitivity-based analysis to study the nonlinear behavior under nonexpected utility with probability distortions (or 'distorted utility' for short). We first discover the 'monolinearity' of distorted utility, which means that after properly changing the underlying probability measure, distorted utility becomes locally linear in probabilities, and the derivative of distorted utility is simply an expectation of the sample path derivative under the new measure. From the monolinearity property, simulation algorithms for estimating the derivative of distorted utility can be developed, leading to gradient-based search algorithms for the optimum of distorted utility. We then apply the sensitivity-based approach to the portfolio selection problem under distorted utility with complete and incomplete markets. For the complete markets case, the first-order condition is derived and optimal wealth deduced. For the incomplete markets case, a dual characterization of optimal policies is provided; a solvable incomplete market example with unhedgeable interest rate risk is also presented. We expect this sensitivity-based approach to be generally applicable to optimization problems involving probability distortions. [ABSTRACT FROM AUTHOR]

This paper introduces a highly detailed radar altimeter simulation model, considering geometric and signal processing aspects. The simulation model is deployed in a simulation environment for a better understanding of the different error sources of radar altimeters. To characterize the strengths and weaknesses of the altimeter simulation model, the simulation results are compared to recorded altimeter flight test data. A slant range compensation algorithm is introduced applying the altimeter simulation model inflight. The performance of the slant range compensation algorithm is shown on recorded flight test data of an octocopter trajectory as well as on a fixed-wing aircraft trajectory. Copyright © 2016 Institute of Navigation [ABSTRACT FROM AUTHOR]

In this paper, we study the decentralized control problem for nondeterministic discrete-event systems (DESs) under bisimulation equivalence. In order to exactly achieve the desired specification in the sense of bisimulation equivalence, we present a synchronous composition for the supervised system based on the simulation relation between the specification and the plant. After introducing the notions of simulation-based controllability and simulation-based coobservability, we present the necessary and sufficient condition for the existence of a decentralized supervisor such that the controlled system is bisimilar to the specification, and an algorithm for verifying the simulation-based coobservability is proposed by constructing a computational tree. [ABSTRACT FROM AUTHOR]

ABSTRACT Time-delay systems (TDSs) frequently arise in circuit simulation especially in high-frequency applications. Model order reduction (MOR) techniques can be used to facilitate the simulation of TDSs. On the other hand, many kinds of variations, such as temperature and geometric uncertainties, can have significant impact on the transient responses of TDSs. Therefore, it is important to preserve parametric dependence during the MOR procedure. This paper presents a new parameterized MOR scheme for TDSs with parameter variations. We derive parameterized reduced-order models (ROMs) for TDSs using balanced truncation by approximating the Gramians in the multi-dimensional space of parameters. The resulting ROMs can preserve the parametric dependence, making it efficient for repeated simulations under different parameter settings. Numerical examples are presented to verify the accuracy and efficiency of our proposed algorithm. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Wireless converge-cast networks (WCNs), such as data collection-based wireless sensor networks, exhibit certain phenomena called funneling effect, where the region close to the sink node is heavily overloaded. In this paper, we identify that the funneling effect occurs not only close to the sink but also within the network region where nodes have collision and induce heavy traffic to relay; we name it hot-spot funneling effect. This paper aims to improve the throughput and fairness of WCNs by mitigating the micro funneling effect. We propose a new mechanism, the backoff differentiation for contention resolution (BDCR), which is targeted to a system-wide high throughput on the basis of the contention resolution mechanism. To achieve high spatial reuses, BDCR divides the network into several regions and does backoff differentiation within each region. Within each backoff differentiation region, the backoff window range is adjusted according to the traffic rate, and at the same time, the backoff values are set with the awareness of the traffic intensity level. All regions share the same algorithm, which uses Kelly's rate control theory and method to allow each sensor to locally adjust its backoff value. One of the key advantages of BDCR is that it is extremely easy to implement. With extensive simulations and testbed experiments, BDCR is proved to achieve much higher throughput over the traditional carrier sense multiple access and some recent media access control protocols in literature, particularly when the network suffers intensive congestions. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Traditional vehicle localization is based on global positioning system. However, the global positioning system is limited in shadowed environments such as underground carports, tunnels, and urban zones. This paper describes a vehicle positioning solution in an urban environment with the aid of vehicle to vehicle (V2V) networking, which utilizes the existing roadside sensors of the V2V network. The designed localization scheme is based on angle of arrival measurements. Compared with beamforming, minimum variance distortionless response, and subspace-based methods, an angle of arrival estimation method presented in this paper called sparsity angle sensing, based on a sparse representation of sensor measurements and compressive sensing theory, outperforms the other three methods in spatial resolution and robustness. Then the paper applies the novel angle of arrival estimation algorithm into an energy-efficient localization scheme design in a V2V network. Compared with sensor-based approaches, the proposed scheme relieves the requirements of sensor size and energy consumption, and reduces communication and computation overhead. Simulation results show the effectiveness of the proposed scheme in terms of reducing the positioning error. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary The influence of economic conditions on the movement of a variable between states (for example a change in credit rating from A to B) can be modelled using a multi-state latent factor intensity framework. Estimation of this type of model is, however, not straightforward, as transition probabilities are involved and the model contains a few highly analytically intractable distributions. In this paper, a Bayesian approach is adopted to manage the distributions. The innovation in the sampling algorithm used to obtain the posterior distributions of the model parameters includes a particle filter step and a Metropolis-Hastings step within a Gibbs sampler. The feasibility and accuracy of the proposed sampling algorithm is supported with a few simulated examples. The paper contains an application concerning what caused 1049 firms to change their credit ratings over a span of ten years. [ABSTRACT FROM AUTHOR]

In this paper we present a new method for improving the performance of the widely used Bounding Volume Hierarchies for collision detection. The major contribution of our work is a culling algorithm that serves as a generalization of the Separating Axis Theorem for non parallel axes, based on the well-known concept of support planes. We also provide a rigorous definition of support plane mappings and implementation details regarding the application of the proposed method to commonly used bounding volumes. The paper describes the theoretical foundation and an overall evaluation of the proposed algorithm. It demonstrates its high culling efficiency and in its application, significant improvement of timing performance with different types of bounding volumes and support plane mappings for rigid body simulations. [ABSTRACT FROM AUTHOR]

Recent advances in physically-based simulations have made it possible to generate realistic animations. However, in the case of solid-fluid coupling, wetting effects have rarely been noticed despite their visual importance especially in interactions between fluids and granular materials. This paper presents a simple particle-based method to model the physical mechanism of wetness propagating through granular materials; Fluid particles are absorbed in the spaces between the granular particles and these wetted granular particles then stick together due to liquid bridges that are caused by surface tension and which will subsequently disappear when over-wetting occurs. Our method can handle these phenomena by introducing a wetness value for each granular particle and by integrating those aspects of behavior that are dependent on wetness into the simulation framework. Using this method, a GPU-based simulator can achieve highly dynamic animations that include wetting effects in real time. [ABSTRACT FROM AUTHOR]

In this paper, we propose an active noise control (ANC) system without secondary path model (Ĉ filter). The proposed system is based on the simultaneous perturbation optimization method with block process. Consequently, the coefficients of the adaptive filter in the proposed system are updated by error signals only. The conventional ANC system using the Filtered-x algorithm becomes unstable due to the error between the secondary path from a secondary source to an error sensor and its model. On the other hand, the proposed ANC system has the advantage of becoming stable because of not using the model. In this paper, we show the principle of the proposed ANC system and also the effectiveness of this system by computer simulations. © 2000 Scripta Technica, Electron Comm Jpn Pt 3, 83(10): 47–55, 2000 [ABSTRACT FROM AUTHOR]

ABSTRACT In the previous works, the real-time fluid-character animation could hardly be achieved because of the intensive processing demand on the character's movement and fluid simulation. This paper presents an effective approach to the real-time generation of the fluid flow driven by the motion of a character in full 3D space, based on smoothed-particle hydrodynamics method. The novel method of conducting and constraining the fluid particles by the geometric properties of the character motion trajectory is introduced. Furthermore, the optimized algorithms of particle searching and rendering are proposed, by taking advantage of the graphics processing unit parallelization. Consequently, both simulation and rendering of the 3D liquid effects with realistic character interactions can be implemented by our framework and performed in real-time on a conventional PC. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high-performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state-of-the-art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner. This paper is not only a stake in the sand on what has been done, it also seeks to give the reader deeper insights to help guide their future research. [ABSTRACT FROM AUTHOR]

The control of the cell contention is a technical problem in the input queueing ATM cross-connect switch. This paper considers this problem and proposes a scheduling control method which dynamically assigns the cell transmission time. A construction of the distributed scheduling circuit also is proposed based on Batcher's sorting network. The proposed method processes the cells in the order of their arrivals, as in the conventional three-phase algorithm but has an advantage in that the throughput can he increased by approximately 26 percent without increasing the number of control processes per cell. Mother merit is that multirate ports can directly be contained in the switch. In this paper, the approximate model for the proposed method is constructed, and the mean delay and the cell loss probability are calculated theoretically. The actual operating performance is evaluated by a computer simulation. By combining the proposed method with the conventional self-routing spatial switch, a distributed switching circuit can he constructed as a whole, which is useful in developing an economical large- capacity ATM cross-connect switch. [ABSTRACT FROM AUTHOR]

SUMMARY The service-oriented distributed network requires more stable and persistent services, but the services from dishonest or unstable nodes would damage the correctness and availability of services. To efficiently obtain the services from high dependable nodes, many trust management systems have been developed. However, the previous trust models in distributed networks ignore a fact that the entity itself could provide trust information for services also. In this paper, we present a novel trust management model based on the subjective logic trust for service-oriented distributed networks. The proposed algorithm involves passive trust of entity and combines the direct trust and recommendation trust. We also propose a novel scheme called passive trust feedback to avoid the deceit of malicious nodes and unstable nodes, and to encourage honest nodes. Our proposed model expands the trust range of service resource via passive trust of entity, which generates a flexible access path to the service resources. Simulations show that the proposed trust management model can significantly improve the feasibility of trust management as well as effectively detect malicious entities. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The paper presents a review of active set (AS) algorithms that have been deployed for implementation of fast model predictive control (MPC). The main purpose of the survey is to identify the dominant features of the algorithms that contribute to fast execution of online MPC and to study their influence on the speed. The simulation study is conducted on two benchmark examples where the algorithms are analyzed in the number of iterations and in the workload per iteration. The obtained results suggest directions for potential improvement in the speed of existing AS algorithms. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

For the scenario where the overall layout is known and the obstacle distribution information is unknown, a dynamic path planning algorithm combining the A* algorithm and the proximal policy optimization (PPO) algorithm is proposed. Simulation experiments show that in all six test environments, the proposed algorithm finds paths that are on average about 2.04% to 5.86% shorter compared to the state‐of‐the‐art algorithms in the literature, and reduces the number of training epochs before stabilization from tens of thousands to about 4000. [ABSTRACT FROM AUTHOR]

Advanced in unpredictability, ergodicity and sensitivity to initial conditions and parameters, chaotic maps are widely used in modern image encryption algorithms. In this study, the authors propose a novel image block encryption algorithm based on several widely used chaotic maps. In their algorithm, the image blocking method is variable, and both shuffling and substitution algorithms are adopted based on different chaotic maps. Several simulations are provided to evaluate the performances of this encryption scheme. The results demonstrate that the proposed algorithm is with high security level and fast encryption speed, which can be competitive with some other recently proposed image encryption algorithms. [ABSTRACT FROM AUTHOR]

The low‐power short‐range networks have gained prevalence in research fields such as machine‐to‐machine communications and the Internet of things. Given the large number of devices that may exist, the IPv6 over low‐power wireless personal area networks (6LoWPAN) standard is expected to be widely used. Although Contiki, NS‐3, and OMNeT++ have developed the 6LoWPAN model, it is still not available in optimized network engineering tools (OPNET) because it is extremely difficult to interface the built‐in IP module with the customized modules in OPNET. To bridge this gap, we first developed a preliminary 6LoWPAN model and implemented the header compression and header restoration functions to handle the incoming and outgoing packets in OPNET. To further improve the system performance, we also proposed an algorithm that aggregates packets, reduces intranetwork collisions and increases the packet delivery ratio. The model and algorithm in this work are free to download, so researchers from the OPNET community can easily extend this work for their own research in the future. [ABSTRACT FROM AUTHOR]

ABSTRACT Simulation of induction logging responses in formations with large conductivity contrasts is an important but challenging problem due to the singularity of a linear system caused by large contrasts. Also, three-dimensional (3D) analysis of complex geophysical structures usually encounters high computational demands. In this paper, a pre-corrected fast Fourier transform (pFFT)-accelerated integral equation method is applied to overcome these difficulties. In the approach, the entire formation is included in the solution domain. The volume integral equation is set up in the region based on the fact that the total field is the summation of the excitation field and the secondary field. The emitted field by the transmitter coil (treated as a magnetic dipole) is regarded as the excitation of the system. Then the method of moments (MoM) is used to solve the integral equation. To reduce the high computational requirements of the MoM, the pFFT method is used to speed up the solution of the matrix equation and reduce the memory requirement as well. The resultant method is capable of computing induction logging problems involving large and complex formations. For problems with high conductivity contrasts, the solution of the matrix equation usually converges very slow or even fails to converge due to the large condition number of the coefficient matrix. To overcome this difficulty, an incomplete LU pre-conditioner is used to significantly speed up the convergence of the matrix equation, thus further reducing the computation time. Numerical results show that the present method is efficient and flexible for 3D simulation of induction logging and is specifically superior for problems with high conductivity contrasts. [ABSTRACT FROM AUTHOR]

SUMMARY The WAVE (IEEE 1609) standard and vehicular technology create a new opportunity for telematics service. Safety is one of the top issues of telematics service. In this paper, we propose a proactive safety method that can alert drivers before the accident occurs using WAVE. An algorithm named Early Collision Warning Algorithm (ECWA) was proposed in this paper. In ECWA, vehicles broadcast Relationship Information (RI) to neighboring vehicles periodically. Each vehicle calculates whether potential collisions may happen or not upon receiving RI messages. After calculation, ECWA sends warning messages to drivers if the collision will occur. ECWA allows drivers to set the warning level and warning distance by themselves. In our simulation, not only vehicles's collisions at an intersection were simulated but also the GPS error range was considered in our design. The results show that ECWA has good performance and can always alert drivers suitably if the GPS error range was small. Even though the GPS error range is large, ECWA also can enhance the hit rate of warning messages. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, we derive a GPS/INS integration algorithm based on the direction cosine matrix (DCM) attitude representation model and analyze its performance. The motivation for this work is to find an algorithm that is capable of tracking the variation of the gyro bias vector during operations and that benefits from the established DCM based attitude estimation algorithms. Filter performance is evaluated using a simulation based on an air vehicle trajectory profile and is compared with an Euler angles-based unscented Kalman filter (UKF). We investigate the effects of improper initialization of the state vector on the filter performance. These results are supplemented using experimental data collected along a car route with two different grades of inertial measurement units (IMUs). The DCM based model has some advantages over other attitude representations due to its relatively moderate computational load and applicability with different categories of inertial sensors. Copyright © 2012 Institute of Navigation [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel structure using different code system division multiple access (DCSDMA) for an optical communication system and a design algorithm to increase the system capacity. This DCSDMA system can transmit two kinds of code systems (for example, the prime code of 7 and 3, respectively). This multicode architecture can improve the theoretical system capacity from P72 to P72+5∗P32. In this paper, we propose an optimal design method to find the simultaneous capacity X%∗72+Y%∗5∗32. X% and Y% are the successful percentages determined by the simulation results. ©1999 John Wiley & Sons, Inc. Microwave Opt Technol Lett 21: 291–295, 1999. [ABSTRACT FROM AUTHOR]

In cognitive radio networks, the most important goal of spectrum sharing is to benefit both the seller and buyer. In order to increase the total benefits generated in spectrum sharing, this paper introduces a memory mechanism between the spectrum agent and multi-primary service providers (PSPs) and proposes a spectrum trading algorithm based on the mechanism. In this algorithm, all PSPs compete with each other and sell their idle spectrum resource to the agent to maximise their own profits. Then, the agent auctions the spectrum resources obtained in multi-secondary users. Finally, a new auction pricing function is designed to decrease the auction trading prices and increase the benefits of secondary users. Nash equilibrium is considered to be the optimal result. Simulation results show that the proposed algorithm provides 10-15% margin over the conventional algorithm both in the price and spectrum quantity. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Penalized regression methods have for quite some time been a popular choice for addressing challenges in high dimensional data analysis. Despite their popularity, their application to time series data has been limited. This paper concerns bridge penalized methods in a linear regression time series model. We first prove consistency, sparsity and asymptotic normality of bridge estimators under a general mixing model. Next, as a special case of mixing errors, we consider bridge regression with autoregressive and moving average (ARMA) error models and develop a computational algorithm that can simultaneously select important predictors and the orders of ARMA models. Simulated and real data examples demonstrate the effective performance of the proposed algorithm and the improvement over ordinary bridge regression. [ABSTRACT FROM AUTHOR]

SUMMARY Gang scheduling is an efficient resource management scheme for distributed systems which combines elements of time sharing and space sharing. It is a suitable technique particularly in the case when parallel tasks have to be running concurrently to make progress in communication. This paper studies the impact on scheduling performance when dynamically generated sequential gangs exist in the workload. In the case of sequential gangs, a subsequent gang can be dynamically generated after the execution of the initial gang based on affinity information which resides on the caches of the previously seized processors. The performance of different gang-scheduling algorithms is examined for various cases of workload compositions which range from cases with a low demand for dynamically generated gangs to cases with a high ratio of sequential gangs to solitary gangs. A simulation model is implemented to address associated performance issues. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In multicarrier communication systems, a time-domain equalizer (TEQ) can be applied to shorten the channel impulse response and to eliminate inter-symbol interference (ISI). However, the presence of impulsive noise in the channel may paralyze the operation of TEQs and subsequently lead to poor error performance. In this paper, a multicarrier receiver that incorporates a constant false alarm rate algorithm and an iterative estimation technique (CFAR-IET) in conjunction with a TEQ is proposed to increase the robustness of the receiver against impulsive noise. Furthermore, an improved version of the CFAR-IET-TEQ scheme, which uses the buffering, sorting, removing and amplitude averaging (BSRA) processes, is presented. Performance comparisons of the proposed schemes with the existing Gaussian-optimized schemes are made. Simulation results show that the BSRA-IET-TEQ scheme is an effective approach to reduce symbol error rate (SER) in impulsive channels while performing satisfactorily in Gaussian channels. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY The IEEE 802.16e standard specifies the QoS support at the MAC level for wireless broadband access network. To meet the QoS requirements, an efficient scheduling algorithm at base station (BS), which is not defined in the standard, is necessary for slots allocation. In this paper, a Slot-based BS scheduling algorithm with Maximum Latency Guarantee and Capacity First (SMLG-CF) is proposed. With SMLG-CF, the connection request is satisfied with highest slot capacity first. Together with the use of dynamic sub-frame adjustment, the overall system transmission can be efficiently improved. Through the finer slots calculation and accurate transmission time scheduling, the maximum latency guarantee can be better achieved for urgent requests. In the simulation, we compare the proposed mechanism with the deficit fair priority queue scheduling algorithm and the Highest Urgency First scheduling algorithm. The simulation results reveal that SMLG-CF outperforms both algorithms from the aspect of maximum latency violation rate and average transmission rate. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]