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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Purpose: An iterative edge-preserving CT reconstruction algorithm for high-resolution imaging of small regions of the field of view is investigated. It belongs to a family of region-of-interest reconstruction techniques in which a low-cost pilot reconstruction of the whole field of view is first performed and then used to deduce the contribution of the region of interest to the projection data. These projections are used for a high-resolution reconstruction of the region of interest (ROI) using a regularized iterative algorithm, resulting in significant computational savings. This paper examines how the technique by which the pilot reconstruction of the full field of view is obtained affects the total runtime and the image quality in the region of interest. Methods: Previous contributions to the literature have each focused on a single approach for the pilot reconstruction. In this paper, two such approaches are compared: the filtered backprojection and a low-resolution regularized iterative reconstruction method. ROI reconstructions are compared in terms of image quality and computational cost over simulated and physical phantom (Catphan600©) studies, in order to assess the compromises that most impact the quality of the ROI reconstruction. Results: With the simulated phantom, new artifacts that appear in the ROI images are caused by significant errors in the pilot reconstruction. These errors include excessive coarseness of the pilot image grid and beam-hardening artifacts. With the Catphan600 phantom, differences in the imaging model of the scanner and that of the iterative reconstruction algorithm cause dark border artifacts in the ROI images. Conclusions: Inexpensive pilot reconstruction techniques (analytical algorithms, very-coarse-grid penalized likelihood) are practical choices in many common cases. However, they may yield background images altered by edge degradation or beam hardening, inducing projection inconsistency in the data used for ROI reconstruction. The ROI images thus have significant streak and speckle artifacts, which adversely affect the resolution-to-noise compromise. In these cases, edge-preserving penalized-likelihood methods on not-too-coarse image grids prove to be more robust and provide the best ROI image quality. [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]

Researches on the unit commitment with transmission network have been reported recently. However, most of these researches mainly discussed the security constrained unit commitment, while the relationship between unit commitment and transmission losses was not considered. However, from the standpoint of operating reserve for ensuring power supply reliability, a unit commitment considering transmission losses is required. Further, under the deregulation and liberalization of the electric power industry, not only the line's security but also transmission losses are expected to play an important role in calculating the network access charge, and unit commitment taking into account transmission losses is also desired from this viewpoint. In this paper, a unit commitment approach with both transmission losses and line flow constraint is presented. Based on a heuristic iterative optimization method, first, an initial schedule is created by using a successively decommitting unit approach that is proposed in this paper. Then, we determine constraints included in the unit commitment schedule by a heuristic iterative optimization approach, in which an algorithm able to get rid of line overload by DC optimal power flow is developed. Through numerical simulations on two test power systems, the effectiveness of the proposed method is shown. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 142(4): 9–19, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10116 [ABSTRACT FROM AUTHOR]

In a preceding paper we have presented a unified view of the identification methods dedicated to adaptive sequential systems. In this paper, we develop the resolution technique based on genetic simulation. We analyse the various parameters of such an approach, then, we propose a tool intended to demonstrate the interest of this new approach, and finally we present some differential identification experiments conducted with this tool. Copyright © 2001 John Wiley & Sons, Ltd. [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]

This paper describes a new parameter tuning method for an elevator group control system. In such a system, tuning parameters describing elevator use and the building environment are important. The new tuning method uses improved genetic algorithms to follow environment changes and to give robustness. Keeping diversity is important in following environment changes. The paper also describes the addition of the random chromosome method and addition of other estimation methods to maintain diversity. Their effects are shown by simulations. © 1998 Scripta Technica, Electr Eng Jpn, 124(1), 55–64, 1998 [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 the communication system using a constant modulus signal, a constant modulus algorithm (CMA) adaptive array antenna is effective for elimination of the frequency-selective tiding generated in multiple propagation paths. On the other hand, in the system in which CMA adaptive loops are installed for each antenna element in an array with mare than 10 elements used for mobile satellite communication, the computing time and the amount of hardware become excessive. in this paper, a beam-space CMA adaptive array antenna (BSCMA) is proposed in which a portion of the multibeam output is selected to form a CMA adaptive array. In the BSCMA, first, a multibeam is formed by means of a fast Fourier transform (FFT) and only the beams whose output power exceeds a threshold level are selected. An adaptive process is carried out with the CMA as a guiding principle only for the selected beam outputs. The BSCMA has an advantage of carrying out the capture of the desired wave and the elimination of the interference wave effectively with degrees of freedom corresponding to the number of arriving waves. The method is effective for an adaptive antenna system applied to an array antenna constructed with many antenna elements. In this paper, the configuration of the BSCMA is shown and its characteristics are investigated by the numerical simulation. [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]

Power system analysis is the basis of operation and planning. Since power systems are very large and complex, however, long computation time is required for the analysis. Development of a fast calculation method for stability analysis is desirable. Recently, the method using multiple time-scale numerical integration algorithm was developed for analyzing long-term dynamics. This method has the problem of calculation time since the coefficient matrix is very large. It is expected that calculation time can be shortened using parallel processing. In order to increase the efficiency of parallel processing, the coefficient matrix must be divided since solution of a set of linear equations is the main part of stability analysis. In this paper, coefficient matrix is converted into BBDF matrix for effective calculation of parallel processing. Each subnetwork block can be divided again since it is sparse. The algorithm discussed in this paper was implemented on the nCUBE2S parallel processing computer system. The computing time is measured so that it can be compared to the computer time of a single-processor system. © 1997 Scripta Technica, Inc. Electr Eng Jpn, 120(4): 14–22, 1997 [ABSTRACT FROM AUTHOR]

With the recent development of semiconductor integration technology, the amount of data that must be handled in the layout design of VLSI is increasing rapidly. Even if the improvement of the processing speed of the computer in the future is considered, it is desired to develop a high-speed layout algorithm compared to the conventional method. This paper discusses the k (> 2)-way graph partitioning problem, which is one of the most basic problems concerning the layout design. A parallel algorithm is proposed. The general method to solve this problem has been to apply hierarchically the two-way graph partitioning algorithm. In this method, the algorithm can easily be executed in parallel by operating a number of processors at each hierarchy. A problem then is the efficiency of the processor and the computation time. This paper considers the k-way graph partitioning and proposes a new method called nonhierarchical k-way graph partitioning, aiming at the education of the computation time by parallel processing. In general, it is considered difficult to improve the speed sufficiently by the parallel processing, while maintaining the same accuracy of the solution as that of the sequential algorithm. In this paper, the effectiveness of the proposed algorithm is shown by a simulation experiment on the sequential computer. [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]

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]

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 Channel assignment in multichannel multiradio wireless mesh networks is a powerful resource management tool to exploit available multiple channels. Channels can be allocated either statically on the basis of long-term steady state behavior of traffic or dynamically according to actual traffic demands. It is a common belief that dynamic schemes provide better performance; however, these two broad classes of channel allocation schemes have not been compared in detail. In this paper, we quantify the achievable performance gain and fairness improvement through an optimal dynamic channel allocation scheme. We develop optimal algorithms for a dynamic and three static schemes using mixed integer linear programming and compare them in the context of QoS provisioning, where network performance is measured in terms of acceptance rate of QoS sensitive traffic demands. Our extensive simulations show that static schemes should optimize channel allocation for long-term traffic pattern and maintain max-min fairness to achieve acceptable performances. Although the dynamic and max-min fair static schemes accomplish the same fairness, the dynamic channel allocation outperforms the static scheme about 10% in most cases. In heavily overloaded regimes, especially when network resources are scarce, both have comparable performances, and the max-min fair scheme is preferred because it incurs less overhead. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The first-order nonnegative integer valued autoregressive process has been applied to model the counts of events in consecutive points of time. It is known that, if the innovations are assumed to follow a Poisson distribution then the marginal model is also Poisson. This model may however not be suitable for overdispersed count data. One frequent manifestation of overdispersion is that the incidence of zero counts is greater than expected from a Poisson model. In this paper, we introduce a new stationary first-order integer valued autoregressive process with zero inflated Poisson innovations. We derive some structural properties such as the mean, variance, marginal and joint distribution functions of the process. We consider estimation of the unknown parameters by conditional or approximate full maximum likelihood. We use simulation to study the limiting marginal distribution of the process and the performance of our fitting algorithms. Finally, we demonstrate the usefulness of the proposed model by analyzing some real time series on animal health laboratory submissions. [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]

This paper presents an automatic process for fabrication-oriented design of custom-shaped rubber balloons. We cast computational balloon design as an inverse problem: given a target shape, we compute an optimal balloon that, when inflated, approximates the target as closely as possible. To solve this problem numerically, we propose a novel physics-driven shape optimization method, which combines physical simulation of inflatable elastic membranes with a dedicated constrained optimization algorithm. We validate our approach by fabricating balloons designed with our method and comparing their inflated shapes to the results predicted by simulation. An extensive set of manufactured sample balloons demonstrates the shape diversity that can be achieved by our method. [ABSTRACT FROM AUTHOR]

Purpose: In laparoscopic surgery, soft tissue deformations substantially change the surgical site, thus impeding the use of preoperative planning during intraoperative navigation. Extracting depth information from endoscopic images and building a surface model of the surgical field-of-view is one way to represent this constantly deforming environment. The information can then be used for intraoperative registration. Stereo reconstruction is a typical problem within computer vision. However, most of the available methods do not fulfill the specific requirements in a minimally invasive setting such as the need of real-time performance, the problem of view-dependent specular reflections and large curved areas with partly homogeneous or periodic textures and occlusions. Methods: In this paper, the authors present an approach toward intraoperative surface reconstruction based on stereo endoscopic images. The authors describe our answer to this problem through correspondence analysis, disparity correction and refinement, 3D reconstruction, point cloud smoothing and meshing. Real-time performance is achieved by implementing the algorithms on the gpu. The authors also present a new hybrid cpu-gpu algorithm that unifies the advantages of the cpu and the gpu version. Results: In a comprehensive evaluation using in vivo data, in silico data from the literature and virtual data from a newly developed simulation environment, the cpu, the gpu, and the hybrid cpu-gpu versions of the surface reconstruction are compared to a cpu and a gpu algorithm from the literature. The recommended approach toward intraoperative surface reconstruction can be conducted in real-time depending on the image resolution (20 fps for the gpu and 14fps for the hybrid cpu-gpu version on resolution of 640 × 480). It is robust to homogeneous regions without texture, large image changes, noise or errors from camera calibration, and it reconstructs the surface down to sub millimeter accuracy. In all the experiments within the simulation environment, the mean distance to ground truth data is between 0.05 and 0.6 mm for the hybrid cpu-gpu version. The hybrid cpu-gpu algorithm shows a much more superior performance than its cpu and gpu counterpart (mean distance reduction 26% and 45%, respectively, for the experiments in the simulation environment). Conclusions: The recommended approach for surface reconstruction is fast, robust, and accurate. It can represent changes in the intraoperative environment and can be used to adapt a preoperative model within the surgical site by registration of these two models. [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]

The standard Pearson correlation coefficient, r, is a biased estimator of the population correlation coefficient, ρ XY, when predictor X and criterion Y are indirectly range-restricted by a third variable Z (or S). Two correction algorithms, Case III, and Case IV, have been proposed to correct for the bias. However, to our knowledge, the two algorithms did not provide a procedure to estimate the associated standard error and confidence intervals. This paper suggests using the bootstrap procedure as an alternative. Two Monte Carlo simulations were conducted to systematically evaluate the empirical performance of the proposed bootstrap procedure. The results indicated that the bootstrap standard error and confidence intervals were generally accurate across simulation conditions (e.g., selection ratio, sample size). The proposed bootstrap procedure can provide a useful alternative for the estimation of the standard error and confidence intervals for the correlation corrected for indirect range restriction. [ABSTRACT FROM AUTHOR]

This paper addresses the analytical evaluation of broadcast protocols in VANET. We focus on the most popular broadcast algorithm, which consists in the current emitter selecting the furthest receiver as the next forwarder. We propose a general framework based on point process to evaluate this protocol. The radio environment is modelled by a generic Frame Error Rate function. It enables us, through the same model, to assess the performances for different radio environments or radio technologies. We derive simple formulae for different quantities relative to the performance of the broadcast protocol: time to propagate the message, emitters' intensity, mean number of receptions for the same message, etc. Results based on the analytical model are compared with simulations using realistic vehicle traffic in order to determine the contexts for which the analytical model is relevant. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Multiuser orthogonal frequency division multiplexing (OFDM) is a promising technology to achieve high uplink/downlink (DL) capacities in the next generation broadband wireless networks such as WiMAX (Worldwide Interoperability for Microwave Access). In this paper, we investigate the DL adaptive power allocation (APA) in multiuser OFDM system from the perspective of cross-layer design. Specifically, we formulate APA as an optimization problem with the traffic profile of each user asit a priori knowledge. To solve the optimization problem, we develop a fairness-constrained optimal prioritized effective throughput (PET) strategy and the corresponding iterative algorithms, aiming at balancing the prioritized effective throughput and the linear or logarithmic user satisfaction-based fairness. Simulation results show that our proposed APA optimization approach can achieve satisfying performance. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This work presents a distributed time-slot assignment algorithm which adopts TDMA as Medium Access Control, specially suited to support applications with strict delay, jitter, and throughput requirements characterized by convergecast traffic pattern in sensor networks. (e.g. wireless video surveillance sensor networks). The proposed algorithm has three characteristics: (1) every node is guaranteed a path to the base station for its data delivery. In the path, sufficient resource is reserved and weighted fairness can be achieved. (2) It uses cascading time-slot assignment and jitter minimization algorithm in each node to minimize jitter and end-to-end delay. (3) Nodes are only active during their scheduled slots and sleep otherwise. This offers energy saving by reducing idle listening and avoiding overhearing. The performance of the proposed algorithm is evaluated over simulations and analyzed theoretically in comparison with existing slot assignment algorithm. The results show that our algorithm provides lower end-to-end delay, jitter, and higher throughput. Copyright © 2010 John Wiley & Sons, Ltd. In this paper, we introduce a time slot assignment algorithm for real time applications in wireless sensor networks. The algorithm has three characteristics: (1) every node is guaranteed a path to the base station for its data delivery. In the path, sufficient resource is reserved and weighted fairness can be achieved. (2) Cascading time slot assignment and jitter minimization algorithm are proposed to minimize jitter and transmission delay. (3) Nodes are only active during their scheduled slots and sleep otherwise. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a differentiated service (DiffServ)-based bandwidth-constrained network layer anycast routing for a mobile IPv6 network. The proposed algorithm comprises three steps: (1) When moving into a new foreign network, the mobile node (MN) chooses a feasible path to easily locate the nearest server that can serve it. To perform path selection, a multi-level list structure (MLLS) is defined and used to store the available bandwidth and hop count of a path. (2) An ingress extended edge router (E-ER) uses the multi-level list algorithm (MLLA) to examine the MLLS for selecting the feasible path with the smallest number of hops that satisfies the MN bandwidth request. (3) The E-ER uses a condition of path change (CPC) variable to determine whether it should optimize the route between itself and the server. Simulation results indicate that the proposed algorithm offers better performance than the existing related approaches in terms of the average running time, request blocking rate, and reducing the control overhead of the simulated network. Copyright © 2010 John Wiley & Sons, Ltd. A DiffServ-based bandwidth constrained anycast routing is used to select a new feasible path satisfying an MN QoS request when the MN changes its point of attachment. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

It is very important to maintain supply reliability in the deregulated environment. The transient stability problem is one of the major concerns in studies of planning and operation of power systems. Time domain simulation is currently the best available tool for allowing the use of detailed models and for providing reliable results. The main limitations of this approach involve long computation times. Therefore, this paper proposes a transient stability evaluation method using minimum transient kinetic energy of postfault trajectories. This method can estimate critical clearing times with only two points of the minimum transient kinetic energy, regardless of whether the trajectories after the clearing time are stable or unstable. The validity of the proposed method is shown by simulation studies with the IEEJ EAST 10-machine 47-bus system. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(3): 18-24, 2011; Published online in Wiley Online Library (). DOI 10.1002/eej.21018 [ABSTRACT FROM AUTHOR]

In this paper, a learning algorithm combining memory-less learning and memory-based learning is proposed for agents operating under POMDP. In the first stage of the proposed algorithm, memory-less learning is applied. The stochastic gradient method is employed as a memory-less learning algorithm. In the first stage, a state-action set series that accomplishes the task is stored in memory. In the second stage, memory-based learning is applied. In this process, only the series obtained in the first stage is used, so that this method is able to reduce significantly the amount of required memory. The proposed algorithm is applied to three simulations for comparison with the memory-less learning algorithm. Through computer simulations, it is shown that the proposed algorithm works more effectively in POMDP than ordinary memory-less learning. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 173(1): 32–40, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20963 [ABSTRACT FROM AUTHOR]

Both intersymbol interference (ISI) and multiple-access interference (MAI) are the important issues in code division multiple access (CDMA) multiuser communication systems. The step size of the traditional least-mean-square (LMS) adaptive receivers must be substantially adjusted to overcome the effect due to different channel responses or different numbers of active users. The normalized-LMS (NLMS) algorithm can automatically manipulate the adjustment to avoid the problem just discussed. This paper proposes the symbol-based interference rejection filter with NLMS algorithm and derives both finite impulse response (FIR)- and infinite impulse response (IIR)-type algorithms. We also derive the optimal step sizes and minimum mean-square errors (MSEs) for both the FIR and IIR symbol-based receivers. The complexity of our proposed FIR receiver is lower than that of the conventional chip-based receivers. In addition, it is shown that the bit error rate performance of our proposed symbol-based receivers is superior to conventional one in the simulations. Simulations also show the correctness of our theoretical analysis of minimum MSE. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The goal of this paper is to enable the interactive simulation of phenomena such as animated fluid characters. While full 3D fluid solvers achieve this with control algorithms, these 3D simulations are usually too costly for real-time environments. In order to achieve our goal, we reduce the problem from a three- to a two-dimensional one, and make use of the shallow water equations to simulate surface waves that can be solved very efficiently. In addition to a low runtime cost, stability is likewise crucial for interactive applications. Hence, we make use of an implicit time integration scheme to obtain a robust solver. To ensure a low energy dissipation, we apply an Implicit Newmark time integration scheme. We propose a general formulation of the underlying equations that is tailored towards the use with an Implicit Newmark integrator. Furthermore, we gain efficiency by making use of a direct solver. Due to the generality of our formulation, the fluid simulation can be coupled interactively with arbitrary external forces, such as forces caused by inertia or collisions. We will discuss the properties of our algorithm, and demonstrate its robustness with simulations on strongly deforming meshes. [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]

Current unsteady multi-field simulation data-sets consist of millions of data-points. To efficiently reduce this enormous amount of information, local statistical complexity was recently introduced as a method that identifies distinctive structures using concepts from information theory. Due to high computational costs this method was so far limited to 2D data. In this paper we propose a new strategy for the computation that is substantially faster and allows for a more precise analysis. The bottleneck of the original method is the division of spatio-temporal configurations in the field (light-cones) into different classes of behavior. The new algorithm uses a density-driven Voronoi tessellation for this task that more accurately captures the distribution of configurations in the sparsely sampled high-dimensional space. The efficient computation is achieved using structures and algorithms from graph theory. The ability of the method to detect distinctive regions in 3D is illustrated using flow and weather simulations. [ABSTRACT FROM AUTHOR]

In this paper, the Voltage Magnitude Constrained OPF (VMC-OPF) algorithm to determine the reactive power injection from compensating equipment to load bus is developed. By introducing the proposed VMC-OPF to the real power related Unit Commitment (UC) [1], a novel daily UC method taking into account the reactive power to secure bus voltage magnitude is presented. The Transmission Access Charge (TAC) and Ancillary Services Charge (ASC) are included in the objective function for considering costs of using transmission network and supplying reactive power to maintain the voltage. Using the proposed UC, the difference between two schedules based on benefit maximization and cost minimization is also discussed. To ascertain the effectiveness of the proposed UC method, we demonstrate various simulation results for a model power system of IEEE-118 bus system. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(3): 17–26, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20590 [ABSTRACT FROM AUTHOR]

In this paper, a multi-region domain decomposition finite-difference time-domain (DD-FDTD) algorithm is proposed and developed for the analysis of multiple-objects electromagnetic (EM) problems. A significant number of mesh nodes between objects are removed since only local meshes are generated for each object. All the separated sub-domains are interconnected by the use of a 3-D time-domain Green's function. The coupling between objects can be regarded as the equivalent spherical wave irradiations. Incident signals of the equivalent spherical waves are expressed as a spherical wave input field array according to the Huygens principle. The near-field to far-field transformation is introduced to obtain the equivalent spherical wave. Moreover, the alternating direction implicit FDTD (ADI-FDTD) scheme is applied to overcome the limit of the stability condition and increase the speed of the simulation. The new algorithm has been demonstrated and applied to solve typical 3-D multi-objects EM scattering problems. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]