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Frequency offset estimation is an important module in the synchronisation of underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems. Different ways are used for carrier frequency offset (CFO) estimation such as maximum likelihood based on a cyclic prefix. In this paper, the Zadoff-Chu (ZC) sequences are used for OFDM synchronisation in underwater communications. The normalised carrier frequency offset can be estimated using the ZC cross-correlation between the primary synchronisation signal and the corresponding local signal, which causes large complexity. The ZC sequences have a time centre symmetric property, and thus the autocorrelation of the received primary synchronisation signal can be used for frequency offset estimation. In this paper, we propose a modified algorithm with low complexity for frequency offset estimation. Simulation results demonstrate that the proposed algorithm can estimate the frequency offset accurately with simple implementation in comparison with the traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for predicting the distributions of people's trajectories on the road network throughout a city. Specifically, we predict the number of people who will move from one area to another, their probable trajectories, and the corresponding likelihoods of those trajectories in the near future, such as within an hour. With this prediction, we will identify the hot road segments where potential traffic jams might occur and reveal the formation of those traffic jams. Accurate predictions of human trajectories at a city level in real time is challenging due to the uncertainty of people's spatial and temporal mobility patterns, the complexity of a city level's road network, and the scale of the data. To address these challenges, this paper proposes a method which includes several major components: (1) a model for predicting movements between neighboring areas, which combines both latent and explicit features that may influence the movements; (2) different methods to estimate corresponding flow trajectory distributions in the road network; (3) a MapReduce-based distributed algorithm to simulate large-scale trajectory distributions under real-time constraints. We conducted two case studies with taxi data collected from Beijing and New York City and systematically evaluated our method. [ABSTRACT FROM AUTHOR]

Flooding produces debris and waste including liquids, dead animal bodies and hazardous materials such as hospital waste. Debris causes serious threats to people's health and can even block the roads used to give emergency aid, worsening the situation. To cope with these issues, flood management systems (FMSs) are adopted for the decision-making process of critical situations. Nowadays, conventional artificial intelligence and computational intelligence (CI) methods are applied to early flood event detection, having a low false alarm rate. City authorities can then provide quick and efficient response in post-disaster scenarios. This paper aims to present a comprehensive survey about the application of CI-based methods in FMSs. CI approaches are categorized as single and hybrid methods. The paper also identifies and introduces the most promising approaches nowadays with respect to the accuracy and error rate for flood debris forecasting and management. Ensemble CI approaches are shown to be highly efficient for flood prediction. [ABSTRACT FROM AUTHOR]

Pavement roughness is a key parameter for controlling pavement construction processes and for assessing ride quality during the life of a pavement system. This paper describes algorithms used in processing three-dimensional (3D) stationary terrestrial laser scanning (STLS) point clouds to obtain surface maps of point wise indices that characterise pavement roughness. The backbone of the analysis is a quarter-car model simulation over a spatial 3D mesh grid representing the pavement surface. With the rich data-set obtained by 3D scanning, the algorithms identify several dynamic responses and inferences (suspension, acceleration and jerk) at each point in the domain. Variability in the indices is compared for a ‘rough’ pavement and a ‘smooth’ pavement in the spatial domain for different speed simulations of the quarter-car model. Results show high spatial variability in the various roughness indices both longitudinally and transversely (i.e. different wheel path positions). It is proposed that pavement roughness characterisation using a spatial framework coupled with univariate statistics provides more details on the severity and location of pavement roughness features compared to the (1D) one-dimensional methods. This paper describes approaches that provide an algorithmic framework for others collecting similar STLS 3D spatial data to be used in advanced pavement roughness characterisation. [ABSTRACT FROM AUTHOR]

Many dual-arm handover systems suffer from low success rates since the grasps are limited to a small number of candidate grasps and handover poses. Large number increases success rate but significantly explodes combinatorics and lowers system performance. How to efficiently exploit the large number of grasps and handover poses is a difficulty faced by many dual-arm manipulation researchers. This paper uses handover heuristics and hierarchical search to. challenge the difficulty. For one thing, it samples large number of grasps and handover poses to ensure success handover. For the other, it employs the handover heuristics to reduce combinatorics and the hierarchical search to reduce search space. Leveraging these technique leads to an algorithm that has high computational efficiency and high success rate. We report the algorithm in this paper and examine its performance using both statistical simulation analysis and real-world experiments. Results show that the algorithm can deal with thousands of grasps within a few seconds using a standard PC. [ABSTRACT FROM PUBLISHER]

This paper suggests a novel 1D Reject Band Filter (RBF) array to prevent the radiation leakage from portable devices around 2.45 GHz. The proposed RBF array is constructed from eight-unit cell elements mounted on the same side of an FR-4 substrate of 1.5-mm thickness. Each two adjacent unit cells are separated with 2 mm. The individual unit cell design is based on fractal-based open-loop resonators of a modified first iteration Minkowski configuration. Such configuration is coupled with an open-stub transmission line to increase the selectivity of the filter stopband response at the frequency of interest. The unit cell performance is evaluated numerically and analytically, and then compared against measurements. Next, the optimal RBF array is fabricated and simulated to evaluate the Specific Absorption Rate (SAR) at 2.45 GHz. The SAR effect on the human thigh tissue is studied numerically to show an excellent reduction from 0.912 to 0.352 W/kg. Finally, the field strength before and after introducing the proposed array underneath a laptop computer, just below the Wi-Fi antenna, is measured and found to be reduced from 497.1 to 171.8 mV/m. [ABSTRACT FROM AUTHOR]

Force identification is a crucial inverse problem in structural dynamics. In this paper, a new method integrating Taylor formula algorithm and acceleration transmissibility concept is put forward to identify the magnitude and location of loads in time domain. The Taylor formula algorithm expresses the response vectors as Taylor-series expansion and then, a series of deductions are implemented. Ultimately an explicit discrete equation which associates output acceleration response, structure characteristic and input excitation together is established. After establishing the explicit discrete equation, acceleration transmissibility concept is utilized to identify the location of forces. Under the premise of knowing the acceleration response and structure characteristic, force magnitude can be calculated. To verify the effectiveness of proposed method, one builds up a theoretical simulation model in which different types of dynamic excitations are exerted on an inflatable cantilever beam. Meanwhile, classical state space algorithm is made a contrast with Taylor formula algorithm in the step of force magnitude identification. Calculation results demonstrate that the integration method is capable of identifying the location of excitations precisely. Reconstruction of force time history reaches a higher accuracy compared to state space algorithm as well. In addition, the anti-noise ability of proposed algorithm is discussed. [ABSTRACT FROM AUTHOR]

The self-updating process (SUP) is a clustering algorithm that stands from the viewpoint of data points and simulates the process how data points move and perform self-clustering. It is an iterative process on the sample space and allows for both time-varying and time-invariant operators. By simulations and comparisons, this paper shows that SUP is particularly competitive in clustering (i) data with noise, (ii) data with a large number of clusters, and (iii) unbalanced data. When noise is present in the data, SUP is able to isolate the noise data points while performing clustering simultaneously. The property of the local updating enables SUP to handle data with a large number of clusters and data of various structures. In this paper, we showed that the blurring mean-shift is a static SUP. Therefore, our discussions on the strengths of SUP also apply to the blurring mean-shift. [ABSTRACT FROM AUTHOR]

The Type-II progressive censoring scheme has become very popular for analyzing lifetime data in reliability and survival analysis. However, no published papers address parameter estimation under progressive Type-II censoring for the mixed exponential distribution (MED), which is an important model for reliability and survival analysis. This is the problem that we address in this paper. It is noted that maximum likelihood estimation of unknown parameters cannot be obtained in closed form due to the complicated log-likelihood function. We solve this problem by using the EM algorithm. Finally, we obtain closed form estimates of the model. The proposed methods are illustrated by both some simulations and a case analysis. [ABSTRACT FROM PUBLISHER]

Modeling has become the most commonly used method in fisheries science, with numerous types of models and approaches available today. The large variety of models and the overwhelming amount of scientific literature published yearly can make it difficult to effectively access and use the output of fisheries modeling publications. In particular, the underlying topic of an article cannot always be detected using keyword searches. As a consequence, identifying the developments and trends within fisheries modeling research can be challenging and time-consuming. This paper utilizes a machine learning algorithm to uncover hidden topics and subtopics from peer-reviewed fisheries modeling publications and identifies temporal trends using 22,236 full-text articles extracted from 13 top-tier fisheries journals from 1990 to 2016. Two modeling topics were discovered: estimation models (a topic that contains the idea of catch, effort, and abundance estimation) and stock assessment models (a topic on the assessment of the current state of a fishery and future projections of fish stock responses and management effects). The underlying modeling subtopics show a change in the research focus of modeling publications over the last 26 years. [ABSTRACT FROM AUTHOR]

Generally, cracks would lead in local discontinuity and sudden change in mode shape, and the local entropy of beam mode will change with the discontinuity of mode shape. Based on this property, cracks can be detected without using a healthy mode shape serving as the baseline. This paper presents a generalised local entropy (GLE) analysis method for crack detection in beam structures, which is a non-baseline mode shape-based damage detection algorithm for beam-type structures. The fundamental and the second-order vibration modes of a cracked cantilever beam are analysed with the presented method. The proposed prediction scheme is validated by simulations and experiments. Based on the results obtained in this paper and the qualities of simplicity and efficiency of GLE method, a mode shape-based crack identification approach is developed as an alternative damage index for structural health monitoring and non-destructive testing. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed fusion estimation problem for a class of multi-sensor asynchronous sampling systems with correlated noises. The state updates uniformly and the sensors sample randomly. Based on the measurement augmentation method, the asynchronous sampling system is transformed to the synchronous sampling one. Local filter is designed by using an innovation analysis approach. Then, the filtering error cross-covariance matrix between any two local filters is derived. Finally, the optimal distributed fusion filter is proposed by using matrix-weighted fusion algorithm in the linear minimum variance sense. Simulation results show the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, two control allocation algorithms have been proposed for overactuated systems. The algorithms are developed by formulating constrained control allocation problem into an equivalent fixed point framework. The first algorithm follows sequential solving method while the other one involves a zero finding technique by the Newton method. In order to consider limiting constraints, the saturation function has been taken into account that leads to a nonsmooth zero finding problem and the proposed method guarantees superlinear convergence. The second algorithm is easy to implement and faster than the algorithm developed based on the sequential solving technique. To demonstrate the effectiveness of the proposed algorithms, a detail simulation study has been carried out, in which one example considers both the actuator rate and amplitude constraints. [ABSTRACT FROM AUTHOR]

This paper is concerned with the estimation of amplitude and phase of an analog multi-harmonic signal based on a series of differential values of the signal. To this end, assuming the signal fundamental frequency is known before hand (i.e., estimated in an independent stage), a complexity-reduced scheme is proposed here, based on the matrix method classically used to estimate the Fourier coefficients. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise root mean square (rms) measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms. [ABSTRACT FROM AUTHOR]

This paper explores the possibility of detecting certain movements of vehicles that might provide useful information for crime investigations. It is known that existing car following models are interested in microscopic interactions between vehicles in randomly formed pairs. The present work, however, introduces the concept of macroscopic analysis of vehicle positions on a network and the idea of seeking if these movements exhibit any meaningful relationships. First of all detection algorithms are produced for two possible types of detection: (a) was a particular vehicle followed by any vehicle? and (b) did a particular vehicle follow any vehicle? These algorithms assume that every link in the network is equipped with some sort of vehicle identification or tracking device and the identities of all vehicles, such as their number plates, are fed into the program. Then a simulation program is developed to implement the first algorithm (Type (a)), as an example, to visualise the concept. Since the present paper is a preliminary and basic approach to the problem, a number of issues and details requiring further research, together with the directions which could be taken, are also identified and discussed. [ABSTRACT FROM AUTHOR]

The objective of this paper is to find an adaptive control strategy which would enable us to estimate the parameters of the ARMAX model as accurately as possible, along with consuming less controlling energy, while keeping the output of the system below a specified level of variability. Using the self-tuning tracker, this paper establishes global convergence of a stochastic adaptive control algorithm for discrete linear system, and the adaptive controller may converge to the one-step-ahead optimal controller at the same time. [ABSTRACT FROM AUTHOR]

The iterative Multilevel Averaging Weight (MAW) algorithm presented in paper [1] is modified to solve the dynamic load imbalance problems arising from the two-dimensional short-range parallel molecular dynamics simulations in this paper. Firstly, five types of load balancing models are given which allows detailed studies of the algorithm. In particular, it shows that for strip decomposition, the number of iteration needs for the system to converge from an initially unbalanced state to a well balanced state is bounded by 2 log P , where P is the number of processors. This result can permit the algorithm to efficiently track fluctuations in the molecular density as the simulation progresses, and is much better than that of the Cellular Automaton Diffusion (CAD) scheme presented in paper [2] . Secondly, we apply MAW algorithm to solve the load imbalance problem in the parallel molecular dynamics simulation for higher speed wall collisions. At last, the numerical experimental results and parallel computing performance with MPI-1.2 under a PC-Cluster consists of 64 Pentium-III 500 MHz nodes connected by 100 Mbps Switches are given in this paper. [ABSTRACT FROM AUTHOR]

This paper addresses the explicit synchronisation of heterogeneous dynamics networks via three-layer communication framework. The main contribution is to propose an explicit synchronisation algorithm, in which the synchronisation errors of all the agents are decoupled. By constructing a three-layer node model, the proposed algorithm removes the assumptions that the topology is fixed and the synchronisation process is coupled. By introducing appropriate assumptions, the algorithm leads to a class of explicit synchronisation protocols based on the states of agents in different layers. It is proved in the sense of Lyapunov that, if the dwell time is larger than a threshold, the explicit synchronisation can be achieved for closed-loop heterogeneous dynamics networks under switching topologies. The results are further extended to the cases in which the switching topologies are only frequently but not always connected. Simulation results are presented with four single-link manipulators to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper presents the detailed evaluation and classification of Surface Electromyogram (SEMG) signals at different upper arm muscles for different operations. After acquiring the data from selected locations, interpretation of signals was done for the estimation of parameters using simulated algorithm. First, different types of arm operations were analysed; then statistical techniques were implemented for investigating muscle force relationships in terms of amplitude estimation. The classification (Artificial Neural Network) based results have been presented for detecting different pre-defined arm motions in order to discriminate SEMG signals. The outcome of research indicates that a neural network classifier performs best with an average classification rate of 92.50%. Finally, the result also inferred the operations which were observed to be easy for arm recognition and the study is a step forward to develop powerful, flexible and efficient prosthetic designs. [ABSTRACT FROM AUTHOR]

In order to realize accurate control of underwater vehicles, this paper proposed a fractal prediction model of surge. Firstly, we introduce the current state-of-the-art of fractal prediction; secondly, we complete a fractal analysis with the R_S method, calculating the fractal dimension of surge using the short-time dimension method; thirdly, we correct the vertical scaling factor of the Iterated Function System (IFS) using the fractal dimension. Then the predictive value can be calculated through anti-iteration according to the statistical significantly IFS and proposing a fractal prediction model. Finally, we complete a simulation analysis based on the actual data and a comparison to another prediction algorithm. The result shows that the fractal prediction algorithm of this article has better comprehensive performance. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of scheduling a nonpreemptive open shop with the objective of minimizing makespan. A neighborhood search algorithm based on the simulated annealing technique is proposed. The algorithm is tested on randomly generated problems, benchmark problems in the literature, and new hard problems generated in this paper. Computational results show that the algorithm performs well on all of the test problems. In many cases, an optimum solution is found, and in others the distance from the optimum or lower bound is quite small. Moreover, some of the benchmark problems in the literature are solved to optimality for the first time. [ABSTRACT FROM AUTHOR]

Efficient rendering of a changing volumetric data-set is central to the development of effective medical simulations that incorporate haptic feedback. A new method referred to as real-time interactive isosurfacing (RTII) is described in this paper. RTII is an algorithm that can be applied to output from Marching Cubes-like algorithms to improve performance for real-time applications. The approach minimises processing by re-evaluating the isosurface around changing sub-volumes resulting from user interactions. It includes innovations that significantly reduce mesh complexity and improve mesh quality as triangles are created from the Marching Tetrahedra isosurfacing algorithm. Rendering efficiency is further improved over other marching isosurfacing algorithm outputs by maintaining an indexed triangle representation of the mesh. The effectiveness of RTII is discussed within the context of an endoscopic sinus surgery simulation currently being developed by the authors. [ABSTRACT FROM PUBLISHER]

This paper proposes a procedure of synthetic detection for the location of a change point and outliers in bilinear time series models with a change after an unknown time point. Based on Bayesian framework, we first derive the conditional posterior distribution of the change point and from that distribution estimate the position of the change point. Then we use these results to detect the outliers in the time series before and after that change point via Gibbs sampler algorithm. Our simulation studies show that the proposed procedure is effective. [ABSTRACT FROM PUBLISHER]

This paper explores whether negative electricity prices can change the rationale that efficient energy storage devices are more economical for arbitrage in electricity markets. An established model algorithm to determine the maximum available arbitrage revenue and optimum schedule of electrical energy storage (EES) operation is used to simulate storage with a time-series of electricity prices which includes some negative prices. Our results suggest that at any likely frequency of negative electricity prices, inefficient EES is not encouraged, and can only be encouraged for EES devices with very low energy capacity to power ratios. [ABSTRACT FROM AUTHOR]

In this paper, equivalence principle algorithm (EPA) with grid-robust higher order vector basis (GRHOVB) is proposed to solve the multiscale problems. The EPA is a kind of domain decomposition method which transforms the interaction of objects into the interaction between virtual equivalence surfaces. Compared with traditional Curvilinear Rao–Wilton–Glisson function, GRHOVB can be used on the equivalence surface to reduce the number of unknowns and also to improve the accuracy. The tap basis is utilized to deal with current continuity when the object is intercepted by an equivalence surface. The equations are simplified further to improve the tap basis scheme. Moreover, to accelerate the solution, multilevel fast multipole algorithm is utilized in EPA. Numerical results are shown to demonstrate the accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a novel theoretic formulation based on adaptive dynamic programming (ADP) is developed to solve online the optimal tracking problem of the continuous-time linear system with unknown dynamics. First, the original system dynamics and the reference trajectory dynamics are transformed into an augmented system. Then, under the same performance index with the original system dynamics, an augmented algebraic Riccati equation is derived. Furthermore, the solutions for the optimal control problem of the augmented system are proven to be equal to the standard solutions for the optimal tracking problem of the original system dynamics. Moreover, a new online algorithm based on the ADP technique is presented to solve the optimal tracking problem of the linear system with unknown system dynamics. Finally, simulation results are given to verify the effectiveness of the theoretic results. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce a complete implementation for efficient and large-scale dissipative particle dynamics (DPD) simulation on Graphics Processing Unit (GPU). The implementation is designed and optimized according to the nature of DPD simulation technique and also takes fully advantage of the computational power of GPUs. From studies of benchmarks, we show that the GPU-based implementation can predict the results correctly and provide nearly 60 times speedup over LAMMPS on a single Central Processing Unit (CPU) core. By using a novel divide-and-conquer (D&C) algorithm to reduce the memory requirement in simulation, our implementation has the capability to perform large-scale DPD simulations with some ten millions of particles on a single current GPU. Furthermore, the thermal fluctuation analysis of a superior large-scale lamellar system (11,059,200 particles) is presented as an important example of practical application of our implementation, and a scaling law at large wavelengths that is inaccessible to small simulation system, is observed. As a result, our GPU-based DPD implementation is very promising for studying various interesting phenomena, which often take place on the mesoscopic length and time scales and are not easily addressed by a conventional CPU-based implementation. [ABSTRACT FROM PUBLISHER]

In this paper, we present an accurate and comprehensive semi-automated algorithm for detection and counting the chemically etched tracks on polycarbonate nuclear Track detectors. The proposed algorithm consists of two main phases: a preprocessing phase for image preparation and quality improvement. It uses a format conversion into gray-scale image and contrast enhancement procedure. The contrast enhancement procedure employs the first-order fuzzy moment of the image and the Sugeno class of fuzzy complements to maximize the parametric indices of fuzziness of the image. In one feature extraction phase, two intrinsic characteristics of tracks are defined and formulated as topological feature (TF) and chromatic feature (CF). TF refers to tracks shape and geometry which are characterized and quantized by calculating the local Gray Level Spatial Correlation histogram of the tracks and CF refers to the color intensity difference of the tracks borders and tracks centric areas. The CF characterizes this difference specified to the tracks. After the feature extraction phase, the algorithm enters the detection and counting phase in which the fuzzy sets of background, noise (including small objects, notches, etc.) and track are constructed. Detected objects are then characterized according to their membership values to the fuzzy sets. The algorithm is designed in order to be applicable for different forms of tracks and track counting systems. Accuracy, linearity, sensitivity to the input parameters and comprehensibility of the method are validated in the simulation section. [ABSTRACT FROM AUTHOR]

Micro-motion features are very useful for target recognition in inverse synthetic aperture radar (ISAR). In this paper, we propose an effective algorithm for micro-motion feature extraction in ISAR imaging with sparse aperture. The micro-Doppler effect induced by rotational micro-motion in ISAR with sparse aperture is analysed first, and then an improved four-parameter Hough transform and an Orthogonal matching pursuit decomposition method are proposed to extract the micro-motion parameters, such as rotation rate and radius. Simulations are given to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new type of sensor: cable sensor. Unlike traditional point sensors, this type of sensor has a rectangular sensing region with a processor installed on it to do processing and communication. The wireless network formed by this kind of sensor is called wireless cable sensor network (WCSN). We study energy-efficient communication algorithms in WCSNs. We address it in two ways: one is through reducing the total transmission power of processors while maintaining the connectivity of the network and the other is through scheduling cable sensors to let them take turns to go to sleep without affecting the coverage and connectivity of the network. In the first approach, we initially develop a distributed algorithm called DTRNG based on the relative neighbourhood graph. Later we enhance it to Algorithm determine the transmission power by removing the largest edge in CYCles (DTCYC). Mathematical proofs show that Algorithm DTCYC provides an optimal solution that can not only minimise the total processor transmission power but maintain the connectivity of the network as well. In the second approach, we propose a cable mode transition algorithm which determines the minimum number of active sensors to maintainK-coverage as well asK-connectivity required by the application. We discuss the relationship between coverage and connectivity and prove the theorems that lay the foundation for our algorithm. Simulation results demonstrate that our algorithm is efficient in saving energy. [ABSTRACT FROM PUBLISHER]

In this paper, a fragile video watermarking algorithm for H.264/AVC is proposed. Watermark information is embedded in the video frame by modulating the horizontal or vertical component of the motion vector difference (MVD). In order to reduce the visual degradation in video, the watermark is embedded into the larger absolute value of the residual component according to the direction of the movement. This scheme could detect the watermark rapidly. Watermark extraction merely needs to decode the motion information instead of decoding the entire video, which meets the requirement of the real time processing of video. Simulation results show that the algorithm brings very small bit rate changes and video distortion, and has a good fragility which can be used for the video authentication or covert communication applications. [ABSTRACT FROM AUTHOR]

A comparison between different modern multi-objective optimization methods applied to the design of concentric rings antenna arrays is presented in this paper. This design of concentric rings antenna arrays considers the optimization of the amplitude and phase excitations across the antenna elements in order to generate the trade-off curves between side lobe level and directivity for a scannable pattern with optimal performance in the whole azimuth plane. Simulation results by using evolutionary multi-objective optimization methods, such as: NSGA-II, DEMO, and EM-MOPSO are provided in this document. Furthermore, a comparative analysis of the performance between these algorithms is presented. [ABSTRACT FROM AUTHOR]

This paper presents the development of a systems-on-chip approach to speed up the simulation of wheel–rail contact laws, which can be used to reduce the requirement for high-performance computers and enable simulation in real time for the use of hardware-in-loop for experimental studies of the latest vehicle dynamic and control technologies. The wheel–rail contact laws are implemented using a field programmable gate array (FPGA) device with a design that substantially outperforms modern general-purpose PC platforms or fixed architecture digital signal processor devices in terms of processing time, configuration flexibility and cost. In order to utilise the FPGA's parallel-processing capability, the operations in the contact laws algorithms are arranged in a parallel manner and multi-contact patches are tackled simultaneously in the design. The interface between the FPGA device and the host PC is achieved by using a high-throughput and low-latency Ethernet link. The development is based on FASTSIM algorithms, although the design can be adapted and expanded for even more computationally demanding tasks. [ABSTRACT FROM AUTHOR]

In this paper we study the cure rate survival model involving a competitive risk structure with missing categorical covariates. A parametric distribution that can be written as a sequence of one-dimensional conditional distributions is specified for the missing covariates. We consider the missing data at random situation so that the missing covariates may depend only on the observed ones. Parameter estimates are obtained by using the EM algorithm via the method of weights. Extensive simulation studies are conducted and reported to compare estimates efficiency with and without missing data. As expected, the estimation approach taking into consideration the missing covariates presents much better efficiency in terms of mean square errors than the complete case situation. Effects of increasing cured fraction and censored observations are also reported. We demonstrate the proposed methodology with two real data sets. One involved the length of time to obtain a BS degree in Statistics, and another about the time to breast cancer recurrence. [ABSTRACT FROM AUTHOR]

Coverage is an important parameter to determine the effectiveness of wireless sensor networks. In this paper, we present a new algorithm called uncovered region exploration algorithm (UREA) to enhance the coverage after an initial random deployment using binary and probabilistic sensor detection models. UREA decides a new location based on an uncovered region around a node. Once the effective sensor positions are identified, a one-time movement of each node is carried out to redeploy a sensor at its new position. This one-time displacement of sensor benefits a deployed network to improve coverage. UREA is found to be consistent, robust and versatile to achieve multi-level coverage and suit non-homogeneous sensor deployments. The extensive simulation results show that UREA performs better than the existing deployment algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, we present a new centralised algorithm to detect and resolve generalised deadlock in distributed systems. The initiator of this algorithm induces a directed spanning tree by diffusing the probe messages among its dependent processes. It then collects replies that carry the dependency information of the dependent process to determine a deadlock. Moreover, the initiator of this algorithm performs reduction once it receives a reply from an active process unlike the existing algorithms. Hence, it terminates the execution when it detects a deadlock without waiting for termination detection. We have asserted the correctness of the algorithm formally. It has a worst-case time complexity of d+2 time units, message complexity of e+2n messages and message size of O(n), where n is the number of nodes, e is the number of edges and d is the diameter in the wait-for graph. The performance of the proposed algorithm is compared with that of the existing centralised algorithms in terms of deadlock duration, message traffic and message size using simulation. Numerical results reveal that the performance of the proposed algorithm is equal or better than that of the existing algorithms. [ABSTRACT FROM PUBLISHER]

The rapid discovery of the contaminant source in a water distribution system (WDS) is vital for generating an efficient control strategy during a contamination event. An inverse problem can be constructed, given sensor measurements in a WDS, to identify the contaminant source characteristics by integrating a WDS simulation model with an optimisation method. However, this approach requires numerous compute-intensive simulation runs to evaluate potential solutions. This paper reports the findings of an investigation by introducing a hybrid method for the real-time characterisation of a contaminant source. This new method integrates a simulation-optimisation approach with a logistic regression and a local improvement method to expedite the convergence and possibly solve the problem quickly. The results of numerical experiments on two example WDS networks demonstrate the efficiency of the proposed hybrid method for contaminant source characterisation. Effects of various hybrid strategies on the algorithm performance are discussed. [ABSTRACT FROM AUTHOR]

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances. [ABSTRACT FROM PUBLISHER]

Beamforming with sparse constraint has shown important performance improvement. In this paper, a robust least squares constant modulus beamforming with sparse constraint is proposed. The proposed approach shows a faster convergence performance, lower sidelobe level, and better steady-state output signal-to-interference-plus-noise ratio (SINR) than that of the conventional linearly constrained least squares constant modulus algorithm, especially in the presence of mismatches between the actual and presumed steering vectors. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Graphics processing unit (GPU) is becoming a powerful computational tool in science and engineering. In this paper, different from previous molecular dynamics (MD) simulation with pair potentials and many-body potentials, two MD simulation algorithms implemented on a single GPU are presented to describe a special category of many-body potentials – bond order potentials used frequently in solid covalent materials, such as the Tersoff potentials for silicon crystals. The simulation results reveal that the performance of GPU implementations is apparently superior to their CPU counterpart. Furthermore, the proposed algorithms are generalised, transferable and scalable, and can be extended to the simulations with general many-body interactions such as Stillinger–Weber potential and so on. [ABSTRACT FROM PUBLISHER]

This paper presents an approach for assessing the accuracy of different frictional rolling contact theories. The main characteristic of the approach is that it takes a statistically oriented view. This yields a better insight into the behaviour of the methods in diverse circumstances (varying contact patch ellipticities, mixed longitudinal, lateral and spin creepages) than is obtained when only a small number of (basic) circumstances are used in the comparison. The range of contact parameters that occur for realistic vehicles and tracks are assessed using simulations with the Vampire vehicle system dynamics (VSD) package. This shows that larger values for the spin creepage occur rather frequently. Based on this, our approach is applied to typical cases for which railway VSD packages are used. The results show that particularly the USETAB approach but also FASTSIM give considerably better results than the linear theory, Vermeulen–Johnson, Shen–Hedrick–Elkins and Polach methods, when compared with the ‘complete theory’ of the CONTACT program. [ABSTRACT FROM PUBLISHER]

Based on a representation of a stochastic integral of Ornstein–Uhlenbeck (O–U) type, the exact simulation algorithm of the tempered stable O–U process is given in this paper. The algorithm employs the double rejection method and the general acceptance–rejection technique. The time complexity of the double rejection method is uniformly bounded over all values of the parameter. And the acceptance probability of the acceptance–rejection technique can be improved to as close to 1 as possible. Thus, the implementation of the algorithm is efficient. The performance of the simulation method is evidenced by some empirical results. [ABSTRACT FROM PUBLISHER]

This paper considers quantile regression models using an asymmetric Laplace distribution from a Bayesian point of view. We develop a simple and efficient Gibbs sampling algorithm for fitting the quantile regression model based on a location-scale mixture representation of the asymmetric Laplace distribution. It is shown that the resulting Gibbs sampler can be accomplished by sampling from either normal or generalized inverse Gaussian distribution. We also discuss some possible extensions of our approach, including the incorporation of a scale parameter, the use of double exponential prior, and a Bayesian analysis of Tobit quantile regression. The proposed methods are illustrated by both simulated and real data. [ABSTRACT FROM PUBLISHER]

Delay tolerant network (DTN) is a sparse wireless mobile network that does not guarantee a path between a source and a destination at any time. In DTN, one critical issue is to reliably deliver data with low latency. In an N-node network, naive forwarding approaches such as flooding and its derivatives make the routing cost very high ( ). Recently, an approach called delegation forwarding (DF) caught significant attention in the research community because it reduces the cost to while maintaining good performance. In this paper, we enhance the DF algorithm by proposing a probability delegation forwarding (PDF) that further reduces the cost to and a threshold-based probability delegation forwarding (TPDF) that closes the latency gap between DF and PDF. Simulation results show that both PDF and TPDF can achieve similar delivery ratio as DF at a lower cost if p is not too small. [ABSTRACT FROM AUTHOR]

Driving simulation aims at reproducing, within a safe and controlled environment, sensorial stimuli as close to those perceived during the actual drive as possible, in order to induce driving behaviour similar to the real one. This paper illustrates an activity carried out on the driving simulator Virtual Environment for Road Safety, bound for system performance optimisation while dealing with subjective and objective tyres evaluation in the field of on-centre manoeuvres. Such activity can be divided into two main steps. The first one, described herewith, has been focusing on platform motion algorithms tuning and has led to driving simulator objective validation within the on-centre range. Device capability of reproducing dynamics, worked out by the vehicle model, has been thoroughly examined. Simulator sensitivity to a few tyre parameters influencing vehicle lateral dynamics has been analysed too. The second step - calling for the support of experienced drivers - will pursue subjective validation. [ABSTRACT FROM AUTHOR]

Although backstepping control design approach has been widely utilised in many practical systems, little effort has been made in applying this useful method to train systems. The main purpose of this paper is to apply this popular control design technique to speed and position tracking control of high-speed trains. By integrating adaptive control with backstepping control, we develop a control scheme that is able to address not only the traction and braking dynamics ignored in most existing methods, but also the uncertain friction and aerodynamic drag forces arisen from uncertain resistance coefficients. As such, the resultant control algorithms are able to achieve high precision train position and speed tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we develop a new forecasting algorithm for value-at-risk (VaR) based on ARMA-GARCH (autoregressive moving average-generalized autoregressive conditional heteroskedastic) models whose innovations follow a Gaussian mixture distribution. For the parameter estimation, we employ the conditional least squares and quasi-maximum-likelihood estimator (QMLE) for ARMA and GARCH parameters, respectively. In particular, Gaussian mixture parameters are estimated based on the residuals obtained from the QMLE of GARCH parameters. Our algorithm provides a handy methodology, spending much less time in calculation than the existing resampling and bias-correction method developed in Hartz et al. [Accurate value-at-risk forecasting based on the normal-GARCH model, Comput. Stat. Data Anal. 50 (2006), pp. 3032-3052]. Through a simulation study and a real-data analysis, it is shown that our method provides an accurate VaR prediction. [ABSTRACT FROM AUTHOR]

Compared to the common monostatic synthetic aperture radar (SAR), the bistatic SAR data are more challenging to process because of their complicated flight geometry. Although several bistatic SAR image formation algorithms have been presented, most of them are only able to handle azimuth-invariant bistatic configuration where the transmitter and receiver platforms are moving in parallel tracks with identical velocities. This paper proposes an Omega-K algorithm to handle a general case of bistatic SAR data. The two-dimensional frequency spectrum expression derived by the method of series reversion is rewritten to a new form with explicit geometric significance. Based on this new frequency spectrum expression, the frequency mapping function can be derived by making use of the multivariable Taylor's theorem. After data mapping operation, the coupling between the range and azimuth can be eliminated, and the final focused image can be obtained using FFT technology. Numerical simulations are performed to validate the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the basic design parameters and propose a two-phase localization algorithm for full-body human locomotion tracking systems using ultra wideband (UWB) radios. The proposed localization is divided into two measurement phases namely, the initial and core phases. The initialization phase is based on the linear least-squares (LS) localization. The proposed initial localization phase has a localization accuracy of 0.247 mm. For core phase, we investigate the use of classical multidimensional scaling (C-MDS) localization and show that the achievable accuracy is approximately 0.47 mm (1 mm and sub-millimeter reported for current optical tracking systems). The reported accuracy in the literature for UWB-based systems is ≈ 400 mm. Thus, the proposed localization technique provides a substantial improvement over existing systems, which makes it suitable for accurate kinematic parameter measurement. Results presented for system performance and design parameters are investigated using simulations and actual measurements. Ultimately, the proposed system is suitable for taking accurate measurements and for tele-rehabilitation. [ABSTRACT FROM AUTHOR]