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Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. [ABSTRACT FROM AUTHOR]

By simulating the change process of the inventory of scientific papers according to a mathematical model of the publishing process, we find that publication delay would cause statistical error of the scientific paper output indicator, i.e. the quantity of published papers. Based on a simulation model and the average publication delay, we construct an optimization algorithm of the actual scientific paper output using a nonlinear least squares algorithm and validate its accuracy. To simplify the solution process, we propose an approximate algorithm of the actual scientific paper output indicator which would help science and technology managers practically deduce an approximation of the actual indicator. This has implications for strategy decision making and allocation of resources for science and technology research by policy makers. [ABSTRACT FROM AUTHOR]

It is vital to consider acoustic scattering when using geometrical acoustic simulation techniques, such as ray tracing. However, there are few methods for modelling scattering, and most rely on strong assumptions of uniformity on the distribution of scattered energy. In this paper, a model for directional scattering in ray tracers is presented. The model is based on an idealized model of a 1D scatterer, which is then used to extend the most commonly used scattering algorithm in ray tracers today. The developed algorithm is implemented in a ray tracer and tested to evaluate its performance compared to existing methods. It is found that the directional scattering algorithm can be used to replicate measured effects on room acoustic parameters caused by changes in the orientation of 1D scatterers. [ABSTRACT FROM AUTHOR]

Navigation and positioning is a new growth point of wireless services. And seamless positioning is the current development trend of navigation and positioning services. In view of the problems that dynamic handover cannot be performed during site movement, STA only selects the optimal AP according to the indication of received signal strength, and the handover delay is too long. This paper proposes a research on indoor and outdoor seamless positioning technology based on artificial intelligence and intelligent switching algorithm. The purpose is to study the influence of reducing the positioning data with too large error on the final positioning result. The method of this paper is to propose an intelligent switching algorithm and then discuss the research status and development direction of indoor positioning technology and outdoor positioning technology, respectively, and point out the switching methods between them. The role of these methods is to analyze the current situation of indoor and outdoor navigation technology, especially the development route of seamless positioning technology. It determines the strategy of integrating heterogeneous positioning systems to build a seamless positioning system to maximize the use of existing positioning system resources. This paper studies the design and implementation of the seamless positioning system through the simulation experiment of the intelligent switching algorithm and finally tests the system through the experimental vehicle. The online experiment results show that the system can achieve high positioning accuracy in indoor and outdoor environments, especially at its junction, and the positioning errors in all directions are within 0.2 m. [ABSTRACT FROM AUTHOR]

Recent increase of spatial resolution for satellite instruments has it made feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (Level 2) onto a longitude-latitude grid (Level 3). The algorithm is designed for the Ozone Monitoring Instrument (OMI) and can be employed easily to similar instruments, for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI). Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrization of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly developed gridding algorithm improves regional trace gas maps; its application could be very helpful for the study of satellite-derived trace gas distributions. [ABSTRACT FROM AUTHOR]

An analytical solution of the Boussinesq equations for the motion of a viscous stably stratified fluid driven by a surface thermal forcing with large horizontal gradients (step changes) is obtained. The solution can be used to verify that computer codes for Boussinesq fluid system simulations are free of errors in formulation of wall boundary conditions, and to evaluate the relative performances of competing numerical algorithms. Because the solution pertains to flows driven by a surface thermal forcing, one of its main applications may be for testing the no-slip, impermeable wall boundary conditions for the pressure Poisson equation. Examples of such tests are presented. [ABSTRACT FROM AUTHOR]

We present a new algorithm for satellite retrievals of the atmospheric water vapor column in the blue spectral range. The water vapor absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations is systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapor retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapor retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, over ocean the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times) higher ocean albedo in the blue. Water vapor retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring instrument (OMI). We investigated details of the water vapor retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2) and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapor column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions like e.g. Sentinel 4 and 5 [ABSTRACT FROM AUTHOR]

This paper does some research and discussion on the finite element analysis of a building structure, especially the computer graphics simulation method in building structure simulation. Moreover, with the support of BIM technology and computer finite element simulation technology, this paper constructs a building structure simulation system and analyzes the building structure simulation system based on actual conditions such as building structure and stress load. In addition, this paper improves the traditional structural analysis algorithm and designs experiments to evaluate the effect of the method proposed in this paper and analyze the data in the form of simulation to compare the validity of the test results. Finally, an experiment is designed to evaluate the data processing capability of the test system in this paper. The experimental analysis results verify the effectiveness of the method in this paper, which can provide relevant theoretical references for subsequent building structure simulation. [ABSTRACT FROM AUTHOR]

The quality of collision detection algorithm directly affects the performance of the whole simulation system. To address the low efficiency and low accuracy in detecting the collisions of flexible cloths in virtual environments, this paper proposes an oriented bounding box (OBB) algorithm with a simplified model, tree structure for a root-node double bounding box, and continuous collision detection algorithm incorporating an OpenNN-based neural network optimization. First, for objects interacting with the cloths with more complex modeling, the model is simplified with a surface simplification algorithm based on the quadric error metrics, and the simplified model is used to construct an OBB. Second, a bounding box technique commonly used for collision detection is improved, and a root-node double bounding box algorithm is proposed to reduce the construction time for the bounding box. Finally, neural networks are used to optimize the continuous collision detection algorithm, as neural networks can efficiently process large amounts of data and remove disjoint collision pairs. An experiment shows that the construction of an OBB using the simplified model is almost identical to that of the original model, but the taken to construct the OBB is reduced by a factor of approximately 2.7. For the same cloth, it takes 5.51%–11.32% less time to run the root-node double bounding box algorithm than the traditional-hybrid bounding box algorithm. With an average removal rate nearly identical to that of the traditional filtering method, the elapsed time is reduced by 7%–11% by using the continuous collision detection algorithm based on an OpenNN neural network optimization. The simulation results are realistic and in line with the requirements for real-time cloth simulations. [ABSTRACT FROM AUTHOR]

This paper introduces a novel and innovative approach to simulating random variates from two distinct probability distributions, namely the neutrosophic uniform distribution and the neutrosophic Weibull distribution. The primary objective of this research is to present a cutting-edge methodology for generating random variates by leveraging the accept-reject simulation method, particularly in the context of managing and addressing uncertainty. In addition to introducing the simulation methodology, this work will also provide comprehensive algorithms tailored to these proposed methods. These algorithms are essential for implementing the simulation techniques and will be instrumental in their practical applications. Furthermore, this study aims to explore the relationship between the level of indeterminacy and the resulting random variates. By investigating how varying degrees of indeterminacy impact random variates, we gain valuable insights into the dynamics of these distributions under different uncertainty conditions. Preliminary results suggest that random variates exhibit a trend of decreasing as indeterminacy levels increase, shedding light on the intriguing interplay between indeterminacy and random variate generation. [ABSTRACT FROM AUTHOR]

The aim of this systematic review is to synthesize and analyze interactive collaborative work in the virtual economy of the metaverse. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout May 2022, with search terms including "metaverse interactive environment" + "virtual employee engagement and immersive workspaces," "wearable augmented reality technology," and "spatial data mining and simulation modeling algorithms." As we analyzed research published in 2022, only 158 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 30, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR. [ABSTRACT FROM AUTHOR]

Throughout the world, the reliability-based approach to safety design of aircraft systems is quite mature and widely used. However, there are still shortcomings in the reliability-based aircraft system safety analysis method. It cannot dynamically analyze the accident evolution process and lack consideration of the complex situation of multifactor coupling. On the basis of the original aircraft system safety analysis method, this paper innovatively proposes a functional hazard analysis (FHA) method based on the analytic hierarchy process (AHP) and multifactor fuzzy comprehensive assessment (FCA). The purpose is to improve the objectivity and quantification of the FHA method in the safety design of aircraft systems. At the same time, in the terminal airworthiness verification, this paper proposes a repeatable and controllable virtual test flight verification method, which aims to reduce the cost and cycle of the terminal airworthiness verification and expand the coverage of the envelope verification. Finally, combined with the clauses in MIL-HDBK-516B, a case calculation is carried out to verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

In the light of the problems that exist in the current cutting algorithms: first, the number of tetrahedron elements increases as the cutting goes on, which leads to the decrease of the algorithm efficiency. Second, the topology structure is constantly updated during the cutting process, which leads to the stutter phenomenon in cutting display. In this paper, a cutting simulation implementation method based on transient display and delay adjustment strategy is proposed. Firstly, the feature points in the original path are screened by the feature criterion function, and the feature path is established. Then, by using the concept of minimum sum of square defined in this paper, the optimal path of the separation is found with the help of feature path points, and the pseudo effect of cutting is directly displayed by designing the transient display module. The delay adjustment is carried out in the cutting gap, and the topology separation in the delay adjustment is implemented by the node offset spread algorithm and the duplicate removal process with timeliness. Finally, the advantages and feasibility of the cutting algorithm proposed in this paper are verified by practical tests. The test results show that the transient display algorithm proposed in this paper takes about 20 ms. With the number of triangular patches increasing, the growth rate of transient display time remains low. The cutting simulation is implemented by using transient display and delay adjustment strategy, which greatly improves the simulation efficiency. [ABSTRACT FROM AUTHOR]

In this paper, the conceptualization of a control hardware architecture aimed to the implementation of integer- and fractional-order identification and control algorithms is presented. The proposed hardware architecture combines the capability of implementing PC-based control applications with embedded applications on microprocessor- and FPGA-based real-time targets. In this work, the potential advantages of this hardware architecture over other available alternatives are discussed from different perspectives. The experimental prototype that has been designed and built to evaluate the control hardware architecture proposed in this work is also described in detail. The thermal-based process taking place in the prototype is characterized for being reconfigurable and exhibiting fractional behaviour, which results in a suitable equipment for the purpose of fractional-order identification and control. In order to demonstrate the applicability and effectiveness of the proposed control hardware architecture, integer- and fractional-order identification and control algorithms implemented in various control technologies have been applied to the temperature-based experimental prototype described before. Detailed discussion about results and identification and control issues are provided. The main contribution of this work is to provide an efficient and practical hardware architecture for implementing fractional-order identification and control algorithms in different control technologies, helping to bridge the gap between real-time hardware solutions and software-based simulations of fractional-order systems and controllers. Finally, some conclusions and concluding remarks are offered in the industrial context. [ABSTRACT FROM AUTHOR]

The article discusses the mathematical models used to analyze and simulate the U.S. kidney transplant system. It focuses on algorithms for matching donors to kidneys. It mentions that kidneys became available when a person dies and must be transplanted quickly. A proper scheme should be developed to find a compatible recipient for the kidney. The article also discusses using a bipartite graph to pair off living donors and recipients. It describes the problem of matching kidney donors and recipients as dynamic. It also analyzes the feasibility and effectiveness of the kidney paired donation model.

A new method of the stochastic simulation algorithm (SSA), named the Hashing-Leaping method (HLM), for exact simulations of a class of Markov jump processes, is presented in this paper. The HLM has a conditional constant computational cost per event, which is independent of the number of exponential clocks in the Markov process. The main idea of the HLM is to repeatedly implement a hash-table-like bucket sort algorithm for all times of occurrence covered by a time step with length t. This paper serves as an introduction to this new SSA method. We introduce the method, demonstrate its implementation, analyze its properties, and compare its performance with three other commonly used SSA methods in four examples. Our performance tests and CPU operation statistics show certain advantages of the HLM for large scale problems. [ABSTRACT FROM AUTHOR]

The three-dimensional intelligent simulation of image art design is an important means of current image art design, which is affected by many factors. The traditional 3D intelligent simulation technology has certain defects, which leads to certain defects in 3D artwork. This paper builds a three-dimensional art design system based on dynamic image detection and genetic algorithm. The system simulates the actual dehazing method, and this paper proposes a dehazing algorithm suitable for this system and proposes to use bilateral filtering instead of median filtering. Because bilateral filtering has good edge retention, it can eliminate the blockiness caused by median filtering. Moreover, this paper uses FMM (Fast Marching Method) algorithm to repair the image. In order to verify the performance of the model, this paper conducts quantitative evaluation through system simulation and user satisfaction survey methods. The research results show that the method proposed in this paper has a certain effect and can be applied to practice. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of maximizing the minimum power gain in a wide main lobe for an array antenna. To obtain the desired power gain pattern, current literatures solve the problem known as shaped beam pattern synthesis (SBPS) by setting the beam pattern expression as the cost function. The power gain in a certain direction of the array antenna is comprehensively decided by the array radiated power density and the total radiated power. Both these two parameters are affected by the selection of array elements’ weights. However, the SBPS-based methods do not take the total radiated power into account. Therefore, the SBPS-based methods cannot obtain the power gain pattern directly, and the optimal power gain pattern, consequently, cannot be guaranteed. To overcome this deficiency, this paper maximizes the minimum power gain in the desired wide main lobe by directly setting the power gain expression as the cost function. Aiming at optimizing the cost function, this paper first sets up a power gain optimization problem which has concave form. Termed this optimization problem as the power gain pattern synthesis (PGPS) problem. The concave PGPS problem is then converted to a series of convex subproblems and an iterative algorithm is proposed to solve it efficiently. Solution to the PGPS problem is proven to be able to achieve higher minimum power gain in a desired wide main lobe than the results from the SBPS-based algorithms. Simulations are carried out with both linear array antenna and planar array antenna. Comparisons with the existed SBPS-based algorithms validate the effectiveness and advantages of the proposed PGPS-based algorithm. In addition, further improvement on suppressing the sidelobe level for the PGPS problem is discussed. [ABSTRACT FROM AUTHOR]

The abnormal rise in contact temperature in switchgear may lead to overheating or even explosion. It is necessary to monitor the rise in real contact temperature to ensure the safety and stability of switchgear. The accurate measurement of real contact temperature is still a problem, and the continuous state of switchgear cannot be assessed accurately by the temperature monitor. In this paper, a particular installation scheme of temperature sensor is put forward and a calculation algorithm for temperature rise of tulip contacts by the measured temperature of bus bar in real time based on artificial neural network (ANN) is established. An electromagnetic-thermal-fluid coupled simulation model for 10-kV/4000-A switchgears was built, and the thermal characteristic was studied taking the influential factors such as load current, ambient temperature, and contact resistance into consideration. The effectiveness of simulation model is discussed by the comparison to temperature rise experiment. Then, an ANN with three layers of structure is established to calculate the temperature of tulip contacts. The sensitivity and accuracy of network are calculated and verified. The results of this paper may provide a novel method for the monitor of switchgear temperature and assess continuous condition of high-current switchgear. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical control architecture for the regulation of frequency and nodal voltages of a microgrid in islanded operation. Considering systems with both dispatchable and nondispatchable generation, as well as noncontrollable loads, the suggested approach allows to coordinate the MG devices in order to maintain the network variables inside the desired operational ranges. Moreover, the proposed algorithm, based on model predictive control, introduces the possibility to define different resource management strategies while taking into account the constraints of the available devices. Simulation examples are reported and described in the final part of this paper. [ABSTRACT FROM AUTHOR]

Data mining is a process of digging data sets from large data-bases, especially for use to improve the operation efficiency of a company, institution, or an organization. With the increasing cases of cyber and other computer-related crimes, computer and mobile data security has become a matter of concern, secure, and non-contaminated data is very important for data mining to improve the performance of a system. This paper proposes a system framework that is able to collect information and then be able to generate alerts in real time. The proposed scheme is then simulated using the K-means clustering algorithm, which is one of the most popular clustering algorithms to determine the efficiency and the accuracy of the proposed scheme. The paper concludes by proposing further improvements to be undertaken on the proposed system to improve its efficiency and accuracy. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Lift-off variation causes errors in the eddy current thickness measurements of metallic plates. In this paper, we have developed an algorithm that can compensate for this variation and produce an index that is linked to the thickness, but is virtually independent of lift-off. This index, termed as the compensated peak frequency, can be obtained from the measured multifrequency inductance spectral data using the algorithm we developed in this paper. This method has been derived through mathematical manipulation and verified by both the simulation and experimental data. Accuracy in the thickness measurements at different lift-offs proved to be within 2%. [ABSTRACT FROM AUTHOR]

A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that combines conditional simulation techniques with nonparametric estimations of the trend and the variability. The nonparametric local linear estimator, considering a bandwidth matrix selected by a method that takes the spatial dependence into account, is used to estimate the trend. The variability is modeled estimating the conditional variance and the variogram from corrected residuals to avoid the biasses. The proposed method allows to obtain estimates of the conditional exceedance risk in non-observed spatial locations. The performance of the approach is analyzed by simulation and illustrated with the application to a real data set of precipitations in the USA.Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5MWreference wind turbine and International Energy Agency 15MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10% compared to the NREL 5MWreference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30% when using the platform feedback routine instead of a more traditional low-bandwidth controller. [ABSTRACT FROM AUTHOR]

Recent mobile applications have required high data rate. In metropolitan areas where data traffic is higher than other areas, heterogeneous networks (HetNet) are used to meet the traffic demand (Hoadley and Maveddat in IEEE Commun Mag 19(2):4-5, 2012). The HetNet has several low power base stations or remote radio heads in a macro cell coverage and sometimes coordinates the low power transmission points forming virtual multiple-input and multiple-output system. In this paper, inter-relay interference (IRI) cancellation for two-path relay system is considered. In existing schemes, IRI cancellation is performed at a destination node but proposed method performs the cancellation at relay nodes to reduce the complexity of detection algorithm for the destination node. Simulation results also show that the method of this paper achieves better BER performance than the existing schemes. [ABSTRACT FROM AUTHOR]

Fault diagnosis and safety analysis of an aero-engine have attracted more and more attention in modern society, whose safety directly affects the flight safety of an aircraft. In this paper, the problem concerning sensor fault diagnosis is investigated for an aero-engine during the whole flight process. Considering that the aero-engine is always working in different status through the whole flight process, a flight status division-based sensor fault diagnosis method is presented to improve fault diagnosis precision for the aero-engine. First, aero-engine status is partitioned according to normal sensor data during the whole flight process through the clustering algorithm. Based on that, a diagnosis model is built for each status using the principal component analysis algorithm. Finally, the sensors are monitored using the built diagnosis models by identifying the aero-engine status. The simulation result illustrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

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]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved. [ABSTRACT FROM AUTHOR]

In this paper, a coupled interaction matrix is proposed to describe the interactions between line outages and the load shed at buses. The coupled interaction matrix is effectively estimated by the Expectation Maximization algorithm. A highly probabilistic coupled interaction model is further proposed to efficiently generate cascades with both line outages and the load shed based on the coupled interaction matrix and the distribution of initial outages. To mitigate cascading failures, critical links are identified based on the coupled interaction matrix by calculating a comprehensive severity index that considers the consequences of both line outages and the load shed. Simulation results on the IEEE 300-bus system verify the effectiveness of the proposed approach. The cascades generated from the coupled interaction model match the statistics of the original cascades very well. The identified critical links based on the comprehensive severity index enable a proper tradeoff between reducing line outages and reducing the load shed, leading to a better mitigation effect than only considering either line outages or the load shed. [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 deals with a modified technique for the recognition of single stage and multiple power quality (PQ) disturbances. An algorithm based on Stockwell's transform and artificial neural network-based classifier and a rule-based decision tree is proposed in this paper. The analysis and classification of single stage PQ disturbances consisting of both events and variations such as sag, swell, interruption, harmonics, transients, notch, spike, and flicker are presented. Moreover, the proposed algorithm is also applied on multiple PQ disturbances such as harmonics with sag, swell, flicker, and interruption. A database of these PQ disturbances based on IEEE-1159 standard is generated in MATLAB for simulation studies. The proposed algorithm extracts significant features of various PQ disturbances using S-transform, which are used as input to this hybrid classifier for the classification of PQ disturbances. Satisfactory results of effective recognition and classification of PQ disturbances are obtained with the proposed algorithm. Finally, the proposed method is also implemented on real-time PQ events acquired in a laboratory to confirm the validity of this algorithm in practical conditions. [ABSTRACT FROM PUBLISHER]

Mixed models: Models allowing for continuous heterogeneity by assuming that value of one or more parameters follow a specified distribution have become increasingly popular. This is known as ‘mixing’ parameters, and it is standard practice by researchers - and the default option in many statistical programs - to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halton draws). Problem 1: Inconsistent LR tests due to asymmetric draws:: This paper shows that when the estimated likelihood functions depend on standard deviations of mixed parameters this practice is very likely to cause misleading test results for the number of draws usually used today. The paper illustrates that increasing the number of draws is a very inefficient solution strategy requiring very large numbers of draws to ensure against misleading test statistics. The main conclusion of this paper is that the problem can be solved completely by using fully antithetic draws, and that using one dimensionally antithetic draws is not enough to solve the problem. Problem 2: Maintaining the correct dimensions when reducing the mixing distribution:: A second point of the paper is that even when fully antithetic draws are used, models reducing the dimension of the mixing distribution must replicate the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood. Again this is not standard in research or statistical programs. The paper therefore recommends using fully antithetic draws replicating the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood and that this should become the default option in statistical programs. JEL classification: C15; C25. [ABSTRACT FROM AUTHOR]

This paper describes a new method of power-grid signal variation measurement, consisting of a demodulation algorithm and a set of measures (indices). The measures that will be presented are the abstract functionals, operating on the complex envelope of a signal. This paper presents a demodulation algorithm, definitions of proposed functionals, results of simulations, as well as laboratory experiments. [ABSTRACT FROM AUTHOR]

The service performance and life of the aero-engine are directly affected by the blade machining accuracy. In the end milling of the flexible blade, the profile tolerance would usually be violated by the deflection errors induced by excessive static deformations under the action of milling force. In order to predict the blade deflection errors, this paper presents an iterative algorithm considering the coupling relationship between milling force and elastic deformation based on the milling finite element simulation model. Then a novel multipoint rod-shaped auxiliary support technology is proposed to suppress the blade deflection errors. Taking the influence of layout parameters on blade deflection errors into account, the layout of auxiliary support is optimized by a genetic algorithm. To verify the effectiveness of the proposed method, an auxiliary support mechanism is designed and manufactured, and the deflection errors suppression experiment is implemented. The measured results show that the prediction error of blade maximum deflection is 17.6%. Furthermore, the blade average deflection error on two measured curves reduces from 45.88 μm to 24.39 μm with the support of the designed mechanism. Thus, this auxiliary support mechanism and layout optimization method can achieve higher accuracy in blade milling. [ABSTRACT FROM AUTHOR]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved. [ABSTRACT FROM AUTHOR]

Dynamic development of Programmable Logic Controller (PLC) technology and Supervisory Control and Data Acquisition (SCADA) software has resulted in their widespread usage in integrated systems of automation, becoming one of the main directions of ship automation. This change justifies the need to improve the training of future crews on simulators built with the use of PLC and SCADA technologies. This paper presents a simulator prototype for selective processes of a main-propulsion boiler's fuel-gas-line nitrogenpurging system, applied in LNG (liquefied natural gas) ships. Control algorithms and appropriateschematic diagrams of the LNG fuel system of these processes were also presented. A Versa Max Micro-series PLC and an InTouch 9.0 PL SCADA software were applied in construction of the simulator. As a result of simulations, a visualisation of different states of fuel line in the form of screenshots was included. Finally, the paper contains a concept for simulator development based on hardware (sensors and actuators) without significant changes in existing software; further development will provide the simulator with more similarities to a real ship system. [ABSTRACT FROM AUTHOR]

Shamir's secret sharing scheme is an effective way to distribute secret to a group of shareholders. The security of the unprotected sharing scheme, however, can be easily broken by cheaters or attackers who maliciously feed incorrect shares during the secret recovery stage or inject faults into hardware computing the secret. In this paper, we propose cheater detection and identification schemes based on robust and algebraic manipulation detection (AMD) codes and m-disjunct matrices (superimposed codes). We present the constructions of codes for cheater detection and identification and describe how the cheater identification problem can be related to the classic group testing algorithms based on m-disjunct matrices. Simulation and synthesis results show that the proposed architecture can improve the security level significantly even under strong cheating attack models with reasonable area and timing overheads. [ABSTRACT FROM PUBLISHER]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved [ABSTRACT FROM AUTHOR]

In this paper, we establish a framework for enabling ultra-reliable and low-latency communications in the control and non-payload communications (CNPC) links of the unmanned aerial vehicle (UAV) communication systems. We first derive the available range of the CNPC links between UAVs and a ground control station. The available range is defined as the maximal horizontal communication distance within which the round-trip delay and the overall packet loss probability can be ensured with a required probability. To exploit the macro-diversity gain of the distributed multi-antenna systems (DAS) and the array gain of the centralized multi-antenna systems (CAS), we consider a modified DAS (M-DAS), where the ground control station is equipped with the distributed access points (APs), and each AP can have multiple antennas. We then show that the available range can be maximized by judiciously optimizing the altitude of UAVs, the duration of the uplink and downlink phases, and the antenna configuration. To solve the non-convex problem, we propose an algorithm that can converge to the optimal solution in DAS and CAS, and then extend it into more general M-DAS. The simulation and numerical results validate our analysis and show that the available range of M-DAS can be significantly larger than those of the DAS and CAS. [ABSTRACT FROM AUTHOR]

To make agents' route decision-making behaviours as real as possible, this paper proposes a layered navigation algorithm, emphasizing the coordinating of the global route planning at strategic level and the local route planning at tactical level. Specifically, by an improved visibility graph method, the global route is firstly generated based on static environment map. Then, a new local route planning (LRP) based on dynamic local environment is activated for multipath selection to allow pedestrian to respond changes at a real-time sense. In particular, the LRP model is developed on the basis of a passenger's psychological motivation. The pedestrians' individual preferences and the uncertainties existing in the process of evaluation and choice are fully considered. The suitable local path can be generated according to an estimated passing time. The LRP model is applied to the choice of ticket gates at a subway station, and the behaviours of gate choosing and rechoosing are investigated. By utilizing C++, the layered navigation algorithm is implemented. The simulation results exhibit agents' tendency to avoid congestion, which is often observed in real crowds. [ABSTRACT FROM AUTHOR]

The multimode power-split architecture for hybrid electric vehicle (HEV) powertrains is generally known for the complexity of its operation. This paper first addresses the challenge of developing an automated on-line near-optimal control strategy for these systems. Particularly, a machine learning logic based on supervised learning is developed for on-line selection of the HEV operating mode, thus the particular set of clutches to be engaged. An efficiency-based approach is then adopted to determine the optimal power-split between powertrain components. Later, the developed strategy finds integration in an optimal design methodology for multimode power-split HEVs considering the effectiveness and ease of on-line controllability. The obtained results are compared with the ones by the traditional HEV design methodology that only considers off-line energy management. The illustrated design methodology with on-line control reveals efficient at identifying the multimode HEV design that demonstrates optimal predicted fuel economy values and ease of on-line controllability simultaneously. Results suggest that the HEV design optimization procedure may produce different outcomes and demonstrate more effective when the evaluation of the on-line controlled operation is integrated. [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]

As Vehicular Ad hoc Network (VANET) features random topology and accommodates freely connected nodes, it is important that the cooperation among the nodes exists. This paper proposes a trust model called Implicit Web of Trust in VANET (IWOT-V) to reason out the trustworthiness of vehicles. Such that untrusted nodes can be identified and avoided when we make a decision regarding whom to follow or cooperate with. Furthermore, the performance of Cooperative Intelligent Transport System (C-ITS) applications improves. The idea of IWOT-V is mainly inspired by web page ranking algorithms such as PageRank. Although there does not exist explicit link structure in VANET because of random topology and dynamic connections, social trust relationship among vehicles exists and an implicit web of trust can be derived. To accomplish the derivation, two algorithms are presented, i.e., BayesTrust and VehicleRank. They are responsible for deriving the local and global trust relationships, respectively. The simulation results show that IWOT-V can accurately identify trusted and untrusted nodes if enough local trust information is collected. The performance of IWOT-V affected by five threat models is demonstrated, and the related discussions are also given. [ABSTRACT FROM AUTHOR]

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

The problem we are trying to solve in this paper is the authenticity identification of speaker digital recording data. As an important basis of the judicial identification, it is crucial to ensure the authenticity of digital recording data. A large number of solutions have been proposed to address the problem. However, classic methods are usually based on logical symbol rather than the physical detection of energy or phase, and these solutions show drawbacks in terms of identification inefficiency, algorithm instability and heavy time overhead. In this paper, we propose to utilize the quantum theory to address the problem. Any tampering operation for digital recording data can lead to the change of charge in the memory, and it can utilize the subtle change to implement the identification. First, we analyze the quantum nature of storage and investigate to extract the transmittance of speech signal as the characteristic value through quantum tunneling theory. Second, aiming at the characteristics of speech signal, we utilize the transmittance to define the rotation angle step function and propose an improved quantum genetic algorithm to detect the change of phase. The proposed method achieves the authenticity identification based on phase detection. The results obtained in this research include the problem can be addressed by phase detection solution based on quantum genetic algorithm, and it shows performance benefits compared with existing solutions by simulation experiment. It is not only theoretically but also practically feasible to realize authenticity identification of speak digital recording data. [ABSTRACT FROM AUTHOR]

Community detection is significative in the complex network. This paper focuses on community detection based on clustering algorithms. We tend to find out the central nodes of the communities by centrality algorithms. Firstly, we define the distance between nodes using similarity. Then, a new centrality measuring the local density of nodes is put forward. Combining the independence of the centrality, the nodes in the network can be divided into four classes. Leveraging the product of centrality and independence, the central nodes in the network are easily identified. We also find that we can distinguish bridge nodes from central nodes using centrality and independence. This research designs a community detection algorithm combining centrality and independence. Simulation results reveal that our centrality is more effective than existing centralities in measuring local density and identifying community centers. Compared with other community detection algorithms, results prove the effectiveness of our algorithm. This paper just shows one application of independence of the centrality. There may be more useful applications of it. [ABSTRACT FROM AUTHOR]