This paper presents the state identification study of 3D partial differential equations (PDEs) using the differential neural networks (DNNs) approximation. There are so many physical situations in applied mathematics ...
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This paper presents the state identification study of 3D partial differential equations (PDEs) using the differential neural networks (DNNs) approximation. There are so many physical situations in applied mathematics and engineering that can be described by PDEs;these models possess the disadvantage of having many sources of uncertainties around their mathematical representation. Moreover, to find the exact solutions of those uncertain PDEs is not a trivial task especially if the PDE is described in two or more dimensions. Given the continuous nature and the temporal evolution of these systems, differential neural networks are an attractive option as nonparametric identifiers capable of estimating a 3D distributed model. The adaptive laws for weights ensure the "practical stability" of the DNN trajectories to the parabolic three-dimensional (3D) PDE states. To verify the qualitative behavior of the suggested methodology, here a nonparametric modeling problem for a distributed parameter plant is analyzed.
In this paper, we conduct feasibility studies on the average delay space for Cloud computing, and we propose a heuristic method to control the vector of average delays, subject to predefined delay constraints. Our wor...
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ISBN:
(纸本)9781457720529
In this paper, we conduct feasibility studies on the average delay space for Cloud computing, and we propose a heuristic method to control the vector of average delays, subject to predefined delay constraints. Our work is strongly motivated by the fact that delay control plays a critical role to improve Service Level Agreements (SLA) between users and Cloud service providers, which is necessary for empowering online business. Specifically, our main contributions are two-fold: First, the feasible regions of various routing algorithms for the system's dispatcher are investigated in depth. Second, a simple heuristic algorithm is designed, to move the average delay point along the feasible direction until achieving the delay constraints. Average delay is dependent on multiple factors such as job size, inter-arrival time, flow rate, and the dispatching rules of the system. Therefore, we vary their distribution, parameters and routing rules to examine how the feasible regions move or change. After establishing the feasible delay space, then by moving along the feasible directions, we show that a simple heuristic algorithm can achieve the delay constraints for a two queue system.
To accurately represent a transmission line, the equivalent PI circuit is required. This representation is based on the distributed parameter line model and fully considers the fact that the parameters including imped...
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ISBN:
(纸本)9781467327275
To accurately represent a transmission line, the equivalent PI circuit is required. This representation is based on the distributed parameter line model and fully considers the fact that the parameters including impedance and admittance are uniformly distributed throughout the entire length of the line. For a single-circuit transmission line or a positive/negative sequence double-circuit line, its equivalent PI circuit based on the distributed parameter line model has been well established in the literature. This paper aims to provide the equivalent PI circuit parameters for the zero-sequence networks of a double-circuit line where there is a mutual coupling between the parallel lines. The derivation is based on the solution of the differential equations in the time-domain. Hyperbolic forms of the parameters of the equivalent PI circuit are resulted. A numerical example is utilized to demonstrate the application of the equivalent PI circuit parameters and compare with the nominal PI circuit parameters.
In this paper we propose using one of the stochastic methods - Probabilistic Collocation Method (PCM) to find simplified polynomial mapping between two uncertain Air-Traffic System (ATS) parameter data sets. These two...
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ISBN:
(纸本)9781457710957
In this paper we propose using one of the stochastic methods - Probabilistic Collocation Method (PCM) to find simplified polynomial mapping between two uncertain Air-Traffic System (ATS) parameter data sets. These two parameter sets can be two distinguished collection of measured parameters depicting various aspects of one specific air-traffic system, and the knowledge of parameters distribution is not a requirement. We show that PCM can be applied to air-traffic systems from immense systems like United States' National Air-space System (NAS), down-scale to middle-sized systems as New York City metro-area air-traffic system with combination of three major airports (JFK, EWR and LGA) or even smaller systems like Chicago O'Hare International Airport (ORD). Compared with commonly used direct polynomial fitting method, PCM has the advantages in both efficient calculation and high accuracy. Along with the mapping relation of PCM from historical parameter data sets, we applied such polynomial mapping relation to predict the future air-traffic within the same system. By comparing the predicted data with the real recorded or FACET simulated data, we have reached the conclusion that the PCM performs excellent in analyzing current data and predicting future value based on historical mapping formula. The capability of forecasting by applying PCM serves as one powerful tool in launching control on air-traffic system as well as managing the system in advance based on the known traffic data.
A gaze concurrence is a point in 3D where the gaze directions of two or more people intersect. It is a strong indicator of social saliency because the attention of the participating group is focused on that point. In ...
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ISBN:
(纸本)9781627480031
A gaze concurrence is a point in 3D where the gaze directions of two or more people intersect. It is a strong indicator of social saliency because the attention of the participating group is focused on that point. In scenes occupied by large groups of people, multiple concurrences may occur and transition over time. In this paper, we present a method to construct a 3D social saliency field and locate multiple gaze concurrences that occur in a social scene from videos taken by head-mounted cameras. We model the gaze as a cone-shaped distribution emanating from the center of the eyes, capturing the variation of eye-in-head motion. We calibrate the parameters of this distribution by exploiting the fixed relationship between the primary gaze ray and the head-mounted camera pose. The resulting gaze model enables us to build a social saliency field in 3D. We estimate the number and 3D locations of the gaze concurrences via provably convergent mode-seeking in the social saliency field. Our algorithm is applied to reconstruct multiple gaze concurrences in several real world scenes and evaluated quantitatively against motion-captured ground truth.
This paper presents a novel methodology for statistical detection of Least Significant Bits (LSB) matching steganography. It proposes to exploit a statistical model of natural images adjacent pixels difference. In thi...
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ISBN:
(纸本)9781467310680
This paper presents a novel methodology for statistical detection of Least Significant Bits (LSB) matching steganography. It proposes to exploit a statistical model of natural images adjacent pixels difference. In this paper, the detection problem is first addressed in a theoretical context when cover image parameters are known. The most powerful likelihood ratio test (LRT) is designed and its statistical performances are analytically expressed. Then, for a practical case of unknown image analysis, an estimation of distribution parameters is proposed to designed a test whose performance are also analytically established. Numerical results on a large image database shows the relevance of proposed methodology.
Sliding mode control problem of a class of Ito^ type partial differential equations with delay is probed. The variable structure controller is designed. The existence of motion of sliding mode is shown. And the charac...
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Sliding mode control problem of a class of Ito^ type partial differential equations with delay is probed. The variable structure controller is designed. The existence of motion of sliding mode is shown. And the character of invariance of sliding control system about uncertainty on the sliding switching surface and stability are analyzed.
In this study, highly accurate closed-form approximations to the probability density function of the sum of independent identically distributed (i.i.d.) generalised-K fading envelopes are derived. These approximations...
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In this study, highly accurate closed-form approximations to the probability density function of the sum of independent identically distributed (i.i.d.) generalised-K fading envelopes are derived. These approximations are valid for a wide range of values of the distribution parameters and number of summands. Based on the previously derived formulas, simple precise approximations for the outage probability and the average bit error probability of equal-gain combining receivers operating on i.i.d. generalised-K fading channels are proposed. Extensive numerically evaluating and computer simulation results are presented to demonstrate the proposed analysis.
We propose a classification algorithm that utilizes the alpha-stable distribution to model the texture features of synthetic aperture radar (SAR) images. The SAR image is first decomposed by stationary wavelet transfo...
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We propose a classification algorithm that utilizes the alpha-stable distribution to model the texture features of synthetic aperture radar (SAR) images. The SAR image is first decomposed by stationary wavelet transform (SWT). After that, the alpha-stable distribution is applied to model the high-frequency subband coefficients of the image at each decomposition scale. A regression-type method is then used to estimate the alpha-stable distribution parameters, which form a feature vector that fully describes the texture. Finally, a SAR image classification algorithm is derived by exploiting this feature vector based on the support vector machines (SVM) approach. Because different combinations of alpha-stable distribution parameters contribute to differences in classification precision, a multi-level SVM (MSVM) classification algorithm is also presented to address the issue. Experimental results indicate that the proposed SAR image classification algorithm is effective and the MSVM algorithm improves the classification performance. Moreover, our proposed algorithm has low computational cost as only a small number of the alpha-stable distribution parameters are processed.
This article presents a prelocalization approach of insulation faults affecting single-phase cables by using electrical measurements of voltage and current available in one substation. This approach is based on the th...
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This article presents a prelocalization approach of insulation faults affecting single-phase cables by using electrical measurements of voltage and current available in one substation. This approach is based on the theory of distributed parameters for modeling the faults to the ground. The specificity of this approach is the introduction of a resistance modeling the sheath-ground insulation allowing us to study the various types of faults to the ground (frankly and resistive). The fault distance and resistances are determined by two methods numerical and analytical. Many fault scenarios applied to the 150 kV underground cable connecting HTB sub-stations of Tyna-Taparoura-Sidimansour in Sfax, show a good agreement between the two methods. A simulation of the global system using the software Simulink-SimPowerSystems of Matlab is carried out giving us the voltages and currents on the source side necessary to the execution of the developed methods and the validation of the obtained results. (C) 2011 Elsevier B.V. All rights reserved.
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