Classical applications of controlengineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are...
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In this paper we consider optimal parameter estimation with a constrained packet transmission rate. Due to the limited battery power and the traffic congestion over a large sensor network, each sensor is required to d...
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ISBN:
(纸本)9781479978878
In this paper we consider optimal parameter estimation with a constrained packet transmission rate. Due to the limited battery power and the traffic congestion over a large sensor network, each sensor is required to discard some packets and save transmission times. We propose a packet-driven sensor scheduling policy such that the sensor transmits only the important measurements to the estimator. Unlike the existing deterministic scheduler in [1], our stochastic packet scheduling is novelly designed to maintain the computational simplicity of the resulting maximum-likelihood estimator (MLE). This results in a nice feature that the MLE is still able to be recursively computed in a closed form, and the Cramer-Rao lower bound (CRLB) can be explicitly evaluated. Moreover, an optimization problem is formulated and solved to obtain the optimal parameters of the scheduling policy under which the estimation performance is comparable to the standard MLE (with full measurements) even with a moderate transmission rate. Numerical simulations are included to show the effectiveness.
This paper is the third in a series that investigates the electrostatic discharge (ESD)-related voltages and risks in data centers. This paper analyzes the risk of damage or upset under the following environmental con...
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In this paper, an approach is proposed for planning distribution networks in which the placement of distribution transformer is optimally planned. The size, number, and placement of distribution transformers are optim...
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ISBN:
(纸本)9781467380416
In this paper, an approach is proposed for planning distribution networks in which the placement of distribution transformer is optimally planned. The size, number, and placement of distribution transformers are optimally determined in order to improve system reliability and to minimize the losses under load growth. An objective function is constituted, composed of the investment cost, maintenance cost, loss cost, and reliability cost. The reliability worth is not usually considered in the optimization of the distribution substation placement. However, it may be effective on the planning problem. The proposed approach is applied to a test system consisting of 42 electric load points. It is observed that the considering reliability in the planning approach reduces the total cost of the distribution transformer placement. However, the associated investment cost is increased but the reliability cost is more decreased.
Face gender recognition is a very challenging problem in computer vision, which plays an important role in many visual applications. In this paper, we present a framework that combines the unsupervised dictionary lear...
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ISBN:
(纸本)9781467395885
Face gender recognition is a very challenging problem in computer vision, which plays an important role in many visual applications. In this paper, we present a framework that combines the unsupervised dictionary learning and supervised classifier training together to this gender recognition problem. We firstly apply sparse nonnegative matrix factorization (sparse NMF) to learn intrinsic part-based dictionary from face images in an unsupervised manner. After that we encode all the data by the learned dictionary, and train a SVM or logistic regression classifier in a supervised manner on those representations. Our experimental results show that the learned dictionaries by sparse NMF can not only capture meaningful features from the faces, but also boost the performance of the subsequent classifier in terms of classification accuracies and speeds.
Accurate and robust mobile robot localization is very important in many robot applications. Monte Carlo localization (MCL) is one of the robust probabilistic solutions to robot localization problems. The sensor model ...
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ISBN:
(纸本)9789897580406
Accurate and robust mobile robot localization is very important in many robot applications. Monte Carlo localization (MCL) is one of the robust probabilistic solutions to robot localization problems. The sensor model used in MCL directly influence the accuracy and robustness of the pose estimation process. The classical beam models assumes independent noise in each individual measurement beam at the same scan. In practice, the noise in adjacent beams maybe largely correlated. This will result in peaks in the likelihood measurement function. These peaks leads to incorrect particles distribution in the MCL. In this research, an adaptive sub-sampling of the measurements is proposed to reduce the peaks in the likelihood function. The sampling is based on the complete scan analysis. The specified measurement is accepted or not based on the relative distance to other points in the 2D point cloud. The proposed technique has been implemented in ROS and stage simulator. The result shows that selecting suitable value of distance between accepted scans can improve the localization error and reduce the required computations effectively.
The paper is dealing with an analysis of behavior of biologic tissue in interaction with a pulsed magnetic field (a magnetic field commonly used within investigations and treatments, but which can also occur by accide...
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The paper is dealing with an analysis of behavior of biologic tissue in interaction with a pulsed magnetic field (a magnetic field commonly used within investigations and treatments, but which can also occur by accident in electric equipments requiring continuous alteration of running energy parameters). In this interaction, the essential feature pointed out in the paper is that of a major influence of extracellular environment of biologic tissue. The analysis is being performed within the theory of electric circuits by using the electric model of cell membrane. As far the extracellular environment is concerned, it was modelled both as conductive and semiconductive environment to visualize the importance of its characteristics on membrane cell polarization and depolarization phenomena. The analysis has been performed using PSIM software environment by reducing the biologic tissue to the size of two cells and the extracellular environment between them, for this purpose.
We study the formation of short-term interest rates in the interbank lending market where banks are modeled as agents with bounded rationality. We propose a novel model which is based on bilateral contracts between ri...
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ISBN:
(纸本)9781479917730
We study the formation of short-term interest rates in the interbank lending market where banks are modeled as agents with bounded rationality. We propose a novel model which is based on bilateral contracts between risk-neutral profit-maximizing agents. To render the model tractable for large financial networks, we assume that banks' beliefs about the borrowing alternatives in the market are governed by a common reference interest rate, which is a function of the rates offered in the bilateral contracts. We show how this reference rate can be determined endogenously from a suitable mean field equilibrium and provide sufficient conditions for the existence of such an equilibrium together with an algorithm to compute it. Using simulation, we study the dependence of the equilibrium on the model parameters.
This paper shows how control techniques, such as PID or generalized predictive control, can improve the performance of TCP/IP networks when dealing with congestion. Drop tail, or more sophisticated AQM techniques such...
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This chapter first attempts to define the term "networked robotics" in the context of this book, and specifies, among a wide range of the research field, the subjects addressed in this book, namely bilateral...
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