This paper presents an extension of previously introduced method for manufacturing systems analysis and design based on so called Machine-Job Incidence matrix. Static model of a manufacturing system is augmented by in...
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This paper presents an extension of previously introduced method for manufacturing systems analysis and design based on so called Machine-Job Incidence matrix. Static model of a manufacturing system is augmented by introduction of timed machine-job incidence matrix that is comprised of operational times required for jobs in the system to be completed as well as times required for setting-up of resources upon completion of requested tasks. The proposed dynamic model has been validated by simulation of free-choice multiple reentrant flow line. Results presented in the paper demonstrate efficiency of the model.
In this paper, gradient method is applied to the problem of satellite orbit determination. We used the ground station data (range, azimuth and elevation), for calculating the satellite position vector in the ECI frame...
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In this paper, gradient method is applied to the problem of satellite orbit determination. We used the ground station data (range, azimuth and elevation), for calculating the satellite position vector in the ECI frame. Satellite orbit is in the elliptic shape and satellite turns in orbital plane. Hence, orbit frame (PQW) is defined. Based on representation of input data in the PQW frame, we can define an ellipse. With the characteristics of an ellipse, beside definition of cost function and optimization technique, the satellite orbit is determined. This method, which can be easily implemented in hardware with moderate computational complexity, yield an efficient satellite positioning without assuming a prior knowledge of measurement noise. The performance, accuracy and error of algorithm are checked, by a test case.
Harvard architecture uses physically separate memories for their instructions and data. In the case of a flash memory with a buffer system, separate data and instruction buffers can lead to diversification of a flash ...
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This article describes an attempt to create an open source equivalent to the data acquisition and control software LabVIEW. The proposed solution uses GNURadio, OpenCV, Scilab, Xcos and COMEDI on Linux. GNURadio gives...
This article describes an attempt to create an open source equivalent to the data acquisition and control software LabVIEW. The proposed solution uses GNURadio, OpenCV, Scilab, Xcos and COMEDI on Linux. GNURadio gives a convenient graphical front end. The computations can be carried out using OpenCV or Scilab and Xcos. The device drivers given in COMEDI are used to access real time data. We also present PyGTK based improved graphical user interface for GNURadio.
This work proposes a fast background learning algorithm for foreground detection under changing illumination. Gaussian Mixture Model (GMM) is an effective statistical model in background learning. We first focus on Ti...
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This work proposes a fast background learning algorithm for foreground detection under changing illumination. Gaussian Mixture Model (GMM) is an effective statistical model in background learning. We first focus on Titterington's online EM algorithm that can be used for real-time unsupervised GMM learning, and then advocate a deterministic data assignment strategy to avoid Bayesian computation. The color of the foreground is apt to be influenced by the environmental illumination that usually produce undesirable effect for GMM updating, however, a collinear feature of pixel intensity under changing light is discovered in RGB color space. This feature is afterward used as a reliable clue to decide which part of mixture to update under changing light. A foreground detection step proposed in early version of this work is employed to extract foreground objects by comparing the estimated background model with the current video frame. Experiments have shown the proposed method is able to achieve satisfactory static background images of scenes as well as is also superior to some mainstream methods in detection performance under both indoor and outdoor scenes.
Load balancing is a technique to distribute workload evenly across two or more computers, network links, CPUs, hard drives, or other resources, in order to get optimal resource utilization, maximize throughput, minimi...
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Load balancing is a technique to distribute workload evenly across two or more computers, network links, CPUs, hard drives, or other resources, in order to get optimal resource utilization, maximize throughput, minimize response time, and ^void overload. When clustering objects to be allocated on a number of processing units, most research focus on either balancing of the workload among the clusters or minimising the communication among them. In this paper, we developed three clustering algorithms that combine both objectives: balancing the load of different clusters of objects while minimizing the communication among them. We show that communication graphs of these hybrid algorithms "H-K Partition algorithm and H-K "Medoids algorithm" methods have a good partition that can be found in distributed technique particularly in the major clusters and objects number. In the Other hand, the D-K Partition algorithm and D-K Medoids algorithm occupy the second level.
While abstractions of dynamical systems render the rigorous and algorithmic synthesis of controllers feasible in principle, the computation of discrete abstractions is known to be feasible only for systems of relative...
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ISBN:
(纸本)9781457710957
While abstractions of dynamical systems render the rigorous and algorithmic synthesis of controllers feasible in principle, the computation of discrete abstractions is known to be feasible only for systems of relatively low dimension. As a step towards making the computations more tractable, this paper proposes to reduce the computational load and the required memory by combining the computation of the abstraction and the solution of an auxiliary discrete control problem. Although the worst-case complexity of the proposed algorithm is worse than for other known procedures, the algorithm shows promising performance for a challenging example.
The mCRL2 language is a formal specification language that is used to specify, model, analyze and verify behavioral properties for distributed systems and protocols. The semantics of the mCRL2 language is defined form...
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GNSS-assisted vehicle navigation services are nowadays very common in most of the developed countries. However, most of those services are either delivered through proprietary technologies, or fall short in flexibilit...
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GNSS-assisted vehicle navigation services are nowadays very common in most of the developed countries. However, most of those services are either delivered through proprietary technologies, or fall short in flexibility because of the limited capability to couple road information with real-time traffic information. This paper presents the motivations and a brief summary of a vehicle navigation service based on real-time traffic information, delivered through an open protocol that is currently under standardization in the Open Mobile Alliance forum.
A new fast monotonic blind deconvolution algorithmic method is investigated based on the constrained variational minimization framework under the periodic boundary conditions. The contributions of our methodology are ...
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ISBN:
(纸本)9781467313971
A new fast monotonic blind deconvolution algorithmic method is investigated based on the constrained variational minimization framework under the periodic boundary conditions. The contributions of our methodology are that the blur operator identification and image restoration can be simultaneously optimized even under high noise level as compared to previous methods. Specifically, the monotone fast iterative shrinkage/thresholding algorithm (MFISTA) combined with the fast gradient projection (FGP) algorithm, is extended to deal with our new proposed algorithm and guarantee the monotonic convergence rate. In addition, the deblurring subproblem is enhanced by incorporating a bisection technique to effectively identify a near optimal value for the regularization parameter of the TV-Frobenius objective function quickly and accurately. Initial experimental results for gray satellite and color wireless capsule endoscopy (WCE) images demonstrate the considerable performance of the proposed algorithm.
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