Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by ex...
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ISBN:
(纸本)9781107152380
Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy. They also reduce the resources needed in distributed deployments and make better use of the limited memory in low-end devices. The field has developed rapidly, reaching a level of maturity that allows practitioners and researchers in application areas to benefit from the use of compact data structures. This first comprehensive book on the topic focuses on the structures that are most relevant for practical use. Readers will learn how the structures work, how to choose the right ones for their application scenario, and how to implement them. Researchers and students in the area will find in the book a definitive guide to the state of the art in compact data structures.
The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobje...
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The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobjective optimization problem of complex expression since the process is composed of one grinding machine and two classification machines. In this paper, a hybrid differential evolution (DE) algorithm with multi-population is proposed. Some infeasible solutions with better performance are allowed to be saved, and they participate randomly in the evolution. In order to exploit the meaningful infeasible solutions, a functionally partitioned multi-population mechanism is designed to find an optimal solution from all possible directions. Meanwhile, a simplex method for local search is inserted into the evolution process to enhance the searching strategy in the optimization process. Simulation results from the test of some benchmark problems indicate that the proposed algorithm tends to converge quickly and effectively to the Pareto frontier with better distribution. Finally, the proposed algorithm is applied to solve a multiobjective optimization model of a grinding and classification process. Based on the technique for order performance by similarity to ideal solution (TOPSIS), the satisfactory solution is obtained by using a decision-making method for multiple attributes.
The modeling and design of a link-layer control algorithm for automated highway systems are presented in this paper. Link-layer control systems address the coordination of traffic on a stretch of highway, and serve as...
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The modeling and design of a link-layer control algorithm for automated highway systems are presented in this paper. Link-layer control systems address the coordination of traffic on a stretch of highway, and serve as the intermediate layer between traffic management (ATMS) and vehicle control (AVCS) systems. The key role of the link layer control system is to use macroscopic traffic information for improved traffic flow. A distributed control algorithm is developed based on optimal control theory. The proposed control law is implemented in a simulation program which keeps track of the motions of each individual vehicles on the highway. Simulation results under three perturbed conditions-uneven traffic distribution, broken vehicle, and traffic merging-are presented.
A technique for using a digital computer to draw both ordinary and time-lag root locus diagrams is described. Ordinary diagrams are drawn much faster and more accurately than ever before. Time-lag diagrams, which had ...
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A technique for using a digital computer to draw both ordinary and time-lag root locus diagrams is described. Ordinary diagrams are drawn much faster and more accurately than ever before. Time-lag diagrams, which had been impossible to obtain, are drawn with the same speed and accuracy as ordinary diagrams. [ABSTRACT FROM AUTHOR]
Fluorescence molecular tomography (FMT) is a promising technique for in vivo small animal imaging. In this paper, a two-stage reconstruction method based on normalized Born approximation is developed for FMT, which in...
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Fluorescence molecular tomography (FMT) is a promising technique for in vivo small animal imaging. In this paper, a two-stage reconstruction method based on normalized Born approximation is developed for FMT, which includes two steps for quantitative reconstruction. First, the localization of fluorescent fluorophore is determined by l1-norm regularization method. Then, in the location region of fluorophore, which is provided by the first stage, algebraic reconstruction technique (ART) is utilized for the fluorophore concentration reconstruction. The validity of the two-stage quantitative reconstruction algorithm is testified by simulation experiments on a 3D digital mouse atlas and physical experiments on a phantom. The results suggest that we are able to recover the fluorophore location and concentration.
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