Over the years, the objective of image and video compression has been to preserve perceived quality according to the Human Visual System (HVS) with minimal rate. Traditional encoders achieve this with the use of Rate-...
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ISBN:
(纸本)9798350338935
Over the years, the objective of image and video compression has been to preserve perceived quality according to the Human Visual System (HVS) with minimal rate. Traditional encoders achieve this with the use of Rate-Distortion optimization (RDO) techniques along with Image Quality Assessment (IQA) metrics that are correlated with human perception. Nowa-days, a fast-growing number of applications fall within the realm of Video Coding for Machines (VCM), where the final recipient of compressed data is not a human but a machine performing a vision task. Recently, the lack of correlation between existing distortion measures and machine perception has been revealed, especially for RDO algorithms where distortion measures are computed on a local scale. In this paper, we propose a machine perception-aware metric designed to be incorporated into a standard-compliant Versatile Video Coding (VVC) encoder. Our proposed metric relies on a supervised training procedure as well as additional information available on the encoder side. In terms of correlation with machine perception, our metric significantly outperforms existing distortion measures in the literature.
We address an energy-efficient scheduling problem for practical multiple-input single-output (MISO) systems with stringent execution-time requirements. Optimal user-group scheduling is adopted to enable timely and ene...
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ISBN:
(纸本)9781538631805
We address an energy-efficient scheduling problem for practical multiple-input single-output (MISO) systems with stringent execution-time requirements. Optimal user-group scheduling is adopted to enable timely and energy-efficient data transmission, such that all the users' demand can be delivered within a limited time. The high computational complexity in optimal iterative algorithms limits their applications in real-time network operations. In this paper, we rethink the conventional optimizationalgorithms, and embed machine-learning based predictions in the optimization process, aiming at improving the computational efficiency and meeting the stringent execution-time limits in practice, while retaining competitive energy-saving performance for the MISO system. Numerical results demonstrate that the proposed method, i.e., optimization with machine-learning predictions (OMLP), is able to provide a time-efficient and high-quality solution for the considered scheduling problem. Towards online scheduling in real-time communications, OMLP is of high computational efficiency compared to conventional optimal iterative algorithms. OMLP guarantees the optimality as long as the machine-learning based predictions are accurate.
Many problems in geotechnical engineering request the use of sophisticated and complex constitutive laws, which require sometimes the calibration of a great number of parameters of the involved materials. In this way,...
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ISBN:
(纸本)9780415437899
Many problems in geotechnical engineering request the use of sophisticated and complex constitutive laws, which require sometimes the calibration of a great number of parameters of the involved materials. In this way, a more skilled approach than the traditional methodology for determination of those parameters becomes necessary. The problem of parameter identification can be treated as an optimization problem and solved by iterative algorithms that allow finding those parameters which turn minimal the difference between the measured values in the laboratory and those calculated by the model. Among the several methods to solve optimization problems, the quasi-Newton method of limited memory LBFGS was chosen due to its readiness and handling easiness. The technique was used to calibrate a constitutive non linear elastic model from triaxial experimental results, showing the capacity of the optimization procedure in correctly determining the model parameters. A sensivity analysis was also performed to explore the complexity found in the optimization of highly non linear functions.
Robust principal component analysis (RPCA) is currently the method of choice for recovering a low-rank matrix from sparse corruptions that are of unknown value and support by decomposing the observation matrix into lo...
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ISBN:
(纸本)9781538610343
Robust principal component analysis (RPCA) is currently the method of choice for recovering a low-rank matrix from sparse corruptions that are of unknown value and support by decomposing the observation matrix into low-rank and sparse matrices. RPCA has many applications including background subtraction, learning of robust subspaces from visual data, etc. Nevertheless, the application of SVD in each iteration of optimisation methods renders the application of RPCA challenging in cases when data is large. In this paper, we propose the first, to the best of our knowledge, multilevel approach for solving convex and non-convex RPCA models. The basic idea is to construct lower dimensional models and perform SVD on them instead of the original high dimensional problem. We show that the proposed approach gives a good approximate solution to the original problem for both convex and non-convex formulations, while being many times faster than original RPCA methods in several real world datasets.
The proceedings contain 54 papers. The topics discussed include: an efficient video program delivery algorithm in tree networks;an efficient content delivery algorithm for intermittently connected mobile ad hoc networ...
ISBN:
(纸本)9780769543123
The proceedings contain 54 papers. The topics discussed include: an efficient video program delivery algorithm in tree networks;an efficient content delivery algorithm for intermittently connected mobile ad hoc networks;one-hop neighbor transmission coverage information based distributed algorithm for connected dominating set;a novel P2P identification algorithm based on genetic algorithm and particle swarm optimization;accelerating reconfiguration for degradable mesh-connected processor arrays;a novel approach for multilevel fixed outline floorplanning;scheduling multiple multithreaded applications on asymmetric and symmetric chip multiprocessors;a hybrid fault tolerance model for reliable scheduling of critical real-time applications on grid systems;GTFTTS: a generalized tit-for-tat based corporative game for temperature-aware task scheduling in multi-core systems;and a scheduling strategy on load balancing of virtual machine resources in cloud computing environment.
We have developed a new approach to solve the ECG inverse problem by means of a heart-simulation-model. We have tested the feasibility of the newly developed technique in localizing the site of origin of cardiac activ...
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ISBN:
(纸本)078036449X
We have developed a new approach to solve the ECG inverse problem by means of a heart-simulation-model. We have tested the feasibility of the newly developed technique in localizing the site of origin of cardiac activation using a pace mapping simulation protocol. The present promising simulation results suggest that this new approach merits further investigation and may become an important alternative to other ECG inverse solutions.
This paper presents an implementation and empirical convergence analysis results of genetic algorithm for solving unit commitment problem in a power market. Various parameter settings are presented including an algori...
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ISBN:
(纸本)9789612640682
This paper presents an implementation and empirical convergence analysis results of genetic algorithm for solving unit commitment problem in a power market. Various parameter settings are presented including an algorithm with a sequence of parameters, also called a variablestructure genetic algorithm. Implemented algorithm successfully solves both small and large scale problems and shows how much more efficient variable-structure genetic algorithm is in practice.
The paper proposes the results of a project developed by the authors in collaboration with a production system working in the field of manufacturing wood products. The first step of the project was an accurate analysi...
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ISBN:
(纸本)9780780394452
The paper proposes the results of a project developed by the authors in collaboration with a production system working in the field of manufacturing wood products. The first step of the project was an accurate analysis of the system together with the design of new production documents in order to collect data about the system itself. The collected data has been used to propose an initial solution of plant lay-out. The second step of the project was the realization of a simulation model. The model has been used to find an optimal plant-layout configuration by means of genetic algorithms with the goal of material handling cost minimization.
This book highlights the latest advances in engineering mathematics with a main focus on the mathematical models, structures, concepts, problems and computational methods and algorithms most relevant for applications ...
ISBN:
(纸本)9783319421049
This book highlights the latest advances in engineering mathematics with a main focus on the mathematical models, structures, concepts, problems and computational methods and algorithms most relevant for applications in modern technologies and engineering. It addresses mathematical methods of algebra, applied matrix analysis, operator analysis, probability theory and stochastic processes, geometry and computational methods in network analysis, data classification, ranking and optimisation. The individual chapters cover both theory and applications, and include a wealth of figures, schemes, algorithms, tables and results of data analysis and simulation. Presenting new methods and results, reviews of cutting-edge research, and open problems for future research, they equip readers to develop new mathematical methods and concepts of their own, and to further compare and analyse the methods and results discussed. The book consists of contributed chapters covering research developed as a result of a focused international seminar series on mathematics and applied mathematics and a series of three focused international research workshops on engineering mathematics organised by the Research Environment in Mathematics and Applied Mathematics at Mlardalen University from autumn 2014 to autumn 2015: the internationalworkshop on Engineering Mathematics for Electromagnetics and Health Technology; the internationalworkshop on Engineering Mathematics, Algebra, Analysis and Electromagnetics; and the 1st Swedish-Estonian internationalworkshop on Engineering Mathematics, Algebra, Analysis and applications. It serves as a source of inspiration for a broad spectrum of researchers and research students in applied mathematics, as well as in the areas of applications of mathematics considered in the book.
Parallel graph algorithms expressed in a Bulk- Synchronous Parallel (BSP) compute model generate highlystructured communication workloads from messages propagating along graph edges. We can expose this structure to tr...
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ISBN:
(纸本)9783866445154
Parallel graph algorithms expressed in a Bulk- Synchronous Parallel (BSP) compute model generate highlystructured communication workloads from messages propagating along graph edges. We can expose this structure to traffic compilers and optimization tools before runtime to reshape and reduce traffic for higher performance (or lower area, lower energy, lower cost). Such offline traffic optimization eliminates the need for complex, runtime NoC hardware and enables lightweight, scalable FPGA NoCs. In this paper, we perform load balancing, placement, fanout routing and fine-grained synchronization to optimize our workloads for large networks up to 2025 parallel elements. This allows us to demonstrate speedups between 1.2× and 22× (3.5× mean), area reductions (number of Processing Elements) between 3× and 15× (9× mean) and dynamic energy savings between 2× and 3.5× (2.7× mean) over a range of realworld graph applications. We expect such traffic optimization tools and techniques to become an essential part of the NoC application-mapping flow.
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