the proceedings contain 33 papers. the special focus in this conference is on algorithms and computation. the topics include: Path Cover Problems with Length Cost;approximating the Bundled Crossing Number;minimum...
ISBN:
(纸本)9783030967307
the proceedings contain 33 papers. the special focus in this conference is on algorithms and computation. the topics include: Path Cover Problems with Length Cost;approximating the Bundled Crossing Number;minimum t-Spanners on Subcubic Graphs;invitation to Combinatorial Reconfiguration;counting and Sampling Orientations on Chordal Graphs;structural Parameterizations of Budgeted Graph Coloring;hypergraph Representation via Axis-Aligned Point-Subspace Cover;vertex-Weighted Graphs: Realizable and Unrealizable Domains;finding Popular Branchings in Vertex-Weighted Digraphs;parameterized Complexity of Immunization in the threshold Model;parameterized Complexity of Reconfiguration of Atoms;parameterized algorithms for Steiner Tree and Dominating Set: Bounding the Leafage by the Vertex Leafage;Isomorphism Testing for T-graphs in FPT;From the W-hierarchy to XNLP: Classes of Fixed Parameter Intractability;on the Harmless Set Problem Parameterized by Treewidth;machine Learning Advised Ski Rental Problem with a Discount;an Optimal Tester for k-Linear;trains, Games, and Complexity: 0/1/2-Player Motion Planning through Input/Output Gadgets;the Complexity of L(p, q)-Edge-Labelling;happy Set Problem on Subclasses of Co-comparability Graphs;reverse Shortest Path Problem in Weighted Unit-Disk Graphs;the Polygon Burning Problem;streamTable: An Area Proportional Visualization for Tables with Flowing Streams;parameterized Complexity of Minimum Membership Dominating Set;Vertex-to-Point Conflict-Free Chromatic Guarding is NP-Hard;some Problems Related to the Space of Optimal Tree Reconciliations: (Invited Talk);preface;Finding Geometric Representations of Apex Graphs is NP-Hard;morphing Tree Drawings in a Small 3D Grid;aspect Ratio Universal Rectangular Layouts;1-Complex s, t Hamiltonian Paths: Structure and Reconfiguration in Rectangular Grids.
this paper tackles the computational hurdles in region-based Petri net (PN) synthesis, focusing on the time-consuming identification of minimal regions essential for accurate model construction. Given the limitations ...
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the proceedings contain 30 papers. the special focus in this conference is on TAPEMS 2016 and BigTrust 2016. the topics include: An in-memory event tracing extension to the open trace format 2;network-aware optimizati...
ISBN:
(纸本)9783319499550
the proceedings contain 30 papers. the special focus in this conference is on TAPEMS 2016 and BigTrust 2016. the topics include: An in-memory event tracing extension to the open trace format 2;network-aware optimization of MPDATA on homogeneous multi-core clusters with heterogeneous network;formalizing data locality in task parallel applications;improving the energy efficiency of evolutionary multi-objective algorithms;a parallel model for heterogeneous cluster;comparative analysis of OpenACC compilers;traffic sign recognition based on parameter-free detector and multi-modal representation;reversible data hiding using non-local means prediction;secure data access in hadoop using elliptic curve cryptography;statistical analysis of CCM.M-K1 international comparison based on monte carlo method;redundancy elimination in the ExaStencils code generator;a dataflow IR for memory efficient RIPL compilation to FPGAs;exploring a distributed iterative reconstructor based on split bregman using PETSc;implementation of the beamformer algorithm for the NVIDIA jetson;efficiency of GPUs for relational database engine processing;geocon;a middleware for location-aware ubiquitous applications and cellular ANTomata as engines for highly parallel pattern processing.
Recent trends show recognition accuracy increasing even more profoundly. Inference process of Deep Convolutional Neural Networks (DCNN) has a large number of parameters, requires a large amount of computation, and can...
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ISBN:
(纸本)9781538610343
Recent trends show recognition accuracy increasing even more profoundly. Inference process of Deep Convolutional Neural Networks (DCNN) has a large number of parameters, requires a large amount of computation, and can be very slow. the large number of parameters also require large amounts of memory. this is resulting in increasingly long computation times and large model sizes. To implement mobile and other low performance devices incorporating DCNN, model sizes must be compressed and computation must be accelerated. To that end, this paper proposes Binary-decomposed DCNN, which resolves these issues without the need for retraining. Our method replaces real-valued inner-product computations with binary inner-product computations in existing network models to accelerate computation of inference and decrease model size without the need for retraining. Binary computations can be done at high speed using logical operators such as XOR and AND, together with bit counting. In tests using AlexNet withthe ImageNet classification task, speed increased by a factor of 1.79, models were compressed by approximately 80%, and increase in error rate was limited to 1.20%. With VGG-16, speed increased by a factor of 2.07, model sizes decreased by 81%, and error increased by only 2.16%.
Arterial oxyhemoglobin saturation (SpO2) values are currently computed using weighted moving average (WMA) techniques. Digital signal processing (DSP) algorithms were explored to identify improved algorithms for SpO2 ...
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ISBN:
(纸本)0780320506
Arterial oxyhemoglobin saturation (SpO2) values are currently computed using weighted moving average (WMA) techniques. Digital signal processing (DSP) algorithms were explored to identify improved algorithms for SpO2computation. the Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT) were identified as potentially superior algorithms. Improvements to the original algorithm using combinations of overlapped processing and averaging techniques were also explored.
A parallel process of computation of dynamic processes is based on a diakoptic theory of the portioning of the system into the sub-systems, that are computed independent of each other, in the fixed time intervals. Eve...
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ISBN:
(纸本)9786176078043
A parallel process of computation of dynamic processes is based on a diakoptic theory of the portioning of the system into the sub-systems, that are computed independent of each other, in the fixed time intervals. Every process is defined by the complexity of computation. this complexity is changed in the time of process of computations. these properties are utilized to implement computation in parallel systems. Currently the growth of parallel systems has been observed for several years. In this article, idea of GPU computations and parallel algorithms are presented. the results of computation on tested parallel system are shown and interpreted.
Ranklets are orientation selective rank features with applications to tracking, face detection, texture and medical imaging. We introduce efficient algorithmsthat reduce their computational complexity from O(N log N)...
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ISBN:
(纸本)9781424456536
Ranklets are orientation selective rank features with applications to tracking, face detection, texture and medical imaging. We introduce efficient algorithmsthat reduce their computational complexity from O(N log N) to O(root N + k), where N is the area of the filter. Timing tests show a speedup of one order of magnitude for typical usage, which should make Ranklets attractive for real-time applications.
Legendre moments have been widely used as feature descriptors in image analysis. this paper presents a new approach for the exact computation of Legendre moments of binary images. Using a Green's formula, the doub...
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ISBN:
(纸本)9781424432974
Legendre moments have been widely used as feature descriptors in image analysis. this paper presents a new approach for the exact computation of Legendre moments of binary images. Using a Green's formula, the double integral is first transformed into a simple integration along the boundary which is represented by a polygon. We then propose an efficient method for computing the line moments. Comparison with some known algorithms shows that the proposed algorithm is more accurate, and is independent of the slope, so that it is stable in numerical computation.
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