Search results for "Abstract data type"
showing 10 items of 1140 documents
Markov Chains and Electrical Networks
2020
There is a natural connection between electrical networks and so called reversible Markov chains. An example for such a chain is the symmetric graph random walk which, in each step, jumps to a randomly chosen graph neighbor at equal probability. This connection is studied here in some detail. As an application, we prove the statement that if such a graph random walk is recurrent, then it is recurrent also on each subgraph. (Although this statement is rather plausible, it is hard to show by different means.) In particular, the graph random walk on a percolation cluster of the planar integer lattice is recurrent.
Fast and Simple Approximation of the Diameter and Radius of a Graph
2006
The increasing amount of data to be processed by computers has led to the need for highly efficient algorithms for various computational problems. Moreover, the algorithms should be as simple as possible to be practically applicable. In this paper we propose a very simple approximation algorithm for finding the diameter and the radius of an undirected graph. The algorithm runs in $O(m\sqrt{n})$ time and gives an additive error of $O(\sqrt{n})$ for a graph with n vertices and m edges. Practical experiments show that the results of our algorithm are close to the optimum and compare favorably to the 2/3-approximation algorithm for the diameter problem by Aingworth et al [1].
SELF-ENERGIES AND VERTEX CORRECTIONS WITH TWO FACTORIZING LOOPS
1999
A complete set of factorizing two-loop self-energies and vertex corrections is calculated analytically for arbitrary masses and momenta — including the case of collinear singularities — within the ℛ-functions approach.
Nonlinear Nonhomogeneous Robin Problems with Almost Critical and Partially Concave Reaction
2020
We consider a nonlinear Robin problem driven by a nonhomogeneous differential operator, with reaction which exhibits the competition of two Caratheodory terms. One is parametric, $$(p-1)$$-sublinear with a partially concave nonlinearity near zero. The other is $$(p-1)$$-superlinear and has almost critical growth. Exploiting the special geometry of the problem, we prove a bifurcation-type result, describing the changes in the set of positive solutions as the parameter $$\lambda >0$$ varies.
Voxel-based General Voronoi Diagram for Complex Data with Application on Motion Planning
2020
One major challenge in Assembly Sequence Planning (ASP) for complex real-world CAD-scenarios is to find appropriate disassembly paths for all assembled parts. Such a path places demands on its length and clearance. In the past, it became apparent that planning the disassembly path based on the (approximate) General Voronoi Diagram (GVD) is a good approach to achieve these requirements. But for complex real-world data, every known solution for computing the GVD is either too slow or very memory consuming, even if only approximating the GVD.We present a new approach for computing the approximate GVD and demonstrate its practicability using a representative vehicle data set. We can calculate a…
Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles
2016
Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…
A Guaranteed performance of a green data center based on the contribution of vital nodes
2016
International audience; In order to satisfy the need for the critical computing resources, many data center architectures proposed to house a huge number of network devices. These devices are used to achieve the highest performance in case of full utilization of the network. However, the peak capacity of the network is rarely reached. Consequently, many devices are set into idle state and cause a huge energy waste leading to a non-proportionality between the network load and the energy consumed. In this paper, we propose a power-aware routing algorithm that saves energy consumption with a negligible trade-off on the performance of the network. The idea is to keep active only the source and …
Using an Adaptive Network-based Fuzzy Inference System to Estimate the Vertical Force in Single Point Incremental Forming
2019
Manufacturing processes are usually complex ones, involving a significant number of parameters. Unconventional manufacturing processes, such as incremental forming is even more complex, and the establishment of some analytical relationships between parameters is difficult, largely due to the nonlinearities in the process. To overcome this drawback, artificial intelligence techniques were used to build empirical models from experimental data sets acquired from the manufacturing processes. The approach proposed in this work used an adaptive network-based fuzzy inference system to extract the value of technological force on Z-axis, which appears during incremental forming, considering a set of…
Analysis of HMAX Algorithm on Black Bar Image Dataset
2020
An accurate detection and classification of scenes and objects is essential for interacting with the world, both for living beings and for artificial systems. To reproduce this ability, which is so effective in the animal world, numerous computational models have been proposed, frequently based on bioinspired, computational structures. Among these, Hierarchical Max-pooling (HMAX) is probably one of the most important models. HMAX is a recognition model, mimicking the structures and functions of the primate visual cortex. HMAX has already proven its effectiveness and versatility. Nevertheless, its computational structure presents some criticalities, whose impact on the results has never been…
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…