Search results for "SOFC"
showing 10 items of 660 documents
Selling a vote
2005
Abstract A voting function is a rule that determines the outcome of an election: taking the voters' votes as input, a voting function selects the winning candidate from the set of candidates receiving some vote. A voting function is immune to vote selling when, given that neither voter i nor voter j votes for the winning candidate, a change ceteris paribus in i's vote cannot make the candidate for which j votes the winner. It is shown that voting functions immune to vote selling have either a dictator (a voter who always determines the winning candidate) or a dictated candidate (a candidate who becomes the winner by just receiving some vote).
Extended Natural Numbers and Counters
2020
Summary This article introduces extended natural numbers, i.e. the set ℕ ∪ {+∞}, in Mizar [4], [3] and formalizes a way to list a cardinal numbers of cardinals. Both concepts have applications in graph theory.
Computation of a few smallest eigenvalues of elliptic operators using fast elliptic solvers
2001
The computation of a few smallest eigenvalues of generalized algebraic eigenvalue problems is studied. The considered problems are obtained by discretizing self-adjoint second-order elliptic partial differential eigenvalue problems in two- or three-dimensional domains. The standard Lanczos algorithm with the complete orthogonalization is used to compute some eigenvalues of the inverted eigenvalue problem. Under suitable assumptions, the number of Lanczos iterations is shown to be independent of the problem size. The arising linear problems are solved using some standard fast elliptic solver. Numerical experiments demonstrate that the inverted problem is much easier to solve with the Lanczos…
Explanation, motivation and question posing routines in university mathematics teachers' pedagogical discourse: a commognitive analysis
2015
This paper investigates the teaching practices used by university mathematics teachers when lecturing, a topic within university mathematics education research which is gaining an increasing intere ...
The Windy clustered prize-collecting arc-routing problem
2011
This paper introduces the windy clustered prize-collecting arc-routing problem. It is an arc-routing problem where each demand edge is associated with a profit that is collected once if the edge is serviced, independent of the number of times the edge is traversed. It is further required that if a demand edge is serviced, then all the demand edges of its component are also serviced. A mathematical programming formulation is given and some polyhedral results including several facet-defining and valid inequalities are presented. The separation problem for the different families of inequalities is studied. Numerical results from computational experiments are analyzed. © 2011 INFORMS.
Joy of Mathematical Modelling: A Forgotten Perspective?
2020
We argue the relevance of including an affective perspective in the mathematical modelling education research and emphasise its importance for the teaching and learning of mathematical modelling at all levels, especially at the university. Our argument is supported by a recent survey of mathematics lecturers’ views on mathematical modelling, several follow-up interviews, and a review of literature on mathematical modelling that relates to enjoyment, pleasure, and appreciation. Findings from the survey and the follow-up interviews indicate that there is a group of practitioners who hold strong views on the importance of enjoyment in doing and teaching mathematical modelling.
Optimal Guard Placement Problem Under L-Visibility
2006
Two points a and b in the presence of polygonal obstacles are L-visible if the length of the shortest path avoiding obstacles is no more than L. For a given convex polygon Q, Gewali et al [4]. addressed the guard placement problem on the exterior boundary that will cover the maximum area exterior to the polygon under L-visibility. They proposed a linear time algorithm for some given value of L. When the length L is greater than half of the perimeter, they declared that problem as open. Here we address that open problem and present an algorithm whose time complexity is linear in number of vertices of the polygon.
Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach
2020
The evolution of Internet of things (IoT) towards massive IoT in recent years has stimulated a surge of traffic volume among which a huge amount of traffic is generated in the form of massive machine type communications. Consequently, existing network infrastructure is facing challenges when handling rapidly growing traffic load, especially under bursty traffic conditions which may more often lead to congestion. By proactively predicting the occurrence of congestion, we can implement necessary means and conceivably avoid congestion. In this paper, we propose a machine learning (ML) based model for predicting successful preamble transmissions at a base station and subsequently forecasting th…
A new method for optimal synthesis of wavelet-based neural networks suitable for identification purposes
1999
Abstract This paper deals with a new method for optimal synthesis of Wavelet-Based Neural Networks (WBNN) suitable for identification purposes. The method uses a genetic algorithm (GA) combined with a steepest descent technique and least square techniques for both optimal selection of the structure of the WBNN and its training. The method is applied for designing a predictor for a chaotic temporal series
Regularized RBF Networks for Hyperspectral Data Classification
2004
In this paper, we analyze several regularized types of Radial Basis Function (RBF) Networks for crop classification using hyperspectral images. We compare the regularized RBF neural network with Support Vector Machines (SVM) using the RBF kernel, and AdaBoost Regularized (ABR) algorithm using RBF bases, in terms of accuracy and robustness. Several scenarios of increasing input space dimensionality are tested for six images containing six crop classes. Also, regularization, sparseness, and knowledge extraction are paid attention.