Results 61 to 70 of about 51,397 (286)
Exact symbolic–numeric computation of planar algebraic curves
Theoretical Computer Science, 2013 We present a novel certified and complete algorithm to compute arrangements of real planar algebraic curves. It provides a geometric-topological analysis of the decomposition of the plane induced by a finite number of algebraic curves in terms of a cylindrical algebraic decomposition.
Berberich, E. +3 more
openaire +5 more sources
Long‐Range Interactions in Topological Superconducting Systems: A Mini Review
Advanced Physics Research, EarlyView.Long‐range interacting quantum systems are surveyed in this review, with an emphasis on the long‐range topological superconductor and its variants. Long‐range interactions decaying in a power‐law manner can lead to exotic phenomena that finds no analogue in short‐range regimes.
Juntong Ren, Haifeng Lü
wiley +1 more source
Asian Journal of Control, EarlyView.Abstract Large swarms often adopt a hierarchical network structure that incorporates information aggregation. Although this approach offers significant advantages in terms of communication efficiency and computational complexity, it can also lead to degradation due to information constraints.
Kento Fujita, Daisuke Tsubakino
wiley +1 more source
Specific "scientific" data structures, and their processing [PDF]
Electronic Proceedings in Theoretical Computer Science, 2011 Programming physicists use, as all programmers, arrays, lists, tuples, records, etc., and this requires some change in their thought patterns while converting their formulae into some code, since the "data structures" operated upon, while elaborating ...
Jerzy Karczmarczuk
doaj +1 more source
Computer Aided Symbolic Linear Algebra [PDF]
, 2003 The aim of this communication is to present a Symbolic Linear Algebra package, written in MAPLE V.5 and working also in the release 7, with general but especially educational purpose. Its goal is to run over MAPLE the different Linear Algebra algorithms developped in [OJ].
openaire +1 more source
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Asian Journal of Control, EarlyView.Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
On structural controllability in complex networks with periodic switching topologies
Asian Journal of Control, EarlyView.Abstract This paper investigates the structural controllability of complex networks with periodic switching topologies. First, several graph transformations that preserve structural controllability are demonstrated. Based on the n‐walk theory, a criterion is derived that determines structural controllability by analyzing only the joint graph within a ...
Jingrui Hou +3 more
wiley +1 more source
Range Space and Similarity Transformation Using Symbolic Mathematics in Python
IEEE AccessLinear systems involved in engineering and scientific calculations can be more easily analyzed using similarity transformation. However, understanding the numerous abstract linear algebra theorems associated with this transformation can be challenging ...
Chainarong Wisassakwichai +1 more
doaj +1 more source
Young people's occupational aspirations beyond the aspiration discourse: A sociocultural perspective
British Educational Research Journal, EarlyView.Abstract Young people's aspirations have been the focus of many educational, sociological and psychological studies. This paper argues, firstly, that the concept of aspirations holds greater generative potential than suggested by the policy‐oriented ‘aspiration discourse’.
Jelena Popov
wiley +1 more source
A‐optimal model‐based design of experiments for processes with uncertain inputs
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Model‐based design of experiments (MBDoE) techniques are tools for selecting experimental conditions that enable accurate parameter estimation for mechanistic models. Most MBDoE approaches assume that the selected experimental conditions will be implemented perfectly, without uncertainties in the independent variables.
Bright Ofori +3 more
wiley +1 more source