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New families of fourth-order composition methods for the numerical integration of initial value problems defined by ordinary differential equations are proposed. They are designed when the problem can be separated into three parts in such a…

Numerical Analysis · Mathematics 2020-06-12 Fernando Casas , Alejandro Escorihuela-Tomàs

A general method for solving linear differential equations of arbitrary order, is used to arrive at new representations for the solutions of the known differential equations, both without and with a source term. A new quasi-solvable…

Mathematical Physics · Physics 2008-04-24 N. Gurappa , Pankaj K. Jha , Prasanta K. Panigrahi

Symmetry is an important problem in many combinatorial problems. One way of dealing with symmetry is to add constraints that eliminate symmetric solutions. We survey recent results in this area, focusing especially on two common and useful…

Artificial Intelligence · Computer Science 2012-04-18 Toby Walsh

In problem solving, understanding the problem that one seeks to solve is an essential initial step. In this paper, we propose computational methods for facilitating problem understanding through the task of recognizing the unknown in…

Computation and Language · Computer Science 2021-11-30 Ndapa Nakashole

Symbolic equations are one of the many representations used in physics. Understanding these representations is important for students because they are how students access knowledge in physics. In this paper I build off of the work by Redish…

Physics Education · Physics 2016-06-08 Eugene T. Torigoe

Assembling parts into an object is a combinatorial problem that arises in a variety of contexts in the real world and involves numerous applications in science and engineering. Previous related work tackles limited cases with identical unit…

Computer Vision and Pattern Recognition · Computer Science 2022-06-22 Jinhwi Lee , Jungtaek Kim , Hyunsoo Chung , Jaesik Park , Minsu Cho

Mathematical reasoning with algebraic and graphical representations is essential for success in physics courses. Many problems require students to fluently move between algebraic and graphical representations. We developed a freely…

The motivation of this work is to illustrate the efficiency of some often overlooked alternatives to deal with optimization problems in systems and control. In particular, we will consider a problem for which an iterative linear matrix…

Optimization and Control · Mathematics 2011-07-05 Emile Simon , Vincent Wertz

We use a probabilistic method to produce some combinatorial inequalities by considering pattern containment in permutations and words.

Combinatorics · Mathematics 2007-05-23 Alexander I. Burstein

Some iterative techniques are defined to solve reversible inverse problems and a common formulation is explained. Numerical improvements are suggested and tests validate the methods.

Optimization and Control · Mathematics 2011-12-06 Sébastien Marinesque

One of the grand challenges of Mathematics instruction is to provide students with problems that are both accessible and have a reasonably elegant solution. Instructors commonly resort to resources like course textbooks, online-learning…

History and Overview · Mathematics 2024-02-13 Ryan H. Allaire , Margaret Reynolds , Andrew C. Lee

Efficient omission of symmetric solution candidates is essential for combinatorial problem-solving. Most of the existing approaches are instance-specific and focus on the automatic computation of Symmetry Breaking Constraints (SBCs) for…

Logic in Computer Science · Computer Science 2022-04-26 Alice Tarzariol , Martin Gebser , Konstantin Schekotihin

We present a quantum solution to coordination problems that can be implemented with present technologies. It provides an alternative to existing approaches, which rely on explicit communication, prior commitment or trusted third parties.…

Quantum Physics · Physics 2015-01-23 Bernardo A. Huberman , Tad Hogg

In order to describe natural phenomena, science develops sophisticated models that use mathematical and formal languages which seem, and often are, very far from common experience. When a phenomenon is not accessible to our senses, its…

Physics Education · Physics 2016-01-08 Vera Montalbano

Previous research has found that introductory physics students perform far better on numeric problems than on otherwise equivalent symbolic problems. This paper describes a framework to explain these differences developed by analyzing…

Physics Education · Physics 2012-07-19 Eugene Torigoe

We consider the problem of aggregation of incomplete preferences represented by arbitrary binary relations or incomplete paired comparison matrices. For a number of indirect scoring procedures we examine whether or not they satisfy the…

Optimization and Control · Mathematics 2011-10-11 Pavel Chebotarev , Elena Shamis

This paper surveys the recent attempts, both from the machine learning and operations research communities, at leveraging machine learning to solve combinatorial optimization problems. Given the hard nature of these problems,…

Machine Learning · Computer Science 2020-03-16 Yoshua Bengio , Andrea Lodi , Antoine Prouvost

In its most general form, a `secret objective' is any inconsistency between the experimental reality and the information provided to students prior to starting work on an experiment. Students are challenged to identify the secret objectives…

Physics Education · Physics 2019-05-20 P. A. Bartlett , K. Dunnett

Mathematical Selection is a method in which we select a particular choice from a set of such. It have always been an interesting field of study for mathematicians. Accordingly, Combinatorial Optimization is a sub field of this domain of…

Computational Complexity · Computer Science 2023-06-29 Anurag Dutta , K. Lakshmanan , A. Ramamoorthy , Liton Chandra Voumik , John Harshith , John Pravin Motha

A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems. Such a system recursively splits the set of classes into two subsets, and trains a binary classifier to distinguish…

Machine Learning · Statistics 2016-07-06 Tim Leathart , Bernhard Pfahringer , Eibe Frank