Hardness of Approximation for H-Free Edge Modification Problems
This book constitutes revised selected papers from the First International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015, held in Taormina, Sicily, Italy, in July 2015. The 32 papers presented in this volume were carefully reviewed and selected from 73 submissions. They deal with the algorithms, methods and theories relevant in data science, optimization and machine learning.
The increasing of the efficiency of technological modes of steel products manufacturing requires simulation of metal forming during hot deformation. To obtain correct results, one should set the correct initial and boundary conditions, including the mechanical properties of materials, which represent the dependence of the stress-strain and strain rate at maintained temperature. In the experiments one must reveal the mechanical properties and constants of the steels according to strain rate, predetermined temperature and chemical composition. So, the type of test is usually dependents on the technology process, which simulation will be using the obtained information. One can identify four main types of tests used in the hot deformation: compression, tension, torsion and rupture tests. The simplest tests are considered as uniaxial compression or tension tests. The results of these tests are the curves of <<flow stress -- strain>>. The present study describes an approximation method of test results for uniaxial compression of cylindrical samples made from AISI304 steel. During this work a mathematical model of the <<stress -- strain>> relation has been described. An algorithm that determines the necessary numerical coefficients for this model was developed. As a result, the equation of the material state, which is characterized by the stress relation on the strain, strain rate (0.15, 0.5, 1.5, 5 and 15 inverse seconds) and temperature (800, 950, 1080 and 1200 degree Celsius) was found. Also the approximation comparison with the experimental results were obtained.
This paper argues that modeling granularity and approximation (Krifka 2007; Lewis 1979) is crucial for capturing important aspects of the distribution and interpretation of adjectives and their modifiers, modulo certain differences between modified adjectives and numerals. In addition, the paper presents supporting experimental results with minimizers like slightly and maximizers like completely.
In the article the methods of processing of statistical data about periodic process by the least squares method with usage of Bessel functions and Fourie numbers are analyzed. The simple method for approximation with a choice of the fluctuation period, proceeding from a minimum of the estimated error is offered.
Consideration was given to the omega square Cramer–von Mises tests intended to verify the goodness hypothesis about the distribution of the observed multivariable random vector with the distribution in the unit cube. The limit distribution of the statistics of these tests was defined by the distribution of an infinite quadratic form in the normal random variables. For convenience of computing its distribution, the residue of the quadratic form was approximated by a finite linear combination of the χ2-distributed random variables. Formulas for determination of the residue parameters were established.