Mixed Integer Linear Programming for Feature Selection in Support Vector Machine

This work focuses on support vector machine (SVM) with feature selection. A MILP formulation is proposed for the problem. The choice of suitable features to construct the separating hyperplanes has been modelled in this formulation by including a budget constraint that sets in advance a limit on the number of features to be used in the classification process. We propose both an exact and a heuristic procedure to solve this formulation in an efficient way. Finally, the validation of the model is done by checking it with some well-known data sets and comparing it with classical classification methods.Comment: 37 pages, 20 figure

Low-thrust chemical propulsion system propellant expulsion and thermal conditioning study. Executive summary

Preferred techniques for providing abort pressurization and engine feed system net positive suction pressure (NPSP) for low thrust chemical propulsion systems (LTPS) were determined. A representative LTPS vehicle configuration is presented. Analysis tasks include: propellant heating analysis; pressurant requirements for abort propellant dump; and comparative analysis of pressurization techniques and thermal subcoolers

Low-thrust chemical propulsion system propellant expulsion and thermal conditioning study

Thermal conditioning systems for satisfying engine net positive suction pressure (NPSP) requirements, and propellant expulsion systems for achieving propellant dump during a return-to-launch site (RTLS) abort were studied for LH2/LO2 and LCH4/LO2 upper stage propellant combinations. A state-of-the-art thermal conditioning system employing helium injection beneath the liquid surface shows the lowest weight penalty for LO2 and LCH4. A technology system incorporating a thermal subcooler (heat exchanger) for engine NPSP results in the lowest weight penalty for the LH2 tank. A preliminary design of two state-of-the-art and two new technology systems indicates a weight penalty difference too small to warrant development of a LH2 thermal subcooler. Analysis results showed that the LH2/LO2 propellant expulsion system is optimized for maximum dump line diameters, whereas the LCH4/LO2 system is optimized for minimum dump line diameter (LCH4) and maximum dump line diameter (LO2). The primary uncertainty is the accurate determination of two-phase flow rates through the dump system; experimentation is not recommended because this uncertainty is not considered significant

The stratified p-center problem

This work presents an extension of the p-center problem. In this new model, called Stratified p-Center Problem (SpCP), the demand is concentrated in a set of sites and the population of these sites is divided into different strata depending on the kind of service that they require. The aim is to locate p centers to cover the different types of services demanded minimizing the weighted average of the largest distances associated with each of the different strata. In addition, it is considered that more than one stratum can be present at each site. Different formulations, valid inequalities and preprocessings are developed and compared for this problem. An application of this model is presented in order to implement a heuristic approach based on the Sample Average Approximation method (SAA) for solving the probabilistic p-center problem in an efficient way.Comment: 32 pages, 1 pictur

Sobre el derecho, la medicina y los cuerpos en transformación. Hacia un modelo normativo de autodeterminación sexual | Law, medicine and changing bodies. Towards a normative model of sexual self-determination

En este trabajo se parte de las tesis de Foucault sobre la integración de ciertos dispositivos de control y de un régimen médico-sexual en el Derecho, que definieron las identidades de los sujetos, para explicar el modo en que estos mecanismos han influido en la regulación jurídica de los cambios de identidad de género. Asimismo, se detalla cómo la medicalización de las identidades por parte del Derecho contradice la evolución del concepto de género. A partir de este análisis, el artículo propone una reflexión sobre algunos cambios legislativos recientes y sobre los puntos de encuentro y desencuentro entre las diversas corrientes al objeto de defender un nue

A mathematical analysis of EDAs with distance-based exponential models

Estimation of Distribution Algorithms have been successfully used to solve permutation-based Combinatorial Optimization Problems. In this case, the algorithms use probabilistic models specifically designed for codifying probability distributions over permutation spaces. One class of these probability models are distance-based exponential models, and one example of this class is the Mallows model. In spite of its practical success, the theoretical analysis of Estimation of Distribution Algorithms for permutation-based Combinatorial Optimization Problems has not been developed as extensively as it has been for binary problems. With this motivation, this paper presents a first mathematical analysis of the convergence behavior of Estimation of Distribution Algorithms based on Mallows models. The model removes the randomness of the algorithm in order to associate a dynamical system to it. Several scenarios of increasing complexity with different fitness functions and initial probability distributions are analyzed. The obtained results show: a) the strong dependence of the final results on the initial population, and b) the possibility to converge to non-degenerate distributions even in very simple scenarios, which has not been reported before in the literature.Spanish Ministry of Science and Innovation through the projects PID2019-104966GB-I00/AEI/10.13039/501100011033, PID2019-104933GB-I00/AEI/10.13039/501100011033, PID2019-106453GA-I00/AEI/10.13039/501100011033 and BCAM Severo Ochoa accreditation SEV-2017-0718; and by the Basque Government through the program BERC 2022-2025 and the projects IT1504-22 and IT1494-22; and by UPV/EHU through the project GIU20/054. Imanol holds a grant from the Department of Education of the Basque Government (PRE_2021_2_0224)

Ceramics with photonic and optical applications

There is a fast growing interest in new applications for advanced ceramic systems in the field of functional materials and in particular for optical materials. Ceramics are entitled to fulfil the gap between glasses and single crystals in the area of photonic materials. The processing versatility and unpaired resistance to high temperature corrosive environments of some ceramics make them good candidates for such applications. However, the critical dependence of the material optical properties on microstructure makes the deep understanding of the processing conditions even more necessary than before for the fabrication of well ordered, transparent, efficient optical ceramics. This review is directed towards ceramists interested in new applications. In the paper we address some fundamental aspects of the relationship between processing, microstructure and optical properties that are illustrated with some examples related with transparent ceramics, glass ceramics, luminescence, random lasers, thermo-emissive applications, scintillators and dielectric metamaterials

The Natural Bias of Artificial Instances

Many exact and metaheuristic algorithms presented in the literature are tested by comparing their performance in different sets of instances. However, it is known that when these sets of instances are generated randomly, they neither have nor fulfill the features the authors believe they do, which implies that wrong conclusions were made. In this paper, we reinforce the importance of analyzing randomly generated instances by sampling the problem coefficients uniformly at random. We generate instances of the Unconstrained Binary Quadratic Problem and the Number Partitioning Problem. In both cases, we verify that the generated set of instances do not represent a uniform set of instances of the problem. We have conducted several experiments to quantify the number of different rankings of solutions that the problems can generate. We have classified those rankings according to how often each ranking is sampled, how many local optimal solutions each ranking has, and how similar they are.PID2019-104966GB-I00, PID2019-104933GB-I00, PID2019-106453GA-I00 funded by MCIN/AEI/10.13039/501100011033, Basque Government through the program BERC 2022–2025, IT1504-22 and IT1494-22; UPV/EHU through GIU20/054. PRE_2021_2_022

A mathematical analysis of edas with distance-based exponential models

Estimation of Distribution Algorithms have been successfully used for solving many combinatorial optimization problems. One type of problems in which Estimation of Distribution Algorithms have presented strong competitive results are permutation-based combinatorial optimization problems. In this case, the algorithms use probabilistic models specifically designed for codifying probability distributions over permutation spaces. One class of these probability models is distance-based exponential models, and one example of this class is the Mallows model. In spite of the practical success, the theoretical analysis of Estimation of Distribution Algorithms for permutation-based combinatorial optimization problems has not been extensively developed. With this motivation, this paper presents a first mathematical analysis of the convergence behavior of Estimation of Distribution Algorithms based on the Mallows model by using an infinite population to associate a dynamical system to the algorithm. Several scenarios, with different fitness functions and initial probability distributions of increasing complexity, are analyzed obtaining unexpected results in some cases