Implicit and hybrid methods for attribute weighting in multi-attribute decision-making: a review study

Artificial Intelligence Review - Attribute weighting is a task of paramount relevance in multi-attribute decision-making (MADM). Over the years, different approaches have been developed to face...     

Algorithms for processing the group K nearest-neighbor query on distributed frameworks

Distributed and Parallel Databases - Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum...     

Does maintainability relate to the energy consumption of software? A case study

Software Quality Journal - Energy consumption of software has been becoming increasingly significant, since it can vary according to how the software has been developed. In recent years, developers...     

Extension of belief functions to infinite-valued events

We generalise belief functions to many-valued events which are represented by elements of Lindenbaum algebra of infinite-valued ?ukasiewicz propositional logic. Our approach is based on mass assignments used in the Dempster–Shafer theory of evidence. A generalised belief function is totally monotone and it has Choquet integral representation with respect to a unique belief measure on Boolean events.     

An algorithm for solving sparse Nonlinear Least Squares problems

We introduce a new method for solving Nonlinear Least Squares problems when the Jacobian matrix of the system is large and sparse. The main features of the new method are the following:

1. The Gauss-Newton equation is “partially” solved at each iteration using a preconditioned Conjugate Gradient algorithm.
2. The new point is obtained using a two-dimensional trust region scheme, similar to the one introduced by Bulteau and Vial.

We prove global and local convergence results and we present some numerical experiments.     

Current oscillations in austenitic stainless steel induced by the presence of chloride ions

The conditions for current oscillations in austenitic stainless steel (AISI Type 303) in 1M H₂SO₄ containing Cl^? ions are given. The periodic oscillations are produced in a close potential range determined at the active-passive transition region. It requires a non-homogeneous distribution of inclusions and carbides at the metal surface and a concentration range of Cl^? ion where active and passive areas coexist on the metal surface. The constraints at the surface determining these two regions are related to the Cl^? ion competitive adsorption and the local accumulation of corrosion products. Electrochemical data and SEM observations are correlated.     

Determination of the solubility parameter of poly(ethylene oxide) at 25°C by gas-liquid chromatography

The solubility parameter of poly(ethylene oxide) at 25°C has been determined using the method developed by DiPaola-Baranyi and Guillet, by the extrapolation of the values of the interaction parameter χ, at high temperatures, ranging from 70°–90°, 90°–110° and 110°–130°C down to 25°C. The values of the solubility parameter obtained, depending on the temperature ranges employed, are 9.8, 9.9 and 10.1, respectively.     

Surface Areas of Nitrated Hydrotalcites

Hydrotalcites in the nitrate form were prepared using microwave irradiation in the hydrotreatment step. The surface area (BET) of nitrated hydrotalcites was evaluated. Solids were characterized by atomic absorption, X-ray diffraction and BET analysis. Thermal pretreatment temperature determined the surface area of the hydrotalcites.     

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.     

Analysis of pentasodium triphosphate hydration kinetics

The present work analyzes the effect of various factors on the hydration of pentasodium triphosphate. The experimental method is based on application of the hydration test. Technical-quality products with different proportions of phase I and phase II have been used. The variables studied are phase I/phase II ratio, initial temperature, particle size, stirring rate and composition of the slurry (presence of hexahydrate crystals and water hardness). The results have been discussed according to a kinetics model that includes a series of stages of a physical nature (dissolution of anhydrous salt and the crystallization of the hexahydrate), as well as of a chemical nature (solvation of the ions in solution). Crystallization of the hexahydrate may be the controlling stage in the process.