Abstract
Rendering photorealistic images is a costly process which can take up to several days in the case of high quality images. In most cases, the task of sampling the incident radiance function to evaluate the illumination integral is responsible for an important share of the computation time. Therefore, to reach acceptable rendering times, the illumination integral must be evaluated using a limited set of samples. Such a restriction raises the question of how to obtain the most accurate approximation possible with such a limited set of samples. One must thus ensure that sampling produces the highest amount of information possible by carefully placing and weighting the limited set of samples. Furthermore, the integral evaluation should take into account not only the information brought by sampling but also possible information available prior to sampling, such as the integrand smoothness. This idea of sparse information and the need to fully exploit the little information available is present throughout this book. The presented methods correspond to the state-of-the-art solutions in computer graphics, and take into account information which had so far been underexploited (or even neglected) by the previous approaches. The intended audiences are Ph.D. students and researchers in the field of realistic image synthesis or global illumination algorithms, or any person with a solid background in graphics and numerical techniques. Table of Contents: Introduction / Spherical Fibonacci Point Sets for QMC Estimates of Illumination Integrals / Bayesian Monte Carlo for Global Illumination / Bibliography / Authors' Biographies Copyright © 2015 by Morgan & Claypool.

Abstract
The society and technologies evolution has resulted in a trend towards a growing amount of data stored by organizations and of the needs inherent to the analysis of that same data, in order to obtain information and knowledge generation. Based on this assumption it became critical to use new and more efficient technologies for processing that data in order to be able to get quality information in a timely manner. In order to meet the previously identified needs, various types of systems have emerged, whose features incorporate data processing functions and obtaining information for supporting decision-making processes. Examples of such systems are the DSS and the use of BI architectures. Given that currently many of the organizations services are supported by the existent IT infrastructure, it is necessary that these are suitable for the supporting the proper functioning of the available services. Assuming the previous concerns, the team inherent to this article assumed as very important to conceptualise a decision support system to address this adequate dimensioning of a University IT infrastructure. In order to achieve this goal, the Information and Communications Services (SIC) of the University of Tras-os-Montes e Alto Douro (UTAD) were used. Through the implementation of this decision support system, the SIC/UTAD improved their ability to make more informed and conscious decisions, thus optimizing and control more effectively the UTAD IT infrastructure.

Abstract

Abstract
The practice of harmonic mixing is a technique used by DJs for the beat-synchronous and harmonic alignment of two or more pieces of music. In this paper, we present a new harmonic mixing method based on psychoacoustic principles. Unlike existing commercial DJ-mixing software which determine compatible matches between songs via key estimation and harmonic relationships in the circle of fifths, our approach is built around the measurement of musical consonance at the signal level. Given two tracks, we first extract a set of partials using a sinusoidal model and average this information over sixteenth note temporal frames. Then within each frame, we measure the consonance between all combinations of dyads according to psychoacoustic models of roughness and pitch commonality. By scaling the partials of one track over ± 6 semitones (in 1/8th semitone steps), we can determine the optimal pitch-shift which maximises the consonance of the resulting mix. Results of a listening test show that the most consonant alignments generated by our method were preferred to those suggested by an existing commercial DJ-mixing system.

Abstract
The ability to select the most appropriate materials for a given application is the fundamental challenge faced by a design engineer. The objective of any material selection procedure is to identify appropriate selection criteria and to obtain the most appropriate combination of criteria in conjunction with requirements. Hence, selection of material is a multicriteria decision making problem. This study investigates and evaluates critical material selection criteria in a priority framework using the fuzzy Delphi-analytical hierarchy process method to overcome all shortcomings from AHP and Delphi methods that are common in material selection problem. 75 of the most important criteria for material selection have been collected from the literature. These criteria have been questioned in automobile interior design firms in Iran for car dashboard design. This ranking method would help product designers to decide on appropriate materials in a consistent method. Results indicate that "general" criteria such as availability, quality, risk, and technology are the most important criteria from the viewpoint of Iranian car manufacturers. Other criteria such as financial, technical, social and environmental, and sensorial criteria are relatively important in subsequent ranks.

Abstract
In the decades to come spatial limitation poses a major challenge for islands, especially where tourism dominates and many heritage and natural conservation sites exist. Simultaneously, alternatives to lower energy import dependency are sought. Since onshore technologies are confronted by spatial limitation, the focus might shift towards integrating offshore technologies. Although most of those technologies lack market maturity, the benefit to be installed (far) off the coast is immense. Yet, it is a challenge to select the most appropriate technology for any given site location. Thereby, it is not pre-dominantly a matter of economic and environmental concerns, rather than an assessment of site conditions and resource characteristics. A set of indicators for, both, conditions and characteristics has been established that allows pre-selecting and comparing the suitability of various offshore technologies. Hence, energy planners will be able to select from the most appropriate technologies when planning for a sustainable future. © 2015 Taylor & Francis Group, London.