3 resultados para Intensity ratios
em Instituto Politécnico do Porto, Portugal
Resumo:
The World Business Council for Sustainable Development (WBCSD) defines Eco-Efficiency as follows: ‘Eco- Efficiency is achieved by the delivery of competitively priced-goods and services that satisfy human needs and bring quality of life, while progressively reducing ecological impacts and resource intensity throughout the life-cycle to a level at least in line with the earth’s estimated carrying capacity’. Eco-Efficiency is under this point of view a key concept for sustainable development, bringing together economic and ecological progress. Measuring the Eco-Efficiency of a company, factory or business, is a complex process that involves the measurement and control of several and relevant parameters or indicators, globally applied to all companies in general, or specific according to the nature and specificities of the business itself. In this study, an attempt was made in order to measure and evaluate the eco-efficiency of a pultruded composite processing company. For this purpose the recommendations of WBCSD [1] and the directives of ISO 14301 standard [2] were followed and applied. The analysis was restricted to the main business branch of the company: the production and sale of standard GFRP pultrusion profiles. The main general indicators of eco-efficiency, as well as the specific indicators, were defined and determined according to ISO 14031 recommendations. With basis on indicators’ figures, the value profile, the environmental profile, and the pertinent eco-efficiency’s ratios were established and analyzed. In order to evaluate potential improvements on company eco-performance, new indicators values and ecoefficiency ratios were estimated taking into account the implementation of new proceedings and procedures, both in upstream and downstream of the production process, namely: a) Adoption of new heating system for pultrusion die in the manufacturing process, more effective and with minor heat losses; b) Implementation of new software for stock management (raw materials and final products) that minimize production failures and delivery delays to final consumer; c) Recycling approach, with partial waste reuse of scrap material derived from manufacturing, cutting and assembly processes of GFRP profiles. In particular, the last approach seems to significantly improve the eco-efficient performance of the company. Currently, by-products and wastes generated in the manufacturing process of GFRP profiles are landfilled, with supplementary added costs to this company traduced by transport of scrap, landfill taxes and required test analysis to waste materials. However, mechanical recycling of GFRP waste materials, with reduction to powdered and fibrous particulates, constitutes a recycling process that can be easily attained on heavy-duty cutting mills. The posterior reuse of obtained recyclates, either into a close-looping process, as filler replacement of resin matrix of GFRP profiles, or as reinforcement of other composite materials produced by the company, will drive to both costs reduction in raw materials and landfill process, and minimization of waste landfill. These features lead to significant improvements on the sequent assessed eco-efficiency ratios of the present case study, yielding to a more sustainable product and manufacturing process of pultruded GFRP profiles.
Resumo:
In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.
Resumo:
This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.