Loading...
Research Project
Center for Mathematics, Fundamental Applications and Operations Research
Funder
Authors
Publications
A strategy to assess water meter performance
Publication . Cordeiro, Clara; Borges, Ana; Ramos, Maria do Rosário
Apparent water losses can be problematic to water companies’ revenues. This type of loss is very difficult to detect and quantify and is often associated with water meter anomalies. This study was motivated by a water company’s challenge that links a decrease in water consumption to water meters’ malfunction. The aim is to develop a strategy to detect decreasing water usage patterns, contributing to meter performance assessment. The basis of the approach is a combination of statistical methods. First, the time series of billed water consumption is decomposed using Seasonal-Trend decomposition based on Loess. Next, breakpoint analysis is performed on the seasonally adjusted time series. After that, the Mann–Kendall test and Sen’s slope estimator are used to analyze periods of progressive decrease changes in water consumption, defined by breakpoints. A quantitative indicator of this change is proposed. The strategy was successfully applied to eight-time series of water consumption from the Algarve, Portugal.
Typability and type inference in atomic polymorphism
Publication . Protin, M. Clarence; Ferreira, Gilda
It is well-known that typability, type inhabitation and type inference are
undecidable in the Girard-Reynolds polymorphic system F. It has recently been proven
that type inhabitation remains undecidable even in the predicative fragment of system F
in which all universal instantiations have an atomic witness (system Fat). In this paper we
analyze typability and type inference in Curry style variants of system Fat and show that
typability is decidable and that there is an algorithm for type inference which is capable of
dealing with non-redundancy constraints.
Organizational Units
Description
Keywords
Contributors
Funders
Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
6817 - DCRRNI ID
Funding Award Number
UIDB/04561/2020