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Drinking water is a vital resource for humanity, and thus, Water Distribution Networks (WDNs) are considered critical infrastructures in modern societies. The operation of WDNs is subject to diverse challenges such as water leakages and contamination, cyber/physical attacks, high energy consumption during pump operation, etc. With model-based methods reaching their limits due to various uncertainty sources, AI methods offer promising solutions to those challenges. In this work, we introduce a Python toolbox for complex scenario modeling \& generation such that AI researchers can easily access challenging problems from the drinking water domain. Besides providing a high-level interface for the easy generation of hydraulic and water quality scenario data, it also provides easy access to popular event detection benchmarks and an environment for developing control algorithms., Comment: Accepted at the Workshop on Artificial Intelligence for Critical Infrastructure (AI4CI 2024) @ IJCAI'24 , Jeju Island, South Korea

A key challenge in designing algorithms for leakage detection and isolation in drinking water distribution systems is the performance evaluation and comparison between methodologies using benchmarks. For this purpose, the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) competition was organized in 2020 with the aim to objectively compare the performance of methods for the detection and localization of leakage events, relying on supervisory control and data acquisition (SCADA) measurements of flow and pressure sensors installed within a virtual water distribution system. Several teams from academia and the industry submitted their solutions using various techniques including time series analysis, statistical methods, machine learning, mathematical programming, met-heuristics, and engineering judgment, and were evaluated using realistic economic criteria. This paper summarizes the results of the competition and conducts an analysis of the different leakage detection and isolation methods used by the teams. The competition results highlight the need for further development of methods for leakage detection and isolation, and also the need to develop additional open benchmark problems for this purpose., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Sanitary Engineering

Numerous real-world problems from a diverse set of application areas exist that exhibit temporal dependencies. We focus on a specific type of time series classification which we refer to as aggregated time series classification. We consider an aggregated sequence of a multi-variate time series, and propose a methodology to make predictions based solely on the aggregated information. As a case study, we apply our methodology to the challenging problem of household water end-use dissagregation when using non-intrusive water monitoring. Our methodology does not require a-priori identification of events, and to our knowledge, it is considered for the first time. We conduct an extensive experimental study using a residential water-use simulator, involving different machine learning classifiers, multi-label classification methods, and successfully demonstrate the effectiveness of our methodology., Comment: 18th International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2022

This paper reports on original results of the Advancing Clinico-Genomic Trials on Cancer integrated project focusing on the design and development of a European biomedical grid infrastructure in support of multicentric, postgenomic clinical trials (CTs) on cancer. Postgenomic CTs use multilevel clinical and genomic data and advanced computational analysis and visualization tools to test hypothesis in trying to identify the molecular reasons for a disease and the stratification of patients in terms of treatment. This paper provides a presentation of the needs of users involved in postgenomic CTs, and presents such needs in the form of scenarios, which drive the requirements engineering phase of the project. Subsequently, the initial architecture specified by the project is presented, and its services are classified and discussed. A key set of such services are those used for wrapping heterogeneous clinical trial management systems and other public biological databases. Also, the main technological challenge, i.e. the design and development of semantically rich grid services is discussed. In achieving such an objective, extensive use of ontologies and metadata are required. The Master Ontology on Cancer, developed by the project, is presented, and our approach to develop the required metadata registries, which provide semantically rich information about available data and computational services, is provided. Finally, a short discussion of the work lying ahead is included., Journal Article, Research Support, Non-U.S. Gov't, SCOPUS: ar.j, info:eu-repo/semantics/published

Magneli phases [A. Magneli, Acta Chem. Scand. 13 (1959) 5] have been introduced as a unique electron conductive and interactive support for electrocatalysis both in hydrogen (HELR) and oxygen (OELR) electrode reactions in water electrolysis and Low Temperature PEM Fuel Cells (LT PEM FC). The Strong Metal-Support Interaction (SMSI) that imposes the former implies: (i) the hypo-hyper-d-interbonding effect and its catalytic consequences, and (ii) the interactive primary oxide (M-OH) spillover from the hypo-d-oxide support as a dynamic electrocatalytic contribution. The stronger the bonding, the more strained appear d-orbitals, thereby the less strong the intermediate adsorptive strength in the rate determining step (RDS), and consequently, the faster the facilitated catalytic electrode reaction arises. At the same time the primary oxide spillover transferred from the hypo-d-oxide support directly interferes and reacts either individually and directly to contribute to finish the oxygen reduction, or with other interactive species, like CO to contribute to the CO tolerance. In such a respect, the conditions to provide Au to act as the reversible hydrogen electrode have been proved either by its potentiodynamic surface reconstruction in a heavy water solution, or by the nanostructured SMSI Au on anatase titania with characteristic strained d-orbitals in such a hypo-hyper-d-interactive bonding (Au/TiO2). In the same context, some spontaneous tendency towards monoatomic network dispersion of Pt upon Magneli phases makes it possible to produce an advanced interactive supported electrocatalyst for cathodic oxygen reduction (ORR). The strained hypo-hyper-d-interelectronic and inter-d-orbital metal/hypo-d-oxide support bonding relative to the strength of the latter, has been inferred to be the basis of the synergistic electrocatalytic effect both in the HELR and ORR.