Human perception in segmentation of sketches

In this paper, we study the segmentation of sketched engineering drawings into a set of straight and curved segments. Our immediate objective is to produce a benchmarking method for segmentation algorithms. The criterion is to minimise the differences between what the algorithm detects and what human beings perceive. We have created a set of sketched drawings and have asked people to segment them. By analysis of the produced segmentations, we have obtained the number and locations of the segmentation points which people perceive. Evidence collected during our experiments supports useful hypotheses, for example that not all kinds of segmentation points are equally difficult to perceive. The resulting methodology can be repeated with other drawings to obtain a set of sketches and segmentation data which could be used as a benchmark for segmentation algorithms, to evaluate their capability to emulate human perception of sketches

Gastrointestinal helminths in calves and cows in an organic milk production system

The main aim of this study was to determine the distribution of populations of gastrointestinal helminths in lactating crossbred cows and calves during the grazing season in an organic milk production system. In addition, the potential importance of the peripartum in relation to the parasite load was examined. Between January 2007 and December 2008, parasitological fecal examinations were performed on cattle belonging to the Integrated Animal Production Program of Embrapa Agrobiology. The cows' parasite load remained low during the study period, and there were no statistical differences (p > 0.05) in comparisons between the seasons. The average egg count showed a positive correlation (0.80) with the peripartum, such that egg elimination per gram (p < 0.05) was higher during the week of labor than during the pre and postpartum periods. Calves showed low parasite loads, with significantly higher egg elimination (p < 0.05) during the winter. The study indicated that infection with gastrointestinal helminths was not a limiting factor for milk production in the organic system. Specifically, it was concluded that the nematode load can be maintained at moderate levels throughout the production system, even in the absence of anthelmintic treatment

Phosphine Oxide Porous Organic Polymers Incorporating Cobalt(II) Ions: Synthesis, Characterization, and Investigation of H2Production

Suitably functionalized porous matrices represent versatile platforms to support well-dispersed catalytic centers. In the present study, porous organic polymers (POPs) containing phosphine oxide groups were fabricated to bind transition metals and to be investigated for potential electrocatalytic applications. Cross-linking of mono- and di-phosphine monomers with multiple phenyl substituents was subject to the Friedel-Crafts (F-C) reaction and the oxidation process, which generated phosphine oxide porous polymers with pore capacity up to 0.92 cm3/g and a surface area of about 990 m2/g. The formation of the R3P·BH3 borohydride adduct during synthesis allows to extend the library of phosphine-based monomeric entities when using FeCl3. The porous polymers were loaded with 0.8-4.2 w/w % of cobalt(II) and behaved as hydrogen evolution reaction (HER) catalysts with a Faradaic efficiency of up to 95% (5.81 × 10-5 mol H2 per 11.76 C) and a stable current density during repeated controlled potential experiments (CPE), even though with high overpotentials (0.53-0.68 V to reach a current density of 1 mA·cm-2). These studies open the way to the effectiveness of tailored phosphine oxide POPs produced through an inexpensive and ecofriendly iron-based catalyst and for the insertion of transition metals in a porous architecture, enabling electrochemically driven activation of small molecules

CONGAS: a collaborative ontology development framework based on Named GrAphS

The process of ontology development involves a range of skills and know-how often requiring team work of different people, each of them with his own way of contributing to the definition and formalization of the domain representation. For this reason, collaborative development is an important feature for ontology editing tools, and should take into account the different characteristics of team participants, provide them with a dedicated working environment allowing to express their ideas and creativity, still protecting integrity of the shared work. In this paper we present CONGAS, a collaborative version of the Knowledge Management and Acquisition platform Semantic Turkey which, exploiting the potentialities brought by recent introduction of context management into RDF triple graphs, offers a collaborative environment where proposals for ontology evolution can emerge and coexist, be evaluated by team users, trusted across different perspectives and eventually converged into the main development stream

Validation and reconstruction of flow meter data in the Barcelona water distribution network

12 páginas, 16 figuras, 1 tabla.-- El PDF es la versión pre-print.-- et al.This paper presents a signal analysis methodology to validate (detect) and reconstruct the missing and false data of a large set of flow meters in the telecontrol system of a water distribution network. The proposed methodology is based on two time-scale forecasting models: a daily model based on a ARIMA time series, while the 10-min model is based on distributing the daily flow using a 10-min demand pattern. The demand patterns have been determined using two methods: correlation analysis and an unsupervised fuzzy logic classification, named LAMDA algorithm. Finally, the proposed methodology has been applied to the Barcelona water distribution network, providing very good results.This work is part of a applied research project granted by ADASA and AGBAR companies. The authors also wish to thank the support received by the Research Commission of the Generalitat of Catalunya (Group SAC Ref. 2009 SGR 1491) and by CICYT (Ref. HYFA DPI2008-01996 and WATMAN DPI2009-13744) of Spanish Ministry of Education.Peer reviewe

Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR

myCBR is a freely available tool for rapid prototyping of similarity-based retrieval applications such as case-based product recommender systems. It provides easy-to-use model generation, data import, similarity modelling, explanation, and testing functionality together with comfortable graphical user interfaces. SCOOBIE is an ontology-based information extraction system, which uses symbolic background knowledge for extracting information from text. Extraction results depend on existing knowledge fragments. In this paper we show how to use SCOOBIE for generating cases from texts. More concrete we use ontologies of the Web of Data, published as so called Linked Data interlinked with myCBR’s case model. We present a way of formalising a case model as Linked Data ready ontology and connect it with other ontologies of the Web of Data in order to get richer cases

Validation and reconstruction of flow meter data in the Barcelona water distribution network

This paper presents a signal analysis methodology to validate (detect) and reconstruct the missing and false data of a large set of flow meters in the telecontrol system of a water distribution network. The proposed methodology is based on two time-scale forecasting models: a daily model based on a ARIMA time series, while the 10-min model is based on distributing the daily flow using a 10-min demand pattern. The demand patterns have been determined using two methods: correlation analysis and an unsupervised fuzzy logic classification, named LAMDA algorithm. Finally, the proposed methodology has been applied to the Barcelona water distribution network, providing very good results.Peer ReviewedPostprint (author’s final draft