Extraction of the beam elastic shape from uncertain FBG strain measurement points

Aim of the present paper is the analysis of the strain along the beam that is equipped with Glass Fibers Reinforced Polymers (GFRP) with an embedded set of optical Fiber Bragg Grating sensors (FBG), in the context of a project to equip with these new structural elements an Italian train bridge. Different problems are attacked, and namely: (i)during the production process [1] it is difficult to locate precisely the FBG along the reinforcement bar, therefore the following question appears: How can we associate the strain measurements to the points along the bar? Is it possible to create a signal analysis procedure such that this correspondence is found?(ii)the beam can be inflected and besides the strain at some points, we would like to recover the elastic shape of the deformed beam that is equipped with the reinforcement bars. Which signal processing do we use to determine the shape of the deformed beam in its inflection plane?(iii)if the beam is spatially inflected, in two orthogonal planes, is it possible to recover the beam spatial elastic shape? Object of the paper is to answer to these questions

Optimization of a new extraction technique for analysis of verbenone and cis-verbenol in pine seeds

Results from a systematic study of the factors affecting extraction of cis-verbenol and verbenone from pine seeds are presented. Five extraction conditions were investigated: extraction solvent, method of extraction, extraction temperature, volume of solvent, and the ratio of the mass of sample to the amount of extraction solvent

Information extraction

In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that expansion of concepts plays an important role in thinking, so we study the expansion of knowledge graphs to use context information for reasoning and merging of templates

Optimizing a sustainable ultrasound assisted extraction method for the recovery of polyphenols from lemon by-products:comparison with hot water and organic solvent extractions

Response surface methodology (RSM) based on a three-factor and three-level Box–Behnken design was employed for optimizing the aqueous ultrasound-assisted extraction (AUAE) conditions, including extraction time (35–45 min), extraction temperature (45–55 °C) and ultrasonic power (150–250 W), for the recovery of total phenolic content (TPC) and rutin from lemon by-products. The independent variables and their values were selected on the basis of preliminary experiments, where the effects of five extraction parameters (particle size, extraction time and temperature, ultrasonic power and sample-to-solvent ratio) on TPC and rutin extraction yields were investigated. The yields of TPC and rutin were studied using a second-order polynomial equation. The optimum AUAE conditions for TPC were extraction time of 45 min, extraction temperature of 50 °C and ultrasonic power of 250 W with a predicted value of 18.10 ± 0.24 mg GAE/g dw, while the optimum AUAE conditions for rutin were extraction time of 35 min, extraction temperature of 48 °C and ultrasonic power of 150W with a predicted value of 3.20 ± 0.12 mg/g dw. The extracts obtained at the optimum AUAE conditions were compared with those obtained by a hot water and an organic solvent conventional extraction in terms of TPC, total flavonoid content (TF) and antioxidant capacity. The extracts obtained by AUAE had the same TPC, TF and ferric reducing antioxidant power as those achieved by organic solvent conventional extraction. However, hot water extraction led to extracts with the highest flavonoid content and antioxidant capacity. Scanning electron microscopy analysis showed that all the extraction methods led to cell damage to varying extents

Extraction of tocopherol-enriched oils from Kalahari melon and roselle seeds by supercritical fluid extraction (SFE-CO2).

Tocopherol-enriched oil was extracted by supercritical fluid extraction of carbon dioxide (SFE-CO2) from Kalahari melon and roselle seeds. The SFE-CO2 process was optimised using response surface methodology(RSM) with central composite design (CCD). Three SFE-CO2 parameters namely extracting pressure,extracting temperature, and flow rate of carbon dioxide were examined. The optimal SFE-CO2 conditions were determined and the quadratic response surfaces were drawn from the mathematical models. The optimal SFE-CO2 conditions for the extraction tocopherol-enriched oil from Kalahari melon seeds were: extracting pressure 290 bar, extracting temperature 58C, and flow rate of carbon dioxide 20 ml/min. The optimum conditions for roselle seeds were extracting pressure 200 bar, extracting temperature 80C, and flow rate of carbon dioxide 20 ml/min. These optimum conditions yielded tocopherol concentration of 274.74 and 89.75 mg/100 g oil from Kalahari seed and roselle seed, respectively. No significant(P > 0.05) differences were obtained between the experimental and predicted values

Evolutionary algorithms for definition extraction

Books and other text-based learning material contain implicit information which can aid the learner but which usually can only be accessed through a semantic analysis of the text. Definitions of new concepts appearing in the text are one such instance. If extracted and presented to the learner in form of a glossary, they can provide an excellent reference for the study of the main text. One way of extracting definitions is by reading through the text and annotating definitions manually — a tedious and boring job. In this paper, we explore the use of machine learning to extract definitions from non-technical texts, reducing human expert input to a minimum. We report on experiments we have conducted on the use of genetic programming to learn the typical linguistic forms of definitions and a genetic algorithm to learn the relative importance of these forms. Results are very positive, showing the feasibility of exploring further the use of these techniques in definition extraction. The genetic program is able to learn similar rules derived by a human linguistic expert, and the genetic algorithm is able to rank candidate definitions in an order of confidence.peer-reviewe

New Resources and Perspectives for Biomedical Event Extraction

Event extraction is a major focus of recent work in biomedical information extraction. Despite substantial advances, many challenges still remain for reliable automatic extraction of events from text. We introduce a new biomedical event extraction resource consisting of analyses automatically created by systems participating in the recent BioNLP Shared Task (ST) 2011. In providing for the first time the outputs of a broad set of state-ofthe-art event extraction systems, this resource opens many new opportunities for studying aspects of event extraction, from the identification of common errors to the study of effective approaches to combining the strengths of systems. We demonstrate these opportunities through a multi-system analysis on three BioNLP ST 2011 main tasks, focusing on events that none of the systems can successfully extract. We further argue for new perspectives to the performance evaluation of domain event extraction systems, considering a document-level, “off-the-page ” representation and evaluation to complement the mentionlevel evaluations pursued in most recent work.