Low-Cost Piezoelectric Sensors for Time Domain Load Monitoring of Metallic Structures During Operational and Maintenance Processes

The versatility of piezoelectric sensors in measurement techniques and their performance in applications has given rise to an increased interest in their use for structural and manufacturing component monitoring. They enable wireless and sensor network solutions to be developed in order to directly integrate the sensors into machines, fixtures and tools. Piezoelectric sensors increasingly compete with strain-gauges due to their wide operational temperature range, load and strain sensing accuracy, low power consumption and low cost. This research sets out the use of piezoelectric sensors for real-time monitoring of mechanical strength in metallic structures in the ongoing operational control of machinery components. The behaviour of aluminium and steel structures under flexural strength was studied using piezoelectric sensors. Variations in structural behaviour and geometry were measured, and the load and μstrains during operational conditions were quantified in the time domain at a specific frequency. The lead zirconium titanate (PZT) sensors were able to distinguish between material types and thicknesses. Moreover, this work covers frequency selection and optimisation from 20 Hz to 300 kHz. Significant differences in terms of optimal operating frequencies and sensitivity were found in both structures. The influence of the PZT voltage applied was assessed to reduce power consumption without signal loss, and calibration to μstrains and loads was performed.This research was funded by Basque Government, grant number KK-2019/00051-SMARTRESNAK and by the European Commission, grant number 869884- RECLAIM

Diseño de estrategias orientadas a la promoción de la salud y a las medidas de prevención y control de los riesgos laborales en el teletrabajo para el área administrativa y de producción de la empresa tecnológica Grupodot para el segundo semestre del año 2022

no aplicaGrupodot es una agencia de marketing, una compañía basada en el diseño de interacción y avanzada. Su enfoque está basado en la conceptualización y el despliegue de servicios que optimicen la relación entre las empresas y sus usuarios, respondiendo a las necesidades de cada industria con un enfoque integral. Cuenta con un equipo multidisciplinario, con los mejores profesionales en diseño, desarrollo, gestión, comunicación, análisis de datos y marketing, posicionándose como la agencia líder en data analytics y machine learning de hispanoamérica. (grupodot agencia, 2022). Basado en un estudio realizado a 100 empleados de la compañía en la modalidad remota, se diseñan estrategias en pro de mejorar la gestión de procesos en la organización orientadas a la promoción de la salud y la prevención e intervención de las condiciones de riesgo presentes en el lugar de trabajo, al implementar la modalidad de teletrabajo y su impacto en la productividad de la organización Grupodot.Grupodot is a marketing agency, a company based on advanced interaction design. its approach is based on the conceptualization and deployment of services that optimize the relationship between companies and their users, responding to the needs of each industry with a comprehensive approach. it has a multidisciplinary team, with the best professionals in design, development, management, communication, data analysis and marketing, positioning itself as the leading agency in data analytics and machine learning in latin america. (grupodot agency, 2022). Based on a study carried out on 100 company employees in the remote mode, strategies are designed to improve the management of processes in the organization aimed at promoting health and the prevention and intervention of risk conditions present in the workplace, by implementing the teleworking modality and its impact on the productivity of the grupodot organization. keywords: human talent, process management, strategic management, working conditions, organizational climate, productivity, decision making, risk

Continuous Phase Measurement in the W7-X Infrared Interferometer by Means of a FPGA and High-Speed ADCs.

Interferometry is used for measuring line average electronic densities in fusion plasmas. The W7-X stellarator will employ a two-color CO2 (10.591 m) and CO (5.295 m) heterodyne-infrared interferometer as an electronic density measurement diagnostic. The frequency displacement is 40 MHz for the CO2 wavelength and 25 MHz for the CO, so these values will fix the heterodyne frequencies. Because the frequency gap between the two carriers is wide enough and the detector sensitivity is similar for both wavelengths, it is possible to use a single detector for the two signals; nevertheless, they should be split with filters. Traditionally, the intermediate-frequency signals should be filtered, downconverted to a lower frequency by the use of analog circuitry, and then processed. A new approach is proposed. The intermediate-frequency signals are directly sampled by means of high-speed analog-to-digital converters followed by a digital diplexer and a specific phase-meter processor implemented in a field-programmable gate array. Preliminary results from the W7-X infrared interferometer prototype, without plasma, are presented

Development of Efficient FPGA-Based Multi-Channel Phase Meters for IR-Interferometers

Infrared (IR) interferometry is a method for measuring the line-electron density of fusion plasmas. The significant performance achieved by FPGAs in solving digital signal processing tasks advocates the use of this type of technology in two-color IR interferometers of modern stellarators, such as the TJ-II (Madrid, Spain) and the future W7-X (Greifswald, Germany). In this work the implementation of a line-average electron density measuring system in an FPGA device is described. Several optimizations for multichannel systems are detailed and test results from the TJ-II as well as from a W7-X prototype are presented

Framework to Evaluate Emerging Systems Designed to Health Field

In recent years, several information and communication technology systems have emerged as tools to improve sleep quality. Research reveals that poor sleep quality may produce irritability and deficits in performance, concentration, and learning ability in the short term, and is associated with chronic disease in the long term. ICT proposals range from the old Polysomnography (PSG) to innovative systems, such as wearable devices, smartphone applications, and suites of sensors embedded in the users’ environment. Since these technological developments concern a health issue, they have raised important questions regarding their reliability and the level of rigor of the evaluations to which they are submitted. We found that some of the emerging systems that we studied, do not meet the requirements that health science demands to be accepted as clinical tools. The rationale behind this apparent weakness is explained with arguments from the field of evaluations for health interventions and evaluation of technological developments. We propose a framework to evaluate this kind of systems through appropriate scientific methods that provide valuable information to the research. These methods must be performed while designs mature and the feasibility of rigorous evaluations became appropriate

Ranking and selection of unsupervised learning marketing segmentation

This research paper has been partially conducted during a three-months visiting period by German Sanchez-Hernandez to the Centre for Computational Intelligence (CCI).NOTICE: this is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Knowledge-Based Systems, 44, pp. 20–33 http://dx.doi.org/10.1016/j.knosys.2013.01.012This paper addresses the problem of choosing the most appropriate classification from a given set of classifications of a set of patterns. This is a relevant topic on unsupervised systems and clustering analysis because different classifications can in general be obtained from the same data set. The provided methodology is based on five fuzzy criteria which are aggregated using an Ordered Weighted Averaging (OWA) operator. To this end, a novel multi-criteria decision making (MCDM) system is defined, which assesses the degree up to which each criterion is met by all classifications. The corresponding single evaluations are then proposed to be aggregated into a collective one by means of an OWA operator guided by a fuzzy linguistic quantifier, which is used to implement the concept of fuzzy majority in the selection process. This new methodology is applied to a real marketing case based on a business to business (B2B) environment to help marketing experts during the segmentation process. As a result, a segmentation containing three segments consisting of 35, 98 and 127 points of sale respectively is selected to be the most suitable to endorse marketing strategies of the firm. Finally, an analysis of the managerial implications of the proposed methodology solution is provided.This work is supported by the SENSORIAL Research Project (TIN2010-20966- C02-01, 02), funded by the Spanish Ministry of Science and Information Technology

Farm management to mitigate disease and financial risks: optimal combination of stocking density, initial culture time, and length of grow-out period for a semi-intensive shrimp farm in northwest Mexico

Low yields caused by viral diseases and their financial consequences are the most important risks jeopardizing commercial shrimp culture in Mexico. Hence, farmers are continuously testing different production strategies to keep their operations into profitable margins. An optimization model was designed based on a farm's (139 ha) database (2001-2005) to find the strategy that maximizes profit resulting from the optimal combination of three decision variables; stocking density, length of grow-out period and initial culture time. The model interface is in Excel" using risk analysis software (@RISK", RISKOPTIMIZER"). Five non-linear multiple regression models were created to describe growth at different stocking densities (6-9Pl/m2, 10-14, 15-19, 20-24, 25-30), randomizing mortality rates, temperatures and feeding ratios; the model was optimized with genetic algorithm-based techniques. Results for production scenarios with the five stocking densities and two initial culture periods March-April and May-June, showed similar harvest weights (min 18g - max 22) to maximize profit but different length of grow-out period (18-22 weeks, 16-19) favoring the second stocking period due to higher survival rates (33%-41%, 38%-45%) and yields (0.69-1.84 tons, 0.74-2.1). Also, the probability of achieving an operation profit margin ratio of 35% was higher (61%, 97%) with less cost ($409,834 U.S. dollar,$398,895) and higher profits ($263,356,$325,512). Optimal solution points out stocking ponds at warmer temperatures (May-June), what brings about reaching marketable sizes faster, reducing operation costs and mainly, reducing the intrinsic risk of longer culture periods. The effect of stocking density is not conclusive. These results confirm the current industry trend to perform one production cycle starting in warmer months as a way to reduce disease and financial risks

X-chromosome SNP analyses in 11 human Mediterranean populations show a high overall genetic homogeneity except in North-west Africans (Moroccans)

Due to its history, with a high number of migration events, the Mediterranean basin represents a challenging area for population genetic studies. A large number of genetic studies have been carried out in the Mediterranean area using different markers but no consensus has been reached on the genetic landscape of the Mediterranean populations. In order to further investigate the genetics of the human Mediterranean populations, we typed 894 individuals from 11 Mediterranean populations with 25 single-nucleotide polymorphisms (SNPs) located on the X-chromosome. A high overall homogeneity was found among the Mediterranean populations except for the population from Morocco, which seemed to differ genetically from the rest of the populations in the Mediterranean area. A very low genetic distance was found between populations in the Middle East and most of the western part of the Mediterranean Sea.A higher migration rate in females versus males was observed by comparing data from X-chromosome, mt-DNA and Y-chromosome SNPs both in the Mediterranean and a wider geographic area.Multilocus association was observed among the 25 SNPs on the X-chromosome in the populations from Ibiza and Cosenza. Our results support both the hypothesis of (1) a reduced impact of the Neolithic Wave and more recent migration movements in NW-Africa, and (2) the importance of the Strait of Gibraltar as a geographic barrier. In contrast, the high genetic homogeneity observed in the Mediterranean area could be interpreted as the result of the Neolithic wave caused by a large demic diffusion and/or more recent migration events. A differentiated contribution of males and females to the genetic landscape of the Mediterranean area was observed with a higher migration rate in females than in males. A certain level of background linkage disequilibrium in populations in Ibiza and Cosenza could be attributed to their demographic background