Behavior patterns in hormonal treatments using fuzzy logic models

Assisted reproductive technologies are a combination of medical strategies designed to treat infertility patients. Ideal stimulation treatment has to be individualized, but one of the main challenges which clinicians face in the everyday clinic is how to select the best medical protocol for a patient. This work aims to look for behavior patterns in this kind of treatments, using fuzzy logic models with the objective of helping gynecologists and embryologists to make decisions that could improve the process of in vitro fertilization. For this purpose, a real-world dataset composed of one hundred and twenty-three (123) patients and five hundred and fifty-nine (559) treatments applied in relation to such patients provided by an assisted reproduction clinic, has been used to obtain the fuzzy models. As conclusion, this work corroborates some known clinic experiences, provides some new ones and proposes a set of questions to be solved in future experiments.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956- C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

Segmented software cost estimation models based on fuzzy clustering

Parametric software cost estimation models are based on mathematical relations, obtained from the study of historical software projects databases, that intend to be useful to estimate the effort and time required to develop a software product. Those databases often integrate data coming from projects of a heterogeneous nature. This entails that it is difficult to obtain a reasonably reliable single parametric model for the range of diverging project sizes and characteristics. A solution proposed elsewhere for that problem was the use of segmented models in which several models combined into a single one contribute to the estimates depending on the concrete characteristic of the inputs. However, a second problem arises with the use of segmented models, since the belonging of concrete projects to segments or clusters is subject to a degree of fuzziness, i.e. a given project can be considered to belong to several segments with different degrees. This paper reports the first exploration of a possible solution for both problems together, using a segmented model based on fuzzy clusters of the project space. The use of fuzzy clustering allows obtaining different mathematical models for each cluster and also allows the items of a project database to contribute to more than one cluster, while preserving constant time execution of the estimation process. The results of an evaluation of a concrete model using the ISBSG 8 project database are reported, yielding better figures of adjustment than its crisp counterpart.Ministerio de Ciencia y Tecnología TIN2004-06689-C0

Smart Face Masks for Covid-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions

Smart sensing technology has been playing tremendous roles in digital healthcare management over time with great impacts. Lately, smart sensing has awoken the world by the advent of Smart Face Masks (SFM) in the global fight against the deadly Coronavirus (Covid-19) pandemic. In turn, a number of research studies on innovative SFM architectures and designs are emerging. However, there is currently no study that has systematically been conducted to identify and comparatively analyze the emerging architectures and designs of SFMs, their contributions, socio-technological implications, and current challenges. In this paper, we investigate the emerging SFMs in response to Covid-19 pandemic and provide a concise review of their key features and characteristics, design, smart technologies, and architectures. We also highlight and discuss the socio-technological opportunities posed by the use of SFMs and finally present directions for future research. Our findings reveal four key features that can be used to evaluate SFMs to include reusability, self-power generation ability, energy awareness and aerosol filtration efficiency. We discover that SFM has potential for effective use in human tracking, contact tracing, disease detection and diagnosis or in monitoring asymptotic populations in future pandemics. Some SFMs have also been carefully designed to provide comfort and safety when used by patients with other respiratory diseases or comorbidities. However, some identified challenges include standards and quality control, ethical, security and privacy concerns

Actividades y resultados del Plan de Innovación Docente para la Participación de Empresas en la Docencia

Participación de Empresas en la Docencia (abreviado como ParED) es el nombre del plan de innovación docente desarrollado durante la segunda mitad del año 2016, en la E.T.S. de Ingeniería Informática de la Universidad de Sevilla, con el objetivo de poner en marcha iniciativas que permitieran adaptar la docencia universitaria con la realidad de las empresas. El objetivo de este artículo es exponer las actividades desarrolladas y realizar un análisis de los resultados obtenidos así como analizar los problemas que surgieron y las lecciones aprendidas de esta experiencia.Participation of Business in Teaching (abbreviated as ParED) is the name of an educational innovation plan. This plan was developed during the second half of t 2016. The goal of ParED was to align university teaching with the reality of the Business. This paper outlines the activities carried out and analyses the results of these activities. This paper also introduces the problems that have arisen and the lessons the authors learned from them.Este trabajo también ha sido apoyado por el proyecto Pololas (TIN2016-76956-C3-2-R) y por la Red SoftPLM (TIN2015-71938-REDT) del Ministerio de Economía y Competitividad

Fuzzy intelligence approach for modeling the migration of contaminants ina reservoir affected by AMD pollution

The Sancho Reservoir, located in the Huelva province (SW Spain), is supplied by the Meca River, which receives water contaminated by mining activities in Tharsis. This study focused on determining the relationship that temperature, pH, and electrical conductivity (EC) had with rainfall. The temperature, pH, and EC were simultaneously measured every 30 min by two probes suspended in the Sancho Reservoir. It was anticipated that the use of fuzzy logic and data mining would lead to a model that would show how the contaminant load evolved over space and time. Similar results were obtained for the two locations, except that the parameters had more outliers near the dam due to the greater distance from the contamination source. As expected, higher pH corresponded with lower EC, since, in the absence of chloride, sulphate was the principal anion. The dependency relationship of the variables as well as the cause–effect relationship with the rate of rainfall was more evident in the up-gradient sampling location than near the dam due to the different residence time and the transit time between the two points

Nanostructure, osteopontin, and mechanical properties of calcitic avian eggshell

Avian (and formerly dinosaur) eggshells form a hard, protective biomineralized chamber for embryonic growth—an evolutionary strategy that has existed for hundreds of millions of years. We show in the calcitic chicken eggshell how the mineral and organic phases organize hierarchically across different length scales and how variation in nanostructure across the shell thicknessmodifies its hardness, elastic modulus, and dissolution properties.We also show that the nanostructure changes during egg incubation, weakening the shell for chick hatching. Nanostructure and increased hardness were reproduced in synthetic calcite crystals grown in the presence of the prominent eggshell protein osteopontin. These results demonstrate the contribution of nanostructure to avian eggshell formation, mechanical properties, and dissolution.This work was supported by a grant from the Canadian Institutes of Health Research (no. MOP-142330) and the Natural Sciences and Engineering Research Council of Canada (NSERC; no. RGPIN-2016-05031) to M.D.M., an NSERC (no. RGPIN-2016-04410) Discovery grant to M.T.H., a Spanish Government grant (CGL2015-64683-P) to A.B.R.-N., an Emmy Noether research grant from the German Research Foundation (no. WO1712/3-1) to S.E.W., and an NSF grant (NSF BMAT; no. 1507736) to J.J.G. M.D.M. is a member of the Fonds de Recherche Quebec–Sante Network for Oral and Bone Health Research and the McGill Centre for Bone and Periodontal Researc

Fuzzy modelling of acid mine drainage environments using geochemical, ecological and mineralogical indicators

Fuzzy logic was applied to model acid mine drainage (AMD) and to obtain a classification index of the environmental impact in a contaminated riverine system. The data set used to develop this fuzzy model (a fuzzy classifier) concerns an abandoned mine in Northern Portugal— Valdarcas mining site. Here, distinctive drainage environments (spatial patterns) can be observed based on the AMD formed in the sulphide-rich waste-dumps. Such environments were established, as the effluent flows through the mining area, using several kinds of indicators. These are physical–chemical, ecological and mineralogical parameters, being expressed in a quantitative or qualitative basis. The fuzzy classifier proposed in this paper is a min– max fuzzy inference system, representing the spatial behaviour of those indicators, using the AMD environments as patterns. As they represent different levels (classes) of contamination, the fuzzy classifier can be used as a tool, allowing a more reasonable approach, compared with classical models, to characterize the environmental impact caused by AMD. In a general way it can be applied to other sites where sulphide-rich waste-dumps are promoting the pollution of superficial water through the generation of AMD

Improvements In The Decision Making In Software Projects

The Simulators of Software Development Projects based on dynamic models have supposed a significant advance in front of the traditional techniques of estimate. These simulators enable to know the evolution of a project before, during and after the execution of the same one. But its use in the estimate of the project before beginning the execution, has been braked by the great number of attributes of the project that it is necessary to know previously. In this paper are presented the improvements that have been added to the simulator developed in our department to facilitate the use of them, and a new improvement obtained when using machine learning and fuzzy logic techniques with the databases generated by the simulator. In this last case, the project manager can know, in function of the decisions that he takes, the level of execution of the project objectives

Migration of pollutants in AMD rivers. Characterization of theTinto River in the generating source and receiving environment

The introduction of acid drainage to the river network is responsible for changing the physico-chemical characteristics of watercourses, increasing acidity in the water, the content of heavy metals and sulphates, and the concentration of metals in their sediments up to extreme values. The main objective of this work is to characterize the behavior of As conditioned by the presence of other elements which are characteristic of AMD pollution, both in the generating milieu, and in the receiving milieu of the Tinto river, and thus to be able to establish the differences in behavior at both sites by using a fuzzy computer tool, PreFurGe, which allows qualitative interpretation of the data recorded in a database relating to the chemistry of water. Fuzzy logic tools allow us to treat large data mass and to propose responses more consistent than those generated with classical statistics, to explain what determines the abundance of each parameter depending on the sampling point, as well as to notice interdependence relationships undetected with correlation analysis for a given watercourse. With this study we observe that the extremely low As values are due to different circumstances at each sampling site: the pH in generating milieu may reach extremely high values while in receiving milieu it does not rise above medium-high values. The differences remain for extremely high As values, proving very much conditioned by the temperature in the generating milieu and only compatible with extremely high values for this, while in the receiving milieu it has barely any influence. It is the redox potential especially that presents a more pronounced difference, while in generating milieu it can have any value except extremely high and low, in receiving milieu we only find extremely low and very concentrated values