Predictive Model of Humidity in Greenhouses Through Fuzzy Inference Applying Optimization Methods

Este documento presenta los resultados para predicción humedad relativa interna en invernaderos, permitiendo describir su comportamiento de forma fácil, sencilla e interpretable para personas interesadas en actividades agrícolas, sin requerir conocimiento especifico sobre el manejo de herramientas de procesamiento de colecciones de datos. Se definen sistemas de inferencia difusa optimizados mediante varios métodos y algoritmos, que obtienen el mayor grado de interpretabilidad y precisión para facilitar el seguimiento y control, implementado mediante herramientas computacionales en ambientes de invernadero. La solución proporciona dos modelos de sistemas de inferencia difusa, dependiendo de los datos disponibles en el entorno de invernadero, optimizados mediante algoritmo genético y de punto interior aplicando una estrategia híbrida, uno de los modelos se basa en datos históricos de humedad relativa y usa sistemas de inferencia difusa tipo ANFIS, el otro basado en variables correlacionadas con la humedad relativa a partir de sistemas de inferencia difusa tipo Mamdani, ambos proporcionan resultados con alto grado de precisión e interpretabilidad.This document presents the results for prediction of internal relative humidity in greenhouses, allowing its behavior to be described in an easy, simple and interpretable way for people interested in agricultural activities, without requiring specific knowledge about handling data collection processing tools. Optimized fuzzy inference systems are defined using various methods and algorithms, which obtain the highest degree of interpretability and precision to facilitate monitoring and control, implemented using computational tools in greenhouse environments. The solution provides two models of fuzzy inference systems, depending on the data available in the greenhouse environment, optimized by means of a genetic and interior point algorithm applying a hybrid strategy, one of the models is based on historical data of relative humidity and uses systems ANFIS-type fuzzy inference systems, the other based on variables correlated with relative humidity from Mamdani-type fuzzy inference systems, both provide results with a high degree of precision and interpretability

Environment humidity and temperature prediction in agriculture using Mamdani inference systems

This paper presents the results of a humidity and temperature prediction model in the environment for agriculture, using diffuse sets and optimizing their parameters by heuristic methods, such as genetic algorithms, and exact methods such as Quasi-Newton. It has been identified that non-specialized users could have difficulties in understanding the system dynamics and the behavior of variables over time. The aim of this research is obtain models with a high level of interpretability and accuracy that allows predicting the temperature and humidity values for the environment. The use of fuzzy logic to present a solution has great advantages as this system is highly rated for interpretability. Furthermore, by relating the obtained values for environment humidity and temperature to qualitative categories as high, medium or low, it allows non-specialized users to have a better understanding of the system dynamics. Two optimization techniques are applied to two different diffuse sets that allow the prediction of the humidity and temperature. It is found that the best implementation involves a Mamdani fuzzy inference system optimized with Quasi-Newton algorithm that uses a set of initial values attained through a previous optimization process with a genetic algorithm

Ontology and framework for semantic labelling of document data and software methods

We present a metadata labelling framework for datasets, software tools, and workflows. An ontology for document image analysis was developed with deep support for historical data. An accompanying open source software framework was implemented to enable ontology editing, data and method annotation, workflow composition, and semantic search. A wide range of examples is used to illustrate real-world application

Predicción rendimiento estudiantes pruebas saber pro en pandemia junto con las características socioeconómicas: Prediction of student performance saber pro test in pandemic together with socioeconomic characteristics

El propósito del presente artículo de investigación es exponer los resultadosobtenidos al aplicar la minería de datos al ámbito educativo de las pruebas saber pro obtenidasen épocas de pandemia del año 2020 con el objeto de determinar las variables más influyentesen el desempeño de los estudiantes y como se vieron afectadas por la pandemia. Para talefecto se utilizaron los resultados obtenidos en el año 2019 y 2020, aplicando la metodologíaCRISP-DM, la cual es un referente en el ámbito de minería de datos. Se realizó un procesode selección inicial de atributos teniendo en cuenta aquellos que en la literatura los autoresencontraron relevantes tales como la información socioeconómica, hábitos de estudio, entreotros. Se procedió a limpiar y transformar en un repositorio de datos con los resultadosobtenidos en estas pruebas y se aplicó la técnica de predicción basada redes neuronalesprofundas y regresión lineal para evidenciar el comportamiento a nivel de predicción de losatributos seleccionados. Se obtuvo que los atributos que influyen de manera importante enlos procesos de predicción son los asociados ..

Measurement of the W gamma Production Cross Section in Proton-Proton Collisions at root s=13 TeV and Constraints on Effective Field Theory Coefficients

A fiducial cross section for W gamma production in proton-proton collisions is measured at a center-of-mass energy of 13 TeV in 137 fb(-1) of data collected using the CMS detector at the LHC. The W -> e nu and mu nu decay modes are used in a maximum-likelihood fit to the lepton-photon invariant mass distribution to extract the combined cross section. The measured cross section is compared with theoretical expectations at next-to-leading order in quantum chromodynamics. In addition, 95% confidence level intervals are reported for anomalous triple-gauge couplings within the framework of effective field theory.Peer reviewe

Search for long-lived particles decaying to jets with displaced vertices in proton-proton collisions at root s=13 Te V

A search is presented for long-lived particles produced in pairs in proton-proton collisions at the LHC operating at a center-of-mass energy of 13 TeV. The data were collected with the CMS detector during the period from 2015 through 2018, and correspond to a total integrated luminosity of 140 fb(-1). This search targets pairs of long-lived particles with mean proper decay lengths between 0.1 and 100 mm, each of which decays into at least two quarks that hadronize to jets, resulting in a final state with two displaced vertices. No significant excess of events with two displaced vertices is observed. In the context of R-parity violating supersymmetry models, the pair production of long-lived neutralinos, gluinos, and top squarks is excluded at 95% confidence level for cross sections larger than 0.08 fb, masses between 800 and 3000 GeV, and mean proper decay lengths between 1 and 25 mm.Peer reviewe

Performance of the CMS muon trigger system in proton-proton collisions at √s = 13 TeV

The muon trigger system of the CMS experiment uses a combination of hardware and software to identify events containing a muon. During Run 2 (covering 2015-2018) the LHC achieved instantaneous luminosities as high as 2 × 10 cm s while delivering proton-proton collisions at √s = 13 TeV. The challenge for the trigger system of the CMS experiment is to reduce the registered event rate from about 40 MHz to about 1 kHz. Significant improvements important for the success of the CMS physics program have been made to the muon trigger system via improved muon reconstruction and identification algorithms since the end of Run 1 and throughout the Run 2 data-taking period. The new algorithms maintain the acceptance of the muon triggers at the same or even lower rate throughout the data-taking period despite the increasing number of additional proton-proton interactions in each LHC bunch crossing. In this paper, the algorithms used in 2015 and 2016 and their improvements throughout 2017 and 2018 are described. Measurements of the CMS muon trigger performance for this data-taking period are presented, including efficiencies, transverse momentum resolution, trigger rates, and the purity of the selected muon sample. This paper focuses on the single- and double-muon triggers with the lowest sustainable transverse momentum thresholds used by CMS. The efficiency is measured in a transverse momentum range from 8 to several hundred GeV

Search for top squark production in fully hadronic final states in proton-proton collisions at root s=13 TeV

A search for production of the supersymmetric partners of the top quark, top squarks, is presented. The search is based on proton-proton collision events containing multiple jets, no leptons, and large transverse momentum imbalance. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 137 fb(-1). The targeted signal production scenarios are direct and gluino-mediated top squark production, including scenarios in which the top squark and neutralino masses are nearly degenerate. The search utilizes novel algorithms based on deep neural networks that identify hadronically decaying top quarks and W bosons, which are expected in many of the targeted signal models. No statistically significant excess of events is observed relative to the expectation from the standard model, and limits on the top squark production cross section are obtained in the context of simplified supersymmetric models for various production and decay modes. Exclusion limits as high as 1310 GeVare established at the 95% confidence level on the mass of the top squark for direct top squark production models, and as high as 2260 GeV on the mass of the gluino for gluino-mediated top squark production models. These results represent a significant improvement over the results of previous searches for supersymmetry by CMS in the same final state.Peer reviewe

Search for top squark pair production using dilepton final states in pp collision data collected at root s=13TeV

A search is presented for supersymmetric partners of the top quark (top squarks) in final states with two oppositely charged leptons (electrons or muons), jets identified as originating from bquarks, and missing transverse momentum. The search uses data from proton-proton collisions at root s = 13 TeV collected with the CMS detector, corresponding to an integrated luminosity of 137 fb(-1). Hypothetical signal events are efficiently separated from the dominant top quark pair production background with requirements on the significance of the missing transverse momentum and on transverse mass variables. No significant deviation is observed from the expected background. Exclusion limits are set in the context of simplified supersymmetric models with pair-produced lightest top squarks. For top squarks decaying exclusively to a top quark and a lightest neutralino, lower limits are placed at 95% confidence level on the masses of the top squark and the neutralino up to 925 and 450 GeV, respectively. If the decay proceeds via an intermediate chargino, the corresponding lower limits on the mass of the lightest top squark are set up to 850 GeV for neutralino masses below 420 GeV. For top squarks undergoing a cascade decay through charginos and sleptons, the mass limits reach up to 1.4 TeV and 900 GeV respectively for the top squark and the lightest neutralino.Peer reviewe

Measurement of the top quark Yukawa coupling from t(t)over-bar kinematic distributions in the dilepton final state in proton-proton collisions at root s=13 TeV

Peer reviewe