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Humanity has suffered throughout its history from different types of pandemics caused by deadly infectious diseases. Mathematical models are very useful tools to understand the dynamics of the behavior and propagation of these. Among these models are those known as SIS, SIR and SEIR. This paper presents a brief explanation of the structure of these models and its use in some pandemics. In particular, some SIR-type models without and with delays are analyzed with special interest, as well as their applications to the current pandemic caused by the SARS-CoV-2 virus. To determine the correspondence between some of the models analyzed and the data of Infectious and Recovered from Mexico reported by the World Health Organization (WHO), simulations are presented in three different time periods between the years 2020-2021. In addition, an unpublished SIR-type mathematical model with three delays is proposed as a main contribution. Finally, a discussion is given on the application of numerical algorithms to identify some parameters of mathematical models, such as ordinary least squares. [ABSTRACT FROM AUTHOR]

This paper proposes a desing of a boost-type DC-DC converter, based on a state space model and calculation of a controller with multiplicative unstructured uncertainty. Performance of the converter at low frequencies was analyzed; as well, weight of the weighting function was adjusted, to reduce noise at certain frequencies. Results of system simulation, in open loop and closed loop, demostrate that the designed controller allows modifying cutoff frequency, through the variation of weighting functions. It is concluded that this technique optimizes dynamics behavior of the system. [ABSTRACT FROM AUTHOR]

Wind generated waves are a very random phenomenon and it is one of the main environmental disturbances that affect the operation of Autonomous Underwater Vehicles (AUV) navigating in shallow waters and coastal zones. In order to attenuate the undesirable effect of the ocean waves on the control system of AUVs, the measurements from the sensors need to be filtered out, using the estimated wave encounter frequency. Developing an estimator capable of providing the encounter frequency in real time using the Algebraic Identification method, is fully reported in this paper. In the design of the proposed algebraic estimator, a linear differential equation to represent the waves spectrum is used, which simplifies the mathematical procedure. The simulations carried out with simulated data and with real data from an experiment at sea, show the excellent results of the estimator in terms of precision in the final value and estimation time. In addition, its show the use of the wave encounter frequency estimation to adjust the filtering techniques previously implemented for the vehicle in a proper way, which results in a reduction of vibrations and energy consumption of the vehicle's rudder system. [ABSTRACT FROM AUTHOR]

The proper use of statistics is key for professionals who answer questions from data, including ecologists. However, statistics is generally confusing for these professionals, in part due to difficulties related to its terminology. Many of these difficulties derive from the multiple meanings that a term has, both inside and outside the statistical scope. For Spanish-speaking professionals, the translation of English terms also contributes to this confusion. In this paper we show (and intend to clarify) some of these problems from two key terms of an introductory statistics course: error and bias. These terms are discussed in the different contexts that involve problem resolution using statistics: sampling, measurement, estimation, inference and prediction. Error is inherent to statistics and is used to quantify different types of variability or to indicate the possibility of making mistakes on decision making, depending on the context. On the other hand, bias reflects the tendency towards certain values and/or elements, and leads to erroneous conclusions if not avoided. We propose that the problems associated with lexical ambiguity should to be addressed from university teaching and based on this, we offer some recommendations. Thus, the present article not only offers a guide for professionals to make an adequate use of some statistical terms but also provides a contribution for teaching. [ABSTRACT FROM AUTHOR]

The purpose of this paper has been to carry out a review of the historical evolution of one aspect of test validity - content validity - as well as to expose some of the most popular methods used for its evaluation. The concept of content validity has undergone many modifications from its inception to the present time. However, in the past these changes have focused on which pieces of evidence must be presented and the different statistical methods used to study it, while keeping its meaning essentially stable over time. Nowadays, evidence for content validity is considered necessary (though not the sole factor) for interpreting test results. Finally, the use of both qualitative and quantitative methods is recognized as the best procedure for performing an in-depth study of content validity. Regarding the former, this paper recommends the IVC index because, besides being currently the most used, it shows the most benefits when compared to the alternatives proposed over the years. Regarding the latter, the Generalizability Theory is understood as the most comprehensive and accurate procedure for measuring this aspect of test validity. [ABSTRACT FROM AUTHOR]

In this paper we analyze the results and processes used by third-year secondary students and prospective elementary teachers in estimation tasks of continuous quantities of length, surface, capacity and mass. The results show no differences between both groups of students. Both are good estimators of length and surface but underestimate capacity and mass. No big differences are detected in the processes and strategies used, except a higher and more effective use of formulas in the case of prospective teachers. [ABSTRACT FROM AUTHOR]

The methodology for estimating shelf life of food proposes the use of one of the two most widely used estimation methods depending on the nature and expected shelf life of the particular product: Weibull analysis or hazard techniques and accelerated shelf life tests for temperature abuse. In this paper the steps to apply both estimation methods and examples are presented. [ABSTRACT FROM AUTHOR]

A shelf-life study is an objective and methodical means to determine or estimate such time, for this estimation it is necessary for food producers and developers to have a methodology that will help them to perform reliable and accurate shelf life studies. The proposed methodology is based on the general procedure for estimating shelf life consisting of three steps: preliminary analysis of the product packaging environment system, storage and characterization tests and application of the appropriate estimation technique. In this paper, we discuss, in a general way, some methodological and practical considerations that must be taken into account for the execution of the first two steps. [ABSTRACT FROM AUTHOR]

Monthly wage series with quarterly periodicity between December 1994 and December 2004 for thirteen regions in Chile are presented in this paper. These series are based on the information gathered by the Superintendencia de Fondos de Pensiones (Pensions Fund Superintendence), but are corrected for truncation and censoring bias. The comparative analysis of corrected and non-corrected series indicates that the series show a statistically differentiated behavior. The non-corrected wage series are not good predictors of the corrected series. Thus, to develop regional wage analysis based on this information source, it is preferable to use the corrected series presented in this paper. [ABSTRACT FROM AUTHOR]

This paper describes the identification by the compound digital filter with two estimators involved in the Kalman filter, the first corresponds to stochastic gradient describing the transition function and the second obtains the innovation process gain through fuzzy logic. The filtering process has time constraints for your response occurring before the reference system changes to another state. The results are formally described throughout the document. Auto-Regressive Moving Averages model was proposed (ARMA (1, 1)) as the reference system. The filtering algorithm was developed in MatLab® software getting the integrated filter operations illustrated with its graphics of convergence and response, concluding with brief an analysis of the results. [ABSTRACT FROM AUTHOR]

This paper presents an Artificial Neural Network (ANN) based model for environmental variables related to the tobacco drying process. A fitting ANN was used to estimate and predict temperature and relative humidity inside the tobacco dryer: the estimation consists of calculating the value of these variables in different locations of the dryer and the prediction consists of forecasting the value of these variables with different time horizons. The proposed model has been validated with temperature and relative humidity data obtained from a real tobacco dryer using a Wireless Sensor Network (WSN). On the one hand, an error under 2% was achieved, obtaining temperature as a function of temperature and relative humidity in other locations in the estimation task. Besides, an error around 1.5 times lower than the one obtained with an interpolation method was achieved in the prediction task when the temperature inside the tobacco mass was predicted with time horizons over 2.5 hours as a function of its present and past values. These results show that ANN-based models can be used to improve the tobacco drying process because with these types of models the value of environmental variables can be predicted in the near future and can be estimated in other locations with low errors. [ABSTRACT FROM AUTHOR]