The three-dimensional multi-container packing problem (3DMCPP) is used to determine the non-overlapping packing of a set of finite three-dimensional rectangular elements into the minimum number of identical containers. We have taken as a starting point the transformation of the 3DMCPP problem as several problems of three-dimensional packaging of a single container (SCLP for its acronym in...
Geosites are places of geological interest. Geo-parks are a set of geo-sites of different geological characteristics, attractive for scientists, tourists and etc. A methodology given by UNESCO, scores geo-parks. In this contribution we propose a model of binary variables for determining which geo-sites shall be included in a geo-park. We define this as a coalition such that including a new...
Mixed values for directed multigraphs (digraphs in which multiple directed links between two given nodes are allowed) are defined. We explore different communication situations depending on the type of communication: series, parallel, minmax or maxmin, and we characterize the resulting allocation rules.
Position values for multigraphs (graphs in which multiple links between two given nodes are allowed) are defined. We explore different models depending on the schedule method of communication (maxmin, minmax, max, min) and we characterize the resulting allocation rules.
Experience in banking institutions is a key factor in attracting and retaining customers. Time is a valuable element within the experience since users make decisions based on the limitation to fulfill daily obligations. High waiting times entail a loss of customers since they affect the satisfaction and perception of banking services. The present study aims to identify different strategies...
In this work, we propose and evaluate an active-set modified Newton-Raphson (AMNR) algorithm for finding electrophysiological sources in both simulated and real data, and then apply it to different penalized models in order to compare the sources of the EEG theta rhythm in two groups of elderly subjects with different levels of declined physical performance, as well as preliminarily studying...
This article presents an aeronautical cybersecurity maturity management framework and the software developed to implement it in an air navigation service provider. In their annual planning, they must determine which requirements to prioritize in order to achieve the desired levels of maturity in aviation cybersecurity. Considering that said framework proposes 600 requirements and 120...
The numerical solution of the physical problem resulting from the flow of heat along a length bar l is presented, which is assumed to have a uniform temperature within each cross-sectional element.The approach we will use to approximate the solution to this problem is the use of finite differences. The algorithm was first developed using the regressive difference method and then to improve the...
In the more and more influential context of the big data, unsupervised mining of textual data content, like topic modeling, is becoming a strategic task. Topic-models, among which LDA, become thus extensively used for various tasks that might make further rich use of the extracted topics for text. However, some former works that performed subjective evaluation of LDA results have shown that...
An EPEC is a mathematical program to find an equilibrium point that simultaneously solves several Mathematical Programs with Equilibrium Constraints (MPECs). This kind of problems arises in real difficult situations such as electric markets, resources management (water, communications), among others. In this work an algorithm to solve equilibrium problems with equilibrium constraints (EPECs) is...
In many parts of the world, rural areas are structurally lagging behind urban regions. This affects the availability of public services as well as the general supply of local population. Attempts to build improved structures are often based on a hierarchical principle of centrality with the aim of significantly improving the accessibility of public (and also commercial) facilities for the...
ue to the significant increase of communications between individuals via social media (Facebook, Twitter, Linkedin) or electronic formats (email, web, e-publication) in the past two decades, network analysis has become an unavoidable discipline. Many random graph models have been proposed to extract information from networks based on person-to-person links only, without taking into account...
Evaluating the impact of an intervention is of vital importance for decision-making based on scientific evidence. In contrast to classical schemes, Bayesian Structural Time Series (BSTS) models allow inferring the time evolution of the attributable impact, incorporating empirical background on the parameters in a fully Bayesian treatment, and flexibly accommodating multiple sources of...
The study of infectious diseases through mathematical models makes it possible to analyze their dynamics, their impact over time and provide valuable information for decision taking, with the purpose of eradicating them. The objective of this paper is first to present an epidemic model SI (susceptible-infected) by means of a reaction-diffusion system, in this case, in the dynamics of the...
The Layered/columnar architecture of the neocortex is key to delivering higher-order brain function. The columnar dynamic of neural populations distributed in six-layers plays specific functional roles. Interlayer connectivity within the column and forward/backward adjacent columns governs the dynamical regime. Sensing the layer-specific activity mean field of the neural populations and such...
The Digital Transformation process in Cuba, which the country's top management started applying from 2022, consists of a deep and accelerated transformation of activities, processes, competencies and business models to fully take advantage of the changes and the opportunities of digital technologies and data for organizations. Business Analytics is part of this transformation since it...
Our work is an attempt to understand the competitive aspects of the diffusion of ideas, innovations, or product adoption in social networks. Grounded in non-cooperative game theory, we propose a framework called "I-Game" (Influence Game), that models the adoption of competing products in social networks as a strategic game in which the firms are the players. The finite strategy space is the...
The incidence of skin cancer cases increases considerably every year. Cuba is not exempt from this growth being this type of cancer the most reported since 2020. Within these malignant skin tumors there are different classifications such as Melanoma and Non Melanoma skin cancer, the latter includes Basal Cell Carcinoma and Spinocellular Carcinoma. For its early detection a non-invasive...
Abstract: The signals associated to eye movements are influenced by different noises affecting important magnitudes as saccadic peak velocity and latency. These biomarkers serve as indicators of neurological disorders in the human and therefore constitute an important tool for the diagnosis of neurodegenerative diseases such as Spinocerebellar Ataxia type 2 (SCA2). The denoising process...
Different indicators epidemiologically describe a disease: incidence, remission, lethality, prevalence, duration of the disease, and mortality. Different models take into account the interrelationships between these indicators, which makes it possible to complete the description in the absence of some of them, and to achieve internal consistency in them.
In this paper some of these models are...
We introduce the balanced incomplete block designs (BIBDs) and some
algorithms to generate them. The BIBDs have their origin in practical
applications in experimental designs in agronomy. They also
have deep theoretical applications in the field of non-Euclidean geometry, as well as in the field of combinatorics, since they can be used, among other things, for the construction of finite...
In this work, a proposal is presented for the estimation of populations using generalized logistic curve fitting. These types of curves are used to study population growth, in this case population of people infected by the Covid-19 virus; and it can also be used to approximate the survival curve used in actuarial and similar studies. The resulting model could also be used to approximate daily...
How functional networks (FN) emerge from the structural organization of the brain is still an open question, in the study of the relationship between the structure and function. The autonomic DMN is a set of brain regions that is active in almost all physiological brain states (i.e. is central to cognition), and arise by the brain functional dynamics from structural connectome (SC). Here, **we...
Experimental evidence suggests that acute myeloid leukemia may originate from multiple clones of malignant cells; however it is unknown how the observed leukemic clones may differ with respect to cellular properties, such as proliferation and self-renewal. There is not much information about how the properties of cells change due to chemotherapy and relapse. Using mathematical models, the...
Classical epidemiological models consider that the entire population lives in an area and that it is homogeneous. However, this is not real, since the populations live in different localities and this spatial heterogeneity affects the transmission of diseases. IN this paper, a model based on metapopulations on networks is proposed; which is nothing more than considering groups of populations...
Classical epidemiological models consider that the entire population lives in an area and that it is homogeneous. However, this is not real, since the populations live in different localities and this spatial heterogeneity affects the transmission of diseases. IN this paper, a model based on metapopulations on networks is proposed; which is nothing more than considering groups of populations...
A newly released scientific article is "too young" to prove its high influence on the scientific community in terms of a high number of citations. Gathering citations requires time. However, text-mining techniques can help in detection of potentially significant scientific work in the early stage when the number of citations is still low. Based on the CORD-19 corpus of biomedical articles, we...
The study of event-related potentials (ERP) has become increasingly popular in the last decades due to its excellent temporal resolution. Still, the waveforms extracted from these paradigms are excessively entangled in the time domain, which causes that the use of deconvolution methods be slow or difficult to converge. The use of techniques that assume variability in the response across...
The estimation of Differences-in-Differences (DiD) using a simple random sampling with replacement (SRSWR) sample is developed. The cases in which s is selected and it is s1 and s0 are determined deterministically or randomly are considered, as well as the case in which non-responses are present. Different alternative models are developed. Their behaviour in a real-life problem is...
Estimation of Manning Coefficients with Nonlinear Least Squares
- $\underline{\text{Fabio Augusto Fortunato Filho}}$ - f235849@dac.unicamp.br;
- José Mario Martínez;
- Rodolfo Gotardi Begiato.
1,2 Institute of Mathematics, Statistics and Scientific Computing - University of Campinas (IMECC - UNICAMP), Campinas, São Paulo, Brazil;
3 Academic Department of Mathematics at the...
In this work we present some experiences of using Pop Culture elements in several Applied Mathematics courses in Mathematics and Computer Science. Those courses are: Numerical Analysis, Ordinary Differential Equations and Optimization. By pop culture we refer to elements taken from fantasy and science fiction books, films and series; video games; TV shows; manga and anime; board and card...
Artificial intelligence continues to advance and, with it, automated machine learning systems (AutoML). These systems extend their functionalities with novel techniques to solve many real-life problems with adequate performance. Still, the application spectrum grows more significant, and new AutoML tools are coming to light increasingly. Because of this, it is necessary to measure the...
This work deals with the so-called time-dependent vehicle routing problem applied to the waste collection problem on a real traffic network while considering one particular type of waste. However, we consider a case where travel time continuously changes according to traffic density. This empirical stochastic property can be discretized into intervals. The objective is to optimize waste...
Retail chains record every customer transaction in their brick-and-mortar stores and are motivated to use their data sources to improve their sales. As some types of customers tend to be more profitable than others, the retailer primarily focuses on the most valuable group of them. To identify them, we describe each transaction, a shopping basket, by simple statistics such as purchase size,...
We present a Ordinary Differential Equations system that combines
a model of a mosquito population on which the Sterile Insect Technique (SIT) is applied, with a classical SIR (Susceptible, Infected, Recovered) model. The $R_0$ epidemiological coefficient is calculated, showing that the SIT is capable not just of reducing the mosquito population, but can also control mosquito-transmitted...
Mesoscopic Neural Mass Models (NMMs) allow biophysical modeling and understanding of network properties and their reflection in EEG, MEG, or fMRI. This work deals with three critical aspects of this type of modeling
• We avoid numerical methods that destroy the dynamical properties of networks, employing the Local Linearization method (LLM) instead.
• We show that by drastically increasing...
The purpose of this communication is to quantify the effects of the process of merging university departments at the Complutense University of Madrid using non-parametric Data Envelopment Analysis (DEA) techniques. More specifically, we seek to evaluate the potential gains from the merging of university departments, relying on the three savings effects introduced by Bogetoft and Wang (2006)...
The purpose of this communication is to quantify the effects of the process of merging university departments at the Complutense University of Madrid using non-parametric Data Envelopment Analysis (DEA) techniques. More specifically, we seek to evaluate the potential gains from the merging of university departments, relying on the three savings effects introduced by Bogetoft and Wang (2006)...
The Global Brain Consortium (GBC ) (https: // globalbrainconsortium.org ) was created in response to the problems identified in the 2016 meeting of the International Brain Projects with the World Health Organization. A gap exists between the well-funded and past-paced advance of neuroscience research in High-Income Countries and its impact on the Global Burden of Brain Disorders in...
LINEAR PROGRAMMING AND FUZZY OPTIMIZATION IN RADIOTHERAPY DECISION-MAKING
- $\underline{\text{Nicole Cristina Cassimiro de Oliveira}}$ - n235160@dac.unicamp.br;
- Aurelio Ribeiro Leite de Oliveira.
1,2 Institute of Mathematics, Statistics and Scientific Computing - University of Campinas (IMECC - UNICAMP), Campinas, São Paulo, Brazil.
*Keywords: Interior Points Method....
This research is the result of three years of work by the student scientific group (M@TUR), it focuses on the decision-making problem in the Havana tourism sector. The objective is to apply mathematical-computational methods for decision-making in the Havana tourism sector. For this, multivariate analysis, multicriteria analysis and computer tools for decision-making in accommodation services,...
Over the past decade, Big Data has drastically changed the industry and science fields. Nowadays is common the analysis of large high dimensional datasets in order to improve the decission making process. Data visualization is one of the most used methods within data analysis, however, visualization design is a complex process which involves multiple design criteria and raises disagreements...
Recent developments in Neural Field Theory have resulted in the creation of Next Generation Neural Field models, which offer a fresh perspective on studying neuronal activity. Unlike previous models, these new models describe activity at a larger scale by considering microscopic laws and assuming a uniform distribution of neurons. However, it is crucial to consider the varying density of...
In policy analysis, two-stage approach consisting in explaining computed DEA efficiency by various regressors is very popular, particularly in agriculture analysis. The theoretical literature provides assumptions both for the description of the large sample properties of the DEA estimator itself, as well as the large sample properties for the second (regression) level of analysis. However,...
Advances in computing power and solution techniques have made stochastic optimization via scenario analysis a popular method for solving complex planning problems, including those with integer variables. This approach allows uncertainty to be considered as an additional element, resulting in valid solutions for representative set of scenarios. However, classical models are risk neutral and do...
Underlying resting-state or standardized task paradigms are large-scale and dense frequency-specific functional networks that produce oscillatory activity from low-order to high-order cortical regions. Neuroimaging methods such as the MEEG inverse-solutions that target this type of neural activity may face severe localization and leakage distortions that are enlarged for EEG. Our rationale is...
Abstract
Introduction: Pharmacometry is a vibrant scientific discipline that is shaped by the cycle of excellence: integration, innovation and impact. Objective: To evaluate different pharmacokinetic parameters of the Cuban biotechnological product Nimotuzumab. Methods: A population pharmacokinetic analysis of nimotuzumab was performed in patients with breast cancer, polycystic kidney cancer,...
The greatest natural disasters of our country’s history have been associated with tropical cyclones, which generate strong winds. For this reason, is important for the Meteorological Institute, especially for the Clime Center to develop a methodology to characterize the meteorological variable maximum wind. For this reason, a series of software’s were developed using statistical methods...
Arrival times in queueing systems are known to exhibit seasonal and diurnal patterns. However, even after accounting for these patterns, there remains an autocorrelation structure in the times between successive arrivals. Ignoring this autocorrelation can lead to underestimation of performance measures and suboptimal decisions. In our study, we propose a method for capturing the remaining...
The great complexity of the human connectome motivates the study of a simpler neural network. For that purpose, the Ising Model was applied on experimental data on the synaptic connectivity of Caenorhabditis elegans (C. elegans) in resting-state, assigning a binary variable (representing active or inactive states) to each neuron in the network. The dynamics of this system is postulated as...
The paper proposes a new method of intrinsic non-parametric Riemannian regression problems using Isometric Riemannian Manifolds (IRMs). IRMs are Riemannian manifolds that share similar geometrical characteristics through isometry. We introduce a method for computing Intrinsic Local Polynomial Regression (ILPR) on IRMs, which enables the global mapping of data from one Riemannian manifold...
Investigating causation in complex systems, especially the brain, is a topic of current great interest. Our research uses a sophisticated data-driven method, TIGRAMITE (Time Series Graph-Based Measures of Transfer entropy), that uses tools from Information Theory to investigate causal relations. This technique may overcome some difficulties of other state-of-the-art techniques. We acknowledge...
In this paper, the nonlinear diffusion model applied to image smoothing (ADIMP), known as the Perona-Malik anisotropic model, is studied. This model is characterized by requirements on the diffusion coefficient, hence the changes that occur in the resulting family of images, depend on the gradient based coefficient expression’s and on the way of estimating the gradient threshold. In this work...
In this paper, the nonlinear diffusion model applied to image smoothing (ADIMP), known as the Perona-Malik anisotropic model, is studied. This model is characterized by requirements on the diffusion coefficient, hence the changes that occur in the resulting family of images, depend on the gradient based coefficient expression’s and on the way of estimating the gradient threshold. In this work...
This research presents a comprehensive numerical study to show the impact of the numerical method for solving the non--linear equations system to find the high--pass filter of a Discrete Shapelet Transform (DST-II). For that, we compared $12$ iterative algorithms to obtain the filter from the null vector, and then establishing a combination of numerical methods to improved the solution...
In this talk we introduce the notion of O-equivalence between probability measures. This is a weaker, but similar notion to the usual equivalence between measures. We prove that this notion of O-equivalence, combined with certain topological property of portfolios, can be used to transfer arbitrage properties between models, in a similar way that equivalence between probability measures is...
Occurrence of Bifurcations in epidemiological models: significance in the prediction of disease transmission
This paper presents the state of the art on the study of the occurrence of different types of bifurcations and their implications in different compartmental epidemiological models applied to different infectious diseases. Emphasis is placed on investigating how deeply the occurrence...
Language policies for the purpose of (re)vitalizing a minority language are analyzed as a dynamic cost-effectiveness problem. We focus on policy measures with two types of costs structures: costs largely proportional to the number of beneficiaries (a rival measure) and costs independent of the number of beneficiaries (a non-rival measure). An example of the former is for instance home nursing...
Most optimization problems involve uncertain data due to measurement errors, unknown future developments and modeling approximations. Stochastic optimization assumes that the uncertain parameter is probabilistic. An other approach is called robust optimization which expects the uncertain parameter to belong to a set that is known prior. In this talk, we consider scalar optimization problems...
Resting-state EEG (rsEEG) patterns are promising for measuring aging-associated functional decline and screening elderly subjects at risk of neurological diseases. Otherwise, gait-speed is used in clinical practice as the main predictor of adverse outcomes. **Here we propose a novel methodology that allows examining the capacity of the spatial patterns of sources of rsEEG (theta rhythms) to...
We discuss problems, models and techniques to evaluate financial contracts based on environmental variables such as temperature and precipitation under a dynamic described by stochastic differential equations with Levy background noises. Closed-form formulas for the price, relying on Fourier inversion and expansions are provided.
In view of the COVID-19 pandemic and the growth of positive cases in Cuba, among other investigations, it became necessary to carry out analytical studies of mathematical models to predict the behavior of the virus transmission. This work proposes models that describe the transmission dynamics of COVID-19, defined by differential equations and a qualitative analysis of them, as well as...
DNA microarray data for cancer are datasets that originate from the use of cDNA microarray technology in the classification of cancer tumors. These sets constitute a very complex classification problem for supervised and unsupervised data modeling. Due to their high dimensions in the number of columns, DNA microarray data in cancer constitute a Column Subset Selection Problem. This problem is...
Score-driven (SD) models, also referred to as generalized autoregressive score (GAS) models and dynamic conditional score (DCS) models, are time series models that can be based on any underlying probability distribution with dynamics driven by the conditional score for any time-varying parameters. In recent years, score-driven models have emerged as a valuable modern methodology for time...
Keywords : Clustering; Sparsity; Group Sparsity; Mixed Data.
When databases include many observations described by a reasonable number of variables, the K-means framework provides useful methods for analyzing, summarizing and representing the data. The task consists in extracting a reduced number of "representatives" from the whole database, and/or what is equivalent to partitioning the...
Many automatic monitoring applications collect high-dimensional time-series data, but only a small number of components contain meaningful information, such as changes in the signal's average value. The rest of the components are just noise. In such a high-dimensional setting, where the useful signal is sparse, we have developed a new segmentation algorithm that identifies the informative...
Real world problems are often affected by diverse types of uncertainty, which we have to take into account in mathematical modelling of the problems. Uncertain data can be represented by various ways, depending on the source and type of uncertainty. In our presentation, we make use of the concept of interval analysis, which assumes that we obtain only nominal values with a given accuracy, so...
Abstract:
Simple phenomenological growth models have been widely used to understand the dynamics of the COVID-19 pandemic as well as to predict future trends and assess intervention strategies forecasting epidemic trajectories. However, most existing phenomenological growth models only support single peak outbreak dynamics whereas real epidemics often display more complex transmission...
Leukemia is a clonal disease of the hematopoietic system that leads to a wide expansion of malignant cells that are nonfunctional and cause abnormalities in blood formation. Recent experimental evidence indicates that the malignant cell population may be composed of multiple clones, maintained by cells with stem cell-like properties. Disease relapse after therapy is a common problem in...
The resting state electroencephalogram (EEG spectrum) has long been the mainstay of research and clinical application. Emphasis has shifted in recent years from nonparametric, frequency-resolved spectral descriptions to parametrizations distinguishing between components. The xi process (also known as the background, 1/f, or aperiodic component) and the alpha rhythm are the most prominent....
The COVID-19 pandemic in Cuba had special circumstances. This work aims to present an expression for the basic reproductive number, with and without vaccination; to study its variation during the pandemic and to analyze how the appearance of an endemic equilibrium position is generated.
We also examine what kind of vaccination strategy should be designed for controlling the epidemic. To do...
Missing data is a common problem in general applied studies, and specially in clinical trials. An improper treatment of missing data may have serious implications for the accuracy of inferences of many clinical studies. Then, it is necessary to provide rigorously validated methodological tools that allow tackling this problem. Maximum likelihood and multiple imputation are recognized methods...
Keywords: Data Analytics, Mental Health, Suicide, Descriptive Statistics
Suicide is a phenomenon that concerns all societies, as it affects a large part of the population, becoming the second leading cause of death among young people. Therefore, the WHO prioritizes suicide prevention worldwide, and to achieve this, demographic characteristics and risk factors associated with suicide...
