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Item Nominal sets in Agda(2022) Pagano, Miguel; Solsona, Jose E.In this paper we present our current development on a new formalization of nominal sets in Agda. Our first motivation in having another formalization was to understand better nominal sets and to have a playground for testing type systems based on nominal logic. Not surprisingly, we have independently built up the same hierarchy of types leading to nominal sets. We diverge from other formalizations in how to conceive finite permutations: in our formalization a finite permutation is a permutation (i.e. a bijection) whose domain is finite. Finite permutations have different representations, for instance as compositions of transpositions (the predominant in other formalizations) or compositions of disjoint cycles. We prove that these representations are equivalent and use them to normalize (up to composition order of independent transpositions) compositions of transpositions.Item Accurate Reduced-Order Models for Heterogeneous Coherent Generators(2021) Min, Hancheng; Paganini, Fernando; Mallada, EnriqueWe introduce a novel framework to approximate the aggregate frequency dynamics of coherent generators. By leveraging recent results on dynamics concentration of tightly connected networks, and frequency weighted balanced truncation, a hierarchy of reduced-order models is developed. This hierarchy provides increasing accuracy in the approximation of the aggregate system response, outperforming existing aggregation techniques.Item Automatic cloud instance provisioning with quality and efficiency(2021) Goldsztajn, Diego; Ferragut, Andrés; Paganini, FernandoA distinctive feature of cloud computing is that it enables customers to dynamically summon server instances. Service providers facing uncertain demand patterns may exploit this feature by setting automatic provisioning rules for right-sizing the capacity contracted from the cloud. This situation can be modeled by a queueing system where the numbers of both jobs and servers evolve in time, the latter subject to delays in creation and deletion. We study in this context different feedback rules with the objective of efficiently matching capacity and load, while simultaneously providing a high quality of service. These rules are analyzed by means of fluid and diffusion limits for Markov chains. In particular we develop suitable extensions of the classical literature on this topic, required to accommodate non-homogeneous intensity scalings and non-differentiable drift fields. With these tools, our final proposal is shown to exhibit properties akin to the Halfin-Whitt regime, achieved automatically without knowledge of the system load. We further investigate by simulation its behavior under time-varying load, demonstrating the capabilities of our design to provide quality and efficiency in highly dynamic scenarios.Item Proximal regularization for the saddle point gradient dynamics(2021) Goldsztajn, Diego; Paganini, FernandoThis paper concerns the solution of a convex optimization problem through the saddle point gradient dynamics. Instead of using the standard Lagrangian as is classical in this method, we consider a regularized Lagrangian obtained through a proximal minimization step.We show that, without assumptions of smoothness or strict convexity in the original problem, the regularized Lagrangian is smooth and leads to globally convergent saddle point dynamics. The method is demonstrated through an application to resource allocation in cloud computing.Item Lacasa inmovilizada para la degradación de residuos de antibióticos en leche(2019) Vaccaro, Víctor; Betancor, Lorena; Jackson, ErienneLos residuos de medicamentos veterinarios, especialmente los antimicrobianos, son considerados un peligro y potencial riesgo para los procesos de industrialización lechera, la salud pública y el medio ambiente. Una posible solución biotecnológica para degradar antibióticos contaminantes en leche surge de la utilización de enzimas. Las lacasas son oxidasas que contienen cobre y pueden catalizar la oxidación de una amplia variedad de compuestos fenólicos y no fenólicos.Item Tables for the Friedman’s Test with ties [archivos](2020) López-Vázquez, Carlos; Hochsztain, EstherEstos archivos acompañan al artículo Tables for the Friedman’s Test with ties: Interim Report. Contenido del artículo: Part of the steps necessary to assess if a new treatment or vaccine is better than other is to test if there exist a statistical difference between the treatments. Since its inception in 1937 this is performed using the Friedman’s Test (Friedman, 1937). The typical problem case is that of a wine contest, with k wines and N judges, not allowing ties for the rankings. Since his seminal paper, it is known that the statistic involved has asymptotic approximations with either the or the normal distribution. Such approximations are very inaccurate for low values of k and N, so Friedman offered a small set of exact tables which has been expanded over the year by other authors. Recently, López-Vázquez and Hochsztain (2017) expanded drastically the existing set of tables covering from low values of k and N not previously tabulated up to those values where the asymptotic expansion is accurate up to 1%. The assumption of no ties by the standard Friedman’s problem is somewhat unrealistic, and there are many application examples where ties are possible. Despite such evidence, only after more than forty years Conover (1980) generalized the expression of the Friedman’s statistic making it valid for both the case with and without ties. The asymptotic distributions are the same as before, and they still suffer for gross inaccuracies for low and mid values of k and N. The problem has been addressed in part only recently, where exact tables for the case with very low k and N have been published, leaving the users’s blinded for intermediate values. In this interim report we presented for the first time tables suitable to use the Friedman’s test in the case of ties covering from low to large values of k and N, considering all pairs where the asymptotic approximation has an error of more than 1%. The computation procedure was very similar to the one applied by López-Vázquez and Hochsztain (2017) and will be described elsewhere; they required more than two years wall time using a cluster of 1200 nodes. Considering the present scientific effort related with the COVID-19 pandemia, we decided to early disclose the numerical results as our two cents contribution to the task. To illustrate, we included in this document tables for those pairs (k,N) that have an error in excess of 10% w.r.t. the asymptotic expansion, and offer a link to the files where the other ~9.000 (k, N) pairs that exceed 1% are presented in tabular form.Item Extended and updated tables for the Friedman rank test [archivos ASCII](Taylor & Francis, 2017) López-Vázquez, Carlos; Hochsztain, Esther; ;Estos archivos en código ASCII acompañan al artículo Extended and updated tables for the Friedman rank test, publicado en Communications in Statistics—Theory and Methods (ISSN: 1532-415X). Contenido del artículo: Muchos test y estadísticos de interés tienen distribuciones complejas, las que suelen aproximarse por distribuciones asintóticas “...para N grande, k pequeño,...” etc. En la práctica hay pocas reglas para evaluar lo adecuado de su aplicación para k y N particulares. Aunque el problema es general, en este trabajo se ilustra el hecho con el Test de Friedman, desarrollado para analizar datos ordinales en 1937. Este test no paramétrico (de variables N y k) tiene dos aproximaciones asintóticas: una válida para todo k y N grande y otra normal para k grande y N pequeño. En nuestro trabajo, se comparó exhaustivamente cada aproximación asintótica contra la distribución empírica obtenida mediante simulación de Monte Carlo, elaborándose cotas del error relativo de los percentiles clásicos en un amplio rango de k y N. Los resultados obtenidos tras más de 100 años-CPU de procesamiento muestran que la discrepancia excede fácilmente el 10%. Asimismo, mediante la revisión de casos reportados en la literatura, se identificaron ejemplos en que el uso de la distribución asintótica llevó a los autores a conclusiones erróneas. Este trabajo de big computing presenta por lo tanto aportes a la estadística teórica y aplicada.