Comportamiento espacial de las partículas suspendidas PM 10 y estrategias de gestión Ambiental del Aire en la Zona Metropolitana de Toluca, México

En esta investigación se identifican los patrones espaciales de las partículas suspendidas (PM10) en la Zona Metropolitana de Toluca, en el periodo 2011 - 2013, la información se obtuvo de la Red Automática de Monitoreo Atmosférico de Toluca (RAMAT), la modelación se realizó a través del módulo Geostatical Analyst integrado a la plataforma del software Arcgis 10.1 . Los modelos espaciales indican que la calidad del aire se mantiene de mala a regular, por ello es necesario avanzar en la cultura de la prevención a través de un Programa de Alerta Temprana, que informe a la población sobre los riesgos que se presentan en las épocas seca y cálida del año, y las medidas de atención en condiciones de contingencia atmosférica

Valor Wrought Asunder: The Mexican General Officer Corps in the U.S.-Mexican War, 1846-1847.

This thesis presents a reappraisal of the performance of the Mexican general officer corps during the U.S.-Mexican War, 1846-1847. Often negatively libeled, Mexicos defeat is often attributed in no small part to the moral shortcomings of the generals who led her armies. By a detailed analysis of their background, motivations, and military careers, a more accurate perspective regarding the Mexican general officer corps\u27 performance during the war can be obtained by the reader. It is the argument of this thesis that the operational tactics and organizational weakness of the Army\u27s High Command sufficiently account for the failures of the generals without examination of its moral shortcomings. Both the Bourbon Spanish military heritage and political/social heterogeneity of the officer corps impeded its success as a corporate entity. By a detailed analysis of senior Mexican military leadership during the war\u27s two major land campaigns, it becomes apparent that the army\u27s failure is attributable in no small part to both of these factors whose detailed analysis has been overlooked in past scholarship

On the Reliability Assessment of Artificial Neural Networks Running on AI-Oriented MPSoCs

Nowadays, the usage of electronic devices running artificial neural networks (ANNs)-based applications is spreading in our everyday life. Due to their outstanding computational capabilities, ANNs have become appealing solutions for safety-critical systems as well. Frequently, they are considered intrinsically robust and fault tolerant for being brain-inspired and redundant computing models. However, when ANNs are deployed on resource-constrained hardware devices, single physical faults may compromise the activity of multiple neurons. Therefore, it is crucial to assess the reliability of the entire neural computing system, including both the software and the hardware components. This article systematically addresses reliability concerns for ANNs running on multiprocessor system-on-a-chips (MPSoCs). It presents a methodology to assign resilience scores to individual neurons and, based on that, schedule the workload of an ANN on the target MPSoC so that critical neurons are neatly distributed among the available processing elements. This reliability-oriented methodology exploits an integer linear programming solver to find the optimal solution. Experimental results are given for three different convolutional neural networks trained on MNIST, SVHN, and CIFAR-10. We carried out a comprehensive assessment on an open-source artificial intelligence-based RISC-V MPSoC. The results show the reliability improvements of the proposed methodology against the traditional scheduling

Fog computing pour l'intégration d'agents et de services Web dans un middleware réflexif autonome

International audienceService Oriented Architecture (SOA) has emerged as a dominant architecture for interoperability between applications, by using a weak-coupled model based on the flexibility provided by Web Services, which has led to a wide range of applications, what is known as cloud computing. On the other hand, Multi-Agent System (MAS) is widely used in the industry, because it provides an appropriate solution to complex problems, in a proactive and intelligent way. Specifically, Intelligent Environments (Smart City, Smart Classroom, Cyber Physical System, and Smart Factory, among others) obtain great benefits by using both architectures, because MAS endows intelligence to the environment, while SOA enables users to interact with cloud services, which improve the capabilities of the devices deployed in the environment. Additionally, the fog computing paradigm extends the cloud computing paradigm to be closer to the things that produce and act on the intelligent environment, allowing to deal with issues like mobility, real time, low latency, geo-localization, among other aspects. In this sense, in this article we present a middleware, which not only is capable of allowing MAS and SOA to communicate in a bidirectional and transparent way, but also, it uses the fog computing paradigm autonomously, according to the context and to the system load factor. Additionally, we analyze the performance of the incorporation of the fog-computing paradigm in our middleware and compare it with other works

Evaluation and mitigation of faults affecting Swin Transformers

In the last decade, a huge effort has been spent on assessing the reliability of Convolutional Neural networks (CNNs), probably the most popular architecture for image classification tasks. However, modern Deep Neural Networks (DNNs) are rapidly overtaking CNNs, as state-of-the-art results for many tasks are achieved with the Transformers, innovative DNN models. Transformers' architecture introduces the concept of attention as an alternative to the classical convolution operation. The aim of this work is to propose a reliability analysis of the Swin Transformer, one of the most accurate DNN used for Image Classification, that greatly improves the results obtained by traditional CNNs. In particular, this paper shows that, similar to CNNs, Transformers are susceptible to single faults affecting weights and neurons. Furthermore, it is shown how output ranging, a well-known technique to reduce the impact of a fault in CNNs, is not as effective for the Transformer. The alternative solution proposed by this work is to introduce a ranging not only on the output, but also on the input and on the weight of the fully connected layers. Results show that, on average, the number of critical faults (i.e., that modify the network's output) affecting neurons decreases by a factor of 1.91, while for faults affecting the network's weights this value decreases by a factor of 1 * 10 ^ 5

Things Behind Bayes’ Theorem A review of Sharon Bertsch McGrayne’s The theory that would not die: How Bayes\u27 theorem allowed to decipher the enigma code, to pursue the Russian submarines and to emerge triumphant from two centuries of controversy from a statistics education perspective

A feeling emerges from reading McGrayne’s book expressed as a paraphrase of a verse from Hamlet: There are more things behind Bayes’ theorem, Horatio, than dreamt of in your philosophy. The book tells a story of the birth and survival of an idea around which social enterprises, personal odysseys, and human passions are masterfully woven by the author. The book has 17 chapters distributed in five parts and two annexes. These parts reveal a narrative structure worthy of Propp: The hero of the story (Bayes’ theorem) is born and raised normally but rejected later. It is forced to act in secret but returns to the light and is submitted to several tests. The hero emerges triumphant from all of them. The above is just an outline of a complex but accessible chronicle that includes many brilliant and fascinating figures and extraordinary situations. We recommend the following three reviews that undoubtedly motivate you to immerse yourself in reading the book: Paulos (2011), Wainer & Savage (2012) and McGrayne (2015)

A critical review of knowledge management in software process reference models

Knowledge Management (KM) is a critical subject for software development organizations. For this reason, the purpose of this article is to provide a critical review on the way that KM is included in several models of reference of software process (SPRM). For this, five SPRM used in the Latin American countries were selected. Then, an analysis of each process of the SPRM was performed in order to identify features related to the KM. Finally, the KM aspects were mapped in relation to the KM schools (Earl) and the KM capacities (Gold et al). The main contribution of the paper is to show some breaches in SPRM content in relation to KM schools and capabilities