Propuesta de diseño de software del sistema ERP Odoo y planes de implementación estándar de la industria, para cumplir con la Ley 9635 de Fortalecimiento de Finanzas Públicas en Costa Rica 2019

Trabajo Final de Graduación (Licenciatura en Administración en Tecnología de Información) Instituto Tecnológico de Costa Rica, Área Académica de Administración de Tecnologías de Información, 2019.El presente documento corresponde al Proyecto Final de Graduación para obtener el título de Licenciatura en Administración de Tecnología de Información del Tecnológico de Costa Rica. La situación descrita se desenvuelve en la compañía Delfix Tecnosoluciones S. A., en la que se identificó una problemática en el sistema de planificación de recursos empresariales Odoo (ERP, por sus siglas en inglés, Enterprise Resource Planning). La razón por la que se planteó este proyecto es la entrada en vigor de la Ley 9635 de Fortalecimiento de Finanzas Públicas en Costa Rica en julio del 2019. Si el software que comercializan no cumple con esta ley, la compañía se expondría a sanciones económicas y legales. El proyecto consistió en crear una propuesta de diseño para el sistema ERP Odoo para cumplir con las normas regulatorias. Por lo tanto, inicialmente se hizo un análisis de la Ley 9635, así como de sus normativas, posteriormente se llevó a cabo una interpretación de los artículos para comprender cuáles afectaban al negocio. Después se levantó una toma de requerimientos con base en el listado de los artículos para brindar un diseño conceptual, a partir de mockups, sobre cambios por implementar en el sistema ERP Odoo. Con esta propuesta de solución, la empresa espera cumplir con todos los requisitos que exige la ley. Además, pretende motivar a sus colaboradores en la innovación de servicios de Tecnologías de Información, al ser una empresa líder y competitiva en el mercado.This document corresponds to the Final Graduation Project to obtain the bachelor’s degree in Information Technology Administration from the Technological of Costa Rica. The situation described below develops in the Delfix Tecnosoluciones S. A. organization, where a problem was identified in the Odoo Enterprise Resource Planning (ERP) system, Enterprise Resource Planning. The reasons for the need to develop this project are the entry into force of Law 9635 on Strengthening Public Finance in Costa Rica in July 2019, since, if the software they sell does not comply with this law, it would be exposed to strong economic and legal sanctions. The project consists in creating a design proposal for the ERP Odoo system to comply with regulatory standards, so initially an analysis of Law 9635, as well as its regulations, was performed, then an interpretation of the articles was made to understand which affected the business, then a requirement was drawn up based on the list of items to finally provide a conceptual design based on mockups about changes to be made in the ERP Odoo system. With this proposal, the company hopes to meet all the requirements required by law, in addition to motivating its employees in the constant innovation of Information Technology services, being a leading and competitive company in the market

Towards a Philological Metric through a Topological Data Analysis Approach

The canon of the baroque Spanish literature has been thoroughly studied with philological techniques. The major representatives of the poetry of this epoch are Francisco de Quevedo and Luis de Góngora y Argote. They are commonly classified by the literary experts in two different streams: Quevedo belongs to the Conceptismo and Góngora to the Culteranismo. Besides, traditionally, even if Quevedo is considered the most representative of the Conceptismo, Lope de Vega is also considered to be, at least, closely related to this literary trend. In this paper, we use Topological Data Analysis techniques to provide a first approach to a metric distance between the literary style of these poets. As a consequence, we reach results that are under the literary experts’ criteria, locating the literary style of Lope de Vega, closer to the one of Quevedo than to the one of Góngora

Topology-based representative datasets to reduce neural network training resources

One of the main drawbacks of the practical use of neural networks is the long time required in the training process. Such a training process consists of an iterative change of parameters trying to minimize a loss function. These changes are driven by a dataset, which can be seen as a set of labeled points in an n-dimensional space. In this paper, we explore the concept of a representative dataset which is a dataset smaller than the original one, satisfying a nearness condition independent of isometric transformations. Representativeness is measured using persistence diagrams (a computational topology tool) due to its computational efficiency. We theoretically prove that the accuracy of a perceptron evaluated on the original dataset coincides with the accuracy of the neural network evaluated on the representative dataset when the neural network architecture is a perceptron, the loss function is the mean squared error, and certain conditions on the representativeness of the dataset are imposed. These theoretical results accompanied by experimentation open a door to reducing the size of the dataset to gain time in the training process of any neural networkAgencia Estatal de Investigación PID2019-107339GB-100Agencia Andaluza del Conocimiento P20-0114

Representative datasets for neural networks

Neural networks present big popularity and success in many fields. The large training time process problem is a very important task nowadays. In this paper, a new approach to get over this issue based on reducing dataset size is proposed. Two algorithms covering two different shape notions are shown and experimental results are given.Ministerio de Economía y Competitividad MTM2015-67072-

Representative Datasets: The Perceptron Case

One of the main drawbacks of the practical use of neural networks is the long time needed in the training process. Such training process consists in an iterative change of parameters trying to minimize a loss function. These changes are driven by a dataset, which can be seen as a set of labeled points in an n-dimensional space. In this paper, we explore the concept of representative dataset which is smaller than the original dataset and satisfies a nearness condition independent of isometric transformations. The representativeness is measured using persistence diagrams due to its computational efficiency. We also prove that the accuracy of the learning process of a neural network on a representative dataset is comparable with the accuracy on the original dataset when the neural network architecture is a perceptron and the loss function is the mean squared error. These theoretical results accompanied with experimentation open a door to the size reduction of the dataset in order to gain time in the training process of any neural network

Exploración de prácticas disruptivas en el aula

En un mundo cambiante y dinámico, la educación es llamada a ser consecuente con dicha transformación, alineándose a necesidades emergentes de individuos que a diario buscan explorar y dar una nueva connotación al aprendizaje significativo, canalizando el nuevo conocimiento a través de experiencias memorables que disten de un esquema memorístico y/o conceptual sin conexión con la realidad y su entorno. Es así como, a través de un ejercicio desarrollado en el aula de clase se pretende articular el arte, la creatividad y la innovación como catalizadores del conocimiento a través de la propia creación de los estudiantes involucrados. Ahora, prácticas como las descritas en el presente artículo, pretenden motivar la labor del docente en su espacio de interacción con estudiantes a través de prácticas disruptivas que asocien múltiples actores de su entorno

Optimizing the Simplicial-Map Neural Network Architecture

Simplicial-map neural networks are a recent neural network architecture induced by simplicial maps defined between simplicial complexes. It has been proved that simplicial-map neural networks are universal approximators and that they can be refined to be robust to adversarial attacks. In this paper, the refinement toward robustness is optimized by reducing the number of simplices (i.e., nodes) needed. We have shown experimentally that such a refined neural network is equivalent to the original network as a classification tool but requires much less storage.Agencia Estatal de Investigación PID2019-107339GB-10

Your Teammate Just Sent You a New Message! The Effects of Using Telegram on Individual Acquisition of Teamwork Competence

[EN] Students’ acquisition of teamwork competence has become a priority for educational institutions. The development of teamwork competence in education generally relies in project-based learning methodologies and challenges. The assessment of teamwork in project-based learning involves, among others, assessing students’ participation and the interactions between team members. Project-based learning can easily be handled in small-size courses, but course management and teamwork assessment become a burdensome task for instructors as the size of the class increases. Additionally, when project-based learning happens in a virtual space, such as online learning, interactions occur in a less natural way. This study explores the use of instant messaging apps (more precisely, the use of Telegram) as team communication space in project-based learning, using a learning analytics tool to extract and analyze student interactions. Further, the study compares student interactions (e.g., number of messages exchanged) and individual teamwork competence acquisition between traditional asynchronous (e.g., LMS message boards) and synchronous instant messaging communication environments. The results show a preference of students for IM tools and increased participation in the course. However, the analysis does not find significant improvement in the acquisition of individual teamwork competence.S

Riesgos laborales presentes en los puestos de trabajo de la MiPyme "Panadería Mendoza", ubicada en el Departamento de León, Municipio de Nagarote, en el período de Agosto a Diciembre de 2022

El presente trabajo se basó en la realización de una evaluación inicial de riesgos laborales en la MiPyme Panadería Mendoza, la cual está conformada por 5 áreas, donde se logró identificar y estimar los peligros, niveles de exposición, probabilidad de ocurrencia y las afectaciones que estos pueden causar a los colaboradores que se encuentren expuestos a los mismos. Para esta evaluación, se tomaron en cuenta aspectos en relación a las condiciones laborales, tanto físicas, de seguridad y ergonómicas. Actualmente la panadería presenta deficiencia en materia de higiene y seguridad laboral, entre las que se destacan caída al mismo nivel y distinto nivel, musco-esqueléticos, fatiga, entre otros. La evaluación se llevó a cabo debido a la falta de un plan de acción que contribuya a la mitigación y control de riesgos existentes en las instalaciones, con esto se espera que la organización implemente medidas/acciones y mejore las condiciones del entorno laboral. Con la información obtenida de la evaluación inicial se elaboró la propuesta de un plan de acción encaminado a la disminución y control de los riesgos encontrados, de modo que permita a los colaboradores desempeñarse de manera segura durante su jornada labora

Impact of climate change on wind and photovoltaic energy resources in the Canary Islands and adjacent regions

© 2021 by the authors. Funding: This research was funded by the European Union’s Horizon 2020 research and innovation program grant number 776661 (SOCLIMPACT project).The progressive energy transition to systems with higher shares of renewable energy is particularly important in islands regions, which are largely dependent on energy imports. In this context, to assess the impact of climate change on renewable energy resources during the 21st century is crucial for polycimakers and stakeholders. In this work, we provide an overview of wind and photovoltaic (PV) resources, its variability and complementarity between them, as well as their future changes, in the Canary Islands and surrounding areas. Variability is assessed through the analysis of energy droughts (low-productivity periods). In addition, a sensitivity test is performed to find the optimal combination of PV (photovoltaic) and wind that reduce energy droughts and the persistence of that conditions at a local scale. A set of climate simulations from the MENA-CORDEX runs are used, in present and future climate (2046-2065, 2081-2100) for two different scenarios (RCP2.6, RCP8.5). Results show different changes in wind productivity depending on the scenario: a decrease in RCP2.6 and an increase in the RCP8.5. PV experienced a subtle decrease, with some exceptions. Changes in variability are small and the complementarity test shows that high shares of PV energy (above 50%) reduce both, energy droughts and the persistence of drought conditions.Depto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEEuropean Commissionpu