Propuesta del plan de gestión de calidad para el área de desposte de Friogan S.A. planta la Dorada

62 Páginas.Friogan S.A Planta La Dorada, es una empresa dedicada a la producción y comercialización de carne. Dado que la compañía no cuenta actualmente con un sistema de calidad integral se propone la elaboración de un plan del sistema de gestión de calidad para el área de desposte de la planta, el cual cubra los aspectos relacionados con el análisis de los costos de calidad, la generación del enunciado estratégico del sistema, elaboración del mapa de procesos y caracterización del proceso principal, así como el establecimiento de los indicadores de evaluación que permita un cambio en el enfoque global de concebir el sistema dentro de la empresa. El plan es una propuesta para el sistema de gestión del área de estudi

Parallel Quantum Computation Approach for Quantum Deep Learning and Classical-Quantum Models

The paradigm of Quantum computing and artificial intelligence has been growing steadily in recent years and given the potential of this technology by recognizing the computer as a physical system that can take advantage of quantum mechanics for solving problems faster, more efficiently, and accurately. We suggest experimentation of this potential through an architecture of different quantum models computed in parallel. In this work, we present encouraging results of how it is possible to use Quantum Processing Units analogically to Graphics Processing Units to accelerate algorithms and improve the performance of machine learning models through three experiments. The first experiment was a reproduction of a parity function, allowing us to see how the convergence of a given Quantum model is influenced significantly by computing it in parallel. For the second and third experiments, we implemented an image classification problem by training quantum neural networks and using pre-trained models to compare their performances with the same experiments carried out with parallel quantum computations. We obtained very similar results in the accuracies, which were close to 100% and significantly improved the execution time, approximately 15 times faster in the best-case scenario. We also propose an alternative as a proof of concept to address emotion recognition problems using optimization algorithms and how execution times can be positively affected by parallel quantum computation. To do this, we use tools such as the cross-platform software library PennyLane and Amazon Web Services to access high-end simulators with Amazon Braket and IBM quantum experience

Quantum machine learning for intrusion detection of distributed denial of service attacks: a comparative overview

In recent years, we have seen an increase in computer attacks through our communication networks worldwide, whether due to cybersecurity systems' vulnerability or their absence. This paper presents three quantum models to detect distributed denial of service attacks. We compare Quantum Support Vector Machines, hybrid Quantum- Classical Neural Networks, and a two-circuit ensemble model running parallel on two quantum processing units. Our work demonstrates quantum models' e ectiveness in supporting current and future cybersecurity systems by obtaining performances close to 100%, being 96% the worst-case scenario. It compares our models' performance in terms of accuracy and consumption of computational resources

¿Que impacto tiene la implementación del SIIF II en el cumplimiento de las normas y características de la información contables establecidas en el régimen de contabilidad publica?

El presente análisis pretende determinar la incidencia que tendrá esta implementación del aplicativo en el cumplimiento de las normas y características de la información contable contenidas en el Régimen de Contabilidad publica y que serán evaluadas por los entes de control

Numerical simulation of the heat penetration in two-plate arc welding

A mathematical model and numerical simulation of the three-dimensional and transient metal arc-welding process is presented. The heat source is considered as spatially distributed following a centered Gaussian bell, while the substract material (Al 6063) is assumed homogeneous and isotropic with temperature-dependent thermal properties. Radiation and convection are also calculated through an empirical temperature dependent correlation. Phase-change phenomenon is included as a discontinuity in the material specific heat. Calculations were performed by using a finite volume code (CFX4.2TM). Computed heat penetration and weld metal area are found to be in good agreement with experimental data

Numerical simulation of the heat penetration in two-plate arc welding

A mathematical model and numerical simulation of the three-dimensional and transient metal arc-welding process is presented. The heat source is considered as spatially distributed following a centered Gaussian bell, while the substract material (Al 6063) is assumed homogeneous and isotropic with temperature-dependent thermal properties. Radiation and convection are also calculated through an empirical temperature dependent correlation. Phase-change phenomenon is included as a discontinuity in the material specific heat. Calculations were performed by using a finite volume code (CFX4.2TM). Computed heat penetration and weld metal area are found to be in good agreement with experimental data

NeuroNorm:An R package to standardize multiple structural MRI

Preprocessing of structural MRI involves multiple steps to clean and standardize data before further analysis. Typically, researchers use numerous tools to create tailored preprocessing workflows that adjust to their dataset. This process hinders research reproducibility and transparency. In this paper, we introduce NeuroNorm, a robust and reproducible preprocessing pipeline that addresses the challenges of preparing structural MRI data. NeuroNorm adapts its workflow to the input datasets without manual intervention and uses state-of-the-art methods to guarantee high-standard results. We demonstrate NeuroNorm’s strength by preprocessing hundreds of MRI scans from three different sources with specific parameters on image dimensions, voxel intensity ranges, patients characteristics, acquisition protocols and scanner type. The preprocessed images can be visually and analytically compared to each other as they share the same geometrical and intensity space. NeuroNorm supports clinicians and researchers with a robust, adaptive and comprehensible preprocessing pipeline, increasing and certifying the sensitivity and validity of subsequent analyses. NeuroNorm requires minimal user inputs and interaction, making it a userfriendly set of tools for users with basic programming experience

Classical simple Lie 2-algebras of odd toral rank and a contragredient Lie 2-algebra of toral rank 4

After the classification of simple Lie algebras over a field of characteristic p > 3, the main problem not yet solved in the theory of finite dimensional Lie algebras is the classification of simple Lie algebras over a field of characteristic 2. The first result for this classification problem ensures that all finite dimensional Lie algebras of absolute toral rank 1 over an algebraically closed field of characteristic 2 are soluble. Describing simple Lie algebras (respectively, Lie 2-algebras) of finite dimension of absolute toral rank (respectively, toral rank) 3 over an algebraically closed field of characteristic 2 is still an open problem. In this paper we show that there are no classical type simple Lie 2-algebras with toral rank odd and furthermore that the simple contragredient Lie 2-algebra G(F4,a) of dimension 34 has toral rank 4. Additionally, we give the Cartan decomposition of G(F4,a)