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En este trabajo se presenta el diseño, modelado e implementación de un sistema de levitación magnética de un grado de libertad, que consiste en una viga actua da por un cojine te magnético activo en configuración pendular. Se obt iene su representación en espacio de estado y, tras una linealización tangente, su función de transferencia correspondiente. Se describen las características del dispositivo experimental, su instrumentación electrónica y mecanismo, particularmente el proce dimiento de diseño del actuador electromagnético empleado, así como su caracterización para determinar la constante de proporc ionalidad de la fuerza electromagné tica. Finalmente, se muestra la simulación numérica e implementación experimental de esquemas c lásicos de control para estabilizar en el punto de equilibrio del sistema.

Lean Manufacturing has become, in recent years, one of the most important philosophies for improving production and organizational systems. The literature shows that Hesitant Fuzzy Linguistic Terms Sets (HFLTSs) are highly capable of manipulating the uncertainty that the judgments made by evaluators carry and that they are subject to their perception, especially when used in combination with multicriteria decision making (MCDM) for the measurement of indicators in this type of system, as well as their general performance. However, it is still of interest to researchers to develop techniques and instruments that facilitate the measurement of the results obtained after applying this philosophy in organizations. This article proposes a model for the evaluation of the Lean Manufacturing performance through the Analytic Hierarchy Process (AHP) and Dimensional Analysis (DA) using HFLTSs. The results obtained show that the proposed model is a solid tool for the evaluation of Lean Manufacturing systems from a different perspective and that it can be integrated into the issuance of evaluations in a better way by considering human subjectivity. At the same time, it offers a strategy to create priorities in the action plans that Lean system managers propose after evaluating. However, it is important to apply the proposed model to multiple organizations and analyze the results obtained to maximize its benefits. [ABSTRACT FROM AUTHOR]

An accurate method is proposed to measure the electrical parameters describing the experimental charge‐discharge curves of Li‐ion batteries and a pack through an equivalent electric dynamic model based on heuristic optimization algorithms (eg, differential evolution approach). The accuracy of these parameters is critical for on‐board state of charge and Health (SOH) estimations of numerous applications and devices. The procedure is constructed, based on the simple Thévenin electrical model. Charge‐discharge experimental curves collected for different chemistry and capacity batteries are described with the model, revealing better estimation results with respect to other algorithms such as impedance‐based methodologies (decreasing the error until 64.19%) and particle swarm optimization based approaches (decreasing the error until 94.02%). The proposal was assessed with different chemistries, capacities and with a 28 battery pack (LiFeMnPO4, 100 Ah) used in an electric vehicle. [ABSTRACT FROM AUTHOR]

Scientists have long conjectured that the neocortex learns patterns in sensory data to generate top-down predictions of upcoming stimuli. In line with this conjecture, different responses to pattern-matching vs pattern-violating visual stimuli have been observed in both spiking and somatic calcium imaging data. However, it remains unknown whether these pattern-violation signals are different between the distal apical dendrites, which are heavily targeted by top-down signals, and the somata, where bottom-up information is primarily integrated. Furthermore, it is unknown how responses to pattern-violating stimuli evolve over time as an animal gains more experience with them. Here, we address these unanswered questions by analyzing responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons tracked over multiple days in primary visual cortex of awake, behaving female and male mice. We use sequences of Gabor patches with patterns in their orientations to create pattern-matching and pattern-violating stimuli, and two-photon calcium imaging to record neuronal responses. Many neurons in both layers show large differences between their responses to pattern-matching and pattern-violating stimuli. Interestingly, these responses evolve in opposite directions in the somata and distal apical dendrites, with somata becoming less sensitive to pattern-violating stimuli and distal apical dendrites more sensitive. These differences between the somata and distal apical dendrites may be important for hierarchical computation of sensory predictions and learning, since these two compartments tend to receive bottom-up and top-down information, respectively. [ABSTRACT FROM AUTHOR]

The calculation of the view factor is an important consideration in radiative heat transfer analysis. Thermal engineering requires the view factor calculations between complex geometries containing parallel and inclined surfaces. There is currently no analytic formula available for this, so the summation rule (SR) must be used. However, when complex geometries are analyzed, processing SR becomes a very intensive task. Therefore, the present study aims to exploit vector calculus to develop a formula for calculating the view factors for radiative heat transfer from any two rectangular oblique or parallel surfaces. The exact solution obtained by means of the contour integration was compared with the numerical integration of the quadruple integral using the multiple Simpson's rule 1/3 with five intervals (MSR) and the summation rule via the Hamilton–Morgan solution (HMS). The lack of similar precedents in the literature reinforces the scientific and practical nature of the proposed method. [ABSTRACT FROM AUTHOR]

Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to improve their product design risk assessment process to gain advantages over competitors, using proven tools like Failure Mode and Effect Analysis (FMEA) and mixing risk assessment methods. However, with current risks assessment tools and a combination of other methods, there is the opportunity to improve risk analysis. This document aims to reveal a novel integrated method, where FMEA, Pythagorean Fuzzy Sets (PFS), and Dimensional Analysis (DA) are cohesive in one model. The proposed method provides an effective technique to identify risks and remove uncertainty and vagueness of human intervention during risk assessment using the Failure Mode and Effect Analysis method. A real-life problem was carried out to illustrate the proposed method. Finally, the study was substantiated by using a correlation and sensitivity analysis, demonstrating the presented integrated method’s usefulness in decision-making and problem-solving.