In this review, we present a description of conventional technologies and new advances for the estimation and sense of moisture content in grains. The operating principles, accuracies and response times are described. The review considers an exhaustive search of scientific developments and patent registrations. It was concluded that most of the new developments correspond to methods of which the measurement principles are based on the analysis of the electrical characteristics of the grains. In addition, new methods of image analysis have been implemented that provide measurements with reduced response times and with precisions of utility for its application in the agro-industrial field. In addition to this, wireless communication technologies have been implemented that allow the implementation of moisture measurement methods in moving grains within processing chains.
This paper presents the fundamentals; criteria; and mechanical, electrical, and electronic aspects required to properly operate and control emerging mechanical ventilators. We present the basis for their design and manufacture as a contribution to implementing this type of equipment at low cost for intensive care units. In particular, we describe the materials and the mechanical, electrical, and electronic aspects used to implement the SURKAN mechanical ventilator, which was developed in Ecuador during the COVID-19 pandemic for some health centers in the country. The proposed mechanical ventilator provides a functional and reliable design that can be considered a reference for future developments and new implementations.
The objective of this scoping review is to characterize the current panorama of inertia sensors for the rehabilitation of hip arthroplasty. In this context, the most widely used sensors are IMUs, which combine accelerometers and gyroscopes to measure acceleration and angular velocity in three axes. We found that data collected by the IMU sensors are used to analyze and detect any deviation from the normal to measure the position and movement of the hip joint. The main functions of inertial sensors are to measure various aspects of training, such as speed, acceleration, and body orientation. The reviewers extracted the most relevant articles published between 2010 and 2023 in the ACM Digital Library, PubMed, ScienceDirect, Scopus, and Web of Science. In this scoping review, the PRISMA-ScR checklist was used, and a Cohen’s kappa coefficient of 0.4866 was applied, implying moderate agreement between reviewers; 23 primary studies were extracted from a total of 681. In the future, it will be an excellent challenge for experts in inertial sensors with medical applications to provide access codes for other researchers, which will be one of the most critical trends in the advancement of applications of portable inertial sensors for biomechanics.
En este trabajo se presenta una comparación de los tiempos de respuesta, optimización de la ruta y complejidad del grafo en métodos de planificación de trayectoria para robots móviles autónomos. Se contrastan los desarrollos de Voronoi, Campos potenciales, Roadmap probabilístico y Descomposición en celdas para la navegación en un mismo entorno y validándolos para un número variable de obstáculos. Las evaluaciones demuestran que el método de generación de trayectoria por Campos Potenciales, mejora la navegación respecto de la menor ruta obtenida, el método Rapidly Random Tree genera los grafos de menor complejidad y el método Descomposición en celdas, se desempeña con menor tiempo de respuesta y menor coste computacional. Palabras Clave: optimización, trayectoria, métodos de planificación, robots móviles. Referencias [1]H. Ajeil, K. Ibraheem, A. Sahib y J. Humaidi, “Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm, ” Applied Soft Computing, vol. 89, April 2020. [2]K.Patle, G. Babu, A. Pandey, D.R.K. Parhi y A. Jagadeesh, “A review: On path planning strategies for navigation of mobile robot,” Defence Technology, vol. 15, pp. 582-606, August 2019. [3]T. Mack, C. Copot, D. Trung y R. De Keyser, “Heuristic approaches in robot path planning: A survey,” Robotics and Autonomous Systems, vol. 86, pp. 13-28, December 2016. [4]L. Zhang, Z. Lin, J. Wang y B. He, “Rapidly-exploring Random Trees multi-robot map exploration under optimization framework,” Robotics and Autonomous Systems, vol. 131, 2020. [5]S. Khan y M. K. Ahmmed, "Where am I? Autonomous navigation system of a mobile robot in an unknown environment," 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV), pp. 56-61, December 2016. [6]V. Castro, J. P. Neira, C. L. Rueda, J. C. Villamizar y L. Angel, "Autonomous Navigation Strategies for Mobile Robots using a Probabilistic Neural Network (PNN)," IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society, pp. 2795-2800, Taipei, 2007. [7]Y. Li, W. Wei, Y. Gao, D. Wang y C. Fan, “PQ-RRT*: An improved path planning algorithm for mobile robots,” Expert Systems with Applications, vol. 152, August 2020. [8]A. Muñoz, “Generación global de trayectorias para robots móviles, basada en curvas betaspline,” Dep. Ingeniería de Sistemas y Automática Escuela Técnica Superior de Ingeniería Universidad de Sevilla, 2014. [9]H. Montiel, E. Jacinto y H. Martínez, “Generación de Ruta Óptima para Robots Móviles a Partir de Segmentación de Imágenes,” Información Tecnológica, vol. 26, 2015. [10] C. Expósito, “Los diagramas de Vornooi, la forma matemática de dividir el mundo,” Dialnet, Diciembre 2016.
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