The use of Inductive Wireless Power Transfer (IWPT) varies from low-power applications such as mobile phones and tablets chargers to high-power electric vehicles chargers. DC–DC converters are used in IWPT systems, and their design needs to consider the demand of high efficiency in the power transfer. In this paper, a DC–DC power converter for IWPT is proposed. Its topology uses a DC–AC converter in the transmitter circuit and an AC–DC converter in the receptor. The transmitter has an interleaved coupled-Buck converter that integrates two Buck converters connected to a half inverter bridge and a parallel resonant load. The control strategy implemented for the semiconductor switching devices allows two operating modes to obtain a sinusoidal output voltage with a low distortion that makes it suitable in high-efficiency power transfer systems. To obtain a DC output voltage, a full wave bridge rectifier is used in the receptor circuit. The proposed topology and the control strategy are validated with simulation and experimental results for a 15 W prototype.

The ever-evolving landscape of healthcare demands innovative solutions, particularly in light of the global health crisis of 2020 and the aging global population. Technological advancements and new approaches in remote health monitoring systems have helped to bridge the gap for vulnerable individuals such as older adults. This review explores methods for the analysis of physiological signals using remote and intelligent systems and mobile and web-based applications, mostly linked to wearable devices, focusing primarily on the elderly population. The main objective is to identify crucial advancements in the development or integration of technology applied to addressing challenges of this magnitude. The research is structured following the PRISMA-ScR guidelines. The search strategy was implemented in databases such as the ACM Digital Library, IEEE Xplore, PubMed, Science Direct, Scopus, and Springer Link. A total of 411 articles were collected, and inclusion and exclusion criteria were applied to focus on studies published between 2020 and 2024. Ultimately, 100 articles from 35 countries were selected for data extraction. The findings reveal significant progress in remote monitoring technologies but emphasize the need for rigorous validation to ensure accuracy and reliability across diverse populations. To develop robust systems that provide equitable and high-quality healthcare, it is essential to address critical challenges such as data privacy, security, accessibility, and ethical considerations.

The hovering flight of a quadrotor Unmanned Aerial Vehicle (UAV) refers to maintaining the aircraft in a fixed position in the air, without lateral, vertical, or rotational movements, using only the vehicle’s control systems to maintain proper balance in all spatial dimensions. Algorithms and control systems have been developed to continuously adjust motor speeds to counteract deviations from the desired position and achieve effective hovering flight. This paper proposes a set of PID controllers with an integral effect based on the Riemann–Liouville fractional-order approach to improve the hovering flight of a quadrotor UAV. This research innovates by introducing a set of fractional-order PID controllers for UAV hover stability, which offer better adaptability to non-linear dynamics and robustness than traditional PID controllers. Also presented is the development of new performance metrics (MSE, BQC-LR), which allow for more comprehensive control system evaluations. A thorough comparative analysis with conventional control methods demonstrates the superior performance of fractional-order control in real-world simulations. The numerical simulation results show the effectiveness of the proposed Fractional Integral Action PID Controller in the control of UAV hovering flight, while comparative analyses against a classical controller emphasize the benefits of the fractional-order approach in terms of control accuracy.

A model and real-time simulation of a gas turbine engine (GTE) by real-time tasks (RTT) is presented. A Kalman filter is applied to perform the state vector identification of the GTE model. The obtained algorithms are recursive and multivariable; for this reason, ANSI C libraries have been developed for (a) use of matrices and vectors, (b) dynamic memory management, (c) simulation of state-space systems, (d) approximation of systems using equations in matrix finite difference, (e) computing the mean square errors vector, and (f) state vector identification of dynamic systems through digital Kalman filter. Simulations were performed in a Single Board Computer (SBC) Raspberry Pi 2^® with a real-time operating system. Execution times have been measured to justify the real-time simulation. To validate the results, multiple time plots are analyzed to verify the quality and convergence time of the mean square error obtained.

Quick Response (QR) two-dimensional codes were designed to send information in a simple and versatile way, such as sharing a product or company website. Nowadays they can be found in documents with sensitive information, such as personal documents (passports, visas, bank transfers) and documents with restricted information of companies (financial reports, legal documents), for this reason it is important to take care of the information that is sent or shared, depending on its use, it is important to add levels of security to the information encoded in QR codes, since in some cases sensitive information is sent. In this paper we propose to add two levels of security to QR codes that will share sensitive information. A first level of security is the encryption of the original information through the Privacy Guard (GPG) method, a second level of security is the multiplexing of two pieces of information in a chromatic QR code, where each color represents an encoded information, the incorporation of the two levels of security will keep the information shared by the users secure.

Every computer task generates response times depending on the computer hardware and software. The response times of tasks executed in real-time operating systems such as RT-Linux can vary as their instances evolve even though they always execute the same algorithm. This variation decreases as the priority of the tasks increases; however, the minimum and maximum response times are still present in the same task, and this complicates its monitoring, decreasing its level of predictability in case of contingency or overload, as well as making resource sizing difficult. Therefore, the need arises to propose a model capable of reconstructing the dynamics of response times for the instances of a task with high priority in order to analyze their offline behavior under specific working conditions. For this purpose, we develop the necessary theory to build the response time reconstruction model. Then, to test the proposed model, we set up a workbench consisting of a single board computer, PREEMPT_RT, and a high priority task generated by the execution of a matrix inversion algorithm. This work demonstrates the application of the theory in an experimental process, presenting a way to model and reconstruct the dynamics of response times by a high-priority task on RT-Linux.