ABSTRACT. Nowadays, internet access and the sophisticated processing capacities of electronic devices for the capture and visualization of visual information, such as images; have allowed young users practices such as downloading, storing, editing, and re-sharing of images without authorization of the image owner. To solve this problem a watermarking algorithm for digital images is proposed, which is able to warranty the image protection against the most common editions incorporated into the capture devices and artistic editions integrated into the upload option of the social media. The experimental results show a high performance of the proposed algorithm, due to, a minimum edition of the protected image exhibiting to the naked eye the watermark pattern, by another way, the average performance is reported with a PSNR=42dB and NCD=0.0885.

ABSTRACT. The automatic evaluation of mental state/emotions during driving constitutes a powerful tool for assessing the risk of accidents. It is known that about 97% of accidents in Mexico during 2021 were related to human causes, while 95% of such causes were attributable to drivers. In this work, we use encephalographic and cardiographic tools to asses the emotions and the state of mind of drivers during a virtual tour of city driving conditions. Two different traffic and pedestrian crossing conditions were used for the same city path. Our results arouse that significant differences between low- and high-traffic conditions are present in drivers dependent mainly on driver experience. Experienced drivers, irrespective of their gender, are considerably more robust to face the variations in traffic measured in both their biometric data and vehicle dynamics performance. The results of this work may help assess the feasibility of deriving customizable driving assistance systems that take into account the emotions of driving.

ABSTRACT. Finding solutions to NP-Complete problems is colloquially related to finding a needle in a haystack because of their complexity, which, in consequence, yields exponential time algorithms. In particular, one strategy to find ``good solutions" to these problems is to evaluate potential solutions generated at random and measure the quality of each in every attempt. However, true randomness cannot be implemented on classical computers. Hence it is emulated through algorithms that create pseudo-random numbers. This paper analyzes two NP-complete problems in graphs: the Traveling Salesman and the Hamiltonian Path Problems. The Ant Colony Optimization algorithm was used to find solutions to these with different random number generators: pseudo-random and quantum-random. The convergence time and overall cost of varying graph setups (different complexity levels, i.e. 50, 100, 150, and 200 nodes) were compared under both random number generators. The results indicate that, generally, when quantum random number generators are used, faster convergence is achieved and better results are obtained.

ABSTRACT. This paper proposes a model predictive control (MPC) algorithm optimized using the artificial bee colony algorithm (ABC) to control the temperature of the pasteurization product in a small-scale pasteurization plant following a set point trajectory and minimizing power consumption. The proposed algorithm is compared with the MPC tuned by trial and error. The results show that the proposed ABC optimization-based MPC algorithm shows improvements in relation to trajectory tracking and disturbance rejection. A significant reduction in the integral squared error (ISE) of approximately 68.12% and in the settle times (up and down) of 58.90% and 84.40%, respectively, was achieved.

ABSTRACT. This paper presents a comparative study of five cutting-edge iterative methods - Particle Swarm Optimization, Quantum Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Damped Least Squares (DLS), and Forward and Backward Reaching Inverse Kinematics (FABRIK) - used to solve the challenging inverse kinematics problem in robots with increasing degrees of freedom in their kinematic chains. The analysis includes 7, 9, 11, 13, and 15 degrees of freedom redundant serial robots with hinge and pivot joints. Performance indicators, such as execution time, iteration count, and final error, were evaluated for each method across 500 randomly generated target poses for the five robotic chains, providing valuable insights into the algorithms' behavior as the degrees of freedom in the kinematic chains increase.

ABSTRACT. Currently, novel approaches are being developed to overcome the imminent Moore's law failure. The techniques attempt to gain greater computing power by reducing the number of transistors. They are based on nonlinear or chaos computing. Nonlinear dynamics is an essential source of various patterns that can represent natural systems or perform computational tasks. This work presents the implementation of a voltage logic gate based on the plane equation. This is achieved by using two variables of the plane equation as inputs and the other as output.

ABSTRACT. The article proposes an adaptive control law to compensate input faults in an electromechanical actuator aiming to restore the output to a desired trajectory. The adaptive control approach explicitly considers in the design both Coulomb and viscous friction, using a smooth model for the static friction term. The proposed adaptive algorithm proves to be useful even in the case of parametric uncertainty, rendering the system globally asymptotically stable. Through simulations, the authors demonstrate the efficacy of the proposed scheme, showcasing the performance under parametric uncertainty and input fault.

ABSTRACT. In this article, reducing the mutual coupling between the elements of a 2x1 compact UWB-MIMO antenna is achieved by applying the defected ground structure (DGS) technique. The DGS consists of two inverted L-shaped slots and one Ishaped notch. The two multiple-input multiple-output (MIMO) antenna elements are rectangular patch antennas with a Tshaped microstrip attached to one end. The dielectric substrate of the antenna is FR4 with a relative permittivity of 4.4 and a thickness of 1.6 mm. The separation between the centers of the two elements has been achieved to be only 0.027 the operating wavelength, and the MIMO antenna has a dimension of 30x25 mm. Simulated and experimental performance results are presented. Certain geometric dimensions of the DGS are optimized in order to achieve suppression of narrow bands in the frequency bands of WiMAX and WLAN technologies, from 3 to 3.6 GHz and from 5.3 to 6.3 GHz, respectively. The proposed antenna has a bandwidth of 3.6 GHz to greater than 12 GHz and an estimated gain of up to 3.8 dB.

ABSTRACT. This work presents the design proposal for a pseudorandom number generator with two Linear Feedback Shift Register LFSR. The operating frequency of one of the registers depends on the frequency of a neuronal module, that is capable of producing spiking of bursting phasic and bursting tonic form, which, for each pulse generated for the neuronal module, produces an LFSR displacement and a new output data. The data obtained from the pseudorandom number generator with the neuronal module was printed in an archive text TXT to process and analyze the sequence by the linear complexity test proposed by the National Institute of Standards and Technology NIST and validate that the sequence is complex enough and aleatory. Also, the circuit implementation was carried out in the FPGA Field Programmable Gate Array Virtex 7 xc7vx485t-2ffg1761 device.

ABSTRACT. The three-phase rectifiers are widely used in different industrial applications, like energy storage systems, uninterruptible power supplies, renewable energy generation systems due to their high-power transfer and its power factor correction capability with high-quality DC output and sinusoidal input currents. To control the power factor, the model predictive control technique has emerged as a suitable and intuitive control strategy, however, the high computational cost limits the converter frequency operation. As a solution, in this paper an artificial neural network based on model predictive control is proposed to obtain a three-phase sinusoidal input currents under different power demands, reducing the computational cost.

ABSTRACT. This paper presents a 1.5-kW active power rectifier that is intended to be the power topology used in a Battery Charger for a 5.6-kW battery pack that is used to propel an 83 kWh Sport Motorcycle. Experimental results demonstrate that the converter topology and the control strategy can keep a 0.99 Power Factor value, reducing the THD in each phase of the AC power supply. The controller is evaluated applying current reference steps and load changes at 1.5 kW power rate operation.

ABSTRACT. The objective of this paper is two-fold: (i) to introduce a full formulation for the calculation of three-phase impedance matrices of underground cables with the explicit representation of the self and mutual impedances that exist between the metallic components of the cable, including bonding and non-bonding cables; (ii) to carry out a power loos analysis in three-phase power systems of underground cables with shunt reactive power compensation, using a full three-phase formulation.

ABSTRACT. This article deals with the problem of harmonic resonance in power systems, which causes harmonic amplification and can worsen existing harmonic problems in the system. Therefore, performing a frequency response analysis is essential to identify series and parallel resonances in the system within a frequency range of interest. To address this issue, it is proposed to use a Frequency-Dependent Network Equivalent (FDNE) based on a rational function in the z-domain. This approach is based on acquiring measurement data and implementing parameter identification techniques using the recursive least squares method to evaluate the frequency response. To validate the proposed method, its implementation is carried out in different case studies.

ABSTRACT. Spinning reserves of generating units are essential for the stability, continuity, and reliability of electrical power systems. However, the increasing integration of wind farms (WF) into power grids has led to a reduction in power reserves due to the displacement of conventional plants based on synchronous generators. Therefore, some grid codes require WF to provide this auxiliary service, which can be achieved by operating variable speed wind turbines (VSWT) in deloading mode. To this end, this paper presents an optimal power flow (OPF) model with WF complying with spinning reserves considering that VSWT use pitch angle control deloading. One where the WF distributes the responsibility of providing spinning reserves among VSWT according to their operating points. As a result, the specific blade pitch angle of each wind turbine contained in the WF is obtained. The present approach is applied to the IEEE 5-bus test system with an 80-MW wind farm comprising 40 turbines. The power system operation is compared with and without the WF, over a period of 12 hours with varying operating conditions, i.e., using variable patterns of system demand and wind speed.

ABSTRACT. This paper presents a study of the proceedings done towards the electrical commissioning of an 83 kW laboratory, all- electric sport motorbike to obtain energetic analysis and thermal experimental results as a social catalyst for electrification transportation. The electric motorbike mainly uses an 83 kW, Permanent Magnet Synchronous Motor (PMSM) driven by a 350 V, 110 kW motor controller powered by a 350 V, 5.6 kWh LiPo battery pack. The electric train system of the motorbike is controlled and operated by a microcontroller with a touchscreen display where several parameters are monitored, such as velocity, temperature, battery SOC among other indexes. A description of the tests done with the motorbike prototype rig is summarized along the paper in different steady-state operating points, such that electrical and thermal results obtained from the system are analyzed verifying the feasibility of the prototype for personal transportation or racing applications.

ABSTRACT. The integration of electric induction machines into digital platforms has gained significant relevance in recent years. Field-Programmable Gate Arrays (FPGAs) provide a flexible and reconfigurable hardware platform for implementing digital control systems and digital system emulators. This work presents an implementation of an electric induction machine in a digital description and investigates the effects of injecting faults into the system. The study aims to demonstrate the importance of digital implementations and fault injection techniques in enhancing the performance, reliability, and fault tolerance of electric induction machines.

ABSTRACT. The human hand is the main mechanical and sensory tool that allows us to interact with the environment. However, amputees face challenges in their daily lives. To address this, prosthetic hands have emerged as an effective solution. Surface electromyography (sEMG) signals are used to automate the control of these prostheses. Electromyographic (EMG) signals are recordings of the electrical activity generated in muscles during muscle contraction and relaxation. The processing and classification of EMG signals, applying statistical feature analysis, are of great importance in biomedical research and related areas. The aim of this study was to classify six EMG signals representing different hand movements by extracting statistical features in the time domain. The importance of key steps such as filtering, rectification and segmentation was emphasized to obtain an adequate representation of the data. Through feature extraction, the classification of hand opening and closing states was achieved. This highlights the need for careful feature selection in the classification process.

ABSTRACT. Monitoring disturbances in power quality (PQD) has gained importance in recent decades. This interest arises from the fact that disturbances associated with power quality directly affect the equipment connected to the grid, leading to malfunctions or complete equipment failure. For this reason, efforts have been made to optimize the methods for detecting these disturbances occurring in the electrical network.

In this study, a Python algorithm is proposed to improve the detection and classification of seven types of simple electrical disturbances (\emph{sag, swell, flicker, oscillatory transient, interruption, harmonics, and notch}). The algorithm varies the combination of characteristic vectors extracted (\emph{energy, mean, standard deviation, skewness, Shannon entropy, RMS, kurtosis, and log-Energy entropy}) obtained from the Discrete Wavelet Transform (DWT) through Multiresolution Analysis (MRA) with 6 levels of detail. A database was generated by sampling four thousand electrical disturbances at 10 \emph{kHz}. The experiment involved connecting a \emph{Beagle Bone Black} (BBB) development board to a \emph{BK Precision 4064} arbitrary waveform generator.

Combinations of two characteristic vectors were extracted from each signal in the database to evaluate them using the \emph{Random Forest} classifier and determine which one is most suitable for this type of analysis based on their accuracy percentages.

ABSTRACT. Currently, induction motor (IM) is the most common electric machine in the industry. IMs are robust machines; however, they are prone to suffer failures, often located in stator winding due to external factors such as electrical or mechanical overstress, thermal changes, and environmental conditions, which affect the proper functioning of the IM. Therefore, implementing a monitoring system serves the purpose of timely detecting stator failures and determining their severity in order to evaluate the physical state of the winding. In this work, a machine learning strategy is proposed for the analysis and recognition of various degrees of severity of short-circuit damages in the winding of an IM. In general, this strategy consists of statistical indicators, the one-way analysis of variance (ANOVA) method, and a support vector machine (SVM) classifier. Results demonstrate the effectiveness of the proposal.

ABSTRACT. As transportation networks continue to advance in their electrification to accommodate Electric Vehicle (EV) charging, there is potential for hazardous effects to occur within electric distribution grids. This is especially true with a new form of charging system known as Dynamic Wireless Power Transfer (DWPT), where EVs are capable of charging their on-board Energy Storage System (ESS) while they are traversing through a transportation infrastructure. This infrastructure utilizes Inductive Power Transfer (IPT) architectures to direct energy through multiply embedded Transmitter (Tx) pads within a roadway network and by installing Receiver (Rx) pads underneath the chassis of each EV. In this presentation, an overview of DWPT networks and their impacts on the grid will be elucidated to provide a comprehensive understanding of the challenges associated with them. Several of these challenges include, but are not limited to, EV traffic flow approximations, EV charging behavior while in-motion, and EV discharging behavior while in-motion. Furthermore, potential electric load demands mitigation strategies will be presented to demonstrate the sustainability of DWPT systems to be efficiently integrated into power distribution system operations.