Convolutional Neural Networks (CNNs) have proven to be an effective approach for solving image classification problems. The output, the accuracy and the computational efficiency of a CNN are determined mainly by the architecture, the convolutional filters, and the activation functions. Based on the importance of an activation function, in this paper, nine new activation functions based on combinations of classical functions such as ReLU and sigmoid are presented. Also, a study about the effects caused by the activation functions in the performance of a CNN is presented. First, every new function is described, also, their graphs, analytic forms and derivatives are presented. Then, a traditional CNN model with each new activation function is used to classify three 10-class databases: MNIST, Fashion MNIST and a handwritten digit database created by us. Experimental results illustrate that some of the proposed activation functions lead to better performances on classifying than classical activation functions. Moreover, our study demonstrated that the accuracy of a CNN could be increased by 1.18% with the new proposed activation functions.

Using the senses is essential to interacting with objects in real-world environments. However, not all the senses are available when interacting with virtual objects in virtual environments. This paper presents a diamond methodology to fuse two technologies to represent the senses of sight and touch when interacting with a virtual object. The sense of sight is represented through augmented reality, and the sense of touch is represented through kinesthetic haptics. The diamond methodology is centered on the user experience and comprises five general stages: (i) experience design, (ii) sensory representation, (iii) development, (iv) display, and (v) fusion. The first stage is the expected, proposed, or needed user experience. Then, each technology takes its homologous activities from the second to the fourth stage, diverging from each other along their development. Finally, the technologies converge to the fifth stage for fusion in the user experience. The diamond methodology was tested by generating a user’s dual sensation when interacting with the elasticity of a tension virtual spring. The user can simultaneously perceive the visual and tactile change of the virtual spring during the interaction, representing the object’s deformation. The experimental results demonstrated that an interactive experience can be felt and seen in augmented reality following the diamond methodology.

This paper presents the development of a voice-controlled didactic robotic system designed to reproduce letters of the Mexican Sign Language (LSM). The prototype integrates eight independent servomotors, a Raspberry Pi 3-based architecture, and a PCA9685 module for coordinated motion control. A mobile application built in MIT App Inventor enables operation through Spanish voice commands or manual control, enhancing user interaction. The results show that 60% of the letters were correctly executed, 33% with minor mechanical limitations, and 7% not achieved, validating the system’s mechanical stability, gesture accuracy, and educational potential. This project fosters technological inclusion and promotes the use of robotics as a tool for social and educational learning.