This paper presents an accessible method for solfège instruction tailored to blind and visually impaired students, using the Ableton Live software. The proposed approach allows users to create custom MIDI instruments by recording the spoken names of musical notes, which are then mapped onto MIDI files to replace traditional note sounds. This personalized method promotes greater familiarity with musical notation and supports the development of music reading skills without relying on visual cues. The process involves converting sheet music into a MIDI file, identifying the main octave, recording the note pronunciations, and assigning them to a sampler in Ableton Live. Once configured, the customized instrument enables real-time auditory feedback as the notes are played, facilitating a more inclusive and autonomous learning experience. This approach addresses common barriers in traditional solfège instruction for blind learners, such as limited access to accessible materials and the visual nature of many teaching methods, by leveraging audio-based interaction and widely available digital tools.

Smartwatches are wearable devices of emerging mobile technology and are increasingly in people's daily lives. They allow you to perform various tasks; however, the interaction with these devices still proves to be a significant challenge. Several studies carried out interaction studies with smartwatches using gesture recognition. Thus, this work presents a comprehensive Systematic Review of Literature (SRL) on interaction with smartwatches using gesture recognition, showing what has already been developed and what is state of the art. We searched in four databases with relevant scientific scope: ACM Digital Library, IEEE Xplore Digital Library, Science Direct, and Scopus. Work on this theme is diverse; gesture recognition is used to perform operations on smartwatches itself or even control other devices or virtual environments. We hope that this work will provide a rich base on the methods developed and that it will become a source of research for future researchers and that can support the development of other methods and applications.

Medical X-ray images are an important and valuable source of studies and diagnoses for diseases with low cost besides its high availability. However, radiological images are subject to degradations related to low contrast and presence of noise. Based on this finding, this article presents a simple but efficient enhancement method for these images with the objective of contrast gain and noise removal. The proposed method (MP) consists of a sequence of interactive steps. Start from the step of double precision conversion and end with removing impulsive noises. An evaluation with the PSNR, Entropy, AMBE, and IQR indicators was performed, besides gain check on the thresholding process and the histogram characterization. The evaluation was conducted on three different datasets in a total of 1409 images chest X-rays. The results compared to others known in the literature proved to be promising and put it as an interesting alternative in the process of enhancement medical X-ray images.