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This study presents the design and evaluation of AquaSignalNet, a deep learning-based system for recognizing underwater visual commands to enable the autonomous navigation of a Remotely Operated Vehicle (ROV). The system is built on a ResNet50 V2 architecture and trained with a custom dataset, UVSRD, comprising 33,800 labeled images across 12 gesture classes, including directional commands, speed values, and vertical motion instructions. The model was deployed on a Raspberry Pi 4 integrated with a TIVA C microcontroller for real-time motor control, a PID-based depth control loop, and an MPU9250 sensor for orientation tracking. Experiments were conducted in a controlled pool environment using printed signal cards to define two autonomous trajectories. In the first trajectory, the system achieved 90% success, correctly interpreting a mixed sequence of turns, ascents, and speed changes. In the second, more complex trajectory, involving a rectangular inspection loop and multi-layer navigation, the system achieved 85% success, with failures mainly due to misclassification resulting from lighting variability near the water surface. Unlike conventional approaches that rely on QR codes or artificial markers, AquaSignalNet employs markerless visual cues, offering a flexible alternative for underwater inspection, exploration, and logistical operations. The results demonstrate the system’s viability for real-time gesture-based control.

Industrial automation in the manufacturing environment has revolutionized production and manufacturing in many industries, generating significant improvements in efficiency, quality, and process effectiveness. However, it has also posed challenges related to feedback in manufacturing environment monitoring systems, and increasing the effectiveness, productivity, and quality in industrial production. Feedback systems in the manufacturing environment are fundamental to industrial automation, which is why an application has been developed for the detection of elements in a printed circuit board manufacturing cell. The solution presented in this article proposes implementing a continuous feedback system with the ability to provide real-time information to identify the location of elements in a manufacturing cell and potentially detect anomalies, with the goal of improving the manufacturing process appropriately.

The perinatal mortality rate is very high throughout the world. A fetal monitor may be used remotely, and this would tackle the problem of continuous monitoring of high-risk pregnancies. There is evidence that current technology is of low reliability, and, therefore, of low precision to identify fetal health. In medical technological implementation, a safe, efficient, and reliable operation must be guaranteed, and the main problem is that remote fetal monitor gathers just a few samples, so the hypothesis of classical theory is not met. We are proposing an approach that improves the data’s lack of reliability that accompanies the use of a remote fetal monitor. The method refers to how, by using the existing technologies and the initial experimental data, it is possible to apply probabilistic models that are truly representative of each application. This leads to the characterization of properties of the statistics used to generate a representative probabilistic model without the need to consider the hard suppositions. Results show that, for every case study, it was possible to improve estimations of measurement uncertainty. The proposed method is a useful tool to increase the reliability of medical technology, especially for pieces of equipment where a health care professional is not available.

Submarine gliders are specialized systems used in applications such as environmental monitoring of marine fauna, in the oil industry, among others. The glider launch and capture is a costly process that requires substantial technological and human resources, so the orderly and error-free storage of data is of fundamental importance due to the subsequent analysis. The amount of information being obtained from the seabed is increasing, this leads to the need to develop robust and low-cost ad-hocsystems for this type of application. The challenge is the integration of the different software layers in the storage system because the monitored variables must be ordered according to different glider operations such as calibration data update and navigation. Additionally, to avoid data corruption in the memory chip, error control coding must be used. The goal of this paper is to present a novel design of different layers of software integrated into a datalogger: reception, error control, and storage logic for the different glider operations. The design of the datalogger is based on a NAND flash memory chip and an MSP430 microcontroller. To correct bit-flipping errors, a BCH code that corrects 4 errors for every 255 bits is implemented into the microcontroller. The design and evaluation are performed for different glider operations, and for different lengths and correction capabilities of the BCH module. A test to calculate the storage time has been carried out. This test shows that in the case of 256 bytes per sample, at 30 samples per minute, and 1 GB of storage capacity, it is possible to collect data from the glider sensors for 84 days. The results obtained show that our device is a useful option for storing underwater sensor data due to its real-time storage, power consumption, small size, easy integration, and its reliability, where the bit error rate BER is of 2.4 ×10−11.

The color and its representation play a basic role in Image Analysis process. Several methods can be beneficial whenever they have a correct representation of wave-length variations used to represent scenes with a camera. A wide variety of spaces and color representations is founded in specialized literature. Each one is useful in concrete circumstances and others may offer redundant color information (for instance, all RGB components are high correlated). This work deals with the task of identifying and sorting which component from several color representations offers the majority of information about the scene. This approach is based on analyzing linear dependences among each color component, by the implementation of a new sorting algorithm based on entropy. The proposal is tested in several outdoor/indoor scenes with different light conditions. Repeatability and stability are tested in order to guarantee its use in several image analysis applications. Finally, the results of this work have been used to enhance an external algorithm to compensate the camera random vibrations.

This work aimed to design a tensile horizontal machine that performs mechanical testing for suspension clamps, transmission line accessories, and overhead conductors with the following features: the suspension clamps device will be a permanent part of the structure, requiring a minimal setup; and it will accept overhead conductor specimens with lengths of up to 12 m and also be able to perform testing for pieces that require the plate-fork fastening option. Analytical and numerical calculations are performed according to the AISC-360-16 standard and static structural module of ANSYS software, respectively, to compare results.

Abstract (en_US) The color and its representation play a basic role in Image Analysis process. Several methods can be beneficial whenever they have a correct representation of wave-length variations used to represent scenes with a camera. A wide variety of spaces and color representations is founded in specialized literature. Each one is useful in concrete circumstances and others may offer redundant color information (for instance, all RGB components are high correlated). This work deals with the task of identifying and sorting which component from several color representations offers the majority of information about the scene. This approach is based on analyzing linear dependences among each color component, by the implementation of a new sorting algorithm based on entropy. The proposal is tested in several outdoor/indoor scenes with different light conditions. Repeatability and stability are tested in order to guarantee its use in several image analysis applications. Finally, the results of this work have been used to enhance an external algorithm to compensate the camera random vibrations.