In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple...
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Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems c...
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Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems capable of identifying defects. This research proposes a framework for recommending machine learning algorithms that diagnose and detect broken bar defects in three-phase induction motors under transient operation based on artificial intelligence. Employing experimental data, features were extracted and selected based on current, voltage, and vibration. A protocol of insertion of white noise showed that the proposed framework admitted 80% of noise without losing the predictive capacity based on a multicriteria performance measure.
Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces ...
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Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism (∼0.6), over a wide range of incident angles ±5°. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications.
Fast, accurate, and realistic simulations of ultrasonic scattering in biological tissues play an important role in biomedical ultrasound research. This study introduces UltraWave, a new open-source ultrasound simulati...
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ISBN:
(数字)9798350371901
ISBN:
(纸本)9798350371918
Fast, accurate, and realistic simulations of ultrasonic scattering in biological tissues play an important role in biomedical ultrasound research. This study introduces UltraWave, a new open-source ultrasound simulation tool we developed for accurately modeling acoustic and elastic wave propagation in two- and three-dimensional heterogeneous media. UltraWave allows the utilization of multiple graphics processing units (GPUs) to deliver faster and more accurate full-wave simulations. The perfectly matched layer was integrated into the simulator. UltraWave was validated against well-established scattering theories in a variety of basic scattering scenarios, and achieved similar or higher accuracy than the widely used k-Wave toolbox. Additionally, UltraWave outperformed k-Wave in terms of computational efficiency with both central processing units (CPUs) and GPUs, particularly when using GPU acceleration for elastic wave simulations. These results demonstrated the potential of UltraWave as a promising tool for biomedical ultrasound simulations.
This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and relate...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D
The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic image...
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The implementation of Gated Recurrent Neural Networks (GRU) to generate background music (BGM) combines deep learning technology with music that is used for the visual content of a commercial or educational. Indeed, t...
The implementation of Gated Recurrent Neural Networks (GRU) to generate background music (BGM) combines deep learning technology with music that is used for the visual content of a commercial or educational. Indeed, this BGM is necessary to enhance the intended message expressed to the other audience. This work aimed to provide the model network of GRU which is based on RNN to generate multi-label genres of music by using the open source of GTZAN to evaluate the new BGM. Our GRU networks can solve the vanishing gradient problem by utilizing both the reset gate and the update gate on the network. In the results, we achieved a new BGM that synchronized with the human mood which made more variety of sounds.
The green transition has brought about a worldwide-shift to the use of renewables as alternative energy sources. Because of this, high voltage DC has been a field of interest in power electronics due to its capability...
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In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is ne...
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ISBN:
(数字)9798331508807
ISBN:
(纸本)9798331508814
In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is necessary to ensure better sensor fusion. Therefore, this article proposes an extrinsic sensor calibration based on markers and associated to three orthogonal planes. This technique is applied to two calibration approaches, LiDAR-Robot and LiDAR-Camera. The first one calculates the transformation between a 3D LiDAR sensor and a robot, and the second system calculates the transformation between a 3D LiDAR and an embedded RGB camera. To demonstrate the efficiency of our method, we performed simulations on the CoppeliaSim simulator and experiments in the laboratory. Then, the results show that it is possible to calibrate the sensors with the methodologies.
This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization ac...
This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people.
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