Adopting MQTT for a multi protocols IoMT system

<span>Coronavirus disease (COVID-19) altered the way of caregiving and the new pandemic forced the health systems to adopt new treatment protocols in which remote follow-up is essential. This paper introduces a proposed system to link a remote healthcare unit as it is inside the hospital. Two different network protocols; a global system for mobile communication (GSM) and Wi-Fi were used to simulate the heath data transfer from the two different geographical locations, using Raspberry Pi development board and Microcontroller units. Message queuing telemetry transport (MQTT) protocol was employed to transfer the measured data from the healthcare unit to the hospital’s Gateway. The gateway is used to route the aggregated health data from healthcare units to the hospital server, doctors’ dashboards, and the further processing. The system was successfully implemented and tested, where the experimental tests show that the remote healthcare units using a GSM network consumed about 900 mWh. A high percentage of success data packets transfer was recorded within the network framework as it reaches 99.89% with an average round trip time (RTT) of 7.5 milliseconds and a data transfer rate up to 12.3 kbps.</span>

DSP TMS320C6678 Based SHVC Encoder Implementation and its Optimization

The programmable processors newest technologies, as for example the multicore Digital Signal Processors (DSP), offer a promising solution for overcoming the complexity of the real time video encoding application. In this paper, the SHVC video encoder was effectively implemented just on a single core among the eight cores of TMS320C6678 DSP for a Common Intermediate Format (CIF)input video sequence resolution(352x288). Performance optimization of the SHVC encoder had reached up 41% compared to its reference software enabling a real-time implementation of the SHVC encoder for CIF input videos sequence resolution. The proposed SHVC implementation was carried out on different quantization parameters (QP). Several experimental tests had proved our performance achievement for real-time encoding on TMS320C6678.

Research on the Water Ridge and Slamming Characteristics of a Semisubmersible Platform under Towing Conditions

During the towing of semisubmersible platforms, waves impact and superpose in front of the platform to form a ridge shaped “water ridge”, which protrudes near the platform and produces a large slamming pressure. The water ridges occur frequently in the towing conditions of semisubmersible platforms. The wave–slamming on the braces and columns of platform is aggravated due to the water ridges, particularly in rough sea conditions. The effect of water ridges is usually ignored in slamming pressure analysis, which is used to check the structural strengths of the braces and columns. In this paper, the characteristics of the water ridge at the braces of a semisubmersible platform are studied by experimental tests and numerical simulations. In addition, the sensitivity of the water ridge to the wave height and period is studied. The numerical simulations are conducted by a Computational Fluid Dynamics (CFD) method, and their accuracy is validated based on experimental tests. The characteristics of the water ridge and slamming pressure on the braces and columns are studied in different wave conditions based on the validated numerical model. It is found that the wave extrusion is the main reason of water ridge. The wave–slamming pressure caused by the water ridge has an approximately linear increase with the wave height and is sensitive to the wave period. With the increase of the wave period, the wave–slamming pressure on the brace and column of the platform increases first and then decreases. The maximum wave–slamming pressure is found when the wave period is 10 s and the slamming pressure reduces rapidly with an increase of wave period.

A Novel Graphite-Based Sorbent for Oil Spill Cleanup

The performance of an innovative material based on expanded graphite, Grafysorber® G+ (Directa Plus), has been tested through laboratory, tank, and confinement tests for oil removal in case of an oil spill and water treatment. In addition to the ability to retain oil, the possibility of reusing this material after regeneration via squeezing was also evaluated. As a comparison, the same experimental tests were conducted using polypropylene flakes (PP), the material currently most used to deal with spill accidents. Oils with different chemical and physical properties were used, namely kerosene, diesel, and crude oil. From the laboratory tests, the capacity of Grafysorber® G+ to retain oil was found to be directly proportional to the viscosity of the latter, with adsorption values ranging from 76.8 g/g for diesel to 50.8 g/g for kerosene, confirming the potential of the innovative material compared to the PP. Cyclical use tests have confirmed certain reusability of the material, even if its adsorbent capacity decreases significantly after the first cycle and continues to decrease in subsequent cycles, but a less marked manner. Finally, some considerations based on the adsorption capacities were found to suggest that the adoption of the new material is also economically preferable, resulting in savings of 20 to 40% per kg of hydrocarbon treated.

Experimental and Numerical Analysis of the Deformation Behavior of Adaptive Fiber-Rubber Composites with Integrated Shape Memory Alloys

Fiber-reinforced rubber composites with integrated shape memory alloy (SMA) actuator wires present a promising approach for the creation of soft and highly elastic structures with adaptive functionalities for usage in aerospace, robotic, or biomedical applications. In this work, the flat-knitting technology is used to develop glass-fiber-reinforced fabrics with tailored properties designed for active bending deformations. During the knitting process, the SMA wires are integrated into the textile and positioned with respect to their actuation task. Then, the fabrics are infiltrated with liquid silicone, thus creating actively deformable composites. For dimensioning such structures, a comprehensive understanding of the interactions of all components is required. Therefore, a simulation model is developed that captures the properties of the rubber matrix, fiber reinforcement, and the SMA actuators and that is capable of simulating the active bending deformations of the specimens. After model calibration with experimental four-point-bending data, the SMA-driven bending deformation is simulated. The model is validated with activation experiments of the actively deformable specimens. The simulation results show good agreement with the experimental tests, thus enabling further investigations into the deformation mechanisms of actively deformable fiber-reinforced rubbers.

Graph-optimisation-based self-calibration method for IMU/odometer using preintegration theory

Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.

Design and Application of Electrical Machines

Design and Application of Electrical Machines is a Special Issue of Energies. In this Special Issue, authors from various research centers present the results of their scientific research on electrical machines. In eighteen papers, they presented simulation studies, design works, and experimental tests on built prototypes.

Efficiency of Hybrid Algorithms for Estimating the Shear Strength of Deep Reinforced Concrete Beams

Earthquakes occurred in recent years have highlighted the need to examine the strength of reinforced concrete (RC) members. RC beams are one of the elements of reinforced concrete structures. Due to the dramatic increase in the population and the number of medium/high-rise buildings, in recent years, the beams of buildings have been mainly designed and executed in the type of deep beams. In this study, the artificial neural network (ANN) with optimization algorithms, including particle swarm optimization (PSO), Archimedes optimization algorithm (AOA), and sparrow search algorithm (SSA), are used to determine the shear strength of reinforced concrete deep (RCD) beams. 271 samples from experimental tests are employed to develop algorithms. The results of this study, design codes equations, and previous research are compared. Comparison between the results shows that the PSO-ANN algorithm is more accurate than previous methods. Finally, SHApley Additive exPlanations (SHAP) method is utilized to explain the predictions. SHAP reveals that the beam span and the ratio of the beam span to beam depth have the highest impact in predicting shear strength.

Cornering the universal shape of fluctuations

Understanding the fluctuations of observables is one of the main goals in science, be it theoretical or experimental, quantum or classical. We investigate such fluctuations in a subregion of the full system, focusing on geometries with sharp corners. We report that the angle dependence is super-universal: up to a numerical prefactor, this function does not depend on anything, provided the system under study is uniform, isotropic, and correlations do not decay too slowly. The prefactor contains important physical information: we show in particular that it gives access to the long-wavelength limit of the structure factor. We exemplify our findings with fractional quantum Hall states, topological insulators, scale invariant quantum critical theories, and metals. We suggest experimental tests, and anticipate that our findings can be generalized to other spatial dimensions or geometries. In addition, we highlight the similarities of the fluctuation shape dependence with findings relating to quantum entanglement measures.