For automobile and aerospace engineers, implementing Hall currents and thermal radiation in cooling systems helps increase the performance and durability of an engine. In the case of solar energy systems, the effectiveness of heat exchangers and solar collectors can be enhanced by the best use of hybrid nanofluids and the implementation of a Hall current, thermophoresis, Brownian motion, a heat source/sink, and thermal radiation in a time-dependent hybrid nanofluid flow over a disk for a Bayesian regularization ANN backpropagation algorithm. In the current physical model of Cobalt ferrite $CoF{e}_2{O}_4$ and aluminum oxide $A{l}_2{O}_3$ mixed with water, a new category of the nanofluid is called the hybrid nanofluid. The study uses MATLAB bvp4c to unravel such intricate relations, transforming PDEs into ODEs. This analysis enables the numerical solution of several BVPs that govern the system of the given problem. Hall currents resulting from the interaction between magnetic fields and the electrically conducting nanofluid, and thermal radiation as an energy transfer mechanism operating through absorption and emission, are central factors for controlling these fluids for use in various fields. The graphical interpretation assists in demonstrating the character of new parameters. The heat source/sink parameter is advantageous to thermal layering, but using a high Schmidt number limits the mass transfer. Additionally, a backpropagation technique with Bayesian regularization is intended for solving ordinary differential equations. Training state, performance, error histograms, and regression demonstration are used to analyze the output of the neural network. In addition to this, there is a decrease in the fluid velocity as magnetic parameter values decrease and a rise in the fluid temperature while the disk is spinning. Thermal radiation adds another level to the thermal behavior by altering how the hybrid nanofluid receives, emits, and allows heat to pass through it.

This paper presents an experimental characterization of the proposed radio link model for an underground mine sensor network. Power efficiency and range are critical factors to consider when designing a wireless sensor network, particularly for low data rate applications where the goal is to have a long-lasting, low-maintenance network. A ‘deploy and forget’ strategy is desirable because it allows the network to operate autonomously without requiring frequent maintenance or intervention from network operators. DASH7 and IEEE 802.15.4f are both excellent choices for low-power, long-range wireless sensor networking applications. The proposed radio link model was developed and evaluated for 433 MHz DASH7 in underground mines, considering the practical electromagnetic properties of mine walls and the propagation medium, which helps in calculating accurate signal characteristics. Radio wave propagation is a critical factor that needs to be considered when designing a wireless sensor network for complex mine structures. The received signal strength indicator (RSSI) and packet error rate (PER) are two key parameters that are used to measure wave propagation and assess the quality of the radio link between sensor nodes. The radio link design has been optimized for complex mine structures by utilizing these parameters in a model, leading to improved performance and reliability. The measurements were carried out in the world’s second largest salt mine at Khewra, Pakistan, with representative irregular mine structures. The RSSI and PER were measured at different node positions and with variable separation between the nodes. The proposed model allows for the easy placement of nodes on either the rooftop or near the side walls of the mine corridors, with an average variation of 6% in RSSI and 1.9% in PER. The proposed model was validated using off-the-shelf wizzi sensor nodes received from Wizzi Lab, France, and was programmed to measure RSSI and PER while operating under the 433 MHz DASH7 protocol. An agreement between modeled and measured parameters has been noted, making the proposed model a decent method for efficient node deployment in underground mine sensor networks.

A novel ground slot-based massive multiple-input multiple-output (MIMO) system with 14 elements for dual-band application of next-generation smartphones is developed. Every single antenna in the array is placed on the borders of a smartphone’s PCB, operating within the 3.55 GHz to 3.7 GHz (n48) and 5.855 GHz to 5.925 GHz (n47) frequency bands. This study also further assesses the performance of this system with analytical results, in which the self-s-parameters are less than −6 dB for each antenna, whereas isolation between components is less than −10 dB. At the same time, the overall efficiency reaches 65.55% and higher in the whole band. The evaluation of MIMO performance parameters such as envelope correlation coefficient (ECC), and DG of the MIMO system is well performed. A proposed MIMO antenna system is deployed and analyzed, which is a massive MIMO antenna, and the simulation results are compared to the measurement. The results validate the fact that the design of this particular MIMO system suits it to be incorporated in the n47 and n48 frequency bands, and therefore the presented MIMO system is suitable to be an option for integration into the upcoming smartphone architecture.

This study presents a photonic integrated optical sensor based on a dual-polarization microring resonator with angular gratings on a silicon-on-insulator (SOI) waveguide, enabling simultaneous and precise refractive index (RI) and temperature measurements. Due to the distinct energy distributions for transverse electric ($\mathit{TE}$) and transverse magnetic ($\mathit{TM}$) modes in SOI waveguides, these modes show distinct sensitivity responses to the variation in ambient RI and temperature. Simultaneous measurements of both temperature and RI are enabled by exciting both these transverse modes in the microring resonator structure. Furthermore, incorporating angular gratings into the microring resonator’s inner sidewall extends the temperature measurement range by mitigating free spectral range limitations. This work presents a novel approach to dual-polarization microring resonators with angular gratings, offering an enhanced temperature measurement range and detection limit in optical sensing applications requiring an extended temperature range. The proposed structure is able to yield a simulated temperature measurement range of approximately 35 nm with a detection limit as low as $2.99\times {10}^{-5}$. The achieved temperature sensitivity is 334 pm/°C and RI sensitivity is 13.33 nm/RIU for the ${\mathit{TE}}_0$ mode, while the ${\mathit{TM}}_0$ mode exhibits a temperature sensitivity of 260 pm/°C and an RI sensitivity of 76.66 nm/RIU.

This paper presents the implementation of the Bayesian inversion method for the characterization and estimation of different dielectric material properties. The scattering parameters of single and multi-layer materials are measured using a free-space experimental setup using a standard gain horn antenna and a Vector Network Analyzer (VNA) at Ka-band (26–40 GHz). The relative permittivity, material thickness, and material positioning error are defined as model parameters and estimated using the observed (measured) data. The FR4 Epoxy, Rogers RT/Duriod 5880, and Rogers AD600 with different relative permittivities and thicknesses are used in the measurement setup. The results displayed good agreement between model parameters and estimated properties of the presented materials, while the corresponding eigenvectors provided a level of confidence in model parameter values. The results were compared with different reported techniques to showcase the possible use of the presented method in microwave imaging, non-destructive testing, and similar applications.