Design and fabrication of a microstrip triplexer with wide flat channels for multi-band 5G applications.

In this paper, a new microstrip triplexer is designed to work at 2.5 GHz, 4.4 GHz and 6 GHz for mid-band 5G applications. All channels are flat with three low group delays (GDs) of 0.84 ns, 0.75 ns and 0.49 ns, respectively. Compared to the previously reported works, the proposed triplexer has the minimum group delay. The designed triplexer has 18.2%, 13.7%, 23.6% fractional bandwidths (FBW%) at 2.5 GHz, 4.4 GHz and 6 GHz, respectively. The obtained insertion losses (ILs) are low at all channels. These features are obtained without a noticeable increase in the overall size. A novel and simple resonator is used to design the proposed triplexer, which includes two pairs of coupled lines combined with a shunt stub. A perfect mathematical analysis is performed to find the resonator behavior and the layout optimization. The type of shunt stub is determined mathematically. Also, the smallness or largeness of some important physical dimensions is determined using the proposed mathematical analysis. Finally, the designed triplexer is fabricated and measured, where the measurement results verify the simulations.

Designing process and analysis of a new SOI-MESFET structure with enhanced DC and RF characteristics for high-frequency and high-power applications.

This research introduces a new designing process and analysis of an innovative Silicon-on-Insulator Metal-Semiconductor Field-Effect (SOI MESFET) structure that demonstrates improved DC and RF characteristics. The design incorporates several modifications to control and reduce the electric field concentration within the channel. These modifications include relocating the transistor channel to sub-regions near the source and drain, adjusting the position of the gate electrode closer to the source, introducing an aluminum layer beneath the channel, and integrating an oxide layer adjacent to the gate. The results show that the AlOx-MESFET configuration exhibits a remarkable increase of 128% in breakdown voltage and 156% in peak power. Furthermore, due to enhanced conductivity and a significant reduction in gate-drain capacitance, there is a notable improvement of 53% in the cut-off frequency and a 28% increase in the maximum oscillation frequency. Additionally, the current gain experiences a boost of 15%. The improved breakdown voltage and peak power make it suitable for applications requiring robust performance under high voltage and power conditions. The increased maximum oscillation frequency and cut-off frequency make it ideal for high-frequency applications where fast signal processing is crucial. Moreover, the enhanced current gain ensures efficient amplification of signals. The introduced SOI MESFET structure with its modifications offers significant improvements in various performance metrics. It provides high oscillation frequency, better breakdown voltage and good cut-off frequency, and current gain compared to the traditional designs. These enhancements make it a highly desirable choice for applications that demand high-frequency and high-power capabilities.

Machine learning algorithm for ventilator mode selection, pressure and volume control.

Mechanical ventilation techniques are vital for preserving individuals with a serious condition lives in the prolonged hospitalization unit. Nevertheless, an imbalance amid the hospitalized people demands and the respiratory structure could cause to inconsistencies in the patient's inhalation. To tackle this problem, this study presents an Iterative Learning PID Controller (ILC-PID), a unique current cycle feedback type controller that helps in gaining the correct pressure and volume. The paper also offers a clear and complete examination of the primarily efficient neural approach for generating optimal inhalation strategies. Moreover, machine learning-based classifiers are used to evaluate the precision and performance of the ILC-PID controller. These classifiers able to forecast and choose the perfect type for various inhalation modes, eliminating the likelihood that patients will require mechanical ventilation. In pressure control, the suggested accurate neural categorization exhibited an average accuracy rate of 88.2% in continuous positive airway pressure (CPAP) mode and 91.7% in proportional assist ventilation (PAV) mode while comparing with the other classifiers like ensemble classifier has reduced accuracy rate of 69.5% in CPAP mode and also 71.7% in PAV mode. An average accuracy of 78.9% rate in other classifiers compared to neutral network in CPAP. The neural model had an typical range of 81.6% in CPAP mode and 84.59% in PAV mode for 20 cm H2O of volume created by the neural network classifier in the volume investigation. Compared to the other classifiers, an average of 72.17% was in CPAP mode, and 77.83% was in PAV mode in volume control. Different approaches, such as decision trees, optimizable Bayes trees, naive Bayes trees, nearest neighbour trees, and an ensemble of trees, were also evaluated regarding the accuracy by confusion matrix concept, training duration, specificity, sensitivity, and F1 score.

Investigation on Vision System: Digital FPGA Implementation in Case of Retina Rod Cells.

The development of prostheses and treatments for illnesses and recovery has recently been centered on hardware modeling for various delicate biological components, including the nervous system, brain, eyes, and heart. The retina, being the thinnest and deepest layer of the eye, is of particular interest. In this study, we employ the Nyquist-Based Approximation of Retina Rod Cell (NBAoRRC) approach, which has been adapted to utilize Look-Up Tables (LUTs) rather than original functions, to implement rod cells in the retina using cost-effective hardware. In modern mathematical models, numerous nonlinear functions are used to represent the activity of these cells. However, these nonlinear functions would require a substantial amount of hardware for direct implementation and may not meet the required speed constraints. The proposed method eliminates the need for multiplication functions and utilizes a fast, cost-effective rod cell device. Simulation results demonstrate the extent to which the proposed model aligns with the behavior of the primary rod cell model, particularly in terms of dynamic behavior. Based on the results of hardware implementation using the Field-Programmable Gate Arrays (FPGA) board Virtex-5, the proposed model is shown to be reliable, consume 30 percent less power than the primary model, and have reduced hardware resource requirements. Based on the results of hardware implementation using the reconfigurable FPGA board Virtex-5, the proposed model is reliable, uses 30% less power consumption than the primary model in the worth state of the set of approximation method, and has a reduced hardware resource requirement. In fact, using the proposed model, this reduction in the power consumption can be achieved. Finally, in this article, by using the LUT which is systematically sampled (Nyquist rate), we were able to remove all costly operators in terms of hardware (digital) realization and achieve very good results in the field of digital implementation in two scales of network and single neuron.

A new compact and low phase imbalance microstrip coupler for 5G wireless communication systems.

Microstrip couplers play a crucial role in signal processing and transmission in various applications, including RF and wireless communication, radar systems, and satellites. In this work, a novel microstrip 180° coupler is designed, fabricated and measured. The layout configuration of this coupler is completely new and different from the previously reported Rat-race, branch-line and directional couplers. To obtain the proposed coupler, the meandrous coupled lines are used and analyzed mathematically. To improve the performance of our coupler, an optimization method is used. The designed coupler is very compact with an overall size of 0.014λg2. The obtained values of S21 and S31 are -3.45 dB and -3.75 dB, respectively at the operating frequency, while the fractional bandwidth (FBW) is 56.2%. It operates at fo = 1.61 GHz (suitable for 5G applications) and can suppress harmonics up to 2.17fo. Another advantage of this coupler is its low phase imbalance, while the phase difference between S21 and S31 is 180°± 0.023°. Therefore, our device is a balanced coupler with ±0.3 dB magnitude unbalance at its operating frequency. It is important to note that it is very difficult to find a coupler that has all these advantages at the same time. The proposed 180° coupler is fabricated and measured. The comparison shows that the measurement and simulation results are in good agreement. Therefore, the proposed coupler can be easily used in designing high-performance 5G communication systems.

Portable Infrared-Based Glucometer Reinforced with Fuzzy Logic.

Diabetes mellitus (DM) is a chronic metabolic condition characterized by high blood glucose levels owing to decreased insulin production or sensitivity. Current diagnostic approaches for gestational diabetes entail intrusive blood tests, which are painful and impractical for regular monitoring. Additionally, typical blood glucose monitoring systems are restricted in their measurement frequency and need finger pricks for blood samples. This research study focuses on the development of a non-invasive, real-time glucose monitoring method based on the detection of glucose in human tears and finger blood using mid-infrared (IR) spectroscopy. The proposed solution combines a fuzzy logic-based calibration mechanism with an IR sensor and Arduino controller. This calibration technique increases the accuracy of non-invasive glucose testing based on MID absorbance in fingertips and human tears. The data demonstrate that our device has high accuracy and reliability, with an error rate of less than 3%, according to the EGA. Out of 360 measurements, 97.5% fell into zone A, 2.2% into zone B, and 0.3% into zone C of the Clarke Error Grid. This suggests that our device can give clinically precise and acceptable estimates of blood glucose levels without inflicting any harm or discomfort on the user.

Multivariable Signal Processing for Characterization of Failure Modes in Thin-Ply Hybrid Laminates Using Acoustic Emission Sensors.

The aim of this study was to find the correlation between failure modes and acoustic emission (AE) events in a comprehensive range of thin-ply pseudo-ductile hybrid composite laminates when loaded under uniaxial tension. The investigated hybrid laminates were Unidirectional (UD), Quasi-Isotropic (QI) and open-hole QI configurations composed of S-glass and several thin carbon prepregs. The laminates exhibited stress-strain responses that follow the elastic-yielding-hardening pattern commonly observed in ductile metals. The laminates experienced different sizes of gradual failure modes of carbon ply fragmentation and dispersed delamination. To analyze the correlation between these failure modes and AE signals, a multivariable clustering method was employed using Gaussian mixture model. The clustering results and visual observations were used to determine two AE clusters, corresponding to fragmentation and delamination modes, with high amplitude, energy, and duration signals linked to fragmentation. In contrast to the common belief, there was no correlation between the high frequency signals and the carbon fibre fragmentation. The multivariable AE analysis was able to identify fibre fracture and delamination and their sequence. However, the quantitative assessment of these failure modes was influenced by the nature of failure that depends on various factors, such as stacking sequence, material properties, energy release rate, and geometry.

Noninvasive Non-Contact SpO2 Monitoring Using an Integrated Polarization-Sensing CMOS Imaging Sensor.

BACKGROUND: In the diagnosis and primary health care of an individual, estimation of the pulse rate and blood oxygen saturation (SpO2) is critical. The pulse rate and SpO2 are determined by methods including photoplethysmography (iPPG), light spectroscopy, and pulse oximetry. These devices need to be compact, non-contact, and noninvasive for real-time health monitoring. Reflection-based iPPG is becoming popular as it allows non-contact estimation of the heart rate and SpO2. Most iPPG methods capture temporal data and form complex computations, and thus real-time measurements and spatial visualization are difficult. METHOD: In this research work, reflective mode polarized imaging-based iPPG is proposed. For polarization imaging, a custom image sensor with wire grid polarizers on each pixel is designed. Each pixel has a wire grid of varying transmission axes, allowing phase detection of the incoming light. The phase information of the backscattered light from the fingertips of 12 healthy volunteers was recorded in both the resting as well as the excited states. These data were then processed using MATLAB 2021b software. RESULTS: The phase information provides quantitative information on the reflection from the superficial and deep layers of skin. The ratio of deep to superficial layer backscattered phase information is shown to be directly correlated and linearly increasing with an increase in the SpO2 and heart rate. CONCLUSIONS: The phase-based measurements help to monitor the changes in the resting and excited state heart rate and SpO2 in real time. Furthermore, the use of the ratio of phase information helps to make the measurements independent of the individual skin traits and thus increases the accuracy of the measurements. The proposed iPPG works in ambient light, relaxing the instrumentation requirement and helping the system to be compact and portable.

An Arithmetic-Trigonometric Optimization Algorithm with Application for Control of Real-Time Pressure Process Plant.

This paper proposes a novel hybrid arithmetic-trigonometric optimization algorithm (ATOA) using different trigonometric functions for complex and continuously evolving real-time problems. The proposed algorithm adopts different trigonometric functions, namely sin, cos, and tan, with the conventional sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to improve the convergence rate and optimal search area in the exploration and exploitation phases. The proposed algorithm is simulated with 33 distinct optimization test problems consisting of multiple dimensions to showcase the effectiveness of ATOA. Furthermore, the different variants of the ATOA optimization technique are used to obtain the controller parameters for the real-time pressure process plant to investigate its performance. The obtained results have shown a remarkable performance improvement compared with the existing algorithms.

Measuring perceived sweetness by monitoring sorbitol concentration in apples using a non-destructive polarization-based readout.

The determination and qualification of sugars in fruits are important for quality control and assurance of horticultural produce. The sugars determine the sweetness levels in fruits. The requirement for a universal technique that is also robust to predict the sweetness of the fruit in a non-destructive fashion is immense. The handheld refractometer, hydrometer, electronic tongues, and high-pressure liquid chromatography (HPLC) in combination with other detectors have long been used to determine the sweetness of horticultural produce. Though these techniques are very accurate and useful, they require extensive sample preparation and are generally time-consuming and expensive. Optical techniques like visible to near-infrared spectroscopy (vis/NIRS) are simple in use and can rapidly predict the sweetness of the fruit in a non-destructive fashion. The instrumentation used in these techniques is simple and cost-effective for routine analysis of the fruits. However, their systems need calibration for each sample, and the measurement variation depends on the type of horticultural produce on which measurements are done. An optical-based technique is proposed that uses reflected phase information of the incident light and correlates the same to the presence of sorbitol concentration in apples. The refractive index of sorbitol varies as the fruit ripens due to its change in concentration, and the reflected phase information accordingly changes. Monitoring the reflected phase information allows a prediction mechanism of the sweetness content in the fruit.