Compact elliptical UWB antenna for underwater wireless communications

The increasing needs of free licensed frequency bands like Industrial, Scientific, and Medical (ISM), Wireless Local Area Network (WLAN), and 5G for underwater communications required more bandwidth (BW) with higher data transferring rate. Microwaves produce a higher transferring rate of data, and their associated devices are smaller in comparison with sonar and ultrasonic. Thus, transceivers should have broad BW to cover more of a frequency band, especially from ultra-wideband (UWB) systems, which show potential outcomes. However, previous designs of similar work for underwater communications were very complicated, uneasy to fabricate, and large. Therefore, to overcome these shortcomings, a novel compact elliptical UWB antenna is designed to resonate from 1.3 to 7.2 GHz. It is invented from a polytetrafluoroethylene (PTFE) layer with a dielectric constant of 2.55 mm and a thickness of 0.8 mm. The proposed antenna shows higher gain and radiation efficiency and stability throughout the working band when compared to recent similarly reported designs, even at a smaller size. The characteristics of the functioning antenna are investigated through fluid mediums of fresh-water, seawater, distilled water, and Debye model water. Later, its channel capacity, bit rate error, and data rate are evaluated. The results demonstrated that the antenna offers compact, easier fabrication with better UWB characteristics for underwater 5G communications

Experimental Evaluation of Thermal and Lighting Performance Using Double Dynamic Insulated Glazing

Designing windows in hot climates that allow occupants to easily control their preferences in a smart home is of considerable importance. This paper aims to contribute to this topic by examining the potential of a smart window system that has double dynamic insulated glazing (DDIG) in preventing heat gain and maximising daylight indoors, considering smart privacy protection during both the day and the night. A small-scale model was developed to examine the proposed window system. Test cell temperature, glass surface temperature and indoor illumination lux were investigated. The results showed that the DDIG had high solar heat control inside the test cell, with a significant reduction of 2.5 °C compared with the common glazing of translucent glass used in Najran City, Saudi Arabia. At high solar irradiation intensities, no significant differences in controlling the heat gain to the test cell were found between coloured DDIG (DDIG-colo) and transparent DDIG (DDIG-trans). A graded reduction between DDIG-trans and DDIG-colo was found with decreasing solar intensity, which was found to be 15%, 10% and 8.7% at irradiation intensities of 200, 400 and 600 W/m2, respectively. The DDIG transparencies maintained the illumination lux with higher reduction under low solar irradiation. The DDIG also provided privacy protection and granted user preferences for outdoor connections

One-Dimensional Phononic Crystals: A Simplified Platform for Effective Detection of Heavy Metals in Water with High Sensitivity

Recently, the pollution of fresh water with heavy metals due to technological and industrial breakthroughs has reached record levels. Therefore, monitoring these metals in fresh water has become essentially urgent. Meanwhile, the conventional periodic one-dimensional phononic crystals can provide a novel platform for detecting the pollution of heavy metals in fresh water with high sensitivity. A simplified design of a defective, one-dimensional phononic crystals (1D-PnC) structure is introduced in this paper. The sensor is designed from a lead-epoxy multilayer with a central defect layer filled with an aqueous solution from cadmium bromide (CdBr2). The formation of a resonant peak through the transmittance spectrum is highly expected. This study primarily aims to monitor and detect the concentration of cadmium bromide in pure water based on shifting the position of this resonant peak. Notably, any change in cadmium bromide concentration can affect the acoustic properties of cadmium bromide directly. The transfer matrix method has been used to calculate the transmission spectra of the incident acoustic wave. The numerical findings are mainly based on the optimization of the cadmium bromide layer thickness, lead layer thickness, epoxy layer thickness, and the number of periods to investigate the most optimum sensor performance. The introduced sensor in this study has provided a remarkably high sensitivity (S = 1904.25 Hz) within a concentration range of (0–10,000 ppm). The proposed sensor provides a quality factor (QF), a resolution, and a figure of merit of 1398.51752, 48,875,750 Hz, and 4.12088 × 10−5 (/ppm), respectively. Accordingly, this sensor can be a potentially robust base for a promising platform to detect small concentrations of heavy metal ions in fresh water

Optical Detection of Fat Concentration in Milk Using MXene-Based Surface Plasmon Resonance Structure

MXene (Ti3C2Tx) has emerged very recently as an interacting material for surface plasmon resonance (SPR) configuration. It was discovered that Ti3C2Tx can facilitate the adsorption of biomolecules due to its higher binding energies, stronger interaction between matter and light, and larger surface area. In this work, a two-dimensional Ti3C2Tx and silicon layer-based SPR refractometric sensor is proposed for the sensitive and fast detection of milk fat concentration due to the high significance of this issue to people all over the world. The proposed SPR structure employs BK7 (BK7 is a designation for the most common Borosilicate Crown glass used for a variety of applications in the visible range) as a coupling prism and silver as a metal layer. The layer thicknesses and the number of Ti3C2Tx sheets are optimized for the highest performance. The highest reached sensitivity is 350 deg./RIU with 50 nm silver and 4 nm silicon with a monolayer of Ti3C2Tx, which is ultra-high sensitivity compared to the latest work that utilizes SPR configuration. The proposed SPR-based sensor’s ultra-high sensitivity makes it more attractive for usage in a variety of biosensing applications

A promising ultra-sensitive CO2 sensor at varying concentrations and temperatures based on Fano resonance phenomenon in different 1D phononic crystal designs

Abstract Detecting of the levels of greenhouse gases in the air with high precision and low cost is a very urgent demand for environmental protection. Phononic crystals (PnCs) represent a novel sensor technology, particularly for high-performance sensing applications. This study has been conducted by using two PnC designs (periodic and quasi-periodic) to detect the CO2 pollution in the surrounding air through a wide range of concentrations (0–100%) and temperatures (0–180 °C). The detection process is physically dependent on the displacement of Fano resonance modes. The performance of the sensor is demonstrated for the periodic and Fibonacci quasi-periodic (S3 and S4 sequences) structures. In this regard, the numerical findings revealed that the periodic PnC provides a better performance than the quasi-periodic one with a sensitivity of 31.5 MHz, the quality factor (Q), along with a figure of merit (FOM) of 280 and 95, respectively. In addition, the temperature effects on the Fano resonance mode position were examined. The results showed a pronounced temperature sensitivity with a value of 13.4 MHz/°C through a temperature range of 0–60 °C. The transfer matrix approach has been utilized for modeling the acoustic wave propagation through each PnC design. Accordingly, the proposed sensor has the potential to be implemented in many industrial and biomedical applications as it can be used as a monitor for other greenhouse gases

Artificial dragonfly algorithm in the Hopfield neural network for optimal Exact Boolean k satisfiability representation.

This study proposes a novel hybrid computational approach that integrates the artificial dragonfly algorithm (ADA) with the Hopfield neural network (HNN) to achieve an optimal representation of the Exact Boolean kSatisfiability (EBkSAT) logical rule. The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EBkSAT logic representation. To assess the performance of the proposed hybrid computational model, a specific Exact Boolean kSatisfiability problem is constructed, and simulated data sets are generated. The evaluation metrics employed include the global minimum ratio (GmR), root mean square error (RMSE), mean absolute percentage error (MAPE), and network computational time (CT) for EBkSAT representation. Comparative analyses are conducted between the results obtained from the proposed model and existing models in the literature. The findings demonstrate that the proposed hybrid model, ADA-HNN-EBkSAT, surpasses existing models in terms of accuracy and computational time. This suggests that the ADA algorithm exhibits effective compatibility with the HNN for achieving an optimal representation of the EBkSAT logical rule. These outcomes carry significant implications for addressing intricate optimization problems across diverse domains, including computer science, engineering, and business

Dual-polarized 8-port sub 6 GHz 5G MIMO diamond-ring slot antenna for smart phone and portable wireless applications.

This manuscript presents high performance dual polarized eight-element multiple input multiple output (MIMO) fifth generation (5G) smartphone antenna. The design consists of four dual-polarized microstrip diamond-ring slot antennas, positioned at corners of printed circuit board (PCB). Cheap Fr-4 dielectric with permittivity 4.3 and thickness of 1.6mm is used as substrate with overall dimension of 150 × 75 × 1.6 mm3. In mobile system due to limited space mutual coupling between nearby antenna elements is an issue that distort MIMO antenna performance. Defected ground structure is used to control coupling. The defected ground structure has advantages like ease of fabrication, compact size and high efficiency as compare to other techniques. Less than 30dB coupling is achieved for adjacent elements. The -10 dB impedance bandwidth of 700 MHz is achieved for all radiating elements ranging from 3.3 GHz to 4.1 GHz. The value is about 900MHz for -6dB. The proposed antenna offers good results in terms of fundamental antenna parameters like reflection coefficient, transmission coefficient, maximum gain, total efficiency. The antenna achieved average gain more than 3.8dBi and average radiation efficiency more than 80% for single dual polarized element. The antenna provides sufficient radiation coverage in all sides. The MIMO antenna characteristics like diversity gain (DG), envelope correlation coefficient (ECC), total active reflection coefficient (TARC) and channel capacity are calculated and found according to standards. Furthermore, effect of user on antenna performance in data-mode and talk-mode are studied. Proposed design is fabricated and tested in real time. The measured results shows that proposed design can be used in future smartphones applications. The design is compared with some of the existing work and found to be the best one in many parameters and can be used for commercial use

A Graphene-Metasurface-Inspired Optical Sensor for the Heavy Metals Detection for Efficient and Rapid Water Treatment

Heavy metal ion contamination of water supplies has significantly increased during the last century due to advances in industry and technology. Therefore, a lot of effort was put into developing chemical and physical methods for detecting and tracking the presence of these potentially harmful solutions. Despite their comparatively high sensitivity and low detection limits, these methods are hindered by complex instrumentation and tedious, expensive, and difficult chemical processes. Therefore, in this study, we present a straightforward and effective sensing method based on the graphene metasurface for detecting several classes of heavy metal ions. A graphene-metasurface-inspired optical sensor with a glass substrate is developed that can detect Cu2+ and Mg2+ with a sensitivity of 113.92 GHz/RIU and 113.9 GHz/RIU, respectively. In addition to that, the linear fitting curve for both the metal ions is established, and R2 score of 0.9997 and 0.9982 is achieved, respectively. Furthermore, the lowest value of the figure of merit (FOM) of 2.98 RIU−1 and the maximum Quality factor (Q factor) of 11.22 is obtained. The proposed structure also exhibited a low detection limit as well as a resolution of 0.52 RIU and 78.14 THz, respectively. As a result of these findings, a simple and accurate tool for detecting water contamination with heavy metals and aqueous solutions with relatively high performance is developed

Global horizontal irradiance prediction for renewable energy system in Najran and Riyadh

Producing and supplying energy efficiently are important for many countries. Using models to predict energy production can help reduce costs, improve efficiency, and make energy systems work better. This research predicts solar electricity production in the Najran and Riyadh regions of Saudi Arabia by analyzing 14 weather factors. The weather factors that were considered in the study include date, time, Global Horizontal Irradiance (GHI), clear sky, top of atmosphere, code, temperature, relative humidity, pressure, wind speed, wind direction, rainfall, snowfall, and snow depth. GHI is the most important factor because it determines how much solar energy a system can produce. Therefore, it is important to be able to predict GHI accurately. This study used a variety of data-driven models to predict GHI, including the elastic net regression, linear regression, random forest, k-nearest neighbor, gradient boosting regressor, light gradient boosting regressor, extreme gradient boosting regressor, and decision tree regressor. The models were evaluated using a set of metrics, including the mean absolute error, mean squared error, root mean square error, coefficient of determination (R2), and adjusted coefficient of determination. This study found that the decision tree regression, Random Forest (RF), and Extreme Gradient Boosting (XGB) models performed better in the Riyadh region than in the Najran region. The R2 values for the Riyadh region were 99%, 99%, and 98%, while the R2 values for the Najran region were 89%, 94%, and 94%. This suggests that the Riyadh region is a more suitable location for solar energy conversion systems. These findings are important for policymakers and investors who are considering the development of solar energy projects in Saudi Arabia

List of some parameters of the ADA-HNN- EB<i>k</i>SAT model.

List of some parameters of the ADA-HNN- EBkSAT model.</p