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A novel technique is shown to improve the isolation between radiators in antenna arrays. The proposed technique suppresses the surface-wave propagation and reduces substrate loss thereby enhancing the overall performance of the array. This is achieved without affecting the antenna’s footprint. The proposed approach is demonstrated on a four-element array for 5G MIMO applications. Each radiating element in the array is constituted from a 3 × 3 matrix of interconnected resonant elements. The technique involves (1) incorporating matching stubs within the resonant elements, (2) framing each of the four-radiating elements inside a dot-wall, and (3) defecting the ground plane with dielectric slots that are aligned under the dot-walls. Results show that with the proposed approach the impedance bandwidth of the array is increased by 58.82% and the improvement in the average isolation between antennas #1&2, #1&3, #1&4 are 8 dB, 14 dB, 16 dB, and 13 dB, respectively. Moreover, improvement in the antenna gain is 4.2% and the total radiation efficiency is 23.53%. These results confirm the efficacy of the technique. The agreement between the simulated and measured results is excellent. Furthermore, the manufacture of the antenna array using the proposed approach is relatively straightforward and cost effective.

In this paper, a multiple-input and multiple-output (MIMO) antenna with high gain and high isolation based on the metamaterial concept is proposed at 30 GHz for millimeter-wave applications such as 5G communication systems. The edge-to-edge distance between the radiation patches is 1.5 mm or 0.1 λ g at 30 GHz. In order to realize the metamaterial environment, a novel unit-cell (Σ-shaped structure) with negative permeability and permittivity was designed. Fifteen unit-cells were used to increase the antenna gain. The gain enhancement is more than 8 dB at 30 GHz. Also, to reduce mutual coupling, 2 unit-cells were loaded in a gap created on the ground plane. Isolation improvement is more than 32 dB at 30 GHz. The radiation efficiency of the proposed MIMO antenna at 30 GHz is equal to 68%. The final dimensions of the proposed antenna are 19.4 × 13 × 0.254 mm 3 or 0.11 λ g 3 at 30 GHz.

An innovative off-chip antenna (OCA) is presented that exhibits high gain and efficiency performance at the terahertz (THz) band and has a wide operational bandwidth. The proposed OCA is implemented on stacked silicon layers and consists of an open circuit meandering line. It is shown that by loading the antenna with an array of subwavelength circular dielectric slots and terminating it with a metamaterial unit cell, its impedance bandwidth is enhanced by a factor of two and its gain on average by about 4 dB. Unlike conventional antennas, where the energy is dissipated in a resistive load, the technique proposed here significantly reduces losses. The antenna is excited from underneath the antenna by coupling RF energy from an open-circuited feedline through a slot in the ground-plane of the middle substrate layer. The feedline is shielded with another substrate layer which has a ground-plane on its opposite surface to mitigate the influence of the structure on which the antenna is mounted. The antenna has the dimensions 12.3 × 4.5 × 0.905 mm 3 and operates across the 0.137–0.158 THz band corresponding to a fractional bandwidth of 14.23%. Over this frequency range the average measured gain and efficiency are 8.6 dBi and 77%, respectively. These characteristics makes the proposed antenna suitable for integration in sub-terahertz near-field electronic systems such as radio frequency identification (RFID) devices with high spatial resolution.

This study develops reliable and robust machine learning (ML) models to predict the outlet air temperature and humidity and thermal efficiency of a solar air heater (SAH). Also, the application of predictive models for optimal control of the SAH operation is proposed. For this, the work contains three main parts: (a) a vertically-mounted symmetrical SAH was installed outside of a building room and operated throughout the winter of 2022. (b) By conducting experiments for five air mass flow rates, a large dataset with more than 62,500 sample points was collected. (c) Six input features containing time, environmental-related attributes, and SAH variables were applied to develop several state-of-the-art ML algorithms. To figure out the most accurate models for predicting output variables, the dataset was partitioned into three parts. Also, various modeling performance evaluation criteria were calculated and compared on the validation and test sets. Among these models, the gradient boosting machine algorithm based on LightGBM implementation achieved the best degree of generalization in modeling the target variables. The results demonstrated that the developed models obtained the lowest R-squared and the highest mean absolute percentage error of 0.9827 and 2.95%, respectively, on the test set. Moreover, the offline analysis of SAH operation based on the proposed control scheme demonstrated that 350 kWh of thermal energy can be generated during the application in the one-year winter season, 24% more than SAH operation without a model-based control strategy.

This study focuses on measuring potentially toxic elements (PTEs) including mercury (Hg), lead (Pb), cadmium (Cd), arsenic (As), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn) in farmed and wild carp by inductively coupled plasma-optical emission spectrometry (ICP-OES) and their intake amount and risk assessment. Estimated Daily Intake (EDI), Target Hazard Quotient (THQ) and the total THQ (TTHQ) were calculated for each element. In the present research, the concentration of As in farmed and wild carp samples was below the detection limit of ICP-OES (< 0.005 mg/kg). The mean concentrations of Pb, Cd, Fe, and Cu in farmed carp samples were significantly higher than that in wild carp samples, while Zn level was higher in the wild carp samples ( P <  0.05). There is no significant difference between Hg and Mn in both fish ( P  > 0.05). The Monte Carlo simulation (MCS) results showed that the ranking order of PTEs based on their THQ was Hg > Pb > Zn > Cu > Fe > Cd > Mn. In the worst-case scenario (in the top 95 percentile) for both wild and farmed carp, the THQ of measured metals was less than one except Hg in children. Overall, this study demonstrated that the levels of PTEs in farmed and wild common carp had a potential non-carcinogenic risk for children (TTHQ > 1).

In general, melting process is not a common method for the production of oxide dispersion strengthened (ODS) alloys due to agglomeration and coarsening of oxide particles. However, vacuum casting process has recently been employed as a promising process to produce micro-scale oxide dispersed alloys. In this paper, we report the process and characterization of in situ formation and uniform dispersion of nano-scale Y-Ti oxide particles in Fe-10Ni-7Mn (wt.%) alloy. The processing route involves a solid-liquid reaction between the added TiO 2 as an oxygen carrier and dissolved yttrium in liquid metal leading to an optimal microstructure with nano-sized dispersed oxide particles. The developed thermodynamic model shows the independence of the final phase constituents from experimental conditions such as melting temperature or vacuum system pressure which offers a general pathway for the manufacture of oxide dispersion strengthened materials.

The design and analysis of an ultra wideband aperture antenna with dual-band-notched characteristics are presented. The proposed antenna consists of a circular ring exciting stub on the front side and a circular slot on the back ground plane. By utilizing a parasitic strip and a T-shaped stub on the antenna structure, two notched bands of 850 MHz (3.5-4.35 GHz) and 900 MHz (5.05-5.95 GHz) are achieved. The proposed antenna is fabricated and measured. Measured results show that this antenna operates from 2.3 GHz to upper 11 GHz for voltage standing wave ratio less than 2, except two frequency notched bands of 3.5-4.35 and 5.05-5.95 GHz. Moreover, the experimental results show that proposed antenna has stable radiation patterns and constant gain. A conceptual circuit model, which is based on the measured impedance of the proposed antenna, is also shown to investigate the dual-band-notched characteristics.

This paper presents a novel miniaturized parallel coupled-line bandpass filter by etching some slot resonators on the strip for suppressing the first spurious response. These slots perform a serious LC resonance property in certain frequency and suppress the spurious signals. By properly tuning these slot dimensions, multiple closed notches can be generated in the vicinity of spurious harmonic and a wide stopband can be obtained. Slot on the strip that is called Defected Microstrip Structure (DMS). The DMS interconnection disturbs the current distribution only across the strip, thereby giving a modified microstrip line with certain stop band and slow-wave characteristics. The simulation and measurement of a 4.7 GHz prototype bandpass filter are presented. The measured results show a satisfactory rejection level more than 30 dB at first spurious passband without affecting the passband response. Good agreement between the experimental and full-wave simulated results has been achieved.

In the twenty first century, there have been various scientific discoveries which have helped in addressing some of the fundamental health issues. Specifically, the discovery of machines which are able to assess the internal conditions of individuals, has been a significant boost in the medical field. Multiple Sclerosis (MS) is a demyelinating disease in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of the nervous system’s parts in various forms to transmit signals, therefore results a wide range of symptoms including physical, mental and psychiatric problems. In this regard, most of the researchers have focused on improving the classification of brain lesions, especially those from MS, which is a relatively difficult task, using different algorithms, but mainly in determining the edge. However, the absence of learning methods have caused complexity and difficulties for having accurate results in the previous works. Therefore, this need motivated us to use various tools of learning methods with a focus on Cellular Learning Automata (CLA) to achieve more accurate results in detection of MS lesions.Cellular Learning Automata (CLA) is a hybrid model of two, Learning Automata and Cellular Automata, which is a simple discrete system that can exhibit complex calculations and behavior through simple and local rules. In this study, we aim to propose a new combinational algorithm using Support Vector Machine (SVM) used for classification and cellular learning automata (CLA) to increase the accuracy of MS lesion detection. The objective is to create artificial models using support vector machines (SVM) to classify MS and normal brain MRI images, analyze the effectiveness of these models and their potential to use them in multiple sclerosis (MS) diagnosis. In order to develop such combination method, we start with simple learning methods such as k-means to find MS lesion.The research was carried out in four stages, respectively, the algorithms are as follows; a) Semi-automatic method and use of K-Means, b) Automatic MS Segmentation Approach Based on Cellular Learning Automata, c) MS Segmentation Approach based on SVM, CLA and K-Means, d) Accurate Simulated Database, 3D MRI to 2D Images, using value of Binary Pattern Classification for MS Detection. The algorithms consist of pre-processing parts, detecting MS-hemispheres, feature extraction, classification and post-processing. In the pre-processing section, the brightness intensity of the normalized images and the brain region are first extracted. Then, to reduce the computational volume, the lesions are diagnosed. The proposed approach can be considered as a supplementary or superior method for other methods such as Graph Cuts (GC), fuzzy c-means, mean-shift, k-Nearest Neighbor (KNN). We try to see the benefits of having a 3D database but to use 2D vectors only for better comparison and more accurate results. Support vector machines (SVM) can be a useful tool during the multiple sclerosis (MS) disease diagnosis process, however, to be able to make better assumptions, more tests are needed.

This paper presents an efficient analysis of a substrate integrated waveguide (SIW) single-layer hybrid ring coupler (rat-race) for millimeter-wave and microwave applications. The scattered field from each circular cylinder is expanded by cylindrical eigenfunctions with unknown coefficients that have been solved by electric and magnetic tangential boundary on each metallic via. The coupler S-matrix is calculated by using mode matching that uses the cylindrical vector expansion analysis to minimize the computational time and provides more physical insight. To achieve higher bandwidth, the radiuses of the coupler under analysis have been optimized in Matlab code by invasive weed optimization (IWO) method, and the results have been verified by CST package. The return loss and the isolation are less than −15 dB, and −18 dB, respectively. The insertion loss is divided equally - 3 ± 0.2 dB, with 0 ± 5 and 180 ± 10 degrees in output ports over the operating frequency bandwidth and the agreement of phase differences in output ports has been examined objectively by feature selective validation (FSV) technique.