Search

This research focuses on developing a uniquely miniaturized 4×4 Butler Matrix Network integrated with a 1×4 linear array antenna, generating four beams with exceptional isolation and transmission coefficients. Extensive analyses evaluate the antenna's radiation characteristics, including gain, directivity, and beam-forming capabilities. Innovative design techniques achieve significant Butler matrix miniaturization without compromising performance, resulting in a compact final design measuring 23mm × 20.5mm. The integrated multi-beam antenna array demonstrates favorable outcomes, ensuring impedance matching at 50Ω, high gain, and four beams directed at angles of ±8º and ±33º. These results highlight the design's superiority over traditional counterparts, with gains of up to 11 dB. Detailed radiation patterns for all ports are presented. The paper also provides insights into the manufacturing process, materials used, and challenges faced. The results conclusively confirm the system's compliance with performance criteria, effectively operating within the 28 GHz frequency band. This research significantly contributes to downsizing antenna systems, facilitating more compact and efficient communication devices in the future. [ABSTRACT FROM AUTHOR]

ABSTRACT Basis of the microwave imaging is the contrast in dielectric properties of breast normal tissue and tumor. Confocal microwave imaging involves transmitting an ultrawideband signal through number of antennas and records the scattered signals. Then by synthetically focusing reflections from the breast, we can make image from breast. In this article, we demonstrate the feasibility of detecting 10- and 5-mm tumors in three dimensions with different antenna arrangements with different number of antennas. Two models of hemispherical array are presented. An image formation algorithm is presented for 3D image making. Successful detection of 10- and 5-mm tumors are achieved with the hemispherical arrangement. The influences of the different breast sizes for tumor detection are also explored. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2917-2929, 2015 [ABSTRACT FROM AUTHOR]

A novel ultra-wideband (UWB) antenna is presented which has UWB characteristics in a medium same as breast. To optimise the antenna for its best operation, effect of variation in different parts of the antenna is analysed and presented. The antenna's characteristics are presented in simulation and experimental measurements. The results of the authors' study show that the antenna has excellent performance across 4 to more than 9 GHz. [ABSTRACT FROM AUTHOR]

The 5G wireless communication system is promised to exploit many kinds of waveform for satisfying various requirements to transmit huge size of data. The Cognitive Radio Networks based 5G can coexist among various kinds of signal to enrich every 5G wireless system with necessary frequency bands regardless the kind of waveform. However, most of Spectrum Sensing (SS) techniques are proposed to detect only one kind of waveform that is used in the 5G wireless communication system. To address this issue, designing a SS technique to sense various kinds of waveforms for the 5G wireless communication system is necessary to help this system. In this paper, a SS technique have been proposed for accurately sensing different waveform kinds (F-OFDM, UFMC, and FBMC) through a 5G network where these waveforms have different rates of some data like cyclic prefix, signal length, energy, mapper, and shape. The proposed sensing technique includes three stages; cosine filtering, Bartlett segmenting, and hamming windowing. The cosine filtering function is differentiating between the traffic signals based 5G and noise. Then, the filtered signals are segmented with the help of the Bartlett Segmenting for decreasing the rest noise then every segment is windowed using the Hamming windowing for maintaining the signal resolution. The simulation results revealed a significant detection performance regarding to the following numerical results; detection probability is ≥ 0.95 and false alarm probability is < 0.05, for less than zero dB of signal-to-noise ratio and a lower complexity level. Furthermore, the detection performance of the proposed SS technique is better than that of the related works as shown in a comparison table and a graphical manner. [ABSTRACT FROM AUTHOR]

According to several research circles, it is predicted that future wireless systems that employ smart antenna techniques would be more effective at using available spectrum and at building new networks at lower cost, while also improving service quality and allowing for cross-technology operation. These systems require constant monitoring in order to function properly, allowing users to apply machine learning algorithms to analyse large amounts of data from various antenna settings. Machine learning is a technique in which a machine learns and improves on its own, based on past data. These techniques enable the smart antenna target to be learned in an efficient, reliable, and adaptive manner. In this paper, the antenna array and antenna developed for the Internet of Things applications were highlighted. In this paper, we review how machine learning techniques can handle these applications effectively and what the concept of adaptive antenna is and when it can be used in this day and age characterized by the rapid development of information technology. [ABSTRACT FROM AUTHOR]

Sliding mode control (SMC) is a nonlinear controller that is used to achieve desired performance in the presence of unstructured uncertainty as a result of carelessness of parameter specification of the system. The main aim for sliding control, or also called Variable Structure Control, is to control the nonlinear plant by introducing a sliding surface. The sliding surface should be reached by making the state of system approach this level. In this paper, an integral augmented sliding mode control (SMC+I) is proposed to improve the control performance of a plant with uncertainty giving the example of bench-top helicopter and the results are compared with the results obtained from conventional sliding mode control with and without a boundary layer. [ABSTRACT FROM AUTHOR]

In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates. [ABSTRACT FROM AUTHOR]

Summary: Reducing the losses of 3‐phase transformers is still considered a significant target by many transformer designers and manufacturers. Core joint design is one of the factors related to the losses. In previous studies, core losses and flux density distribution motivated researchers to design appropriate T‐joints. However, the variation of load and thermal profiles are the most important factors related to the losses in transformers. This study proposed a new T‐joint configuration for the core of the 3‐phase transformer. The proposed model was built after considering the variation of load and thermal profiles. Results were compared with those of conventional T‐joint designs, such as butt‐lap and 45° mitered designs, that are currently used. The no‐load losses of the proposed model were reduced by more than 6.8% and 10% compared with those of the butt‐lap and mitered T‐joint designs, respectively. Furthermore, the total losses, the hot spot temperature of the core, and the oil temperature decreased significantly. The proposed model contributes to the literature on new T‐joint designs for improving transformer performance. [ABSTRACT FROM AUTHOR]

A double SAW resonator system was developed as a novel method for gas sensing applications. The proposed system was investigated for hydrogen sensing. Commercial Surface Acoustic Wave (SAW) resonators with resonance frequencies of 433.92 MHz and 433.42 MHz were employed in the double SAW resonator system configuration. The advantages of using this configuration include its ability for remote measurements, and insensitivity to vibrations and other external disturbances. The sensitive layer is composed of functionalized multiwalled carbon nanotubes and polyaniline nanofibers which were deposited on pre-patterned platinum metal electrodes fabricated on a piezoelectric substrate. This was mounted into the DSAWR circuit and connected in parallel. The sensor response was measured as the difference between the resonance frequencies of the SAW resonators, which is a measure of the gas concentration. The sensor showed good response towards hydrogen with a minimum detection limit of 1%. [ABSTRACT FROM AUTHOR]