COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long /Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.
Antennas are a vital component of the wireless body sensor networks devices. A wearable antenna in this system can be used as a communication component or energy harvester. This paper presents a detailed review to recent advances fabrication methods for flexible antennas. Such antennas, for any applications in wireless body sensor networks, have specific considerations such as flexibility, conformability, robustness, and ease of integration, as opposed to conventional antennas. In recent years, intriguing approaches have demonstrated antennas embroidered on fabrics, encapsulated in polymer composites, printed using inkjets on flexible laminates and a 3-D printer and, more interestingly, by injecting liquid metal in microchannels. This article presents an operational perspective of such advanced approaches and beyond, while analyzing the strengths and limitations of each in the microwave as well as millimeter-wave regions. Navigating through recent developments in each area, mechanical and electrical constitutive parameters are reviewed, and finally, some open challenges are presented as well for future research directions.
This research work presents a planar compact electromagnetic bandgap (EBG) structure with the potential to reduce the mutual coupling between the elements of a microstrip antenna array. The proposed structure is investigated at 5.59 GHz, which is the centre frequency of the wireless local area network band. To achieve the highest radiation performance for microstrip antenna arrays, with minimal inter‐element spacing and mutual coupling, different unit cell arrangements were considered along with two adjacent patch elements. The simulations and measurement results for the proposed arrangements indicate that the mutual coupling tends to diminish significantly. For instance, when adjacent patches are spaced by 0.4λ, the mutual coupling improves by ∼25 dB. For the particular spacing of 0.4λ, it is favourably observed that the proposed EBG cells can also improve the antenna gain by ∼2.5 dB. Such improvements can be attributed to the compactness of the cells (∼λ/8 × λ/10) and their remarkable ability to suppress the surface waves.
In this paper, a new neuro-based approach using a feed-forward neural network is presented to design a Wilkinson power divider. The proposed power divider is composed of symmetrical modified T-shaped resonators, which are a replacement for quarter-wave transmission lines in the conventional structure.The proposed technique reduces the size of the power divider by 45% and suppresses unwanted bands up to the fifth harmonics. To verify the concept, a prototype of the power divider has been fabricated and tested, exhibiting good agreement between the predicted and measured results. The results show that the insertion loss and the isolation at the center frequency are about 3.3 ± 0.1 dB and 23 dB, respectively. K E Y W O R D Sartificial intelligence, couplers, evolutionary optimization, harmonic suppression, lumpedequivalent circuit, microstrip technology, neural network, Wilkinson power divider
A simple conformal ultrawideband (UWB) antenna with monopole-like radiation patterns is proposed in this communication. To achieve the wide bandwidth, two rings are arranged concentrically around the main annular-ring circular patch antenna, in which two rectangular slots are added. The antenna has monopole-like radiation patterns generated by combining four propagation modes of TM01, TM02, TM03, and TM04 throughout the operating bands. To enhance the flexibility and robustness, the proposed antenna is fabricated using conductive fabric embedded into polydimethylsiloxane (PDMS) polymer. To our knowledge, this is the first flexible UWB antenna with monopole-like radiation patterns reported in the open literature. The measured results show that the antenna achieves a 10 dB return loss bandwidth from 2.85 to 8.6 GHz. Monopole-like radiation patterns are maintained throughout the frequency band, agreeing well with simulated results. This has been validated through the measured Mean Realized Gain (MRG) pattern from 2.85 to 8.6 GHz. The fabricated antenna was bent and tested at various curvatures to verify its conformability. To evaluate suitability for UWB communications, the system-fidelity factors of the antenna are investigated using full-wave analysis in CST Microwave Studio, in both flat and bent conditions, validating its potential for UWB pulse transmission. Index Terms-Circular patch, conformal antenna, flexible antenna, monopole-like radiation pattern, ring patch, ultrawideband (UWB).
A dual-band bandpass filter (BPF) composed of a coupling structure and a bent T-shaped resonator loaded by small L-shaped stubs is presented in this paper. The first band of the proposed BPF covers 4.6 to 10.6 GHz, showing 78.9% fractional bandwidth (FBW) at 7.6 GHz, and the second passband is cantered at 11.5 GHz with a FBW of 2.34%. The bent T-shaped resonator generates two transmission zeros (TZs) near the wide passband edges, which are used to tune the bandwidth of the first band, and the L-shaped stubs are used to create and control the narrow passband. The selectivity performance of the BPF is analyzed using the transfer function extracted from the lumped circuit model verified by a detailed even/odd mode analysis. The BPF presents a flat group delay (GD) of 0.45 ns and an insertion loss (IL) less than 0.6 dB in the wide passband and a 0.92 IL in the narrow passband. A prototype of the proposed BPF is fabricated and tested, showing very good agreement between the numerically predicted and measured results.
This paper presents the simultaneous application of Minkowski fractal geometry and EBG structures for mutual coupling reduction in microstrip array antennas for the first time. In this approach, a modified version of Minkowski fractal geometry is applied on the patch elements, and at the same time 1D electromagnetic bandgap (EBG) structures, composed of 4 EBG elements, are placed between the array elements in a very close distance. Unlike many other coupling reduction methods, which have at least one of the issues of gain reduction or complex fabrication, the proposed method does need any via or double-sided etching and slightly increases the gain of the antenna, while an excellent reduction level of 22.7 dB has been achieved. To verify the concept, 2 array antennas with the spacing of λ 0 and λ 0 /3 were fabricated and tested, showing very good agreement between predicted and measured results.
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