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.

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.

A narrowband dual-band bandpass filter (BPF) with independently tunable passbands is presented through a systematic design approach. A size-efficient coupling system is proposed with the capability of being integrated with additional resonators without increasing the size of the circuit. Two flag-shaped resonators along with two stepped-impedance resonators are integrated with the coupling system to firstly enhance the quality response of the filter, and secondly to add an independent adjustability feature to the filter. The dual passband of the filter is centered at 4.42 GHz and 7.2 GHz, respectively, with narrow passbands of 2.12% and 1.15%. The lower and upper passbands can be swept independently over 600 MHz and 1000 MHz by changing only one parameter of the filter without any destructive effects on the frequency response. According to United States frequency allocations, the first passband is convenient for mobile communications and the second passband can be used for satellite communications. The filter has very good in- and out-of-band performance with very small passband insertion losses of 0.5 dB and 0.86 dB as well as a relatively strong stopband attenuation of 30 dB and 25 dB, respectively, for the case of lower and upper bands. To verify the proposed approach, a prototype of the filter is fabricated and measured showing a good agreement between numerically calculated and measured results.

A new design method for an asymmetric microstrip-to-coplanar stripline (CPS) transition based on the analytical electromagnetic model is presented. The cross section at each stage of the transition is analyzed through conformal transformation, and the corresponding line impedance is calculated. Then, the ground linewidth on the substrate bottom is adjusted to form an optimal Klopfenstein impedance taper. To demonstrate the design method, a transition between a 50-Ω microstrip line and a high-impedance CPS line (147 Ω) was implemented. Good transition performance with more than 10-dB return loss and less than 1-dB insertion loss was obtained for frequency ranges of 6-40 GHz.