Statistical analysis in cellular systems for channel capacity improvement with dynamic pilots across different angles users.

Accurate channel state information (CSI) is crucial for optimizing wireless communication systems. In scenarios with varying user-to-base station angles, the angle-dependent coherence time impacts conventional pilot strategies. Due to small angles, the coherence time of the user decreases dramatically because of doppler shift, which causes an increase in the number of pilots. We introduces an innovative sub-block design approach for systems with different user angles. This method harmonizes coherence time of high and low-angle users, while maintaining a constant pilot count. This not only improves spectral efficiency but also ensures accurate channel estimation. Through simulations, we demonstrate the effectiveness of our approach in enhancing both spectral efficiency upt to 10 % and CSI precision. This breakthrough contributes to the advancement of channel estimation techniques in scenarios with angle-dependent coherence time, offering practical benefits to wireless communication systems.

Hybrid deep learning model based smart IOT based monitoring system for Covid-19.

Recently, COVID-19 becomes a hot topic and explicitly made people follow social distancing and quarantine practices all over the world. Meanwhile, it is arduous to visit medical professionals intermittently by the patients for fear of spreading the disease. This IoT-based healthcare monitoring system is utilized by many professionals, can be accessed remotely, and provides treatment accordingly. In context with this, we designed an IoT-based healthcare monitoring system that sophisticatedly measures and monitors the parameters of patients such as oxygen level, blood pressure, temperature, and heart rate. This system can be widely used in rural areas that are linked to the nearest city hospitals to monitor the patients. The collected data from the monitoring system are stored in the cloud-based data storage and for the classification our approach proposes an innovative Recurrent Convolutional Neural Network (RCNN) based Puzzle optimization algorithm (PO). Based on the outcome further treatments are made with the assistance of physicians. Experimental analyses are made and analyzed the performance with state-of-art works. The availability of more data storage capacity in the cloud can make physicians access the previous data effortlessly.

First-Principles Insights into Structural, Optoelectronic, and Elastic Properties of Fluoro-Perovskites KXF3 (X = Ru, Os).

The need for new and better semiconductor materials for use in renewable energy devices motivates us to study KRuF3 and KOsF3 fluoride materials. In the present work, we computationally studied these materials and elaborate their varied properties comprehensively with the assistance of density functional theory-based techniques. To find the structural stability of these under-consideration materials, we employed the Birch-Murnaghan fit, while their electronic characteristics were determined with the usage of modified potential of Becke-Johnson. During the study, it became evident from the band-structure results of the KRuF3 and KOsF3 materials that both present an indirect semiconductor nature having the band gap values of 2.1 and 1.7 eV, respectively. For both the studied materials, the three essential elastic constants were determined first, which were further used to evaluate all the mechanical parameters of the studied materials. From the calculated values of Pugh's ratio and Poisson's ratio for the KRuF3 and KOsF3 materials, both were verified to procure the nature of ductility. During the study, we concluded from the results of absorption coefficient and optical conduction in the UV energy range that both the studied materials proved their ability for utilization in the numerous future optoelectronic devices.

Influence of Zirconium (Zr4+) Substitution on the Crystal Structure and Optical and Dielectric Properties of Sr0.8Mg0.2(Sn1-xZrx)O3 Ceramics.

In this work, new compositions of Sr0.8Mg0.2(Sn1-xZrx)O3 0.00 ≤ x ≤ 0.06 ceramics are designed and synthesized by the conventional solid-state route. The influence of Zr doping on the phase, microstructural, optical, and dielectric properties is thoroughly investigated. The peaks (0 0 4) and (1 1 0) are observed to shift toward lower 2θ values, due to the variation of the ionic radius between Zr4+ and Sn4+. X-ray diffraction patterns reveal the orthorhombic structure with the space group Pbnm. Scanning electron microscopy images reveal the presence of pores and particles with a high degree of agglomeration. The functional groups and modes of vibration are determined by Fourier transform infrared spectroscopy of the prepared metal oxide samples. The existence of green emission of all the synthesized samples around 554.91 nm is identified by photoluminescence spectroscopy. The dielectric properties of the fabricated samples are measured by using an impedance analyzer. The values of the tangent loss and relative permittivity are found to decrease with increasing frequency.