This letter introduces Adaptive Nyström Spectral Analysis (ANSA) as a new technique for Direction of Arrival (DOA) estimation in coprime arrays. ANSA exploits Nyström-based root-MUSIC, employing matrix decomposition, polynomial root-finding, and adaptive noise subspace construction. The extended coprime array configuration, comprising distinct subarrays strategically positioned with physical sensors, adeptly captures uncorrelated far-field narrowband sources. ANSA significantly enhances direction-of-arrival (DOA) estimation accuracy, particularly in scenarios with high signal-to-noise ratio (SNR), while demonstrating robustness against parameter variations. A comprehensive analysis, incorporating the Cramér–Rao bound (CRB), substantiates ANSA's performance by establishing a stringent lower bound on the variance of the DOA estimator. This approach underscores exceptional potential for coprime arrays across varied signal environments, delivering a blend of precision and computational efficiency.

This study addresses the challenge of efficient Direction of Arrival (DOA) estimation in 3D sparse arrays, crucial for applications such as radar and wireless communication systems. We introduce a novel methodology that combines the Nystrom approximation with the unitary root-MUSIC algorithm to precisely estimate DOAs while significantly reducing computational complexity. Our approach strategically selects a subset of sensors using the Nystrom approximation, resulting in a notable decrease in simulation time compared to conventional methods like Root-MUSIC and MR-ESPRIT. Extensive simulations validate the efficacy of our method, demonstrating a reduction of up to 39% in simulation time with a sensor subset size of 20. This technique, which enhances efficiency, has the potential to transform DOA estimation in 3D sparse arrays, making it suitable for real-world applications that demand rapid and accurate signal processing.

This study investigates the impact of the adoption of smart healthcare technologies (ASHT) on the quality of patient care (QoPC) in India by employing a tw

The use of biomass is becoming increasingly important as an alternative energy resource for developing countries. In India, various Chula or biomass Gasifier stoves are utilized in various restaurants, including kitchens and roadside tea stands. These Chula or existing biomass Gasifier stoves have higher smoke emissions as well as lower thermal efficiency. Therefore, sustainable design and performance evaluation of biomass Gasifier cookstoves are required. IDBG cookstove has an inner diameter, outer diameter, and height of 19 cm, 21.5 cm, and 45 cm used for experimentation. Wooden blocks, Charcoal, and Animal dung were used as feedstocks with three repetitions of experimentations. The present case study illustrated the design and analysis of an inverted downdraft Biomass gasifier (IDBG) cook stove. It was tested in climate conditions of A D Patel Institute of Technology, Anand, Gujarat, India. Animal Dung found outstanding performance compared to other feedstocks, such as wooden blocks and Charcoal, with a thermal efficiency of 11-20% from the experiments. It has also been found that smoke emission of up to 20 to 40% is reduced using the IDBG cookstove. The current research has concluded that the IDBG cookstove reduced smoke emissions and improved thermal efficiency.