Multi-sensor fusion and segmentation for autonomous vehicle multi-object tracking using deep Q networks.

Autonomous vehicles, often known as self-driving cars, have emerged as a disruptive technology with the promise of safer, more efficient, and convenient transportation. The existing works provide achievable results but lack effective solutions, as accumulation on roads can obscure lane markings and traffic signs, making it difficult for the self-driving car to navigate safely. Heavy rain, snow, fog, or dust storms can severely limit the car's sensors' ability to detect obstacles, pedestrians, and other vehicles, which pose potential safety risks.

Application of natural solar photocatalytic and DSSC's studies AC loaded on Ag-InO nanoparticles by hydrothermal approach.

Contaminants are repeatedly being released into the land, water and air about the world as a consequence of the high levels of human movement and development, which causes a fast an increase in the growing of pollution. In this assessment, activated charcoals supported on Ag-InO nanomaterials were blended by hydrothermal system. The morphology constitution, surface assets and optical description of synthesized nanomaterials were characterized by XRD, UV-DRS, PL, HR-SEM and EDAX, HR-TEM, SAED pattern, FT-IR, XPS, BET, CV and VSM techniques.

Impact of non-covalent interactions on the solvation of ovalbumin in an aqueous environment of different pHs: Thermodynamic and diffusion studies.

The solvation behavior of protein is an important factor in protein-based food products. In the present study, the xylitol (XY) - ovalbumin (OVN) interaction in an aqueous solution of different pH conditions is analyzed in two methods. In one method, the thermodynamic parameters Gibbs free energy, free volume, and internal pressure are calculated by using ultrasonic velocity, density, and viscosity in addition the refractive index is also measured.

Energy-efficient quad tree-based clustering using edge-assisted UAV-relay to enhance network lifetime in WSN.

Wireless sensor networks' most prominent concern is energy optimization. It faces significant problems like high energy consumption, data loss, delay, and low network lifetime. To improve, it uses clustering.

Efficient removal of chromate from wastewater using a one-pot synthesis of chitosan cross-linked ceria incorporated hydrous copper oxide bio-polymeric composite.

Remediating hexavalent chromium [Cr(VI)] from contaminated water systems is a significant concern due to its harmful effects on human health, aquatic life, and plants. To tackle this issue, scientists have created a chitosan cross-linked hydrous ceria incorporated cupric oxide bio-polymeric composite (CHCCO) by combining chitosan biopolymer with corresponding metal ions using glutaraldehyde as a cross-linker. The composite was characterized using advanced analytical instruments such as FTIR, p-XRD, SEM, XPS, etc.