Himanshi Chaudhary

Abstract The Random Vector Functional Link (RVFL) network provides an efficient and quick method of training feedforward single hidden neural networks. It solves major disadvantages of classical neural networks, i.e. dealing with slow convergence and overfitting by exploiting fixed random weights and closed-form output computation. DenseNet121 architecture has huge potential in the artificial intelligence field and more specifically in object recognition tasks.

Key takeaways: Steel supply chains in the Gulf remain severely disrupted, with raw‑material shortages, high freight costs and logistical uncertainty persisting despite ceasefire reports. Rebar prices have risen sharply and further increases are expected, as production cuts and tighter DRI availability strain supply. Mills’ shift toward scrap is pushing scrap prices to record highs, raising costs and creating additional supply pressure across Saudi Arabia and the wider GCC.

INTRODUCTION Both plants and animals can adapt their growth in response to environmental signals. The immobile nature of plants has led to the evolution of intricate mechanisms, as shown by genome sequencing studies. Plants exhibit dynamic gene regulatory mechanisms that enable them to endure extreme environmental conditions (Xu et al., 2020).