Rapid and accurate assessment of civic infrastructure following a natural or artificial disaster is essential to planning emergency response and recovery. This paper introduces a control system based on deep reinforcement learning (DRL) to coordinate unmanned aerial vehicle (UAV) swarms and methodically approach the post-disaster infrastructure ins...

By Moti Ranjan Tandi, Archana Mishra

Nanoscience and nanotechnology transformed material science with the introduction of nanomaterials that have special physical, chemical, optical, and mechanical characteristics because of their tiny size on the nanoscale. The materials have superior surface areas, quantum imagery, and unique electrical properties when compared to bulk materials, wh...

By Anil Kumar, Swati, Niharika

The automotive industry is increasingly focused on developing lightweight, fuel-efficient, and structurally robust components to meet stringent performance and sustainability requirements. Additively manufactured lattice structures have emerged as a promising solution due to their high strength-to-weight ratio, energy absorption capability, and geo...

By Sapna Bawankar, Priya Vij

To solve the problems of traditional Apriori algorithm in power marketing big data processing, such as candidate item set redundancy, low single-machine computing efficiency, and difficulty in adapting to multi-dimensional time series data, this study proposes an improved Apriori algorithm that integrates Resilient Distributed Dataset (RDD) distrib...

By Fan Pan, Lingen Zhou, Lu Gan, Wei Kang, Xiaolei Li

The stability of smart grids (SG) plays a critical role in improving the stability of power supply, particularly when system failures or sensor breakdowns could occur and result in a lack of input data. This paper provides a new method of prediction of smart grid consistency by using a Gradient Policy prediction model, which is based on reinforceme...

By S. Mahendran, B. Gomathy

It presents a dynamic model of inventory management of the deteriorating items with time-sensitive demand and variable holding costs. The model is used to solve the problem in industries where demand is seasonal or because of other external conditions, like weather or market conditions. A two-tier inventory model is implemented as a way of minimizi...

By Prashant Sharma, Birendra Kumar Chauhan, Gajraj Singh

The innovation of Machine Learning (ML) techniques is evolving from basic techniques to optimized techniques, considerably improving the performance of prediction models. In the proposed work, the study primarily explores fundamental ML classification methods to classify banking customers based on their credit information. The classification of cus...

By Sufaira Shamsudeen, K. Ranjith Singh

Understanding the impact of geological processes on the environment is very important in comprehending Earth's evolving ecosystem and predicting future ecological challenges. This paper reviews how interactions between different Earth layers-the crust and mantle, affect ecological dynamics. Geological interactions, including tectonic shifts, minera...

By Azamat Saidov, Zukhra Yakhshieva, Nodira Makhkamova, Mirkomil Gudalov, Nilufar Djuraeva, Oybek Umirzaqov, Ozoda Adilova, Anvar Juraev

This research focuses on the energy performance of buildings with glass windows to allow daylight in three different locations in India. The utilization of glass in modern commercial buildings is rapidly increasing for aesthetic views and daylighting through the glazing. Much research has been conducted on WWR and daylight integration into the buil...

By Biswajit Biswas, Subhasis Neogi, Biswanath Roy

In nature, the bucking behavior of the web of I section reduces the member's strength considerably. Hence, in common practice, people use the intermediate and end stiffeners to improve the strength of the beam. The stiffeners are connected to the web using the welded connections. In this paper, the experimental study on steel beams with and without...

By S. Kalaiselvi, R. Santhosh Kumar