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Abstract The present work aims at the application of different optimization strategies in the electromagnetic analysis of the Variable Reluctance Motor (VRM) through Finite Element (FE) simulation. Two case studies are i...

The widespread growth of Internet of Things (IoT) devices, in industries has led to a rise in energy requirements underscoring the importance of sustainable power management solutions. This study talks about the methods ...

"A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of ...

Deep learning (DL) has emerged as a promising tool for photonic inverse design. Nevertheless, despite the initial success in retrieving spectra of modest complexity with nearly instantaneous readout, DL-assisted design m...

Network congestion remains a critical challenge in dynamic communication environments, often degrading data delivery performance and Quality of Service (QoS). This study proposes a Hybrid Deep Reinforcement Learning with...

The increasing adoption of Renewable Energy Sources (RES) is attributed to their sustainability, reduced environmental impact, and reliance on abundant natural resources. Microgrids are becoming more prevalent in existin...

Abstract The ground plane plays an important role on the performance of a planar inverted-F antenna (PIFA). In this regard, the ground plane modification using slots is proposed in this research to obtain a dual band ant...

Abstract Here we present a numerical analysis and the optimization of a multi-pump discrete Raman amplification system based on the use of a Tellurite optical fiber as the gain media. By using previously reported optimiz...

Abstract Biochar yield prediction plays a critical role in optimizing pyrolysis processes and advancing sustainable biomass utilization. This study introduces a hybrid machine learning framework that integrates Decision ...

Abstract Generative artificial intelligence is reshaping how researchers discover protein-binding compounds and develop them into drug candidates. Unlike traditional methods that screen existing molecules, structure-base...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

Abstract Diplexers are used to separate or combine two bands of frequencies and they are designed by combining channel filters using distribution circuit or alternatively designed based on coupled resonator circuits. Des...

"The amount of multidimensional data published on the semantic web (SW) is constantly increasing, due to initiatives such as Open Data and Open Government Data, among other ones. Models, languages, and tools, that allow ...

This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge comput...

Recent advancements in inverse design approaches, exemplified by their large-scale optimization of all geometrical degrees of freedom, have provided a significant paradigm shift in photonic design. However, these innovat...

Controlling nonlinear pulse propagation in optical fibers is paramount for applications spanning spectroscopy and optical communication networks. However, the inherent complexity of laser pulse evolution in matter, shape...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

Augmented and virtual reality (AR/VR) is transforming how humans interact with technology in a wide range of fields and industries, from healthcare and education to entertainment. However, current device limitations have...

Abstract There are several techniques for optimization of Frequency Selective Surfaces (FSS). Generally, in literature, we can find a few articles about the Taguchi's method applied in electromagnetic. This method is bas...