Galgotias University

Prioritizing the critical enablers of Quality 4.0 implementation in automotive manufacturing industry: implications for industrial managers and policy-makers

Purpose This study aims to explore and prioritize the critical enablers (CEs) for the successful deployment of Quality 4.0 (Q4.0) in automotive manufacturing industry. Design/methodology/approach Initially, comprehensive literature review related to Q4.0 adoption in manufacturing...

Automated Sleep Stage Classification for Closed-Loop Lucid Dream Induction via CNN-LSTM on Single-Channel EEG

Automated Sleep Stage Classification for Closed-Loop Lucid Dream Induction via CNN-LSTM on Single-Channel EEG is the title of this paper which is the first paper and starting of something bigger in the future. I think if it works then it will change the perspective humans and how...

A novel optimized deep ensemble for monkeypox lesion detection using transfer learning and ABC algorithm

Monkeypox, a reemerging zoonotic disease, has become a serious global health concern that requires rapid and accurate diagnostic methods. The increasing prevalence of skin lesion images highlights the scope of automated deep learning solutions. However, current approaches face ch...

Four-port triple notched wide-band MIMO antenna and verification by theory of characteristics mode for multiple applications

Abstract This paper presents a compact four-port multiple-input-multiple-output (MIMO) antenna featuring a triple notched-band characteristic for wideband, multiple applications. The single-element antenna is systematically developed and analyzed using the Theory of Characteristi...

Translational design of multifunctional novasomes for theranostic-driven precision therapy of cutaneous oncology

Cutaneous oncology needs to be treated locally with maximal exposure to the target with minimum systemic toxicity. Novasomes, surfactant-rich vesicles, have proven to be promising theranostic carriers for both topical and intralesional delivery. This review aims to establish a tr...

Optimization-driven feature learning for long-tailed object detection in optical remote sensing imagery

With the rapid advancement of remote sensing technologies, deep learning–based object detection has been widely adopted for large-scale optical remote sensing imagery. Despite the remarkable progress achieved by convolutional and transformer-based detectors, their performance rem...