Publications by authors named "Fahad Alasim"
Article Synopsis
- * Micromechanical methods employing Ji and Mori-Tanaka models reveal that a 3% silica-filled polyimide matrix significantly boosts the elastic and piezoelectric properties, particularly at a fiber volume fraction of 60%.
- * The study also finds that smaller nanoparticle sizes lead to better properties, but excessive agglomeration of nanoparticles can negatively affect the composite’s performance, with a thicker interphase improving piezoelectric performance.
Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain the best model parameters and outcomes.
View Article and Find Full Text PDFThe pursuit of enhanced cooling and lubrication methods for machining processes that are energy-efficient, environmentally friendly, and cost-effective is receiving significant attention from both academia and industry. The reduction of CO emissions is closely tied to electrical and embodied energy consumption. This study introduces a novel LN oil-on-water (LNOoW) cooling/lubrication (lubricooling) approach for the machining of Ti-6Al-4V alloy.
View Article and Find Full Text PDFArticle Synopsis
- The rise of social media has made sharing reviews a common practice, leading customers to check online feedback before choosing fast food restaurants, which can influence their decisions.
- Restaurants can leverage customer feedback to improve the quality of their food and services, although manually collecting and analyzing this feedback can be time-consuming.
- This study explores the effectiveness of deep ensemble models, like BiLSTM+GRU, in sentiment analysis of tweets about major fast food chains, finding that these models outperform traditional lexicon methods, especially in identifying negative sentiments for certain restaurants like Subway.