As cities continue to grow and populations surge, ensuring easy access to essential services, including healthcare facilities, has become increasingly difficult. One of the major contributors to patient fatalities is the lack of timely access to medical care, which can severely compromise the effectiveness of treatment.
This article provides a comprehensive review of the application of Artificial Intelligence (AI) in the design and optimization of microsystem integrated circuits, particularly for robotic systems. The study covers AI-based methods for both single-field and multi-field designs.
Artificial Intelligence (AI) has become a transformative tool in medicine, improving disease prediction, its management and patient healthcare. This study employs a data driven approach to analyze the usage of AI techniques and Machine Learning (ML) models.
The indicated thermal efficiency is a core parameter that significantly affects the calculation accuracy of the fuel consumption rate in the diesel Mean Value Engine Model (MVEM). In order to improve the accuracy of the mean value engine model
This study presents a novel approach to electronically steering X-rays using Janus spheres arranged in multiple layers, each reflecting at an example 4o Bragg angle. Utilizing 11 layers of these dual-material spheres, our method aims to achieve rapid x-ray steering, significantly reducing radiation dose, particularly in early breast cancer detection, via new CTR algorithms.
Pediatric epilepsy, which affects 0.5%-1% of children-predominantly those under 5 years of age-is frequently associated with cognitive challenges, drug resistance, and increased mortality. Early-onset cases occur with an incidence of 82.1-118 per 100,000 person-years and are frequently accompanied by developmental delays.
Catalyst design plays a crucial role in numerous chemical processes, significantly impacting efficiency and sustainability. Although traditional catalyst development is often time-consuming and labor-intensive, the embedding of Artificial Intelligence (AI) into catalyst design has initiated a transformative era in catalysis, providing unprecedented opportunities to accelerate the discovery, optimization, and application of novel catalysts.
Sport data analytics has revolutionized the way we understand and engage with sport. By leveraging vast amounts of data, advanced algorithms, and cutting-edge technology, sport analytics provides insights that were previously unimaginable. This commentary delves into the technological advancements, applications, business aspects, ethical concerns, and future trends in sport data analytics.
This paper presents our solution to the cartoon photo face recognition competition of the CCF Big Data & Computing Intelligence Contest (CCF BDCI) training track, focusing on symmetry in AI-enhanced recognition. Our approach utilizes a robust baseline of person re-identification, improved by integrating symmetrical data processing techniques.
Today's Connected Autonomous Vehicles (CAVs) and collaborative robots are considered smart things because they are networked and have the ability to send and receive data over the network. Moreover, due to Software Defined Vehicle (SDV), which originated with Tesla cars, one of the biggest challenges in the future of mobility is ensuring the security and reliability of the vehicles against cyber attacks [1].
