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Technologies, Volume 12, Issue 2

February 2024 - 15 articles

Cover Story: Atrial fibrillation (AF) has an increasing prevalence and association with major adverse cardiovascular events (MACE). In recent years, there has been growing interest in identifying new predictors of MACE in AF patients. This novel approach is associated with a reduction in the risk of MACE. The role of artificial intelligence and machine learning techniques offer a promising avenue for more effective prediction of AF progression. Incorporating machine learning algorithms into the clinical management of people at high risk of AF and those with AF offers potential benefits, such as personalised risk assessment, data-driven decision support and improved patient care. This study shows that the application of machine learning is highly effective in predicting MACE in patients with newly diagnosed AF. View this paper
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Articles (15)

  • Communication
  • Open Access
5 Citations
8,952 Views
22 Pages

This manuscript addresses the critical need for precise paint application to ensure product durability and aesthetics. While manual work carries risks, robotic systems promise accuracy, yet programming diverse product trajectories remains a challenge...

  • Article
  • Open Access
3 Citations
3,697 Views
22 Pages

Change management for technology adoption in the transportation sector is often used to address long-term challenges characterized by complexity, uncertainty, and ambiguity. Especially when technology is still evolving, an analysis of these challenge...

  • Communication
  • Open Access
2 Citations
2,868 Views
16 Pages

Exploiting PlanetScope Imagery for Volcanic Deposits Mapping

  • Maddalena Dozzo,
  • Gaetana Ganci,
  • Federico Lucchi and
  • Simona Scollo

During explosive eruptions, tephra fallout represents one of the main volcanic hazards and can be extremely dangerous for air traffic, infrastructures, and human health. Here, we present a new technique aimed at identifying the area covered by tephra...

  • Communication
  • Open Access
2 Citations
2,837 Views
10 Pages

High Affinity of Nanoparticles and Matrices Based on Acid-Base Interaction for Nanoparticle-Filled Membrane

  • Tsutomu Makino,
  • Keisuke Tabata,
  • Takaaki Saito,
  • Yosimasa Matsuo and
  • Akito Masuhara

The introduction of nanoparticles into the polymer matrix is a useful technique for creating highly functional composite membranes. Our research focuses on the development of nanoparticle-filled proton exchange membranes (PEMs). PEMs play a crucial r...

  • Article
  • Open Access
6 Citations
3,905 Views
16 Pages

Multistage Malware Detection Method for Backup Systems

  • Pavel Novak,
  • Vaclav Oujezsky,
  • Patrik Kaura,
  • Tomas Horvath and
  • Martin Holik

This paper proposes an innovative solution to address the challenge of detecting latent malware in backup systems. The proposed detection system utilizes a multifaceted approach that combines similarity analysis with machine learning algorithms to im...

  • Feature Paper
  • Article
  • Open Access
2 Citations
3,139 Views
16 Pages

Angle Calculus-Based Thrust Force Determination on the Blades of a 10 kW Wind Turbine

  • José Rafael Dorrego-Portela,
  • Adriana Eneida Ponce-Martínez,
  • Eduardo Pérez-Chaltell,
  • Jaime Peña-Antonio,
  • Carlos Alberto Mateos-Mendoza,
  • José Billerman Robles-Ocampo,
  • Perla Yazmin Sevilla-Camacho,
  • Marcos Aviles and
  • Juvenal Rodríguez-Reséndiz

In this article, the behavior of the thrust force on the blades of a 10 kW wind turbine was obtained by considering the characteristic wind speed of the Isthmus of Tehuantepec. Analyzing mechanical forces is essential to efficiently and safely design...

  • Review
  • Open Access
28 Citations
9,664 Views
26 Pages

Energy Efficiency in Additive Manufacturing: Condensed Review

  • Ismail Fidan,
  • Vivekanand Naikwadi,
  • Suhas Alkunte,
  • Roshan Mishra and
  • Khalid Tantawi

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase pro...

  • Article
  • Open Access
2,442 Views
24 Pages

Parametric Metamodeling Based on Optimal Transport Applied to Uncertainty Evaluation

  • Sergio Torregrosa,
  • David Muñoz,
  • Vincent Herbert and
  • Francisco Chinesta

When training a parametric surrogate to represent a real-world complex system in real time, there is a common assumption that the values of the parameters defining the system are known with absolute confidence. Consequently, during the training proce...

  • Article
  • Open Access
6 Citations
2,937 Views
15 Pages

An Optimum Load Forecasting Strategy (OLFS) for Smart Grids Based on Artificial Intelligence

  • Asmaa Hamdy Rabie,
  • Ahmed I. Saleh,
  • Said H. Abd Elkhalik and
  • Ali E. Takieldeen

Recently, the application of Artificial Intelligence (AI) in many areas of life has allowed raising the efficiency of systems and converting them into smart ones, especially in the field of energy. Integrating AI with power systems allows electrical...

  • Article
  • Open Access
3 Citations
3,316 Views
31 Pages

In this research paper, a comprehensive performance analysis was carried out for a 48-watt transformerless DC-DC boost converter using a Proportional–Integral–Derivative (PID) controller through dynamic modeling. In a boost converter, the...

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Technologies - ISSN 2227-7080