Published: 17 Mar 2025
Volume 2
Mircea Ţălu
talu.s.mircea@gmail.com
Published: 20 Mar 2025
Volume 2
Tianming Zhu
tianming.zhu@nie.edu.sg
Carol Anne Hargreaves
carol.hargreaves@nus.edu.sg
Yi Xin Cheng
Christopher Chen Li-Hsian
phccclh@nus.edu.sg
Siama Hilal
Dementia is a decline in cognitive function, typically diagnosed when the acquired impairment becomes severe enough to impact social or occupational functioning. Between no cognitive impairment (NCI) and dementia, there are many intermediate states. Predictive cognitive impairment can be useful for initiating treatment to prevent further brain damage. Several deep learning-based approaches have been proposed for the classification of Magnetic Resonance Imaging (MRI) to diagnose Alzheimer’s disease (AD) or dementia...
Published: 31 Dec 2024
Volume 1
Moussa Ayyash
msma@ieee.org
Welcome to the inaugural volume of the Computing & AI Connect (CAIC) Journal, a peer-reviewed, open-access journal committed to fostering advancements and innovation in computing sciences and technologies, and artificial intelligence. CAIC is a platform that is dedicated to exploring the profound and transformative impacts of computing and artificial intelligence on the different aspects of life. In recent years, AI has become the focus of researchers from different fields, working to..
Published: 31 Dec 2025
Volume 1
Senthil Kumar Jagatheesaperumal
senthilkumarj@mepcoeng.ac.in
Mohamed Rahouti
mrahouti@fordham.edu
Mohammed Aledhari
mohammed.aledhari@unt.edu
Abdelatif Hafid
a.hafid@esisa.ac.ma
Diogo Oliveira
dko5179@psu.edu
Hamza Drid
h.drid@univ-batna2.d
Ruhul Amin
mamin17@fordham.edu
Published: 07 Feb 2025
Volume 2
Nijat Taghizad
tagizadenijat@gmail.com
Pietro Lio
pl219@cam.ac.uk
Modern electrical systems rely on sensors and relays for fault detection in three-phase transmission lines and distribution transformers, but these devices often face time complexity issues and false alarms. In this study, the fault detection accuracy is compared in models studied in 2023 and 2024 following PRISMA guidelines. The objectives were to identify fault types, utilize machine learning models to assess their predictive efficacy, and establish accuracy levels. To explore..
Published: 12 Dec 2024
Volume 1
Muhammad Asif Ayub
asifayub836@gmail.com
Muhammad Tayyab Zamir
mzamir2023@cic.ipn.mx
Imran Khan
imran.cse@uetpeshawar.edu.pk
Hannia Naseem
hanninaseem836@gmail.com
Nasir Ahmad
nasir.ahmad@mtu.ie
Kashif Ahmad
kashif.ahmad@mtu.ie
Crowd-sourcing has been widely explored for monitoring and feedback on infrastructure and services, such as air and water quality analysis. However, the traditional methods of crowd-sourcing for feedback and analysis of water quality, namely offline and online surveys, have several limitations, such as the limited number of participants and low frequency due to the labor involved in conducting such surveys. Social media analytics could overcome these challenges by providing a..
Published: 13 Dec 2024
Volume 1
Denis S. Pashchenko
denpas@rambler.ru
This article presents a complex vision on software production practices aimed at enhancing the Scrum methodology within software project management. The recommended best practices are closely aligned with contemporary trends in the IT sector, including the total digitalization and virtualization of production processes, the transition to fully remote software development models, the incorporation of artificial intelligence technologies, and the implementation of cost-effective models in team organization. The modifications to software..
Published: 28 Aug 2024
Volume 1
Vishnu Vardhan Baligodugula
baligodugula.2@wright.edu
Ashutosh Ghimire
ghimire.18@wright.edu
Fathi Amsaad
fathi.amsaad@wright.edu
Published: 02 Aug 2024
Volume 1
Amjad Yousef Majid
amjad.y.majid@gmail.com
Tomas van Rietbergen
t.l.vanrietbergen@student.tudelft.nl
R Venkatesha Prasad
r.r.venkateshaprasad@tudelft.nl
Effective indoor navigation in the presence of dynamic obstacles is crucial for mobile robots. Previous research on deep reinforcement learning (DRL) for robot navigation has primarily focused on expanding neural network (NN) architectures and optimizing hardware setups. However, the impact of other critical factors, such as backward motion enablement, frame stacking buffer size, and the design of the behavioral reward function, on DRL-based navigation remains relatively unexplored. To address this..
Published: 29 Jul 2024
Volume 1
Mariia Baidachna
2828197b@student.gla.ac.uk
Haneen Fatima
h.fatima.1@research.gla.ac.uk
Rahaf Omran
rahaf.omran@hotmail.com
Nour Ghadban
nour.ghadban@glasgow.ac.uk
Muhammad Ali Imran
muhammad.imran@glasgow.ac.uk
Ahmad Taha
ahmad.taha@glasgow.ac.uk
Lina Mohjazi
lina.mohjazi@glasgow.ac.uk
Published: 13 Jun 2024
Volume 1
Lossy compression has become an essential technique to reduce data size in many domains. This type of compression is especially valuable for large-scale scientific data, whose size ranges up to several petabytes. Although Autoencoder-based models have been successfully leveraged to compress images and videos, such neural networks have not widely gained attention in the scientific data domain. Our work presents a neural network that not only significantly compresses large-scale scientific..
Published: 31 Dec 2025
Volume 2
Moussa Ayyash
msma@ieee.org
Editor-in-Chief Editorial Volume 2 of Computing & AI Connect (CAIC) presents 21 high-quality, peer-reviewed research articles that reflect CAIC’s commitment to advancing the theory, design, and application of computing and artificial intelligence–driven systems. Volume 2 articles cover contemporary challenges in intelligent systems, communication networks, security, data analytics, and human-centered technologies. They also contribute to the development of foundational methodologies and interdisciplinary perspectives. A central focus of this volume is the..
