An adaptive k-means clustering algorithm based on grid and domain centroid weights for digital twins in the context of digital transformation by Wei Cai, Fei Yang, Bo Yao, Chuanxian Li, Guangyu Sun

“…This characteristic presents challenges in digital twin data mining, including high computational costs, performance limitations, and inefficiencies. …”
Get full text

AI-Enhanced Threat Intelligence in Remote Patient Monitoring Systems: A Survey on Recent Advances, Challenges and Future Research Directions by Jolly Trivedi, Mohammad Tahir, Jouni Isoaho

“…Furthermore, the benefits and challenges of deploying AI-driven threat intelligence, cross-platform compatibility, and the need for explainable AI to improve trust in automatically made decisions are presented. Moreover, this review highlights research gaps, including the necessity of comprehensive end-to-end architectures for maintaining security and privacy in RPM systems. …”
Get full text

The role of the measurement and measurement equipment management system in the arms industry by Monika Bernatek, Mieczysław Jan Magierski

“…Research objectives and hypothesis/research questions The aim of this paper is to present partial results of an experimental study on the influence of measurement uncertainty on gauges used at different stages of product manufacture. …”
Get full text

Issues of establishing the permissible discharge levels of ²³⁸U to surface waters taking into account its radiation and toxic effects by A. I. Kryshev, T. G. Sazykina, N. N. Pavlova

“…At present, discharges of 238U to surface waters by nuclear industry enterprises are limited by radiation factor. …”
Get full text

Machine Learning-Based Detection of Icebergs in Sea Ice and Open Water Using SAR Imagery by Zahra Jafari, Pradeep Bobby, Ebrahim Karami, Rocky Taylor

“…In this paper, we propose a method for automatically detecting and classifying icebergs in various sea conditions using C-band dual-polarimetric images from the RADARSAT Constellation Mission (RCM) collected throughout 2022 and 2023 across different seasons from the east coast of Canada. …”
Get full text

Artificial intelligence driven mental health diagnosis based on physiological signals by P.R. Naregalkar, A.A. Shinde, M.V. Patil

“…This work aims to automatically detect stressful situations in humans using physiological data collected during anxiety-inducing scenarios. …”
Get full text

Adaptive overcurrent protection considering fault current limiters effect by R. A. Mahmoud, K. G. Ghaly, S. A. Hasan

“…The simulation results indicate that the proposed algorithm can operate online and adjust its operating time settings automatically. As a consequence, it is able to detect fault instances upon which the relay sends a tripping flag, yet remains inactive under normal operating conditions. …”
Get full text

On the Question of Islamization of Ugrian Population in Western Siberia from the sixteenth to early eighteenth centuries and Some Aspects of Study of This Process by Maslyuzhenko D.N., Samigulov G.Kh.

“…Research materials: The present study was based on the analysis of published sources: chronicles, memoirs, and archaeological as well as historiographical data. …”
Get full text

Recent Advancements in Neuroimaging‐Based Alzheimer's Disease Prediction Using Deep Learning Approaches in e‐Health: A Systematic Review by Zia‐Ur‐Rehman, Mohd Khalid Awang, Ghulam Ali, Muhammad Faheem

“…DL models have received significant interest due to their capability to identify AD in its early phases automatically, which reduces the mortality rate and treatment cost of AD. …”
Get full text

Adaptive Anomaly Detection Framework Model Objects in Cyberspace by Hasan Alkahtani, Theyazn H. H. Aldhyani, Mohammed Al-Yaari

“…In particular, an adaptive anomaly detection framework model was developed using deep and machine learning algorithms to manage automatically-configured application-level firewalls. …”
Get full text

Planificación y optimización asistida por computadora de secuencias de ensamble mecánico. by L. L. Tomás García

“…El presente trabajo versa sobre la generación, planificación y optimización de secuencias de ensamble mecánico a partir de su modelo geométrico tridimensional. …”
Get full text

Accuracy of Probabilistic Linkage Using the Enhanced Matching System for Public Health and Epidemiological Studies. by Robert W Aldridge, Kunju Shaji, Andrew C Hayward, Ibrahim Abubakar

“…Probabilistic matching was most accurate when including address variables and using the automatically generated threshold for determining links with manual review.…”
Get full text

Algae-Mamba: A Spatially Variable Mamba for Algae Extraction From Remote Sensing Images by Yaoteng Zhang, Shuaipeng Wang, Yanlong Chen, Shiqing Wei, Mingming Xu, Shanwei Liu

“…Traditional threshold-based methods and standard machine learning techniques often fall short in accurately and automatically distinguishing algae types. This study presents Algae-Mamba, an advanced network for algae extraction that builds upon the visual state-space (VSS) model. …”
Get full text

Development of an Automated Aquarium Monitoring System with an IoT Interface using Google Sheets by Theodore Tochuckwu Chiagunye, Somtochukwu Francis Ilo, Godspower Ikechukwu Ndukwe, Henrietta Uchenna Udeani, Ogobuchi Daniel Okey

“…A servo motor dispenses feed precisely every 12 hours, while two DC pumps are triggered automatically when turbidity exceeds 50 NTU, ensuring proactive water quality management. …”
Get full text

A self-configuration framework for balancing services in the fog of things by Edson Mota, Jurandir Barbosa, Gustavo B. Figueiredo, Maycon Peixoto, Cássio Prazeres

“…Within this context, this paper presents a novel self-organizing environment based on the Fog of Things approach, designed to address these challenges. …”
Get full text

A machine-learning approach for predicting butyrate production by microbial consortia using metabolic network information by Claudia Silva-Andrade, Sergio Hernández, Pedro Saa, Ernesto Perez-Rueda, Daniel Garrido, Alberto J. Martin

“…Despite its importance, there is a lack of computational methods capable of predicting its production as a function of the consortium composition. Here, we present a novel machine-learning approach leveraging automatically generated genome-scale metabolic models to tackle this limitation. …”
Get full text

Artificial intelligence-based model for diagnosing Helicobacter pylori in whole-slide images by Kehan Teng, Lihua Ren, Xiaoyu Yan, Yawei Duan, Zhe Chen, Hansheng Li, Lihua Zhang, Lei Cui

“…The reliability of DS-MIL is confirmed through the Visual model.DiscussionOur research presents an AI - based predictive model for H. pylori infection, which significantly enhances clinical efficiency and diagnostic accuracy. …”
Get full text

Toward Specialized Wireless Networks Using an ML-Driven Radio Interface by Kamil Szczech, Maksymilian Wojnar, Katarzyna Kosek-Szott, Krzysztof Rusek, Szymon Szott, Dileepa Marasinghe, Nandana Rajatheva, Richard Combes, Francesc Wilhelmi, Anders Jonsson, Boris Bellalta

“…These networks, equipped with cognitive capabilities, dynamically adapt to the unique demands of each application, e.g., by automatically selecting and configuring network mechanisms. …”
Get full text

Using a transformer language model to curate a pulmonary embolism dataset from the Medical Information Mart for Intensive Care IV: MIMIC-IV-Ext-PE by Barbara D. Lam, Shengling Ma, Iuliia Kovalenko, Peiqi Wang, Omid Jafari, Ang Li, Steven Horng

“…Objectives: In this study, we experiment using a machine learning language model to automatically add PE labels to a large dataset. Methods: We extracted all computed tomography pulmonary angiography radiology reports (N = 19,942) from the Medical Information Mart for Intensive Care IV, a database of adult patients who presented to the emergency room or were admitted to the intensive care unit at one tertiary care center between 2008 and 2019. …”
Get full text

Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data by Paul Fergus, Carl Chalmers, Naomi Matthews, Stuart Nixon, André Burger, Oliver Hartley, Chris Sutherland, Xavier Lambin, Steven Longmore, Serge Wich

“…Combined, this information is used to automatically generate structured reports, providing biodiversity stakeholders with deeper insights into, for example, species abundance, distribution, animal behaviour, and habitat selection. …”
Get full text