Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

“…This research presents a data-driven structural health monitoring (SHM) approach for pipeline systems that leverages frequency response function (FRF) signals and artificial neural network (ANN) algorithms to accurately identify and classify diverse pipeline fault conditions. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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How does the level of functional impairment vary in individuals with non-communicable disease and comorbidity? Cross-sectional analysis of linked census and administrative data in... by Barry Milne, Nicholas Bowden, Lisa Underwood, Andrea M Teng, Hamish Jamieson

“…Objectives This study examines national patterns of functional impairment, and how they vary by the presence of non-communicable disease (NCD), type of health condition, comorbidity, age, sex, ethnicity, deprivation and living situation.Design A cross-sectional examination using a national research database of linked administrative and survey data sets including census, tax and health data.Setting Aotearoa New ZealandParticipants All individuals living in NZ on 30 June 2018, identified by the Statistics NZ Integrated Data Infrastructure estimated residential population (4.79 million individuals). …”
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THE ACCEPTANCE OF AN EDUCATIONAL INTEGRATED DEVELOPMENT ENVIRONMENT TO LEARN PROGRAMMING FUNDAMENTALS by Nor Farahwahida Mohd Noor, Aslina Saad, Abu Bakar Ibrahim, Norashady Mohd Noor

“… Programming is an important course for any IT or engineering-related course. However, previous research shows that students face difficulties in learning programming due to its abstract concepts. …”
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Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…Conclusion: Despite these advancements, challenges such as data scarcity, image heterogeneity, interpretability issues, regulatory compliance, and poor workflow integration hinder the seamless adoption of AI in onychology practice. Ongoing research and collaboration between AI developers and nail experts is crucial to realize the full potential of AI in improving patient outcomes in onychology.…”
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Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis by Liang Xu, Jing Li, Wei Gong

“…In recent years, machine learning (ML) technology in the medical field has gained momentum, which utilize various algorithms to analyze input data, identify potential patterns and trends, develop predictive models, and generate high-precision predictions of unknown data, demonstrating its clinical potential in disease diagnosis. …”
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GIS-based framework for assessing priority locations for blue-green infrastructure implementation in urban areas by Ewelina Pochodyła-Ducka, Paweł Burandt, Katarzyna Glińska-Lewczuk

“…These indicators aim to delineate essential characteristics of land use patterns, sealing density, building density, and areas excluded from development. …”
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Hybrid Intelligence approach to study post-processing impact on the mechanical performance of notched additively manufactured AlSi10Mg by Erfan Maleki, Sara Bagherifard, Okan Unal, Mario Guagliano

“…AI identified patterns and developed predictive models that provided deeper insights into how process parameters affect material properties and performance. …”
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A Comparative study on the impact of urbanisation on microclimate in Cairo (Egypt) and London (UK) using remote sensing and Machine Learning by L. Sabobeh, T. Ali, M. Md. Mortula

“…Several machine learning (ML) algorithms were compared, with Support Vector Machine (SVM) ultimately selected for its superior performance. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…Recent advancements in nanomaterials and fabrication techniques, coupled with emerging computational approaches such as artificial intelligence (AI), machine learning, and deep learning, have revolutionized high-throughput screening and laboratory automation. AI-driven algorithms now process and analyze salivary proteomic data with remarkable accuracy, identifying patterns and biomarkers associated with diseases such as oral cancer at an early stage. …”
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A Proactive Caching Approach to Boost Network Offloading in Urban Areas by Ahmed Hassan, Khaled Metwally, Tamer Mekkawy, Ashraf Mahran

“…At its core is the Cognitive File Caching Algorithm (CFCA), a proactive, scalable, and adaptive approach designed to address complex challenges involving varying file popularity in cities and user movement patterns. …”
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Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…Timely and accurate diagnosis of bearing faults is essential for preventing unexpected failures and minimizing downtime. This research addresses these challenges by employing advanced signal processing techniques and machine learning algorithms. …”
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Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…This enables the generation of precise modulatory patterns of neuronal circuits. Deep learning-based spike sorting algorithms are based on power-intensive dot products, which poses challenges for on-chip processing with resource-constrained devices. …”
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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…Support Vector Machine (SVM) and ID3 decision tree algorithms were employed to classify vowel formant parameters (F1-F2) patterns. …”
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A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification by Shravan Venkatraman, S. Kanthimathi, K. S. Jayasankar, T. Pranay Jiljith, R. Jashwanth

“…This research addresses this gap by introducing a novel approach for DDoS attack detection. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…This study aimed to analyze the background patterns of electroencephalogram (EEG) signals from such patients to identify the key indicators for assessing the prognosis after coma. …”
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Determining the Boundaries of Overlying Strata Collapse Above Mined-Out Panels of Zhomart Mine Using Seismic Data by Sara Istekova, Alexander Makarov, Dina Tolybaeva, Arman Sirazhev, Kuanysh Togizov

“…The present article is devoted to the issue of studying the patterns of displacement of superincumbent rock over panels of a mine obtained using advanced seismic technologies, allowing for the study of the boundaries of caving zones in the depths of rock mass. …”
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Fiber Sensing in the 6G Era: Vision Transformers for <i>ϕ</i>-OTDR-Based Road-Traffic Monitoring by Robson A. Colares, Leticia Rittner, Evandro Conforti, Darli A. A. Mello

“…Backscattered traces are consolidated into space–time matrices, illustrating traffic patterns and enabling analysis through image processing algorithms. …”
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