Logical-semantic knowledge model for the knowledge base of a lecturer by Serhii Dotsenko, Olga Banit, Dmytro Nor, Olga Morozova

“…The methods used include an approach that identifies general patterns and hypotheses underlying the construction of lecturers’ knowledge bases to organize the educational process in higher education institutions. …”
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Multiobjective Approach to the Transit Network Design Problem with Variable Demand considering Transit Equity by Su Jin Park, Seungmo Kang, Young-Ji Byon, Seung-Young Kho

“…Existing research on the transit network design problem has tended to focus on minimizing the various costs for both transit operators and users. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…Abstract With the rapid advancement of technology, aerial interaction patterns have become increasingly complex, making intelligent air combat a prominent and cutting-edge research area in multi-agent systems. …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
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Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting. by Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola

“…In recent years, numerous methods were developed for Supply Chain (SC) demand forecasting, which posed several limitations related to inadequate handling of dynamic time series patterns and data requirement problems. Thus, this research proposes a Migrative Armadillo Optimization-enabled one-dimensional Quantum convolutional neural network (MiA + 1D-QNN) for effective demand forecasting. …”
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Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Based on an empirical analysis of 3,135,675 social media dissemination data points from 94 corporate crisis incidents, this study explores effective crisis response patterns for enterprises through three dimensions: response timing, methods, and content. …”
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Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…The rationale for splitting the dataset into [Formula: see text] sub-datasets is to separate similar patterns in one sub-dataset. Second, the utilization of the dynamic time warping (DTW) algorithm on the BSSs data was proposed for the clustering purpose, as the DTW usage is very limited in the current literature of BSSs. …”
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Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation by Alexander J. Sharp, Michael T. B. Pope, Andre Briosa e Gala, Richard Varini, Timothy R. Betts, Abhirup Banerjee

“…We apply the CDM inverse algorithm to both sets of reconstructions in order to compare derived conductions across various heart rhythms and AF conduction patterns. …”
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A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma by Beibei Xiong, Wenqiang Liu, Ying Liu, Tong Chen, Anqi Lin, Jiaao Song, Le Qu, Peng Luo, Aimin Jiang, Linhui Wang

“…<b>Methods:</b> In a meticulous research effort, we have identified new molecular categories designated as CRCS1 and CRCS2 through the application of an unsupervised clustering algorithm. …”
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Machine Learning-Enhanced Attribute-Based Authentication for Secure IoT Access Control by Jibran Saleem, Umar Raza, Mohammad Hammoudeh, William Holderbaum

“…Traditional authentication systems struggle to balance security, privacy and computational efficiency, particularly in resource-constrained environments such as Industry 4.0. This research presents the SmartIoT Hybrid Machine Learning (ML) Model, a novel integration of Attribute-Based Authentication and a lightweight machine learning algorithm designed to enhance security while minimising computational overhead. …”
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Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap dataGithub by Mahdi Rasoulinezhad, Nasim Eslamirad, Jenni Partanen

“…The resulting dataset enables researchers to identify recurring patterns in urban street networks, study urban morphology, and compare structural similarities between different urban areas. …”
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Influence of Source Shape on Semi-Airborne Transient Electromagnetic Surveys by Lei Liu, Jianghai Xie, Wentao Liu, Jianmei Zhou

“…The semi-airborne transient electromagnetic (SATEM) method has garnered increasing attention and research interest due to its superior detection depth and high efficiency. …”
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Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

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Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek by Kosmas Kosmidis, Vassiliki Apostolouda, Anthi Revithiadou

“…Pseudowords are essential in (psycho)linguistic research, offering a way to study language without meaning interference. …”
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Beyond accuracy: Multimodal modeling of structured speaking skill indices in young adolescents by Candy Olivia Mawalim, Chee Wee Leong, Guy Sivan, Hung-Hsuan Huang, Shogo Okada

“…The experimental results demonstrate that fusing interpretable features, including prosody, action units, and turn-taking, significantly enhances the accuracy of spoken English skill prediction, achieving an overall accuracy of 83% when a machine learning model based on the light gradient boosting algorithm is used. Furthermore, this research underscores the significant influence of external factors, such as interviewer behavior and the interview setting, particularly on the coherence aspect of spoken English proficiency. …”
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Hybrid deep learning for IoT-based health monitoring with physiological event extraction by Sivanagaraju Vallabhuni, Kumar Debasis

“…In this regard, the research also paves the way for designing next-gen IoT healthcare analytics and their actual clinical applications.…”
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Multimodal image fusion for ich detection and classification using parallel Dl models by Sri Sangepu Nagaraju, S. Prince Mary, V. Pavani Chandra, Nandam Gayatri

“…This paper introduces an innovative multimodal medical image fusion method using parallel Deep Learning (DL) models. The research uses a carefully chosen multimodal dataset, including CT and MRI, and a novel segmentation algorithm called DFA-UNet. …”
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An Explainable Machine Learning Model for Predicting Macroseismic Intensity for Emergency Management by Federico Mori, Giuseppe Naso

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Financial Technology and Financial Inclusion in Remote Areas of Algeria. Analytical Study Using Data Mining by Hassiba Hadouga

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