A fuzzy-optimized multi-level random forest (FOMRF) model for the classification of the impact of technostress by Gabriel James, Ifeoma, David, John, Samuel, Enefiok, Imeh Umoren, Ubong Etuk, Aloysius, Anietie, Saviour, Chikodili

“…To address this, this study proposes a Fuzzy-Optimized Multi-Level Random Forest (FOMRF) model that integrates fuzzy logic with machine learning to enhance classification accuracy and interpretability. …”
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A Hybrid KAN-BiLSTM Transformer with Multi-Domain Dynamic Attention Model for Cybersecurity by Aleksandr Chechkin, Ekaterina Pleshakova, Sergey Gataullin

“…The study used explainable visualization techniques, including SHAP and LIME, to analyze the interpretability of the Hyb-KAN model, providing a deeper understanding of the decision-making mechanisms. …”
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Reservoir Characterisation and Modelling for CO2 Sequestration in ‘‘Han’’ Field, Onshore Niger Delta, Nigeria by S. Kemisola Oyero, Abiola Olubola, O. Kazeem Ayinde

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Permissible Extrapolation Justification of the Multiplicative Multifactorial Model and Its Application to the White Soot Production Technology by Lyutsiya Karimova, Guldana Makasheva, Vitaliy Malyshev, Yelena Kharchenko, Yerlan Kairalapov

“…A multifactorial experiment was designed, and the experimental results were processed using a probabilistic deterministic method for experiment design (PDED) to obtain a nonlinear multiplicative combined model. A new interpretation of the subordination of the nonlinear multiple correlation coefficient R and the R2 value was given as relating to the structural and adaptive components of complex self-organizing systems. …”
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A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets by Ciaran O’Connor, Mohamed Bahloul, Steven Prestwich, Andrea Visentin

“…Unlike standard reviews focused solely on the day-ahead market, we assess model performance across day-ahead, intra-day, and balancing markets, with each posing unique challenges due to differences in time resolution, data availability, and market structure. …”
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Complex q-Rung Orthopair Fuzzy N-Soft Sets: A New Model with Applications by Muhammad Akram, Faiza Wasim, Ahmad N. Al-Kenani

“…It is able to capture a great deal of graded imprecision and vagueness, which so often appear together in human interpretations. This model renders a parameterized mathematical tool for the ranking-based fuzzy modeling of two-dimensional paradoxical data. …”
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A large model for non-invasive and personalized management of breast cancer from multiparametric MRI by Luyang Luo, Mingxiang Wu, Mei Li, Yi Xin, Qiong Wang, Varut Vardhanabhuti, Winnie CW Chu, Zhenhui Li, Juan Zhou, Pranav Rajpurkar, Hao Chen

“…We develop a large mixture-of-modality-experts model (MOME) that integrates multiparametric MRI information within a unified structure, leveraging breast MRI scans from 5205 female patients in China for model development and validation. …”
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Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of Materials by Lai Wei, Qinyang Li, Yuqi Song, Stanislav Stefanov, Rongzhi Dong, Nihang Fu, Edirisuriya M. D. Siriwardane, Fanglin Chen, Jianjun Hu

“…These models have demonstrated superior performance in the generation, structure classification, and functional predictions for proteins and molecules with learned representations. …”
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Knowledge Extraction via Machine Learning Guides a Topology‐Based Permeability Prediction Model by Jia Zhang, Gang Ma, Zhibing Yang, Jiangzhou Mei, Daren Zhang, Wei Zhou, Xiaolin Chang

“…While machine learning (ML) and deep learning (DL) models demonstrate promising performance, but encounter challenges of data availability, computational cost, and model interpretability. …”
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ASSESSMENT OF AVIATION SECURITY SCREENERS PROFFICIENCY BY MEANS OF APPLYING THE A. BIRNBAUM TWO-PARAMETER MODEL by B. V. Zubkov, A. K. Volkov

“…Within the model the qualification level characteristic functions, which describe multi-complexity level of x-ray image interpretation competency of the aviation security screener, were generated and explored. …”
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Understanding Interventions to Address Infodemics Through Epidemiological, Socioecological, and Environmental Health Models: Framework Analysis by Jennifer N John, Sara Gorman, David Scales

“…We applied framework analysis to describe and interpret patterns within these interventions through their alignment with codes derived from 3 frameworks selected for their prominence in public health and infodemic-related scholarly discourse: the epidemiological model, the socioecological model, and the environmental health framework. …”
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TrBot: A Turkish Deep Learning Chatbot Utilizing Seq2Seq Model by Bilal Babayigit, Habibelahi Rahmani, Mohammed Abubaker

“…However, creating an effective chatbot remains a complex task, as it must accurately interpret user input and generate appropriate responses. …”
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A Fluid Flow‐Based Deep Learning (FFDL) Architecture for Subsurface Flow Systems With Application to Geologic CO2 Storage by Zhen Qin, Yingxiang Liu, Fangning Zheng, Behnam Jafarpour

“…Despite their powerful learning capabilities and computational appeal, deep learning models have important limitations, including lack of interpretability, extensive data needs, weak extrapolation capacity, and physical inconsistency that can affect their adoption in practical applications. …”
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Presenting a Leadership Empowerment Model through Sense-making by Using the Cognitive and Behavioral Scripts by Hamid Zare, Aliasghar Pourezzat, Hasan Zareei Matin, Arezoo Salmani

“…Objective Leadership has consistently been recognized as a fundamental element in any group of individuals, playing a critical role whether in defining their roles within society or within the structural confines of an organization. Effective leadership within an organization is crucial for steering its members toward the attainment of established goals and upholding the values defined by the organization. …”
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AN ANALYSIS OF MIRIN D ZANGA 12DA NOVEL ACCORDING TO SARA MILLS' FEMINIST STYLISTIC MODEL by Aveen Salih, Hussein Abdulrahman

“… Feminist stylistics’ is a modern and critical approach that integrates linguistics and feminist criticism to examine how societal structures influence the language and style of literary texts. …”
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Fishes in Warming Waters, the Gill-Oxygen Limitation Theory and the Debate Around Mechanistic Growth Models by Johannes Müller, Daniel Pauly

“…However, critical assessments of even the most prominent theories are not always based on accurate interpretations of their underlying mechanistic models. …”
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Scalable topic modelling decodes spatial tissue architecture for large-scale multiplexed imaging analysis by Xiyu Peng, James W. Smithy, Mohammad Yosofvand, Caroline E. Kostrzewa, MaryLena Bleile, Fiona D. Ehrich, Jasme Lee, Michael A. Postow, Margaret K. Callahan, Katherine S. Panageas, Ronglai Shen

“…We show that SpatialTopic is highly scalable to large-scale images, along with high precision and interpretability. It consistently identifies biologically and clinically significant spatial topics, such as tertiary lymphoid structures, and tracks spatial changes over disease progression. …”
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Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models by Fatma Yasmine Loumachi, Mohamed Chahine Ghanem, Mohamed Amine Ferrag

“…Traditional approaches rely on processing structured artefacts, such as logs and filesystem metadata, using multiple specialised tools for evidence identification, feature extraction, and timeline reconstruction. …”
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Time series prediction for monitoring cardiovascular health in autistic patients by Congsha Ma, Ming Lei

“…Central to our method is the CardioGraph Synaptic Encoder (CGSE), a generative model that fuses multimodal data—such as ECG waveforms, blood pressure signals, and structured clinical annotations—into a unified latent space. …”
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Automated Skin Cancer Report Generation via a Knowledge-Distilled Vision-Language Model by Lawhori Chakrabarti, Boyu Zhang, Hengyi Tian, Aleksandar Vakanski, Min Xian

“…This study presents a multimodal vision-language model (VLM) trained using a two-stage knowledge distillation (KD) framework to generate structured medical reports from dermoscopic images, with descriptive features based on the 7-point melanoma checklist. …”
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