Characterisation of Tribological Properties and Morphologies of Ni-P and Ni-B Coatings by Kristóf Bányai, Máté Czagány, Sándor Kovács, Gabriella Bognár

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Unmasking Nuances Affecting Loneliness: Using Digital Behavioural Markers to Understand Social and Emotional Loneliness in College Students by Malik Muhammad Qirtas, Evi Zafeiridi, Eleanor Bantry White, Dirk Pesch

“…Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. …”
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A study on the correlation between MBTI dimensions and driving behavior characteristics by Liwei Bai, Tao Wang, Jianyao Tu, Bozhezi Peng, Zhuoyu Wang

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A deep fusion‐based vision transformer for breast cancer classification by Ahsan Fiaz, Basit Raza, Muhammad Faheem, Aadil Raza

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The utility of combining deep learning with metabarcoding to model biodiversity dynamics at a national scale by Adrian Baggström, Robert Goodsell, Laura van Dijk, Ela Iwaszkiewicz-Eggebrecht, Andreia Miraldo, Ayco J.M. Tack, Tobias Andermann

“…By combining detailed biodiversity surveys, geospatial data, and machine learning, we can model biodiversity with the aim of gaining insights into how these complex patterns behave. …”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…Distinct AU patterns were found for all five phases, with gradient boosting machine and random forest models achieving the highest predictive accuracy. …”
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On the use of kolmogorov–arnold networks for adapting wind numerical weather forecasts with explainability and interpretability: application to madeira international airport by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…A key outcome of this study comes from the model’s ability to generate mathematical formulas that provide insights into the physical and mathematical dynamics influencing local wind patterns and improve the transparency, explainability, and interpretability of the employed machine learning models for atmosphere modeling.…”
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Chlorophyll-a Outliers in the Banda Sea and its surroundings: Implications for Ecosystem Dynamics by Sunarwan Asuhadi, Mukti Zainuddin, Safruddin Safruddin, Musbir Musbir, Achmad Fachruddin Syah

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Unveiling the drivers contributing to global wheat yield shocks through quantile regression by Srishti Vishwakarma, Xin Zhang, Vyacheslav Lyubchich

“…Here, we study the spatiotemporal patterns of wheat yield shocks, quantified by the lower quantiles of yield fluctuations, in 86 countries over 30 years. …”
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Enhancing agricultural commodity price forecasting with deep learning by R. L. Manogna, Vijay Dharmaji, S. Sarang

“…This study evaluates the performance of traditional stochastic models, machine learning techniques, and deep learning approaches in forecasting the prices of 23 commodities using daily wholesale price data from January 2010 to June 2024. …”
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A Scene–Object–Economy Framework for Identifying and Validating Urban–Rural Fringe Using Multisource Geospatial Big Data by Ganmin Yin, Ying Feng, Yanxiao Jiang, Yi Bao

“…Our results reveal distinct spatial patterns and characteristics of these transitional zones, providing valuable insights for urban planners and policymakers. …”
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Identifying common disease trajectories of Alzheimer’s disease with electronic health recordsResearch in context by Mingzhou Fu, Sriram Sankararaman, Bogdan Pasaniuc, Keith Vossel, Timothy S. Chang

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Citrus quality grading based on statistical complexity measurement and multifractal spectrum method by Cao Leping, Wen Zhiyuan

“…It can also make huge economic and social benefits and increase farmers income and agricultural productivity so as to promote the sustained and healthy development of the citrus industry.For the purpose of precise measurement of citrus quality grading, the complexity measurement of Bingtang orange defective fruit damaged by diseases and insect pest patterns were studied by machine recognition, along with the navel orange fruit perimeter-area fractal dimension and the shape, color grading and sugar acid nondestructive detection of section tone unit coordinates multifractal spectrum height and width.Physiological boron deficiency, Eriophyes oleivorus and rind oil spotting disease were very common in Bingtang orange fruits. …”
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A comparative study of convolutional neural networks and traditional feature extraction techniques for adulteration detection in ground beef by Leila Bahmani, Saied Minaei, Alireza Mahdavian, Ahmad Banakar, Mahmoud Soltani Firouz

“…This shows the superiority of CNN algorithm over machine learning algorithms in identifying adulteration in minced meat. …”
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LSTM model to predict missing data of dissolved oxygen in land-based aquaculture farm by Sang-Yeon Lee, Deuk-Young Jeong, Jinseo Choi, Seng-Kyoun Jo, Dae-Heon Park, Jun-Gyu Kim

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Drivers of Structural and Functional Resilience Following Extreme Fires in Boreal Forests of Northeast China by Jianyu Yao, Xiaoyang Kong, Lei Fang, Zhaohan Huo, Yanbo Peng, Zile Han, Shilong Ren, Jinyue Chen, Xinfeng Wang, Qiao Wang

“…A comprehensive wall-to-wall assessment was conducted, integrating gradient boosting machine (GBM) modeling with Shapley Additive Explanation (SHAP) to identify the dominant factors influencing postfire resilience. …”
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Big data in visual field testing for glaucoma by Alex T. Pham, Annabelle A. Pan, Jithin Yohannan

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Fatigue Detection of Air Traffic Controllers Through Their Eye Movements by Yi Hu, Haoran Shen, Hui Pan, Wenbin Wei

“…Eye movement patterns have become an essential element in modern approaches for identifying air traffic controller fatigue. …”
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Apk2Audio4AndMal: Audio Based Malware Family Detection Framework by Oguz Emre Kural, Erdal Kilic, Ceyda Aksac

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A Data-Driven Approach for Urban Heat Island Predictions: Rethinking the Evaluation Metrics and Data Preprocessing by Berk Kıvılcım, Patrick Erik Bradley

“…A 2D raster data representing building volumes of each grids are derived from 3D vector-format urban data for use in machine learning applications. Since the task is to explore patterns, i.e., urban heat islands, Gaussian blurring is implemented on these generated 2D raster data before the training process. …”
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