Automatic detection of cognitive events using machine learning and understanding models’ interpretations of human cognition by Quang Dang, Murat Kucukosmanoglu, Michael Anoruo, Golshan Kargosha, Sarah Conklin, Justin Brooks

“…We report three key findings: (1) the generalized model reduces the specificity to enhance the sensitivity, illustrating the trade-off from specialization to generalization; (2) the permutation feature importance analyses show that both pupil dilation and gaze position contribute to model predictions, with task-specific models focusing on task-specific structure patterns to predict while the generalized model is using human cognitive responses; and (3) in an online simulation environment, models performance decreases by approximately 0.05 on MCC. …”
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Forecasting Eruptions at Steamboat Geyser: Time Scales, Differentiability, and Detectability of Seismic Precursors Through Data‐Driven Methods by Alberto Ardid, Anna Barth, David Dempsey, Michael Manga, Shane J. Cronin

“…We analyzed seismic data from March to December 2018 to identify patterns that occurred before 31 eruptions. Four seismic amplitude measures and 700 time‐series features were computed from the seismic data. …”
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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

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Optimizing Group Activity Recognition With Actor Relation Graphs and GCN-LSTM Architectures by M. R. Tejonidhi, C. V. Aravinda, S. V. Aruna Kumar, C. K. Madhu, A. M. Vinod

“…Traditional video-based activity recognition methods often grapple with persistent obstacles such as environmental noise, background clutter, and the inter-class similarities inherent in activity patterns. Recent advancements in this field have largely focused on spatial feature extraction, which alone proves inadequate for thorough group activity analysis. …”
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A dual-domain perception gate-controlled adaptive fusion algorithm for road crack detection by Ziyang Zhang, Yong’an Feng

“…Abstract Road crack detection presents critical challenges, including diverse defect patterns and complex anomaly characteristics. The current object detection algorithms demonstrate deficiencies in considering feature redundancy across channel-spatial dimensions, employ indiscriminate fusion strategies for multi-stage feature information, and particularly neglect the high-frequency characteristics inherent in crack features, leading to inefficient network performance and a loss of crucial information. …”
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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…To examine the significance of features in tree-based models, permutation importance and SHAP values were utilized. …”
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Masked and Noise-Masked Multimodal Brain Tumor Image Segmentation Using SegFormer and Shared Encoder Framework by K. Hemalatha, P. R. Vishnu Vardhan, Alfred Dharmaraj Aravindraj, S. Hari Hara Sudhan

“…MNMS employs masking to overcome computational complexity while maintaining local and global features essential for accurate medical image segmentation. …”
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Physics-based modeling and mechanism of polycrystalline diamond tool wear in milling of 70 vol% Si/Al composite by Lianjia Xin, Guolong Zhao, Zhiwen Nian, Haotian Yang, Liang Li, Ning He

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Attention-Driven Emotion Recognition in EEG: A Transformer-Based Approach With Cross-Dataset Fine-Tuning by Ghulam Ghous, Shaheryar Najam, Mohammed Alshehri, Abdulmonem Alshahrani, Yahya AlQahtani, Ahmad Jalal, Hui Liu

“…A transformer encoder with integrated spectral and temporal attention mechanisms captures intricate patterns and long-range dependencies within the EEG signals. …”
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VETC predicting model based on CE-CT can predict prognosis and assisting treatment plan for solitary HCC: better together with radiomics by Yu-Meng Zhao, Shuang-Shuang Xie, Jian Wang, Zhan-Dong Hu, Sheng-Juan Yao, Rui-Hang Wang, Jia-Ming Qin, Cheng Zhang, Ya-Min Zhang, Zhao-Xiang Ye, Jian-Hua Yan, Wen Shen

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Synthesis of Amplitude-Phase Distribution in Quasiconcave an Antenna Array by M. R. Bibarsov, E. V. Gribanov, D. D. Gabrielyan, D. S. Fedorov, D. S. Fedorov

“…Such a transition leads to a change in the radiation pattern, i.e. to a shift in its main maximum, an increase in the level of the side lobes, and appearance of two maxima of the radiation pattern. …”
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Changes in visitor behaviour in Canadian National Parks due to COVID-19: focusing on visitor spatial location and the distance between park facilities and visitors by Huaiyi Wang, Xiangfei Lu, Yaquan Dou, Xuanqin Yang, Xiaodi Zhao

“…To investigate these changes, this study selected six NPs and examined shifts in spatial visitation patterns and their relationship with proximity to park facilities before and during the pandemic. …”
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Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

“…There is an urgent need for non-invasive methods to diagnose various stages of liver dysfunction and uncover hidden pattern based on individual disease characteristics. …”
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Genome-wide characterization of monoacylglycerol lipase (MAGL) gene family in soybean and functional analysis of GmMAGLs in storage lipid metabolism and drought resistance by Haiqing Jing, Yan Sun, Bicheng Wang, Juhua Ma, Kun Wan, Zhanqian Li, Yali Zhou, Runzhi Li, Haiping Zhang, Jinai Xue

“…RNA-seq data revealed that GmMAGL genes displayed tissue-specific or distinct expression patterns in response to abiotic stresses and hormone treatments. …”
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Incremental Adversarial Learning for Polymorphic Attack Detection by Ulya Sabeel, Shahram Shah Heydari, Khalil El-Khatib, Khalid Elgazzar

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A Hybrid Deep Transfer Learning-based Approach for COVID-19 Classification in Chest X-ray Images by Khosro Rezaee, Afsoon Badiei, Hossein Ghayoumi Zadeh, Saeed Meshgini

“…In this paper, we presented an approach to diagnosis COVID-19 using CXR images based on the concatenated features vector of the three DTL structures and soft-voting feature selection procedure, including Receiver of Curve (ROC), Entropy, and signal-to-noise ratio (SNR) techniques. …”
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Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion by Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

“…This hybrid design leverages deep representations for pattern recognition and SVM’s robustness on small sample sets. …”
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A machine learning approach to identifying key predictors of Peruvian school principals' job satisfaction by Luis Alberto Holgado-Apaza, Dany Dorian Isuiza-Perez, Nelly Jacqueline Ulloa-Gallardo, Yban Vilchez-Navarro, Ruth Nataly Aragon-Navarrete, Wilian Quispe Layme, Marleny Quispe-Layme, Danger David Castellon-Apaza, Remo Choquejahua-Acero, Jaime Cesar Prieto-Luna

“…This study identified key predictors of job satisfaction among Peruvian school principals by applying an ensemble of feature selection methods and evaluating five machine learning algorithms (Random Forest, Decision Trees-CART, Histogram-Based Gradient Boosting, XGBoost, and LightGBM) with data from the 2018 National Survey of Directors. …”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…The prediction uncertainty exhibited a similar pattern. Topographic and climatic variables played crucial roles in SOC estimation. …”
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Clinical features of post-COVID-19 period. Results of the international register “Dynamic analysis of comorbidities in SARS-CoV-2 survivors (AKTIV SARS-CoV-2)”. Data from 6-month f... by G. P. Arutyunov, E. I. Tarlovskaya, A. G. Arutyunov, Yu. N. Belenkov, A. O. Konradi, Yu. M. Lopatin, A. P. Rebrov, S. N. Tereshchenko, A. I. Chesnikova, H. G. Hayrapetyan, A. P. Babin, I. G. Bakulin, N. V. Bakulina, L. A. Balykova, A. S. Blagonravova, M. V. Boldina, A. R. Vaisberg, A. S. Galyavich, V. V. Gomonova, N. Yu. Grigorieva, I. V. Gubareva, I. V. Demko, A. V. Evzerikhina, A. V. Zharkov, U. K. Kamilova, Z. F. Kim, T. Yu. Kuznetsova, N. V. Lareva, E. V. Makarova, S. V. Malchikova, S. V. Nedogoda, M. M. Petrova, I. G. Pochinka, K. V. Protasov, D. N. Protsenko, D. Yu. Ruzanau, S. A. Sayganov, A. Sh. Sarybaev, N. M. Selezneva, A. B. Sugraliev, I. V. Fomin, O. V. Khlynova, O. Yu. Chizhova, I. I. Shaposhnik, D. A. Shchukarev, A. K. Abdrahmanova, S. A. Avetisian, H. G. Avoyan, K. K. Azarian, G. T. Aimakhanova, D. A. Ayipova, A. Ch. Akunov, M. K. Alieva, A. V. Aparkina, O. R. Aruslanova, E. Yu. Ashina, O. Yu. Badina, O. Yu. Barisheva, T. I. Batluk, A. S. Batchayeva, R. A. Bashkinov, A. M. Bitieva, I. U. Bikhteyev, N. A. Borodulina, M. V. Bragin, A. M. Budu, G. A. Bykova, K. R. Vagapova, D. D. Varlamova, N. N. Vezikova, E. A. Verbitskaya, O. E. Vilkova, E. A. Vinnikova, V. V. Vustina, E. A. Gаlova, V. V. Genkel, E. I. Gorshenina, E. V. Grigorieva, E. Yu. Gubareva, G. M. Dabylova, I. A. Demchenko, O. Yu. Dolgikh, M. Y. Duyshobayev, D. S. Evdokimov, K. E. Egorova, A. N. Ermilova, A. E. Zheldybayeva, N. V. Zarechnova, Yu. D. Zimina, S. Yu. Ivanova, E. Yu. Ivanchenko, M. V. Ilina, M. V. Kazakovtseva, E. V. Kazymova, Yu. S. Kalinina, N. A. Kamardina, A. M. Karachenova, I. A. Karetnikov, N. A. Karoli, M. K. Karsiev, D. S. Кaskaeva, K. F. Kasymova, Zh. B. Kerimbekova, A. Sh. Kerimova, E. S. Kim, N. V. Kiseleva, D. A. Klimenko, A. V. Klimova, O. V. Kovalishena, E. V. Kolmakova, T. P. Kolchinskaya, M. I. Kolyadich, O. V. Kondriakova, M. P. Konoval, D. Yu. Konstantinov, E. A. Konstantinova, V. A. Kordukova, E. V. Koroleva, A. Yu. Kraposhina, T. V. Kriukova, A. S. Kuznetsova, T. Yu. Kuzmina, K. V. Kuzmichev, Ch. K. Kulchoroeva, T. V. Kuprina, I. M. Kouranova, L. V. Kurenkova, N. Yu. Kurchugina, N. A. Kushubakova, V. I. Levankova, N. A. Lyubavina, N. A. Magdeyeva, K. V. Mazalov, V. I. Majseenko, A. S. Makarova, A. M. Maripov, A. A. Marusina, E. S. Melnikov, N. B. Moiseenko, F. N. Muradova, R. G. Muradyan, Sh. N. Musaelian, A. O. Myshak, E. S. Nekaeva, N. M. Nikitina, B. B. Ogurlieva, A. A. Odegova, Yu. M. Omarova, N. A. Omurzakova, Sh. O. Ospanova, E. V. Pahomova, L. D. Petrov, S. S. Plastinina, V. A. Pogrebetskaya, D. V. Polyakov, D. S. Polyakov, E. V. Ponomarenko, L. L. Popova, N. A. Prokofeva, I. A. Pudova, N. A. Rakov, A. N. Rakhimov, N. A. Rozanova, S. Serikbolkyzy, A. A. Simonov, V. V. Skachkova, D. V. Soloveva, I. A. Soloveva, I. M. Sukhomlinova, A. G. Sushilova, D. R. Tagayeva, Yu. V. Titojkina, E. P. Tikhonova, D. S. Tokmin, A. A. Tolmacheva, M. S. Torgunakova, K. V. Trenogina, N. A. Trostianetckaia, D. A. Trofimov, M. A. Trubnikova, A. A. Tulichev, A. T. Tursunova, N. D. Ulanova, O. V. Fatenkov, O. V. Fedorishina, T. S. Fil, I. Yu. Fomina, I. S. Fominova, I. A. Frolova, S. M. Tsvinger, V. V. Tsoma, M. B. Cholponbaeva, T. I. Chudinovskikh, O. A. Shevchenko, T. V. Sheshina, E. A. Shishkina, K. Yu. Shishkov, S. Yu. Sherbakov, E. A. Yausheva

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