A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME) by C. Mathison, C. Mathison, E. J. Burke, G. Munday, C. D. Jones, C. D. Jones, C. J. Smith, C. J. Smith, C. J. Smith, C. J. Smith, N. J. Steinert, N. J. Steinert, A. J. Wiltshire, A. J. Wiltshire, C. Huntingford, E. Kovacs, L. K. Gohar, R. M. Varney, D. McNeall, D. McNeall

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Identification of Gas-Water Two-Phase Flow Patterns in Horizontal Wells of Shale Gas Reservoirs Based on Production Logging Data by Xiaoyun Zhao, Hongwei Song, Mingxing Wang, Xinlei Shi

“…Secondly, a series of production logging instruments including CAT instrument was used to conduct experimental research on gas-water two-phase flow under different flow conditions, and the measured values of each CAT probe were extracted to reflect the local holdup under different flow patterns. …”
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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

“…Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. …”
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Synergistic use of satellite, legacy, and in situ data to predict spatio-temporal patterns of the invasive Lantana camara in a savannah ecosystem by Lilly Theresa Schell, Emma Evers, Sarah Schönbrodt-Stitt, Konstantin Müller, Maximilian Merzdorf, Drew Arthur Bantlin, Insa Otte

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Enhancing Creativity and Validation in Explanatory Deep Learning-Based Symbolic Music Generation: A Hybrid Approach With LSTM and Genetic Algorithms by Ahmad Zainul Fanani, Arry Maulana Syarif, Ika Novita Dewi, Abdul Karim

“…This research proposes an explanatory deep learning-based music generation approach, where the output of a deep learning model is validated through a set of predefined musical rules, with a refinement process applied when inaccuracies are detected. …”
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Cognitive load assessment through EEG: A dataset from arithmetic and Stroop tasksMendeley Data by Ali Nirabi, Faridah Abd Rahman, Mohamed Hadi Habaebi, Khairul Azami Sidek, Siti Yusoff

“…The proposed dataset serves as a valuable resource for advancing research in the realm of brain-computer interfaces and offers insights into identifying EEG patterns associated with stress.The proposed dataset serves as a valuable resource for researchers, offering insights into identifying EEG patterns that correlate with different stress states. …”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

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Linking patterns to processes: Using hunting bag data to classify raccoon (Procyon lotor) invasion stages in Germany since the 2000s by Sarah Cunze, Gaby Schneider, Norbert Peter, Sven Klimpel

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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…This approach is considered a hybrid of optimization algorithms and classifiers in machine learning. Binary Whale Optimization (BWO) and Binary Grey Wolf Optimization (BGWO) algorithms are used for feature selection and K-Nearest Neighbor (KNN) and Fuzzy K-Nearest Neighbor (FKNN) algorithms are applied as the classifiers in this research. …”
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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

“…Next, the main techniques in sequential recommendation are summarized in detail, including: traditional methods based on Markov chains, which model user behavior sequences by relying on state transition probabilities; deep learning-driven methods, which utilize neural network models to capture long-term dependencies and complex patterns; hybrid models, which combine multiple algorithms to enhance the accuracy and robustness of recommendation systems; and emerging methods based on large language models, which improve the understanding of user behavior and recommendation content through the integration of pre-trained large language models. …”
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Research on Methods for the Recognition of Ship Lights and the Autonomous Determination of the Types of Approaching Vessels by Xiangyu Gao, Yuelin Zhao

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A comparative structural module study of Balla Lompoa and Ba’anjung by Fermanto Lianto, Denny Husin, Rudy Trisno

“…The steps are 1) Architectural redrawing, 2) Module extraction, and 3) Algorithm pattern. The output is an architectural algorithm as the patterns. …”
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Research on Grouting Dynamic Monitoring Based on Borehole–Tunnel Joint Resistivity Method by Cheng Wang, Lei Zhou, Liangjun Yan, Bofan Li

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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

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AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

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Generation and Classification of Novel Segmented Control Charts (SCC) Based on Hu’s Invariant Moments and the K-Means Algorithm by Roberto Baeza-Serrato

“…Finally, a grouping is made to classify the samples in clear and simple language as excellent, good, or regular using the k-means algorithm. The results visually display the total pattern behavior of the samples and their interpretation when they are classified intelligently. …”
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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

“…To address these limitations, this research proposes three innovative hybrid models that integrate metaheuristic optimization algorithms with support vector machine (SVM): multi-verse optimizer-SVM (MVO-SVM), salp swarm algorithm-SVM (SSA-SVM), and Harris’s Hawk optimization-SVM (HHO-SVM). …”
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Assessing the spatial-temporal performance of machine learning in predicting grapevine water status from Landsat 8 imagery via block-out and date-out cross-validation by Eve Laroche-Pinel, Vincenzo Cianciola, Khushwinder Singh, Gaetano A. Vivaldi, Luca Brillante

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Cluster Sort: A Novel Hybrid Approach to Efficient In-Place Sorting Using Data Clustering by Mohit Subramaniam, Tanya Tripathi, Omkumar Chandraumakantham

“…This research work introduces a clustering-based in-place sorting algorithm, cluster sort. …”
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Microcontroller-Driven Battery Management in Hybrid Energy Systems: A Systematic Review of Applications, Control Strategies, and Emerging Trends by Ripfumelo Humphrey Malele, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…The study further identifies patterns, themes, and emerging trends in the literature, highlights research gaps, and proposes directions for future work in this field.…”
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