Machine learning aids in the discovery of efficient corrosion inhibitor molecules by Haiyan GONG, Lingwei MA, Dawei ZHANG

“…Specifically, ML models can extract key information and construct predictive models through feature extraction and pattern recognition using existing data. …”
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Multivariate analysis of energy and solar performance across Dubai: insights from MANOVA and cluster analysis by Mayyas Alsalman, Marwa Alraeesi, Ayman Alzaatreh

“…Abstract Solar energy adoption became a key component in achieving the UAE’s sustainability strategy, featuring the abundance of solar irradiance in the region that tends to reduce the dependence on carbon-based resources through solar energy integration. …”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…A data set of average feature counts has been executed through a Splunk search command in 1-min intervals. …”
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Methodological approach to evaluation the level of a university organizational culture by E. V. Kotov, Yu. O. Roschina

“…The purpose of the study was to identify the features and patterns in the formation and implementation of the organizational culture of the university of humanitarian profile. …”
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A Turkish Word Frequency Tool: LexiTR Frequency by Taner Sezer, Özay Karadağ

“…Word frequency plays a critical role in understanding the characteristics and usage patterns of a word. This study introduces the "Turkish Word Frequency Tool" (TWFT), developed as part of the LexiTR Project, along with its features. …”
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Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model by Klavdia Zemlianova, Amitabha Bose, John Rinzel

“…Abstract Despite music’s omnipresence, the specific neural mechanisms responsible for perceiving and anticipating temporal patterns in music are unknown. To study potential mechanisms for keeping time in rhythmic contexts, we train a biologically constrained RNN, with excitatory (E) and inhibitory (I) units, on seven different stimulus tempos (2–8 Hz) on a synchronization and continuation task, a standard experimental paradigm. …”
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Monitoring irrigated dryland in China from 2000 to 2015 by integrating time series vegetation indices and environmental factors by Zijuan Zhu, Lijun Zuo, Zengxiang Zhang, Yun Shao, Haijun Bao, Xiaoli Zhao, Xiao Wang, Shunguang Hu, Sisi Yu, Tianshi Pan, Ziyuan Liu

“…Meanwhile changes of features were employed to identify changes of irrigated dryland. …”
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Advancing sedimentation modeling in large reservoir systems: Insights from multi-scale process coupling and machine learning by Yuning Tan, Huaixiang Liu, Yongjun Lu, Zhili Wang, Wenjie Li

“…Random Forest outperformed XGBoost, Support Vector Regression, and Artificial Neural Network, demonstrating the most robust performance and the clearest feature attribution. Our climate scenario simulations revealed uneven sedimentation patterns and projected declining sedimentation rates over the next 30 years. …”
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Optimizing Sensitivity in Machine Learning Models for Pediatric Post-operative Kyphosis Prediction by Raja Ayu Mahessya, Dian Eka Putra, Rostam Ahmad Efendi, Rayendra, Rozi Meri, Riyan Ikhbal Salam, Dedi Mardianto, Ikhsan, Ismael, Arif Rizki Marsa

“…This study demonstrates the capacity of decision tree models to extract clinically meaningful patterns from small, imbalanced surgical datasets that elude conventional statistical approaches.…”
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Predicting female football outcomes by machine learning: behavioural analysis of goals as high stress events by Aratz Olaizola, Ibai Errekagorri, Elsa Fernández, Julen Castellano, John Suckling, Karmele Lopez-de-Ipina

“…We applied a comprehensive approach that integrates spatiotemporal and behavioural data during the transitional period following goals focusing on team dynamics, including chaotic and collective behavioural analysis with entropy and fractality, spatial area, movement trajectories, and locomotor patterns. Several well-established ML models and feature extraction techniques were deployed with overall good performance of greater than 70% accuracy, with some specific methodology combinations have superior performance. …”
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A New Two‐Stage Probabilistic Remaining Useful Life Prediction Method for Wind Turbines by Weifei Hu, Xuewei Zhou, Qing Jiao, Feng Zhao, Ning Tang, Ke Li, Zili Wang

“…However, the degradation data of WTs exhibit complex patterns and are often interfered with by noise, making it challenging to extract meaningful features from the data. …”
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Improving ICESat-2 photon classification and tree height estimation using Moran's I and machine learning by Mei-Kuei Lu, Sorin Popescu, Lonesome Malambo

“…Random Forest models were developed and compared, with one model incorporating Moran's I to capture spatial patterns. …”
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Advances in Bract Coloration: Diversity, Pigment Synthesis, and Regulatory Mechanisms in Ornamental Plants by Xiaoyang Li, Yang Liu, Zhiquan Cai, Yiwei Zhou

“…While previous research has primarily focused on floral pigmentation, studies on bract coloration—particularly in species where bracts serve as the primary ornamental feature—have received less attention until recent advances. …”
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An Explainable Hybrid CNN–Transformer Architecture for Visual Malware Classification by Mohammed Alshomrani, Aiiad Albeshri, Abdulaziz A. Alsulami, Badraddin Alturki

“…Visual malware classification, which transforms malware binaries into grayscale images, has emerged as a promising alternative for recognizing patterns in malicious code. This study presents a hybrid deep learning architecture that combines the local feature extraction capabilities of ConvNeXt-Tiny (a CNN-based model) with the global context modeling of the Swin Transformer. …”
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Automated multi-class MRI brain tumor classification and segmentation using deformable attention and saliency mapping by Erfan Zarenia, Amirhossein Akhlaghi Far, Khosro Rezaee

“…In this research, we present a novel framework that enables both tumor classification and post-classification diagnostic feature extraction, allowing for the first-time classification of multiple tumor types. …”
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Graph convolutional neural networks improved target-specific scoring functions for cGAS and kRAS in virtual screening by Bo Wang, Muhammad Junaid, Wenjin Li

“…This indicates that the graph convolutional network can be generalized to the prediction of heterogeneous data based on the complex patterns of molecular protein binding that have been learned. …”
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Impact and elastic modulus of coal mining on terrestrial ecosystems by Jihong Dong, Wenting Dai, Jiren Xu, Hui Zhang, Yunpeng Li, Fei Xie

“…Furthermore, it delineates the life cycle stages and distinctive features of the five principal open-pit coal mines. …”
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A PatchTST-GRU based heterogeneous seq2seq model with numerical weather prediction refinement for multi-step wind power forecasting by Shiwei Xu, Yongjun Wang, Xinglei Xu, Guang Shi, He Huang, Yingya Zheng

“…Furthermore, a fusion attention mechanism with asymmetric query-key-value matrices is introduced to dynamically fuse historical wind power temporal patterns with refined NWP features, optimizing prediction outcomes. …”
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Clinical and pathological analysis of primary well-differentiated neuroendocrine tumors in the kidney- a case series by Dan Yuan, Jing Wu, Dong-Yue Wang, Jin-Jing Wang

“…Abstract Objective To investigate the clinicopathological characteristics and key diagnostic/therapeutic features of primary well-differentiated neuroendocrine tumors (WDNET) of the kidney. …”
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De l’hypothese de Sapir-Whorf au prototype : sources et genese de la theorie d’Eleanor Rosch. by Jean-Michel Fortis

“…This paper deals with the origins of the theory of categorization developed by Eleanor Rosch in the 1970s. It is divided into two parts. …”
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