La topographie selon Ruskin : saillance du visible et du lisible dans Modern Painters by Laurence Roussillon-Constanty

“…Applying the salience model to Ruskin’s prose might therefore prove a new way to uncover some of the more elusive and distinctive features of his writing.…”
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Fingernail analysis management system using microscopy sensor and blockchain technology by Shih Hsiung Lee, Chu Sing Yang

“…Histogram of oriented gradients and local binary patterns are used to capture the characteristic value. …”
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Analyzing the Application of Machine Learning in Anemia Prediction by Li Yuxi

“…This paper examines decision trees, random forests, support x'ector machines, and neural networks. emphasizing their efficacy in identifying patterns and risk factors associated with anemia. Obstacles such as data quality, feature selection, and model interpretability continue to hinder clinical adoption. …”
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Comparative Investigation of Machine Learning and Deep Learning Approaches for Air Quality Prediction by Zhang Borui

“…Deep learning captures nonlinear patterns more effectively but lacks interpretability and requires more data. …”
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Improving stock price forecasting with M-A-BiLSTM: a novel approach by Zihan Liu

“…This model is designed to enhance feature selection capabilities and capture nonlinear patterns in financial time series. …”
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Statistical Mechanics of Directed Networks by Marián Boguñá, M. Ángeles Serrano

“…Robust null models are crucial for identifying meaningful patterns in these representations, yet designing models that preserve key features remains a significant challenge. …”
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Deterministic chaos in modulated multi-cell drifts of localized lower-hybrid oscillations excited by high-frequency waves in the ionosphere by T. B. Leyser

“…<p>The prominent broad upshifted maximum (BUM) feature in electromagnetic emissions stimulated by powerful high-frequency radio waves in the ionosphere exhibits an exponential spectrum for pump frequencies near a harmonic of the ionospheric electron gyro frequency. …”
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Development of anticipatory coarticulation of /u/ in typically Malayalam speaking children in the age range of 3-6 years by Litna A. Varghese

“…Studies in the past have shown that children have more coarticulation than adults; adults have more coarticulation than children; children and adult have similar coarticulatory patterns. Malayalam is a Dravidian language with extra lip rounding feature and also with five place of nasal articulation. …”
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Of Ruskinian Topography: Visible and Legible Salience in Modern Painters by Laurence Roussillon-Constanty

“…At first sight, salience is one feature of landscape that one can easily visually apprehend but much less easily account for in prose writing. …”
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Direct-Write Ion Beam Lithography by Alexandra Joshi-Imre, Sven Bauerdick

“…Indeed, the capability of easily creating three-dimensional patterns and shaping objects by milling and deposition is probably the most recognized feature of ion beam lithography (IBL) and micromachining. …”
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Dermoscopy of kaposiform hemangioendothelioma: a case report by Filomena Barbato, Maria Maddalena Nicoletti, Gaetano Licata, Eugenia Veronica Di Brizzi, Giuseppe Argenziano, Caterina Mariarosaria Giorgio

“…The findings contribute to the understanding of dermoscopic patterns in KHE, highlighting its potential role in early diagnosis. …”
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Federated Learning for Privacy-Preserving Employee Performance Analytics by Jay Barach

“…The framework integrates feature-level and instance-level attention to model complex workforce patterns, applies differential privacy through gradient masking to ensure compliance with data protection regulations, and enhances interpretability using local SHAP and LIME explanations. …”
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Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao, Jinwei Sun

“…This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), (2) a feature-optimized XGBoost variant incorporating Pearson correlation analysis (XGBoost2), and (3) an enhanced CPSO-XGBoost model integrating hybrid particle swarm optimization with dual mechanisms of binary feature selection and parameter tuning. …”
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AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder by Yunseung Lee, Pilsung Kang

“…Subsequently, the feature map, which has been transformed into three dimensions, is used to perform decoding. …”
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Enhancing LoRa-Based Outdoor Localization Accuracy Using Machine Learning by Nur Kelesoglu, Marzena Halama, Anna Strzoda

“…We further propose a Hybrid Model that combines convolutional feature extraction with gradient-boosted regression. …”
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Ultrafast Laser High-Aspect-Ratio Extreme Nanostructuring of Glass beyond λ/100 by Guodong Zhang, Anton Rudenko, Razvan Stoian, Guanghua Cheng

“…The ultimate feature size is key in ultrafast laser material processing. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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CINNAMON: A hybrid approach to change point detection and parameter estimation in single-particle tracking data by Jakub Malinowski, Marcin Kostrzewa, Michał Balcerek, Weronika Tomczuk, Janusz Szwabiński

“…The method offers a high level of interpretability due to its analytical and feature-based components. A potential use of features from topological data analysis is also discussed.…”
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An Inverted Transformer Framework for Aviation Trajectory Prediction with Multi-Flight Mode Fusion by Gaoyong Lu, Yang Ou, Wei Li, Xinyu Zeng, Ziyang Zhang, Dongcheng Huang, Igor Kotenko

“…This framework leverages multi-flight inputs and inverted data processing to enrich feature representation and optimize the modeling of multi-variate time series. …”
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Machine learning-based prediction of optimal antenatal care utilization among reproductive women in Nigeria by Jamilu Sani, Adeyemi Oluwagbemiga, Mohamed Mustaf Ahmed

“…After data preprocessing and feature selection, six supervised ML algorithms—Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Decision Tree, Random Forest, and XGBoost—were applied using Python 3.9. …”
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