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

“…As contemporary critics have shown, John Ruskin’s lifelong interest in geology not only provided him with a unique understanding of the mountain as a painting subject but also allowed him to develop an idiosyncratic theory of perception where movement and salience prevail – a theory he then applied to his often memorable prose.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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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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Evaluating and Optimizing MySejahtera App Analytics for Sustainable Digital Government Services by Adawiyah Ashar, Nur Fazidah Elias, Ruzzakiah Jenal, Meng Chun Lam, Maheshwara Rao Appannan, Siti Aishah Iskandar

“…This study undertakes a comprehensive evaluation of MySejahtera through the meticulous analysis of application analytics and user feedback, aiming to assess its operational efficacy, patterns of user engagement, and performance indicators. …”
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Deep-CABPred: Deep learning model for predicting functional chlorophyll a-b binding proteins in trait-based plant ecology using hybrid embedding with semi-normalized temporal convo... by Farman Ali, Raed Alsini, Tamim Alkhalifah, Fahad Alturise, Wajdi Alghamdi, Majdi Khalid

“…Our approach leverages a combination of advanced feature embedding techniques. We extract multi-source protein information from primary sequences, employing FastText for discriminative subword-level patterns and ProtBERT (a protein large language model) for contextualized sequential features. …”
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Fluid Equation-Based and Data-Driven Simulation of Special Effects Animation by Yujuan Deng

“…Finally, the 3D motion trajectory of the point feature object and the motion pattern at a certain moment are shown, and the method in this paper obtains more ideal results, which proves the effectiveness of the method.…”
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An exploration of the research framework for the coupling of farmland and rural residential land use transition under the perspective of spatial production by LI Jingjing, FENG Yingbin, GU Lei, LI Yue

“…Overall, the research framework of “feature identification - pattern judgment - mechanism response” for the coupling of farmland and rural residential land use transition from the perspective of spatial production was formed. …”
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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

“…Improving soil health evaluation and crop output forecasting are essential for developing sustainable agricultural methods. By applying data-driven insights, farmers may optimize resources, increase productivity, and promote environmental sustainability. …”
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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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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Handling Sensor Faults in Hydroponics: A Deep Learning Imputation Technique for Accurate Tomato Yield Prediction by Viji Venugopal, Paresh Tanna, Ramesh Karnati

“…DLPIM introduces a feature encoder-based generator with a 4-headed self-attention mechanism and a Crop Growth Rate (CGR) guided temporal processor to capture complex time-series patterns while maintaining physiological consistency. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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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

“…Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. 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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Transcriptome analysis reveals the sex-switching mechanism of juvenile hermaphroditism in silver pomfret (Pampus argenteus) by Yaya Li, Jiabao Hu, Chongyang Wang, Man Zhang, Youyi Zhang, Yuanbo Li, Mengke Tang, Chunlai Qin, Zukang Feng, Shanliang Xu, Xiaojun Yan, Xubo Wang, Haimin Chen, Yajun Wang

“…Heatmaps were generated to visualize gene expression patterns across developmental stages and samples. Sex hormones concentrations were measured using commercial assay kits to assess their role in gonadal differentiation. …”
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Imitating Human Go Players via Vision Transformer by Yu-Heng Hsieh, Chen-Chun Kao, Shyan-Ming Yuan

“…Using a dataset from the KGS Go server, our ViT-based model achieves 51.49% accuracy in predicting expert moves with a simple feature set. Comparative analysis against CNN-based models highlights the ViT’s superior performance in capturing patterns and replicating expert strategies. …”
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Application of Deep Learning Algorithm for Web Shell Detection in Web Application Security System by Rezky Yuranda, Edi Surya Negara

“…Through preprocessing techniques such as opcode extraction and feature selection, useful pattern recognition for web shell detection is achieved. …”
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Living with Credit and Installment Plans: The Situation in a Southern Kazakhstan by Murat O. Nassimov

“…In modern developed economies, the prevalence of credit usage and installment plans has become a notable feature of consumer behavior. …”
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Identifying trade-offs and synergies among land use functions using an XGBoost-SHAP model: A case study of Kunming, China by Kun Li, Junsan Zhao, Yongping Li, Yilin Lin

“…Finally, a self-organizing feature mapping network (SOM) was developed to identify LUF clusters. …”
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Smart wearable sensor-based model for monitoring medication adherence using sheep flock optimization algorithm-attention-based bidirectional long short-term memory (SFOA-Bi-LSTM) by Yasser Alatawi, Palanisamy Amirthalingam, Narmatha Chellamani, Manimurugan Shanmuganathan, Mostafa A. Sayed Ali, Saleh Fahad Alqifari, Vasudevan Mani, Muralikrishnan Dhanasekaran, Abdulelah Saeed Alqahtani, Ahmed Aljabri

“…Due to its ability to continuously monitor a patient's MA behavior, the recent focus on sensor technology for MA monitoring is a promising development. The primary objective of this research is to implement sensor devices/smart wearables powered by advanced deep learning (DL) techniques to evaluate complex data patterns effectively and make accurate predictions. …”
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Deep Learning for the Early Diagnosis of Candidemia by Daniele Roberto Giacobbe, Sabrina Guastavino, Anna Razzetta, Cristina Marelli, Sara Mora, Chiara Russo, Giorgia Brucci, Alessandro Limongelli, Antonio Vena, Malgorzata Mikulska, Alessio Signori, Antonio Di Biagio, Anna Marchese, Ylenia Murgia, Marco Muccio, Nicola Rosso, Michele Piana, Mauro Giacomini, Cristina Campi, Matteo Bassetti

“…Further exploration of candidemia prediction using laboratory features through machine learning techniques remains a promising area of research, serving as a valuable complement to the development of large-scale models that also incorporate clinical features.…”
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