Multi-task advanced convolutional neural network for robust lymphoblastic leukemia diagnosis, classification, and segmentation by Sercan Yalcin, Zuhal Cetin Yalcin, Muhammed Yildirim, Bilal Alatas

“…The proposed framework achieved an accuracy of 0.978, precision of 0.979, recall of 0.967, F1-score of 0.973, specificity of 0.991, Cohen’s kappa of 0.979, and negative predictive value (NPV) of 0.990. These metrics significantly outperform baseline models, highlighting the MTA-CNN’s ability to accurately identify and classify ALL cases. …”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

“…The proposed MFD-YOLO(1.5) model achieves significant progress in detecting personal protective equipment on construction sites, with a substantial reduction in parameter count, making it suitable for deployment on resource-constrained edge devices.…”
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Trends and research networks in greening business: A bibliometric analysis by Dana Kangalakova, Zaira Satpayeva, Makpal Nurkenova, Gulnara Nyussupova

“…The greening of businesses is becoming a priority area of strategic management for companies, considering the growing environmental challenges and the need to move toward sustainable business models. This study aims to identify the historical, evolutionary, spatial, and conceptually scientific landscape of greening businesses through bibliometric analysis. …”
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Infrared Monocular Depth Estimation Based on Radiation Field Detail Enhancement by Rihua Hao, Chao Xu, Chonghao Zhong

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Research on dynamic uplift of contact wires in high-speed railway by TANG Yang

“…This paper aims to study the dynamic behaviors of the pantograph-catenary system for high-speed railway lines, focusing on the overall uplift data of contact wires. To achieve this, models of overhead contact systems (OCS) were established for four typical high-speed railway systems, along with three-degree-of-freedom models with reduction parameters for three types of high-speed pantographs. …”
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Geographic Information Systems and Cartography for a Sustainable World by Andriani Skopeliti, Anastasia Stratigea, Vassilios Krassanakis, Apostolos Lagarias

“…At the heart of the discussion in this SI lies: (i) GIS, a valuable tool and a means for modeling, designing, and analyzing (spatial) data and processes related to the pursuance of sustainability objectives at both local and global scales; and (ii) Cartography as a discipline, which through maps and visualizations can convey the present state. …”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The study highlights the effectiveness of the MLP-NN model in accurately predicting changes in LULC. The model’s exceptional accuracy and proficiency make it a powerful tool for future LULC forecasts. …”
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Spatiotemporal Variability in Wind Turbine Blade Leading Edge Erosion by Sara C. Pryor, Jacob J. Coburn, Rebecca J. Barthelmie

“…To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. …”
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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…CBAM adjusts the importance of each channel and spatial location in the feature maps through operations like global average pooling, maxpooling, and small fully connected neural networks in both channel and spatial attention dimensions. …”
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Deep Time Series Intelligent Framework for Power Data Asset Evaluation by Lihong Ge, Xin Li, Li Wang, Jian Wei, Bo Huang

“…In the evaluation of the complex and rich Solar-Power dataset and Electricity dataset, TSENet achieved significant performance improvements over other state-of-the-art baseline methods.Through the synergistic design of deep convolutional structures and an efficient memory mechanism, it effectively addresses issues such as inadequate modeling of long-term dependencies, insufficient extraction of short-term features, and high prediction volatility, thereby significantly enhancing both the accuracy and robustness of forecasting in power asset evaluation tasks.…”
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Wildlife students as community scientists provide statewide detection data to help non‐invasively monitor Oklahoma bobcats by Nathan J. Proudman, Michelle L. Haynie, Victoria L. Jackson, Jerrod Davis, W. Sue Fairbanks

“…Abstract Community science projects are ideal for collecting species data at large spatial scales and can connect the public with the management and conservation of native wildlife. …”
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On the propeller wake evolution using large eddy simulations and physics-informed space-time decomposition by Zhan Zhang, Peng Sun, Long Pan, Teng Zhao

“…A novel modal analysis methodology, denoted as the physics informed sparsity-promoting dynamic mode decomposition (pi-SPDMD) model, was introduced for the reduction and reconstruction analysis of intricate propeller wake flows, aiming to provide insight into the inherent flow structures spanning diverse temporal and spatial scales. …”
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Supply-Demand Matching Evaluation and Coupling Coordination of Cultural Ecosystem Services in Urban Park Green Spaces by Yang YU, Xian YANG, Xiang LI, Liyuan QIAN, Sixiang ZHOU

“…First, an evaluation indicator system and a supply-demand relationship model encompassing supply potential, supply opportunity, and resident demand dimensions are constructed to analyze the matching relationship and spatial distribution characteristics of CES. …”
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Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds by Joarder Jafor Sadique, Imtiaz Nasim, Ahmed S. Ibrahim

“…Furthermore, we introduce a separate model, the convolutional neural network (CNN) over Riemannian manifolds, which captures geometric relationships between satellites and users by extracting spatial features from the network topology across all links. …”
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Mapping Tropical Forested Wetlands Biomass with LiDAR: A Machine Learning Comparison by Jonathan V. Solórzano, Candelario Peralta-Carreta, J. Alberto Gallardo-Cruz

“…The model’s robustness and uncertainty were evaluated through bootstrapping and spatial prediction across the study area, with higher AGB values concentrated near the main water channels. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…The proposed framework is built upon a hybrid deep neural architecture that integrates convolutional layers (CNN) for spatial representation, bidirectional GRUs for temporal modeling, and multi-head self-attention for long-range dependency learning. …”
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Optimizing Fertilizer Use in Precision Agriculture with GIS and Remote Sensing by Fallah Mohammed Hussein, Ramadan Ghazi Mohamad, Venkatcharyulu S.

“…In the processing stage, spatial analysis is done to discover nutrient and crop health variations which lead to a fertilizer optimization model that allocates specific rates of fertilizer application. …”
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Quantifying Karenia brevis bloom severity and respiratory irritation impact along the shoreline of Southwest Florida. by Richard P Stumpf, Yizhen Li, Barbara Kirkpatrick, R Wayne Litaker, Katherine A Hubbard, Robert D Currier, Katherine Kohler Harrison, Michelle C Tomlinson

“…Both BSI and RI consider spatial extent and temporal evolution of the bloom, and can be updated routinely and used as objective criteria to aid future socioeconomic and scientific studies of K. brevis. …”
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Numerical Simulation of Streaming Discharge Characteristics of Free Metal Particles in SF₆/CF₄ Gas Mixtures Under Highly Heterogeneous Electric Field by Bing Qi, Hui Wang, Chang Liu, Fuyou Teng, Daoxin Yu, Yuxuan Liang, Feihu Wang

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