Dual-Modal Approach for Ship Detection: Fusing Synthetic Aperture Radar and Optical Satellite Imagery by Mahmoud Ahmed, Naser El-Sheimy, Henry Leung

“…This framework incorporates a detection system for optical images that utilizes Contrast Limited Adaptive Histogram Equalization (CLAHE) in combination with the YOLOv7 model to improve accuracy and processing speed. For SAR images, a customized Detection Transformer model, SAR-EDT, integrates advanced denoising algorithms and optimized pooling configurations. …”
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Village-level climate and weather variability, mediated by village-level crop yield, is associated with linear growth in children in Uganda by Vernon M Chinchilli, Paddy Ssentongo, Djibril M Ba, Claudio Fronterre

“…Normalised rainfall anomaly and total precipitation were derived from the African Rainfall Estimation Algorithm Version 2 product. Linear regression models were used to associate total annual precipitation and anomalies with height-for-age z-scores and to explore the mediating role of crop yield qualitatively. …”
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Digitalization of Processes of Small and Average Business by A. V. Polyanin, Yu. P. Soboleva, V. V. Tarnovskiy

“…The relevant national project is implemented within the framework of five federal projects aimed at improving the conditions of entrepreneurship, access of business entities to financial resources, acceleration of business entities, popularization of entrepreneurship, and development of rural cooperation. …”
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SpecTE: Parameter Estimation for LAMOST Low-resolution Stellar Spectra Based on Denoising Pretraining by Xirong Zhao, Xiangru Li, Hui Li, Xianqi Liu

“…The estimated stellar catalog, code, pretrained model, and experimental data are released online for astronomical exploration and algorithm research.…”
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Using individual tractor wheel drive through electric traction by А. V. Bizhaev, S. M. Vetrova, A. S. Barchukova, N. S. Krivyh

“…The model proves to be applicable up to a slip limit of 30 percent. …”
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Analysis of Congestion-Propagation Time-Lag Characteristics in Air Route Networks Based on Multi-Channel Attention DSNG-BiLSTM by Yue Lv, Yong Tian, Xiao Huang, Haifeng Huang, Bo Zhi, Jiangchen Li

“…First, to account for the interdependency across segments in air route networks, we construct a point–line congestion state assessment model and introduce the FCM-WBO algorithm for precise congestion state identification. …”
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A framework for scalable ambient air pollution concentration estimation by Liam J. Berrisford, Lucy S. Neal, Helen J. Buttery, Benjamin R. Evans, Ronaldo Menezes

“…The machine learning framework used is LightGBM, a gradient boosting algorithm based on decision trees, for efficient and scalable modeling. …”
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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
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An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…Crow Search Optimization (CSO) and fractional calculus are used to create an optimal solution in the proposed crow search fractional calculus optimization (CSFCO) algorithm for deep learning. CSO is inspired by the intelligent foraging behavior of crows, and when combined with fractional calculus, it provides a robust optimization framework that improves the accuracy and efficiency of the AI model. …”
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Experimental and Numerical Investigation on the Influence of the Rate of Injection (Roi) on Engine Performance for B100 Fuel Control Strategy in Diesel Engines by Moïse Ligan Noukpo, Claude Valery Ngayihi Abbe, Joseph Nkongho Anyi, Dieudonné Essola, Cyrille Mezoue, Ruben Mouangue, Robert Nzengwa

“…This work proposes a fuel control strategy and methodology based on diesel engine operating data obtained from an experimentally designed rate of injection model (ROI) at different injection pressures and a jet and spray droplet distribution validated a two-zone model. …”
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Comprehensive Quantitative Analysis of Coal-Based Liquids by Mask R-CNN-Assisted Two-Dimensional Gas Chromatography by Huan-Huan Fan, Xiang-Ling Wang, Jie Feng, Wen-Ying Li

“…Applying DL to analyze chromatograms improves analysis efficiency and provides a new method for analyzing GC × GC chromatograms, which is important for fast and accurate analysis.…”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The Lung-PET-CT-Dx public dataset was used for the model training and evaluation. The performance of the You Only Look Once (YOLO) series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer detection and classification. …”
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Design and accuracy evaluation of AI orthognathic surgery plates by LIU Zhikai, XU Chunwei, ZHU Zhaokun, LIU Yao, LUO En

“…[Methods:] This research established an AI algorithm for orthognathic surgical splints and obtained the available automatic design program. …”
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Direct Estimation of Forest Aboveground Biomass from UAV LiDAR and RGB Observations in Forest Stands with Various Tree Densities by Kangyu So, Jenny Chau, Sean Rudd, Derek T. Robinson, Jiaxin Chen, Dominic Cyr, Alemu Gonsamo

“…Our results show that using an unsupervised LiDAR-only algorithm for tree crown delineation alongside a self-supervised RGB deep learning model trained on LiDAR-derived annotations leads to an 18% improvement in AGB estimation accuracy. …”
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Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study by Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson

“…Eighty percent (80%) of the data was used for model development and 20% for model validation. Results All ML models showed better performance than RETTS-A and NEWS2 with respect to all evaluated performance metrics. …”
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Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning by Feng Lu, Yingying Liu, Zhen Chen, Shuning Chen, Weidong Liang, Fuzhou Hua, Maolin Zhong, Lifeng Wang

“…A total of 113 diagnostic models were developed through 12 machine learning algorithms, with the optimal model, “Lasso + Stepglm[both],” featuring six genes: Abca1, Cdh1, Glipr1, Glt8d2, Il10ra, and Pde5a. …”
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AI-Based Ransomware Detection: A Comprehensive Review by Jannatul Ferdous, Rafiqul Islam, Arash Mahboubi, Md Zahidul Islam

“…This study contributes significantly to the development of a systematic evaluation framework that evaluates each component of the AI-based detection model framework using specific criteria and methodologies and analyzes how various AI algorithms respond to different ransomware attacks, thereby providing insights for more effective and robust detection methods. …”
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Android Malware Category and Family Identification Using Parallel Machine Learning by Ahmed Hashem El Fiky, Mohamed Ashraf Madkour, Ayman El Shenawy

“…The paper ex-periments with many machine learning algorithms and compares the proposed model with the most recent related work.  …”
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High‐Precision Prediction of Ionospheric TEC in the China Region Based on CMONOC High‐Resolution Data and an Auxiliary Attention Temporal Convolutional Network by Jianghe Chen, Pan Xiong, Haochen Wu, Xiaoran Zhang, Xuemin Zhang, Rongzi Chai, Ting Zhang, Kaixin Wang, Chaoyu Wang

“…At the data level, a non‐integrated spherical harmonic model and Differential Code Bias correction method are employed to significantly reduce interpolation errors and improve model accuracy. …”
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Unlabeled-Data-Enhanced Tool Remaining Useful Life Prediction Based on Graph Neural Network by Dingli Guo, Honggen Zhou, Li Sun, Guochao Li

“…Since multiple sensors are frequently used to simultaneously collect cutting data, this paper uses a graph neural network (GNN) for multi-sensor data fusion, extracting more useful information from the data to improve unlabeled data enhancement. Through multiple sets of comparative experiments and validation, the proposed method effectively enhances the accuracy and generalization capability of the RUL prediction model for cutting tools by utilizing unlabeled data.…”
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