Enhancing hand-drawn diagram recognition through the integration of machine learning and deep learning techniques by Vanita Agrawal, MVV Prasad Kantipudi, Jayant Jagtap

“…This research proposes improvised methods such as Fossum Soergel k-means clustering, morphological Canny Bessel radial basis contour shape factor, Fisher kernel k-nearest neighbor, sing-scurve fuzzy rule generation, and wide context faster regional convolutional neural network to enhance the system’s performance. The system’s performance is evaluated by experimentation with benchmark datasets of hand-drawn flowcharts, finite automata, and business process models. …”
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Crystal structure map for materials classification and modeling by Tamio Oguchi

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Spatial-temporal baseline study of nutrients and trace elements characterization of a large tropical transition system in West Africa by Celso Paulo, João A. Carreiras, Susanne Tanner, Carmen Van-Dúnem dos Santos, Vanessa F. Fonseca, Bernardo Duarte

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Deep learning-based multi-omics model to predict nasopharyngeal necrosis of re-irradiation for recurrent nasopharyngeal carcinoma by Xingwang Gao, Xingwang Gao, Xingwang Gao, Yinglin Peng, Shanfu Lu, Yuhan An, Meining Chen, Jun Zhang, Runda Huang, Yiran Wang, Zhenyu Qi, Yao Lu, Chong Zhao, Xiaowu Deng, Jingjing Miao, Yimei Liu

“…The performance and prediction accuracy of each deep learning network model were then evaluated.ResultsThirty-two features correlated with necrosis of rNPC. …”
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Quality of Service Routing in Manet Using a Hybrid Intelligent Algorithm Inspired by Cuckoo Search by S. Rajalakshmi, R. Maguteeswaran

“…A hybrid computational intelligent algorithm is proposed by integrating the salient features of two different heuristic techniques to solve a multiconstrained Quality of Service Routing (QoSR) problem in Mobile Ad Hoc Networks (MANETs) is presented. …”
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Yuri Borko – a Founder of European Integration Studies in Russia by O.V. Butorina

“…His reasoning about universal and specific features of the EU experience proves seminal for the national research community. …”
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Advancements in image classification for environmental monitoring using AI by Jinjing Zhu, Ling Li

“…Spatial and channel attention mechanisms are incorporated to dynamically adjust feature importance, allowing the model to focus on key visual information while minimizing noise.In addition to the network architecture, we propose the Adaptive Environmental Training Strategy (AETS), a robust training framework designed to improve model generalization across diverse environmental datasets. …”
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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…Underwater photogrammetry is challenged by image degradation caused by water absorption and scattering, which negatively impacts feature detection and 3D reconstruction quality. This study aims to evaluate the effectiveness of a Feedforward Neural Network-based colour correction method designed to enhance underwater image quality, thereby improving feature matching and subsequent 3D reconstruction processes. …”
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Eagle-YOLOv8: UAV Object Detection Inspired by the Eagle-Eye Vision System by Dianwei Wang, Zehao Gao, Jie Fang, Yuanqing Li, Zhijie Xu

“…Second, we propose a feature weight fusion network inspired by the double field of view characteristics of eagle eye. …”
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Public Database-based Study to Explore the Expression and Role of DDB1 
in Lung Adenocarcinoma by Xinkai ZOU, Ziyi HE, Yanfei ZHANG, Yi HU, Xiaomin WANG, Zhongjie WU

“…Methods The expression, clinicopathological features and prognosis of DDB1 in LUAD were analysed using databases such as UALCAN, Kaplan-Meier Plotter and GEPIA; The interaction network and enriched functional pathways were constructed by GeneMANIA and Metascape; the correlation between DDB1 and immune cells by combining with TISIDB infiltration was evaluated, and the clustering results of cell subtypes and the expression of DDB1 in different immune cell subpopulations were analysed by single-cell sequencing; finally, tissue microarrays were used to further verify the expression and prognostic value of DDB1 in LUAD. …”
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Exploring multidimensional brain mechanisms in robot-assisted surgical simulation by Haoxin Cui, Yujing Liang, Fankai Sun, Desheng Li, Xiangqing Wang, Rong Wang, Nan Zheng

“…Graph theoretical analyses further highlighted differences in network organization, with higher-level surgeons achieving a balanced interplay between local specialization and global integration of brain networks. …”
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Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security by Mateo Mejia-Herrera, Juan Botero-Valencia, José Ortega, Ruber Hernández-García

“…Its compatibility with LoRa or LoRaWAN networks enables long-range communication, while solar-powered operation reduces environmental impact. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Immune response characteristics and functional enrichment patterns were further evaluated in these cohorts.ResultsOur study delved into disulfidptosis in LUAD through a series of analyses: scRNA-seq data processing, WGCNA analysis, construction of a prognostic model, evaluation of clinical features and risk, enrichment analysis, mutation landscape assessment, and examination of the tumor microenvironment. …”
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Remodeling of the extracellular matrix in human uveal melanoma by А.Yu. Shatruk, N.P. Bgatova, V.R. Moon, A.V. Yeremina, A.N. Trunov, V.V. Chernykh, Yu.S. Taskaeva

“…A key component of the tumor microenvironment is the extracellular matrix (ECM) – a network of macromolecules that maintain the integrity of tissues and organs. …”
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GPU Acceleration for FHEW/TFHE Bootstrapping by Yu Xiao, Feng-Hao Liu, Yu-Te Ku, Ming-Chien Ho, Chih-Fan Hsu, Ming-Ching Chang, Shih-Hao Hung, Wei-Chao Chen

“…Furthermore, compared to the SoTA GPU solution TFHE-rs, we achieve a maximum speedup of 1.69x in AND gate evaluation. Finally, we benchmark several private machine learning applications, showing real-time solutions for (1) encrypted neural network inference for MNIST in 0.04 seconds per image, which is the fastest implementation to our knowledge.(2) private decision trees in 0.38 seconds for Iris dataset, where as prior 16 cores CPU implementation (Lu et al., IEEE S&P 2021) required 1.87 seconds; These results highlight the effectiveness and efficiency of our GPU-acceleration in real-world applications. …”
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Transfer learning and single-polarized SAR image preprocessing for oil spill detection by Nataliia Kussul, Yevhenii Salii, Volodymyr Kuzin, Bohdan Yailymov, Andrii Shelestov

“…The preprocessing technique normalizes SAR intensity values and encodes extracted features into RGB channels.Through an experiment, we have shown that a combination of the LinkNet with an EfficientNet-B4 is superior to pairs of other well-known architectures and encoders.Quantitative evaluation revealed a significant improvement in F1-score of 0.064 compared to traditional dB-scale preprocessing methods. …”
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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

“…Furthermore, fusion models such as Inception-V3 and EfficientNet-B0 perform the feature extraction. Moreover, the hybrid of convolutional neural network and bidirectional long short-term memory (CNN-BiLSTM) model is employed for the brain stroke classification process. …”
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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…This network integrates feature maps from different levels to detect isolation switches at multiple scales in monitoring scenarios. …”
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A Comparative Study of Lesion-Centered and Severity-Based Approaches to Diabetic Retinopathy Classification: Improving Interpretability and Performance by Gang-Min Park, Ji-Hoon Moon, Ho-Gil Jung

“…Transfer learning from NMC to APTOS notably improved severity classification, achieving performance gains of 15.2% in mild cases and 66.3% in severe cases through feature fusion using Bidirectional Feature Pyramid Network (BiFPN) and Feature Pyramid Network (FPN). …”
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Am I attached? A patient-partnered approach to creating infographics about attachment to primary care in Ontario, Canada by Maggie MacNeil, Aya Tagami, Peter Sheffield, Vivian R. Ramsden, Joan Barker, Jennifer Boyle, Clare Cruickshank, Eliot Frymire, Richard H. Glazier, Anita Gombos Hill, Michael E. Green, Mary Huang, Marijke Jurriaans, Caron Leid, Melissa McCallum, Sarah Precious, Jo-Ann Stans, Julie Vizza, Murray Walz, Sue Wilkins, Rebecca Ganann

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