Advanced Diagnosis of Cardiac and Respiratory Diseases from Chest X-Ray Imagery Using Deep Learning Ensembles by Hemal Nakrani, Essa Q. Shahra, Shadi Basurra, Rasheed Mohammad, Edlira Vakaj, Waheb A. Jabbar

“…Despite the strengths of individual models, the ensemble meta-model achieved the best overall performance, with a Hamming Loss of 0.1408 and consistently higher ROC-AUC values across multiple diseases, demonstrating its superior capability to handle complex classification tasks. This robust ensemble learning framework underscores its potential for reliable and precise disease detection, offering significant improvements over traditional methods. …”
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Advancing the Contemporary Multidisciplinary Heart Valve Team: Update on Priorities for Clinicians and Programs by Sandra B. Lauck, PhD, Connie Clark, MSN, Sophie Offen, MD, PhD, Erin Tang, MSN, Stephanie Sellers, PhD

“…A recalibrated perspective on the key principles guiding the MDT for clinicians and programs offers opportunities to make the most of lessons learned by promoting quality of care and building a VHD collective and culture that can meet patients’ needs along their journey of care while prioritizing a nimble, tailored, efficient, and high-impact approach.…”
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Evaluating pedestrian crossing safety: Implementing and evaluating a convolutional neural network model trained on paired aerial and subjective perspective images by Dylan Russon, Antoine Guennec, Juan Naredo-Turrado, Binbin Xu, Cédric Boussuge, Valérie Battaglia, Benoit Hiron, Emmanuel Lagarde

“…With pedestrian crossings implicated in a significant proportion of vehicle-pedestrian accidents and the French government's initiatives to improve pedestrian safety, there is a pressing need for efficient, large-scale evaluation of pedestrian crossings. …”
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Estimating the Spectral Response of Eight-Band MSFA One-Shot Cameras Using Deep Learning by Pierre Gouton, Kacoutchy Jean Ayikpa, Diarra Mamadou

“…These models learn the complex relationship between 8-band multispectral data from the camera and 31-band multispectral data from the multi-object database, enabling accurate and efficient conversion. …”
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…We suggest using RF due to its ease in model building, computational time, and efficient feature selection for predicting canopy height. …”
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Leveraging Digital Twin for operational resilience in the oil and gas industry by Giovanni Mazzuto, Ilaria Pietrangeli, Marco Ortenzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua

“…Future work: Future improvements will focus on refining the air flow modelling and expanding the dataset to improve predictive performance in extreme conditions providing an efficient anomaly detection system based on the DT prediction.…”
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Context-Aware Markov Sensors and Finite Mixture Models for Adaptive Stochastic Dynamics Analysis of Tourist Behavior by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong, Zhengchun Song

“…The proposed method addresses this limitation by introducing virtual sensors that dynamically detect contextual anomalies and trigger regime switches in real-time. …”
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Edge–Cloud Intelligence for Sustainable Wind Turbine Blade Transportation: Machine-Vision-Driven Safety Monitoring in Renewable Energy Systems by Yajun Wang, Xiaodan Wang, Yihai Wang, Shibiao Fang

“…These risks arise from collision hazards, complex terrain, and the difficulty of real-time monitoring under adverse environmental conditions. …”
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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…Furthermore, the CFOPS-BSBEA technique has the potential to inspire further research in secure cloud computing environments, making the way for the development of more robust and efficient security measures.…”
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Structural and morphological studies of non-covalent functionalization carbon nanotubes wrapped poly(3-hexylthiophene-2,5-diyl) nanocomposites by N. Abdullah, N.M. Nurazzi, I.P. Silverwood, S.K. Matam, S.Z.N. Demon, N.S.N. Sa'aya, N.A. Halim, K.W. Baharin

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A High-Precision Temperature Compensation Method for TMR Weak Current Sensors Based on FPGA by Jie Wu, Ke Zhou, Qingren Jin, Baihua Lu, Zhenhu Jin, Jiamin Chen

“…Tunnel magnetoresistance (TMR) sensors, known for their high sensitivity, efficiency, and compact size, are ideal for detecting weak currents, particularly leakage currents in smart grids. …”
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Evaluation of the Ratio of Spot Tests and Plaque-Forming Activity Tests of Bacteriophages of Prevalent Pathogens by I. M. Pchelin, D. V. Azarov, V. A. Dedik, D. A. Kushnirenko, B. I. Aslanov, A. E. Goncharov, D. A. Lioznov

“…In general, the observation of clear lysis spots on the spot test in most cases indicates bacteriophage replication, which allows us to consider the spot test method as indicative, but requiring subsequent validation by more complex methods characterizing the efficiency of phage replication.…”
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Heptad green metrics and quality by design tool evaluated chromatography method for content determination of Bexagliflozin in formulation product by Satyajit Raj Nethekar, Phani Raja Kanuparthy, Leela Prasad Kowtharapu, Vishnuvardhana Kishore Polisetti, Pankaj Kumar Lahoti, Sreekantha B Jonnalagadda, Naresh Kumar Katari

“…The study created an eco-friendly, rapid, sensitive, cost-efficient, stability-assessing method for analyzing Bexagliflozin in pharmaceuticals using a RP-UPLC approach. …”
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A Study on the Extraction of Satellite Image Information for Two Types of Coastal Fishery Facility Fish Cages and Rafts Influenced by Clouds and Vessels by Ao Chen, Jialu Yu, Junbo Zhang, Gangyi Yu, Rong Wan

“…It is applicable to satellite image classification tasks in complex environments, including influence of clouds and vessels. …”
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Citrus Disease Classification Model Based on Improved ConvNeXt by Jichi Yan, Yongbin Mo, Yannan Yu, Shiqing Dou, Rongfeng Yang

“…Early diagnosis of citrus diseases directly affects the yield and quality of citrus cultivation, and a citrus disease classification model based on improved ConvNeXt is proposed to address the problems of high cost and low efficiency of traditional citrus disease detection methods. …”
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The Optimal Acoustic Measurement Point Selection for UHV Reactors in Substations Based on Equivalent Impedance and Information Entropy Theory by Yingwen Li, Zhen Wei, Huilian Liao, Lin Li, Peizhong Zhang, Jingyun Zhao

“…Finally, the model accurately reconstructed and simulated the near-field of the parallel reactor, and achieved quantitative evaluation of the optimal voiceprint detection position. The results indicate the high accuracy and reliability of the sound field reconstruction model, significantly improving computational efficiency, and the measurement point can fully characterize the acoustic properties of the reactor. …”
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A Consistency-Aware Hybrid Static–Dynamic Multivariate Network for Forecasting Industrial Key Performance Indicators by Jiahui Long, Xiang Jia, Bingyi Li, Lin Zhu, Miao Wang

“…The accurate forecasting of key performance indicators (KPIs) is essential for enhancing the reliability and operational efficiency of engineering systems under increasingly complex security challenges. …”
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PolyReg: Autoregressive Building Outline Regularization via Masked Attention Sequence Generation by Longfei Cui, Chao Li, Xin Chen, Xiao Wang, Haizhong Qian

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Explainable Multi-Scale CAM Attention for Interpretable Cloud Segmentation in Astro-Meteorological Applications by Qing Xu, Zichen Zhang, Guanfang Wang, Yunjie Chen

“…The proposed framework balances accuracy, interpretability, and computational efficiency, offering a trustworthy solution for cloud detection systems in operational settings.…”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…Accurate counting of cucumber flowers using intelligent algorithms to monitor their sex ratio is essential for intelligent facility agriculture management. However, complex greenhouse environments impose higher demands on the precision and efficiency of counting algorithms. …”
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