A deep transfer learning model for green environment security analysis in smart city by Madhusmita Sahu, Rasmita Dash, Sambit Kumar Mishra, Mamoona Humayun, Majed Alfayad, Mohammed Assiri

“…In this paper, we propose a morphologically augmented fine-tuned DenseNet-121(MAFDN) LULC classification model to automate the categorization of high spatial resolution scene images for environmental conservation. …”
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Epidemiology and Genetic Traits of Carbapenemase-Producing Enterobacterales: A Global Threat to Human Health by Gualtiero Alvisi, Antonio Curtoni, Rossella Fonnesu, Aurora Piazza, Caterina Signoretto, Giorgia Piccinini, Davide Sassera, Paolo Gaibani

“…Carbapenemase-producing Enterobacterales (CPE) represent an important threat to global health, resulting in an urgent issue in clinical settings. CPE often exhibit a multidrug-resistant (MDR) phenotype, thus reducing the antimicrobial armamentarium, with few antibiotics retaining residual antimicrobial activity against these pathogens. …”
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Condition Monitoring of Photovoltaic Panels Through Electrical Impedance Spectroscopy and Machine Learning Focusing on Temperature, Dust, and Microcracks by Saeed Iqbal, Syed Maaz Hasan, Yasar Ayaz, Emad Ud Din, Adeel Waqas, Muhammad Sajid

“…The light gradient boosting machine (LGBM) demonstrated great performance, achieving an F1 score of 0.856 for temperature classification and 0.975 for detection of dust and microcracks. …”
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Long-Term Integrated Measurements of Aerosol Microphysical Properties to Study Different Combustion Processes at a Coastal Semi-Rural Site in Southern Italy by Giulia Pavese, Adelaide Dinoi, Mariarosaria Calvello, Giuseppe Egidio De Benedetto, Francesco Esposito, Antonio Lettino, Margherita Magnante, Caterina Mapelli, Antonio Pennetta, Daniele Contini

“…Biomass burning processes affect many semi-rural areas in the Mediterranean, but there is a lack of long-term datasets focusing on their classification, obtained by monitoring carbonaceous particle concentrations and optical properties variations. …”
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Advancing endometrial cancer treatment: exploring immunotherapy and tyrosine kinase inhibitors through clinical cases by Vanda Salutari

“…This article is part of the New treatment options for advanced endometrial carcinoma Special Issue: https://www.drugsincontext.com/special_issues/new-treatment-options-for-advanced-endometrial-carcinoma…”
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A Deep Learning Approaches for Enhancing Clinical Solutions to Cardiovascular Prediction Using EHR by Mounika Valasapalli, Nallagatla Raghavendra Sai

“…Current methods for cardiovascular disease prediction is leading to so many miss classifications, urging the need of modern automated Deep learning approaches. …”
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Deep Learning-Based Object Detection Strategies for Disease Detection and Localization in Chest X-Ray Images by Yi-Ching Cheng, Yi-Chieh Hung, Guan-Hua Huang, Tai-Been Chen, Nan-Han Lu, Kuo-Ying Liu, Kuo-Hsuan Lin

“…Moreover, schemes incorporating binary classification consistently improved performance, and CNN-based models outperformed Transformer-based models across all scenarios. …”
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Vulnerability of peatland fires in bengkalis regency during the ENSO El nino phase using a machine learning approach by Fauziah, Lilik B. Prasetyo, Nonon Saribanon, Nur Hayati

“…Peatland fires are increasingly becoming a concern as a recurring environmental issue in Indonesia, particularly along the east coast of Sumatra Island, in Bengkalis Regency. …”
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BIG DATA AND ARTIFICIAL INTELLIGENCE IN INFORMATION SYSTEMS OF PRODUCT QUALITY MANAGEMENT by Zhandaraly Sadyraliev, Tuganay K. Zhumanbayeva, Olga V. Dybina, Aleksandr A. Krutilin, Grisha M. Amirkhanyan

“…This work addresses the issue of improving information systems for product quality management through innovative technologies which are based on artificial intelligence (AI) and big data analysis. …”
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MFHG-DDI: An Enhanced Hybrid Graph Method Leveraging Multiple Features for Predicting Drug–Drug Interactions by Xiang Li, Xiangmin Ji, Chengzhen Xu, Jie Hou, Xiaoyu Zhao, Guodong Peng

“…MFHG-DDI reframes the heterogeneous network as a graph classification task, capturing DDI information efficiently through an enhanced hybrid graph. …”
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Adaptive Disconnector States Diagnosis Method Based on Adjusted Relative Position Matrix and Convolutional Neural Networks by Peifeng Yan, Chenzhang Chang, Dong Hua, Haomin Huang, Suisheng Liu, Peiyi Cui

“…Finally, we achieve high-accuracy diagnosis and classification of HVD states using a CNN that incorporates Batch Normalization (BN) and GELU activation functions. …”
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Handling imbalanced samples in landslide susceptibility evaluation by You TIAN, Bo GAO, Hong YIN, Yuanling LI, Jiajia ZHANG, Long CHEN, Hongliang LI

“…In landslide susceptibility assessment, different approaches to handling sample imbalance can introduce significant uncertainty in evaluation outcomes. To address this issue, this study focused on the Changdu area of eastern Tibet and constructed the landslide susceptibility evaluation model using a dataset with imbalanced landslide and non-landslide samples. …”
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Leveraging SARs and Advanced Deep Learning Techniques for Oil Spill Detection in UAE by M. Alkhalifa, A. Alowais, A. Manousakis, A. Manousakis

“…The system uses an automated Vision Transformer (ViT) as its base for the classification and segmentation of oil spills, which was trained on SAR patches falling under two classes. …”
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Short-term Results of Vagus Nerve Stimulation in Pediatric Patients with Refractory Epilepsy by Chih-Yi Chen, Hsu-Tung Lee, Chu-Chin Chen, Shang-Yeong Kwan, Shyi-Jou Chen, Liang-Po Hsieh, Jeng-Dau Tsai

“…In addition to ketogenic diet and epilepsy surgery, VNS provides an alternative way to manage this issue. Our results suggest that VNS is well tolerated in pediatric patients, and is a favorable and safe method of treating intractable seizure in common clinical practice.…”
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Apple leaf disease severity grading based on deep learning and the DRL-Watershed algorithm by Zhifang Bi, Fumin Ma, Jiaxiong Guan, Jie Wu, Juxia Li, Fuzhong Li, Yanwen Li, Zhanli Liu

“…Existing methods for disease detection and severity classification struggle to quickly and accurately segment and quantify diseased areas on leaves, particularly in complex backgrounds. …”
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A Drowsiness Reduction Strategy Utilizing Visual Stimulation With Different Colors of Light: An fNIRS Study by Zeshan Shoaib, Arbab Akbar, Muhammad Ahmad Kamran, Junhyun Kim, Myung Yung Jeong

“…Numerous counter-measures have been proposed to resolve this issue like adaptive environmental settings (temperature, sound, and light). …”
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Denoising and Recognition Method for Weak Acoustic Abnormal Signals in Hot-Wall Hydrogenation Reactors Using DnCNN-CNN by Xueqin Wang, Shilin Xu, Yun Tu, Ying Zhang, Mingguo Peng

“…The DnCNN module removes noise from the mixed spectrogram, while the CNN module performs signal classification. The model was validated through three representative case studies. …”
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Artificial intelligence-driven predictive framework for early detection of still birth by Sarah A. Alzakari, Asma Aldrees, Muhammad Umer, Lucia Cascone, Nisreen Innab, Imran Ashraf

“…Despite advancements in prenatal care, the prevention of stillbirths remains a complex issue requiring further research and interventions. …”
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Machine Learning Based Method for Insurance Fraud Detection on Class Imbalance Datasets With Missing Values by Ahmed A. Khalil, Zaiming Liu, Ahmed Fathalla, Ahmed Ali, Ahmad Salah

“…Insurance fraud is a prevalent issue that insurance companies must face, particularly in the realm of automobile insurance. …”
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Wind Turbine Fault Diagnosis with Imbalanced SCADA Data Using Generative Adversarial Networks by Hong Wang, Taikun Li, Mingyang Xie, Wenfang Tian, Wei Han

“…Then, another CNN is trained to perform fault classification using the augmented balanced dataset. The proposed approach is verified utilizing actual SCADA data derived from a wind farm. …”
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