Detection of Wormhole Attack in Vehicular Ad-hoc Network over Real Map using Machine Learning Approach with Preventive Scheme by Shahjahan Ali, Parma Nand, Shailesh Tiwari

“…VANET (Vehicular Ad-hoc Network) is a developing technology, which is a combination of cellular technology, ad-hoc network & wireless LAN to improve the safety of vehicle as well as driver. VANET communication can be of two types, first one is broadcast and second one is unicast. …”
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Masked Feature Modeling for Generative Self-Supervised Representation Learning of High-Resolution Remote Sensing Images by Shiyan Pang, Hanchun Hu, Zhiqi Zuo, Jia Chen, Xiangyun Hu

“…This methodology has several advantages: 1) The hybrid CNN + Transformer architecture not only retains the advantages of the local feature representation of the CNN architecture but also has the full-text information modeling capabilities of the Transformer architecture; 2) the feature extraction network outputs multiscale features, and it is easier to add upsampling and a skip connection to improve the accuracy of the downstream dense prediction task; and 3) the pretrained MFM can be applied to various downstream tasks through fine-tuning with limited samples. …”
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A Method for Prediction and Analysis of Student Performance That Combines Multi-Dimensional Features of Time and Space by Zheng Luo, Jiahao Mai, Caihong Feng, Deyao Kong, Jingyu Liu, Yunhong Ding, Bo Qi, Zhanbo Zhu

“…The prediction and analysis of students’ academic performance are essential tools for educators and learners to improve teaching and learning methods. Effective predictive methods assist learners in targeted studying based on forecast results, while effective analytical methods help educators design appropriate educational content. …”
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Enhanced 3-D Reconstruction Method for Polarimetric Coherent Optimal-Based Tomographic SAR by Shuhang Dong, Zekun Jiao, Liangjiang Zhou, Xiaolan Qiu, Qiancheng Yan

“…However, in the practical application, there are relatively few models and algorithms for full-polarized SAR joint 3-D imaging. …”
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Diagnostic Utility of ¹⁸F-FDG PET/CT in Infective Endocarditis by Corina-Ioana Anton, Alice-Elena Munteanu, Mihaela Raluca Mititelu, Militaru Alexandru Ștefan, Cosmin-Alexandru Buzilă, Adrian Streinu-Cercel

“…Its integration into diagnostic algorithms may improve clinical management and outcomes in complex IE cases.…”
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Modern advancements of energy storage systems integrated with hybrid renewable energy sources for water pumping application by Marwa M. Ahmed, Haneen M. Bawayan, Mohamed A. Enany, Mahmoud M. Elymany, Ahmed A. Shaier

“…The manuscript also highlights the integration of artificial intelligence (AI) to optimize energy management, predict irrigation demands, and improve operational efficiency. Additionally, recent advancements in energy storage, such as hybrid configurations of batteries and supercapacitors, are discussed in the context of enhancing system sustainability and reducing operational costs. …”
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Approach to Neonates and Young Infants with Fever without a Source Who Are at Risk for Severe Bacterial Infection by Susanna Esposito, Victoria Elisa Rinaldi, Alberto Argentiero, Edoardo Farinelli, Marta Cofini, Renato D’Alonzo, Antonella Mencacci, Nicola Principi

“…To favour the differentiation between low- and high-risk infants, several algorithms based on analytical and clinical parameters have been developed. …”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…This study proposes a novel hybrid model combining a variational autoencoder (VAE) and a generative adversarial network (GAN) to improve the quality and diversity of generated TEC samples. …”
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STING is significantly increased in high-grade glioma with high risk of recurrence by Meishi Zhong, Manmei Long, Chenjie Han, Saiyan Ji, Qingyuan Yang

“…Translation of these findings will ultimately improve the outcomes for ATRX and IDH1 genomically stratified subgroups in HGG.…”
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Fatal pulmonary infection by trimethoprim-sulfamethoxazole resistant Nocardia otitidiscaviarum: report of two cases and review by Rushika Saksena, Dabet Rynga, Santosh Rajan, Rajni Gaind, Reetika Dawar, Raman Sardana, Manas Kamal Sen, Jagdish Chandra Suri

“…Mass spectrometry can become an integral part of diagnostic algorithms for nocardiosis. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…In this study, we propose a machine learning framework to predict vehicle maintenance visits for after-sales services, leading to significant operational improvements. Furthermore, the integration of AI-driven workforce allocation strategies, as studied within the AI4LABOUR (reshaping labor force participation with artificial intelligence) project, has contributed to more efficient service personnel deployment, reducing idle time and improving customer experience. …”
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Plasma methylated HIST1H3G as a non-invasive biomarker for diagnostic modeling of hepatocellular carcinoma by Weiwei Zhu, Weiwei Zhu, Huifen Wang, Huifen Wang, Yudie Cai, Yudie Cai, Jun Lei, Jun Lei, Jia Yu, Jia Yu, Ang Li, Zujiang Yu

“…Here, we comprehensively evaluated the diagnostic value of plasma methylated HIST1H3G, and constructed diagnostic and prognostic models aimed at facilitating early detection and improving the prognosis of hepatocellular carcinoma (HCC).MethodsThe level of HIST1H3G promoter methylation in HCC tissues was evaluated based on the UALCAN database, followed by validation through serum samples collected from HCC patients. …”
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Though the models performed less effectively for follow-ups, the addition of public data enhanced their performance, providing a viable solution to improve their efficacy for the follow-ups. These algorithms hold promise as a valuable tool for clinicians for automated segmentation of planning and follow-up MRI scans during stereotactic radiosurgery treatment planning and response evaluations, respectively. …”
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RAPO: An Automated Performance Optimization Tool for Redis Clusters in Distributed Storage Metadata Management by Yunkai Zhu, Tian Xia, Te Zhu, Zhoujie Zhao, Kexin Li, Xingbo Hu

“…By implementing load balancing among main nodes and read-write separation between main and secondary nodes, the tool aims to improve the metadata service performance of Redis clusters during system maintenance and in high-concurrency scenarios. …”
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Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy by Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, Hiroki Masumoto, Hiroki Enno, Naofumi Ishitobi, Tomoaki Sonobe, Masahiro Kameoka, Masanori Niki, Ken Hayashi, Yoshinori Mitamura

“…Training to construct the DL model using deep convolutional neural network algorithms was provided using ultrawide-field fundus images. …”
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Evaluation of Machine Learning Models for Estimating Grassland Pasture Yield Using Landsat-8 Imagery by Linming Huang, Fen Zhao, Guozheng Hu, Hasbagan Ganjurjav, Rihan Wu, Qingzhu Gao

“…These data, combined with field-measured pasture yields, were employed to construct models using four machine learning algorithms: elastic net regression (Enet), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM). …”
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Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…Through a systematic review of recent studies, this work aims to identify how <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula> can improve computational efficiency across various computing domains. …”
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Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions by Shuxian Yu, Haiyang Jiang, Jing Xia, Jie Gu, Mengting Chen, Yan Wang, Xiaohong Zhao, Zehua Liao, Puhua Zeng, Tian Xie, Xinbing Sui

“…Then, the prediction model was established using ten different machine learning algorithms and the Random Forest (RF) model achieved the highest accuracy at 85.65%. …”
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Information and measuring system for geometric and motion parameters determination of industrial products by their video images by Yurii Podchashynskyi, Oksana Luhovykh, Anna Polianska, Volodymyr Nevmerzhytskyi

“…The proposed system provides an error of (0.13–0.54) mm when measuring the geometric parameters of industrial products, which may be sufficient for routine inspection, but insufficient for use in precision measurements. The main way to improve the accuracy to the requirements of precision measurements is to use a more advanced digital camera, software and algorithmic procedures for approximating and smoothing the contours of objects and motion parameters. …”
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