Hybrid EXGBStackQoE Classifier and Stackelberg Game-Theoretic Approaches for Enhanced QoE in Video Services Over 5G Wireless Networks by K. B. Ajeyprasaath, Vetrivelan Pandu

“…At the initial level, various machine learning (ML) models are trained using the entire dataset, while the subsequent level leverages meta-features generated from the initial predictions to improve overall accuracy. …”
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IEWNet: Multi-Scale Robust Watermarking Network Against Infrared Image Enhancement Attacks by Yu Bai, Li Li, Shanqing Zhang, Jianfeng Lu, Ting Luo

“…In this paper, we propose a novel multi-scale robust watermarking model under IRE attack, called IEWNet. This model trains a preprocessing module for extracting image features based on the conventional Undecimated Dual Tree Complex Wavelet Transform (UDTCWT). …”
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A Two-Stage Hidden Markov Model for Medium- to Long-Term Multiple Wind Farm Power Scenario Generation by Lingxue Lin, Zuowei You, Fengjiao Li, Jun Liu, Chengwei Yang

“…First, based on the key features of the wind power output sequence, the daily typical patterns of wind power output are extracted. …”
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Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models by Zonglin Yi, Yi Zhou, Hao Liu, Li Li, Yan Zhao, Jiayuan Li, Yixuan Mao, Fangyuan Su, Cheng-Meng Chen

“…Machine-learning models are trained based on the organic and inorganic electrolyte solvents that possess experimentally identified reduction mechanisms. …”
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Szkoła jako przestrzeń inkubacji aktywności cyfrowej nauczycieli edukacji wczesnoszkolnej by Natalia Walter

“…In the paper we argue that school is a space for growing and developing digital activity of early education teachers. Based on an observational study and a literature review, we identified factors affecting such activity, i.e., individual features of teachers (competences, motivation, attitude towards self-development, lowliness, and willingness for change), their competence in handling electronic devices, technical equipment available at school, support from the school community along with clearly stated expectations (that the use of digital media is a must, not an option) and availability of trainings and places for exchanging experience and good practices. …”
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Determination of sexual dimorphism with CBCT images of the frontal sinus using a predictive formula and an artificial neural network by Julyana de Araújo OLIVEIRA, Natália Rogério BORELLA, Flávia Maria de Moraes RAMOS-PEREZ, Andrea dos Anjos PONTUAL, Maria Alice Andrade CALAZANS, Felipe Alberto Barbosa Simão FERREIRA, Francisco MADEIRO, Maria Luiza dos Anjos PONTUAL

“…These features were subsequently used to validate the predictive formula and the machine learning-based classification system. …”
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Identifying Ocean Submesoscale Activity From Vertical Density Profiles Using Machine Learning by Leyu Yao, John R. Taylor, Dani C. Jones, Scott D. Bachman

“…In this paper, we propose an unsupervised machine learning algorithm to identify submesoscale activity using vertical density profiles. The algorithm, based on the profile classification model (PCM) approach, is trained and tested on two model‐based data sets with vastly different resolutions. …”
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Deep Ensembling of Multiband Images for Earth Remote Sensing and Foramnifera Data by Loris Nanni, Sheryl Brahnam, Matteo Ruta, Daniele Fabris, Martina Boscolo Bacheto, Tommaso Milanello

“…Multichannel images are fed into an ensemble of Convolutional Neural Networks (CNNs) (ResNet50, MobileNetV2, and DenseNet201), where each network is trained using three channels obtained from the multichannel images, and two custom networks (one based on ResNet50 and the other one based on attention) where the input is a multiband image. …”
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Deep-learning model for embryo selection using time-lapse imaging of matched high-quality embryos by Lisa Boucret, Floris Chabrun, Magalie Boguenet, Pascal Reynier, Pierre-Emmanuel Bouet, Pascale May-Panloup

“…We used self-supervised contrastive learning to train convolutional neural networks to ensure an unbiased and comprehensive learning of the morphokinetics features of the embryos, followed by a Siamese neural network fine-tuning and an XGBoost final prediction model to prevent overfitting. 1580 embryo videos of 460 patients were included between January 2020 and February 2023. …”
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Identification of Environmental Noise Traces in Seismic Recordings Using Vision Transformer and Mel-Spectrogram by Qianlong Ding, Shuangquan Chen, Jinsong Shen, Borui Wang

“…Therefore, relying solely on amplitude-based criteria has certain limitations. To improve noise identification accuracy, we use the Mel-spectrogram to extract features from seismic data and construct the dataset. …”
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Enhancing the classification of isolated theropod teeth using machine learning: a comparative study by Carolina S. Marques, Emmanuel Dufourq, Soraia Pereira, Vanda F. Santos, Elisabete Malafaia

“…In this study, we compared six different ML techniques based on datasets with morphometric features used to classify isolated theropod teeth at both genus and higher taxonomic levels. …”
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Beyond binary: multi-class skin lesion classification with AlexNet transfer learning-towards enhanced dermatological diagnosis by Abida Noaman, Reyaz Ahmad, Muhammad Farhan Khan, Abdul Salam Mohammed, Muhammad Farooq, Khan Muhammad Adnan

“…This proposed model was trained, validated, and tested using ISIC 2019 challenge data with a very abnormal class distribution. …”
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Canopy extraction of mango trees in hilly and plain orchards using UAV images: Performance of machine learning vs deep learning by Yuqi Yang, Tiwei Zeng, Long Li, Jihua Fang, Wei Fu, Yang Gu

“…Based on their accuracy, the best-performing models, HR-Net from DL and Extra Trees Classification (ETC) from ML were selected. …”
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New Method of Impact Localization on Plate-like Structures Using Deep Learning and Wavelet Transform by Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

“…The procedure segmented each PWAS signal to 30 samples with equal intervals, regardless of the features of the signal. Segmenting and transforming different PWAS signals into image-based data points led to data samples that had similar features. …”
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MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data by Nami Sakamoto, Takaki Oka, Yuki Matsuzawa, Kozo Nishida, Jayashankar Jayaprakash, Aya Hori, Makoto Arita, Hiroshi Tsugawa

“…However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. <b>Methods</b>: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. …”
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Strategy of Fully Automatic Operation and Energy Conservation for Rail Transit by YANG Yanjie, HE Deqiang, GUO Rui

“…Finally, based on the reduction of dwell time by using the FAO system and the features of different city planning, the more effective operational strategy of FAO as well as the trend of region and whole net energy conservation strategy development in rail transit was discussed. …”
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Developing Effective Techniques for the Recognition of Shanghai Dialect Text by Yida Bao, Zheng Zhang, Mohammad Arifuzzaman, Tran Duc Le, Qi Li, Masuzyo Mwanza, Jiaqing Lin, Philippe Gaillard, Jiafeng Ye

“…Next, we independently train both a BERT-Chinese-Based classifier and a traditional Support Vector Machine classifier for dialect recognition. …”
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Millise lauliku lapsepõli? Laulu „Kui ma olin väiksekene” allikatest ja autoritest by Taive Särg

“…For Lauliku lapsepõli, Tamm and Härma composed a melody based on shepherds’ calling tunes (karjasehelletused) featuring the refrain “alle-a, alle-la”, which Tamm remembered from her childhood in Tarvastu. …”
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A Gamified Assessment Tool for Antisocial Personality Traits (Antisocial Personality Traits Evidence-Centered Design Gamified): Randomized Controlled Trial by Yaobin Tang, Yongze Xu, Qunli Zhou, Ran Bian

“…Ontology development (study 1): semistructured interviews were conducted with 9 workplace professionals to translate the DSM-5 criteria into 24 observable workplace behaviors, which were integrated into a text-based game featuring 10 subscenarios, 34 interactive questions, and logic rooted in logical jumps to simulate real-world decision-making. …”
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Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

“…Most existing machine-learning-based intrusion-detection systems for IoT have been trained using outdated datasets that do not accurately reflect IoT scenarios. …”
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