An enhanced CNN with ResNet50 and LSTM deep learning forecasting model for climate change decision making by Ahmed M. Elshewey, Mona M. Jamjoom, Eman H. Alkhammash

“…It involves long-term, noticeable changes in key climatic factors such as wind power, temperature, wind speed, and wind patterns. Addressing climate change is essential to safeguarding our environment, societies, and economies. …”
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Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction by Mutiara Khairunisa, Desak Made Sidantya Amanda Putri, I Gusti Ngurah Lanang Wijayakusuma

“…LSTM excelled in capturing complex temporal patterns in menstrual cycle data, while CNN effectively identified key patterns, and Decision Tree offered interpretability despite lower performance. …”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…Background: Electroencephalography (EEG) signals play a crucial role in diagnosing epilepsy by reflecting distinct patterns associated with normal brain activity, ictal (seizure) states, and interictal (between-seizure) periods. …”
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Discriminating and classifying odontocete echolocation clicks in the Hawaiian Islands using machine learning methods. by Morgan A Ziegenhorn, Kaitlin E Frasier, John A Hildebrand, Erin M Oleson, Robin W Baird, Sean M Wiggins, Simone Baumann-Pickering

“…Types defined by clustering were then used as input classes in a neural-network based classifier, which was trained, tested, and evaluated on 5-minute binned data segments. …”
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Spatio-temporal evolution of land subsidence and susceptibility zonation of associated ground fissures in the urban area of loess plateau: a case in Xianyang city, China by Yuemin Sun, Jiewei Zhan, Fei Qiang, Quanzhong Lu, Cong Liu, Zhaowei Yao, Jianbing Peng

“…Therefore, we proposed for the first time to introduce the land subsidence gradient factors for the susceptibility mapping of ground fissures using the artificial neural network algorithm. The susceptibility zonation results show that integrating the gradient factor can improve the rationality of the susceptibility evaluation. …”
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Machine-Learning-Driven Analysis of Wear Loss and Frictional Behavior in Magnesium Hybrid Composites by Barun Haldar, Hillol Joardar, Arpan Kumar Mondal, Nashmi H. Alrasheedi, Rashid Khan, Murugesan P. Papathi

“…Data-driven machine learning (ML) algorithms were utilized to identify complex patterns and predict relationships between input variables and output responses. …”
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Predicting danceability and song ratings using deep learning and auditory features by Wei Wu

“…Our model integrates a Bidirectional Long Short-Term Memory (BiLSTM) network to capture sequential and contextual patterns from categorical inputs, alongside a Residual Network (ResNet) that extracts hierarchical representations from numerical auditory features. …”
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Bibliometric Analysis of Medical Waste Research Using Python-Driven Algorithm by Ilie Cirstea, Andrei-Flavius Radu, Delia Mirela Tit, Ada Radu, Gabriela Bungau, Paul Andrei Negru

“…South Korea stands out for high citation rates. Network analysis identified collaboration patterns, while trend mapping highlighted a shift toward sustainable waste management practices. …”
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Dynamic Deployment of Mobile Roadside Units in Internet of Vehicles by Alaa E. Abdel-Hakim, Wael Deabes, Kheir Eddine Bouazza, Abdel-Rahman Hedar

“…The dynamic nature of urban environments faces challenges in optimizing the deployment of mRSUs to adapt to varying vehicular densities and traffic patterns in real-time. In this article, we propose a novel real-time optimization approach for the dynamic deployment of mobile Roadside Units (mRSUs) in urban environments to support the rapid growth of the IoV. …”
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Understanding Problematic Smartphone and Social Media Use Among Adults in France: Cross-Sectional Survey Study by Laurent Karila, Nathaniel Scher, Clement Draghi, Delphine Lichte, Ilan Darmon, Hanene Boudabous, Hanah Lamallem, Olivier Bauduceau, Marc Bollet, Alain Toledano

“…ObjectiveThe aim of the study is to assess the prevalence of compulsive smartphone use among French adults and identify patterns of problematic behaviors, including their impact on daily activities, sleep, and safety. …”
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Production forecasting for normal pressure shale gas wells based on coupling of production decline method and LSTM model by HAN Kening, WANG Wei, FAN Dongyan, YAO Jun, LUO Fei, YANG Can

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Environmental DNA supports importance of heterogeneous pond landscapes for arthropod diversity conservation by Vera Zizka, Katharina Schwesig, Nele Engel, Norbert Hölzel, Christoph Scherber

“…Here, we investigate arthropod diversity and conservation status across lakes and ponds in mining sites; analyze how water body size, age, and vegetation cover affect diversity patterns; and discuss how results can contribute to management actions and conservation schemes. …”
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Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

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The real-world safety of Nivolumab: a pharmacovigilance analysis based on the FDA adverse event reporting system by Yutong Wu, Yue Zhou, Shiyue Xia, Zhaoyou Meng

“…To evaluate the association between nivolumab and adverse events (AEs), we employed four distinct disproportionality analysis methods: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-item Gamma Poisson Shrinker (MGPS) and Bayesian Confidence Propagation Neural Network (BCPNN). …”
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View-label driven cross-space structure alignment for incomplete multi-view partial multi-label classification by Shenrun Ding, Jiarui Chen, Tongwei Gao, Yinghao Ye, Xiaohuan Lu

“…The incompleteness of multi-view features degrades the comprehensiveness of sample representations, leading to failure in capturing semantically discriminative patterns essential for classification. To address the aforementioned challenges, we propose a novel learning framework termed View-Label Driven Cross-Space Structure Alignment Network (VLCSA). …”
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Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas by Yue Hu, Xin Cao, Hongyi Chen, Daoying Geng, Kun Lv

“…The biological interpretability of selected features reflects distinct neuroplasticity patterns between LGGs and HGGs, advancing understanding of glioma-network interactions.…”
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Machine learning-optimized dual-band wearable antenna for real-time remote patient monitoring in biomedical IoT systems by Umar Musa, Amor Smida, Muhammad S. Yahya, Mohamed I. Waly, Jun Jiat Tiang, Nazih Khaddaj Mallat, Surajo Muhammad, Abubakar Salisu

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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…It can identify hidden patterns and non-linear, complex relationships within claims data. …”
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Prognostic Value of Radiological and Laboratory Biomarkers for Assessing Risk of Adverse Outcome in Patients with COVID-19 by А. D. Strutynskaya, M. А. Karnaushkina, L. I. Dvoretskiy, I. Е. Tyurin

“…Both CT signs (crazy-paving pattern, bronchial dilatation inside a lesion, peripheral distribution of symptoms, absence of a predominant distribution pattern, lesion grade and extent), and most of laboratory markers were associated with deterioration and its criteria. …”
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Study on main controlling factors of CO2 huff-n-puff for enhanced oil recovery and storage in shale oil reservoirs by CHEN Jun, WANG Haimei, CHEN Xi, TANG Yong, TANG Liangrui, SI Rong, WANG Huijun, HUANG Xianzhu, LENG Bing

“…The study clarified the influence patterns of reservoir engineering parameters in CO₂ huff-n-puff on both cumulative oil increment and CO₂ storage capacity, and determined the primary controlling factors among these parameters. …”
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