High-precision prediction of non-resonant high-order harmonics energetic particle modes via stacking ensemble strategies by Sheng Liu, Zhenzhen Ren, Weihua Wang, Kai Zhong, Jinhong Yang, Hongwei Ning

“…The evaluation results indicate that the performance of the proposed model surpasses most supervised learning algorithms. …”
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Enhanced cardiovascular risk prediction in the Western Pacific: A machine learning approach tailored to the Malaysian population. by Sazzli Kasim, Putri Nur Fatin Amir Rudin, Sorayya Malek, Nurulain Ibrahim, Xue Ning Kiew, Nafiza Mat Nasir, Khairul Shafiq Ibrahim, Raja Ezman Raja Shariff

“…<h4>Conclusions</h4>These findings underscore the effectiveness of ML models in improving CVD risk stratification and decision-making in Malaysia and beyond.…”
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Semi-Active Suspension Control Strategy Based on Negative Stiffness Characteristics by Yanlin Chen, Shaoping Shen, Zhijie Li, Zikun Hu, Zhibin Li

“…Our research identifies shortcomings of classical semi-active control algorithms and introduces a new band selector to combine improved control methods. …”
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A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design by Chen Li

“…However, existing image restoration algorithms have disadvantages such as fuzzy restoration effect and slow speed; to solve such problems, this paper adopts a dual discriminator model based on generative adversarial networks, which effectively improves the restoration accuracy by adding local discriminators to track the information of local missing regions of images. …”
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A comprehensive survey on machine learning for workplace injury analysis: risk prediction, return to work strategies, and demographic insights by Gonzalo A. Vivian, Richard A. Bauder, Taghi M. Khoshgoftaar

“…It emphasizes the importance of leveraging ML in personalized RTW programs, which use data-driven insights to improve recovery outcomes and reduce economic demands. …”
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SPARCQ: Enhancing Scalability and Adaptability of Proactive Edge Caching Through Q-Learning by Shruti Lall, Johan de Clercq, Nelishia Pillay, Bodhaswar T. Maharaj

“…By dynamically adjusting hyperparameters, our approach ensures accurate predictions, improving caching efficiency and adaptability. Using the MovieLens dataset, we achieve an average improvement of 8% in cache hit ratios compared to baseline models, including popularity-based and untuned models. …”
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The Role of Intelligent Transport Systems and Smart Technologies in Urban Traffic Management in Polish Smart Cities by Ewa Puzio, Wojciech Drożdż, Maciej Kolon

“…A key contribution of the paper is the presentation of new proposals for improvements, such as the inclusion of behavioral data in traffic modeling, integration with GPS navigation, and dynamic emergency and public transport priority management. …”
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Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program by Samuel Dagogo-Jack, Søren Brunak, Carlos Lorenzo, Kieren J Mather, Marinella Temprosa, Tibor V Varga, Jinxi Liu, Ronald B Goldberg, Guannan Chen, Xavier Pi-Sunyer

“…Across all algorithms, models with baseline 2-hour glucose performed the best (max MCC=0.36). …”
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A Robust Behavioral Biometrics Framework for Smartphone Authentication via Hybrid Machine Learning and TOPSIS by Moceheb Lazam Shuwandy, Qutaiba Alasad, Maytham M. Hammood, Ayad A. Yass, Salwa Khalid Abdulateef, Rawan A. Alsharida, Sahar Lazim Qaddoori, Saadi Hamad Thalij, Maath Frman, Abdulsalam Hamid Kutaibani, Noor S. Abd

“…Our analysis, supported by experimental results, ensure that the RF model outperforms the two other ML algorithms by getting F1-Score, accuracy, recall, and precision of 95.1%, 95.2%, 95.5%, and 94.8%, respectively. …”
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Characterizing Satellite Soil Moisture Drydown: A Bivariate Filtering Approach by Jhilam Sinha, Ashish Sharma, Lucy Marshall, Seokhyeon Kim

“…Although the algorithm assumes spatial stationarity, improvements exist across different soil properties and climatic conditions, providing a parsimonious alternative to better capture the dynamics of soil moisture loss.…”
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Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma by Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU

“…Although adjuvant radiotherapy in combination with Temozolomide administration has clearly demonstrated the benefit in improving the prognosis of patients with multiforme glioblastoma, radiotherapy as only treatment or in combination with systemic treatment is one of the best supportive in unresectable cases. …”
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LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network by Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs, Jennifer C. Yee, Andrew Vanderburg, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

“…We demonstrate a classification accuracy above 87.5% and anticipate further improvements as we expand our training set and continue to refine the algorithm.…”
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Easy Data Augmentation untuk Data yang Imbalance pada Konsultasi Kesehatan Daring by Anisa Nur Azizah, Misbachul Falach Asy'ari, Ifnu Wisma Dwi Prastya, Diana Purwitasari

“…The EDA process with RI gave better coherences of 0.55, and it could support the EDA application to handle imbalanced data, eventually improving the classification performance. …”
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Unsupervised Feature Selection via a Dual-Graph Autoencoder with <inline-formula><math display="inline"><semantics><mrow><msub><mi mathvariant="bold-script">l</mi><mrow><mn mathvar... by Zhichao Song, Meiling Chen, Liang Xie, Xi Fang

“…Experiments on multiple benchmark datasets and [⁶⁸Ga]Ga-Pentixafor PET/CT glioma imaging data demonstrate that the proposed DGA significantly improves clustering performance and accurately identifies features associated with lesion regions. …”
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INFLUENCE OF MAIN GEAR RATIO ON CAR FUEL EFFICIENCY IN THE DRIVE CYCLE by S. A. Gorozhankin, N. V. Savenkov, V. V. Ponyakin

“…The article presents the improvement efficiency of fuel and economic properties of the vehicle in WLTC driving cycle by means of the main gear ratio changing. …”
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A survey of task deployment and recovery in space-air-ground integrated networks based on SDN and NFV by CAO Yilu, JIA Ziye, YOU Jiahao, ZHANG Lei, WU Qihui

“…Finally, a use case was constructed, setting node deployment and service function chain modeling. The effectiveness of the proposed strategies in improving the completion efficiency of service function chains and dealing with resource failures was verified, providing a theoretical basis for the resource allocation for the space-air-ground integrated network.…”
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Metodologías para el desarrollo de Interfaces Visuales de Recuperación de Información: análisis y comparación by Víctor Herrero-Solana, Yusef Hassan

“…This paper proposes an exhaustive review of the different models, methods and algorithms that can be used to develop Visual Interfaces for Information Retrieval. …”
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A Public Dataset of Annotated Orcinus orca Acoustic Signals for Detection and Ecotype Classification by K. J. Palmer, Emma Cummings, Michael G. Dowd, Kait Frasier, Fabio Frazao, Alex Harris, April Houweling, Jasper Kanes, Oliver S. Kirsebom, Holger Klinck, Holly LeBlond, Lauren Laturnus, Craig Matkin, Olivia Murphy, Hannah Myers, Dan Olsen, Caitlin O’Neill, Bruno Padovese, James Pilkington, Lucy Quayle, Amalis Riera Vuibert, Krista Trounce, Svein Vagle, Scott Veirs, Val Veirs, Jen Wladichuk, Jason Wood, Tina Yack, Harald Yurk, Ruth Joy

“…This curated dataset aims to improve the accuracy of killer whale detection algorithms, support conservation efforts, and advance our understanding of killer whale acoustic communication across different populations.…”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

“…This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches.…”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…For example, among the 17 identified benefits, the top-ranked ones include AI capabilities to improve analytics, AI’s facilitation of digital twins in modeling complex real-world systems, and the facilitation of strategic decision making. …”
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