Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
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Clinical Phenotype Identification and Validation of Patients with Sepsis in the Intensive Care Unit by GONG Chao, YU Na, CHEN Haoran

“…Then, supervised machine learning algorithms (lightweight gradient boosting machine) were used for the prediction of the patient's phenotypes, and were further combined with SHAP (Shapely Additive eXplanations) for the identification of important features. …”
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Deep Learning Frontiers in 3D Object Detection: A Comprehensive Review for Autonomous Driving by Ambati Pravallika, Mohammad Farukh Hashmi, Aditya Gupta

“…The progression of reference datasets, such as KITTI, Waymo, and NuScenes, was examined, emphasizing their crucial role in propelling detection algorithms forward and enabling comparative studies across diverse methodologies. …”
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Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

“…However, the limitations inherent in IoT edge nodes complicate the deployment of robust cryptographic algorithms, which are fundamentally reliant on finite-field multiplication operations. …”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The incidence of AS in patients with infertility and recurrent miscarriage can be as high as 10%, while the pregnancy rate in cases of moderate to severe adhesions can be as low as 34%. …”
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Synthetic Data Generation for AI-Informed End-of-Line Testing for Lithium-Ion Battery Production by Tessa Krause, Daniel Nusko, Johannes Rittmann, Luciana Pitta Bauermann, Moritz Kroll, Carlo Holly

“…To make these predictions, we implement artificial intelligence algorithms to extract information from the measurements. …”
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Exploring Trends and Variability of Water Quality over Lake Titicaca Using Global Remote Sensing Products by Vann Harvey Maligaya, Analy Baltodano, Afnan Agramont, Ann van Griensven

“…Nowadays, remote sensing offers an alternative source of data to be used in water quality monitoring; by applying appropriate algorithms to satellite imagery, it is possible to retrieve water quality parameters. …”
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Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…The integration of Digital Twins allowed for precise real-time modeling of system behavior, while Deep Learning algorithms effectively identified and predicted faults. …”
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Evaluation of the predictors of tooth loss using artificial intelligence-based machine learning approach: A retrospective study by Amit Rajabhau Pawar, Sankari Malaiappan, Pradeep Kumar Yadalam, P R Ganesh

“…Conclusion: By analyzing comprehensive datasets, machine learning models can enhance the accuracy and objectivity of tooth loss prediction. While challenges remain, such as data quality and privacy concerns, integrating machine learning algorithms in dentistry can revolutionize dental healthcare, improve patient outcomes, and reshape the future of periodontics.…”
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Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…Concurrently, the utilization of machine learning algorithms has facilitated the development and implementation of predictive models. …”
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Métodos de geração de colunas para problemas de atribuição Column generation methods for assignment problems by Edson Luiz França Senne, Luiz Antonio Nogueira Lorena, Silvely Nogueira de Almeida Salomão

“…Computational experiments are presented in order to confirm the effectiveness of the proposed algorithms.…”
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Spatial differences in predicted Phalaris arundinacea (reed canarygrass) occurrence in floodplain forest understories by John T. Delaney, M. Van Appledorn, N. R. De Jager, K. L. Bouska, J. J. Rohweder

“…Flood frequency, distance to contiguous floodplain, distance to forest edge, and distance to invaded wet meadow were among the most important environmental predictors across the three algorithms. Generally, the mean probability of reed canarygrass presence decreased with increasing flood depth, distance to contiguous floodplain, distance to invaded wet meadow, forest cover, and forest height, while relationships with other predictors were more variable. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…The model uses a wrapper-based feature selection technique using machine learning algorithms to select the best features, which are then combined and fed into a Multi-Head Attention-based transformer for getting the predictions. …”
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Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis by Shervin Mossavarali, Ali Vaezi, Zahra Gholami, Alireza Molaei, Mir Saeed Yekaninejad, Folkert W. Asselbergs, Akbar Shafiee

“…Seventeen original studies utilizing AI algorithms to measure HDA and cardiovascular risk factors, outcomes, or mortality were included. …”
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Design of a microservices-based architecture for residential energy efficiency monitoring by Ivonne Nuñez, Carlos Rovetto, Edmanuel Cruz, Andrzej Smolarz, Dimas Concepcion, Elia Esther Cano

“…This proposal seeks to enable end users to effectively monitor and control their electrical devices while effectively integrating them into a wide network of power systems. …”
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Heterogeneous III-V/Si micro-ring laser array with multi-state non-volatile memory for ternary content-addressable memories by Stanley Cheung, Yanir London, Yuan Yuan, Bassem Tossoun, Yiwei Peng, Yingtao Hu, Thomas Van Vaerenbergh, Di Liang, Chong Zhang, Geza Kurczveil, Raymond G. Beausoleil

“…These non-volatile III-V/Si micro-ring lasers (MRLs) exhibit non-volatile wavelength shifts of  ~80 pm with  ~40 dB signal extinction ratio while consuming 0 electrical static tuning power. …”
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Multi-Plane Virtual Vector-Based Anti-Disturbance Model Predictive Fault-Tolerant Control for Electric Agricultural Equipment Applications by Hengrui Cao, Konghao Xu, Li Zhang, Zhongqiu Liu, Ziyang Wang, Haijun Fu

“…Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. …”
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Automated analysis and textual summarization of time-varying references in advanced greenhouse climate control by Ramesh Arvind Naagarajan, Kiran Kumar Sathyanarayanan, Nadja Bauer, Stefan Streif, Stefan Streif

“…Potential reasons are the lack of transparency and the understandability of the control algorithms. This study introduces a language-based support system to improve the usability of advanced control strategies like MPC. …”
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Review of models for estimating 3D human pose using deep learning by Sani Salisu, Kamaluddeen Usman Danyaro, Maged Nasser, Israa M. Hayder, Hussain A. Younis

“…We assess the most widely used datasets and evaluation metrics, providing a comparison of leading algorithms in terms of precision and computational efficiency in tabular form. …”
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Tube-Based Robust Model Predictive Control for Autonomous Vehicle with Complex Road Scenarios by Yang Chen, Youping Sun, Junming Li, Jiangmei He, Chengwei He

“…To facilitate computational tractability and algorithmic implementation, the model is systematically linearized and discretized. …”
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