Open-Loop Control System for High Precision Extrusion-Based Bioprinting Through Machine Learning Modeling by Javier Arduengo, Nicolas Hascoet, Francisco Chinesta, Jean-Yves Hascoet

“…Thus, the control system offers predictability and adaptability capabilities to ensure the consistent production of high-quality bioprinted structures. …”
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Dim and Small Target Detection Based on Improved Bilateral Filtering and Gaussian Motion Probability Estimation by Fan Xiangsuo, Qin Wenlin, Feng Gaoshan, Huang Qingnan, Min Lei

“…Six scenes and eleven comparison algorithms are selected for experiments, experimental results show the effectiveness and robustness of the proposed algorithm.…”
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Symmetry-Based Data Augmentation Method for Deep Learning-Based Structural Damage Identification by Long Li, Xiaoming Tao, Hui Song, Xiaolong Li, Zhilong Ye, Yao Jin, Qiuyu He, Shiyin Wei, Wenli Chen

“…These methods typically use ML algorithms to identify patterns within features extracted from data representing structural conditions, thereby inferring damage from changes in these patterns. …”
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Measured spectrum environment map dataset with multi-radiation sources in urban scenariosMendeley Data by Haotian Zou, Qiuming Zhu, Qianhao Gao, Jie Wang, Zhipeng Lin, Yang Huang, Qihui Wu, Weizhi Zhong

“…Its applications include the verification of spectrum map completion algorithms, wireless channel modelling, deep learning-driven signal prediction, and the optimization of Wi-Fi/cellular networks.…”
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Hypothesis: the generation of T cells directed against neoepitopes employing immune-mediating agents other than neoepitope vaccines by Renee N Donahue, Jeffrey Schlom, James L Gulley, James W Hodge, Claudia Palena, Duane H Hamilton, Sofia R Gameiro

“…As with all cancer therapy modalities, neoepitope vaccine development and delivery also has some drawbacks, including the level of effort to develop a patient-specific product, accuracy of algorithms to predict neoepitopes, and with the exception of melanoma and some other tumor types, biopsies of metastatic lesions of solid tumors are often not available. …”
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Exploring Protein Conformational Changes Using a Large‐Scale Biophysical Sampling Augmented Deep Learning Strategy by Yao Hu, Hao Yang, Mingwei Li, Zhicheng Zhong, Yongqi Zhou, Fang Bai, Qian Wang

“…Abstract Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. …”
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On the Potential of Bayesian Neural Networks for Estimating Chlorophyll-a Concentration from Satellite Data by Mohamad Abed El Rahman Hammoud, Nikolaos Papagiannopoulos, George Krokos, Robert J. W. Brewin, Dionysios E. Raitsos, Omar Knio, Ibrahim Hoteit

“…The performance of the proposed probabilistic model is compared to that of standard ocean color algorithms, namely ocean color 4 (OC4) and ocean color index (OCI). …”
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Federated Learning-Based State of Charge Estimation in Electric Vehicles Using Federated Adaptive Client Momentum by Metin Yilmaz, Eyup Cinar, Ahmet Yazici

“…Traditional Battery Management System (BMS) algorithms can be inadequate for State of Charge (SoC) estimation due to incorrect measurements and unobservable battery characteristics. …”
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State-of-the-Art on IoV-Based Deep Learning Framework for Enhanced Driving Behavior Recognition: Recent Progress, Technology Updates, Challenges, and Future Direction by Hongguang Li, Shafrida Sahrani, Mahidur R. Sarker, Yinglin Xiao

“…However, these advanced algorithms still face several challenges. We analyze relevant literature from 2015 to 2024, to uncover key trends and gaps in the development of applications for identifying dangerous driving behaviors, with a primary focus on optimizing integration to improve the accuracy and real-time capability of driving behavior prediction. …”
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A Survey on the Deep Learning-Based Mismatch Removal: Principles and Methods by Shiyu Chen, Cailong Deng, Yong Zhang, Yong Wang, Qixin Zhang, Zhimin Zhou

“…Due to the inherent limitations of matching algorithms and the complexities associated with image contents, mismatches are inevitable and can have detrimental effects on downstream tasks in computer vision and remote sensing. …”
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An Application of Modified S-CLSVOF Method to Kelvin-Helmholtz Instability and Comparison with Theoretical Result by Naoki Shimada, Mako Sato, Yuta Yaegashi, Thorsten Koch, Thi Thai Le

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Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

“…The accuracy of DL algorithms has been shown across a range of scientific fields. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

“…The system is able to function independently thanks to the use of machine learning algorithms, including LSTM for prediction, Kalman filter for data cleaning, Isolation Forest for anomaly detection, and K-means for clustering sleep patterns.…”
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Integrative multi-omics and machine learning reveal critical functions of proliferating cells in prognosis and personalized treatment of lung adenocarcinoma by Shun Wang, Dingtao Hu, Ruohuang Wang, Jie Huang, Baoqing Wang

“…An integrative machine learning program, comprising 111 algorithms, was developed to construct a Scissor+ proliferating cell risk score (SPRS). …”
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Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

“…The present research utilized the Isolation Forest algorithm to detect outliers in high-dimensional data sets. …”
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Two‐stage video anomaly detection based on dual‐stream networks and multi‐instance learning by Dejun Zhang, Wenbo Fang, Yuhang Liu, Zirong Lyu, Chen Xiong, Zhan Wang

“…Therefore, it is crucial to develop intelligent algorithms for video anomaly detection. The method can detect whether segments of a video contain abnormal events. …”
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Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

“…The findings were contrasted to those from various algorithms, such as whale optimization algorithm, multi-verse optimizer, sine cosine algorithm, arithmetic optimization algorithm, particle swarm optimization, red kite optimization algorithm, tree-seed algorithm, and white shark optimizer. …”
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A Novel Toolbox for Generating Realistic Biological Cell Geometries for Electromagnetic Microdosimetry by Mehrdad Saviz, A.H. Buchali Safiee, Elham Sharifi

“…We have designed a free, user-friendly tool in MATLAB that combines several known or new algorithms for easy production of three-dimensional complex cell shapes based on minimum data. …”
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Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks by Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru

“…The outcomes of this research pave the way for more personalized and effective educational interventions, ultimately contributing to improved learning experiences and outcomes.…”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
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