Decannulation ahead: a comprehensive diagnostic and therapeutic framework for tracheotomized neurological patients by Rainer Dziewas, Tobias Warnecke, Bendix Labeit, Volker Schulte, Inga Claus, Paul Muhle, Anna Brake, Lena Hollah, Anne Jung, Jonas von Itter, Sonja Suntrup-Krüger

“…This framework promotes flexibility, enabling clinicians to tailor interventions to individual patient needs while maintaining safety and optimizing outcomes.…”
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Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering by Sirui Zhou, Jun Lin, Chuandong Jiang, Haigen Zhou, Yanzhang Wang

“…Based on the sequential processing strategy of measuring while inverting, the REKF algorithm yields the optimal solution of the inversion objective function in just a few iterations, or even a single iteration, enabling near real-time calculations. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…To minimize overfitting in each algorithm, K-fold cross-validation methodology is employed during the training phase. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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Reinforcement learning-based assimilation of the WOFOST crop model by Haochong Chen, Xiangning Yuan, Jian Kang, Danni Yang, Tianyi Yang, Xiang Ao, Sien Li

“…Our results demonstrate that the Time-Series Driven RL model achieved assimilation accuracy comparable to the SUBPLEX optimization algorithm, with an average MAE of 0.65 compared to 0.76 for SUBPLEX, and a slight decrease in RMSE, while significantly reducing the computational burden by 365 times. …”
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Adaptive sequential estimator for InSAR time series phase estimation by Guanya Wang, Zhiwei Li, Han Gao, Jun Hu, Mi Jiang, Peng Ren, Jie Zhang

“…First, an adaptive coherence-weighted matrix partitioning method is proposed. Utilizing Otsu’s algorithm and a local subset merging algorithm, it adaptively generates data subsets which are dynamically tailored to the coherence distribution. …”
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An Over-the-Air Multi-User Convolutional Code for URLLC by Rafael Santos, Daniel Castanheira, Adao Silva, Atilio Gameiro

“…A zero-terminated CC (ZTCC) enables efficient maximum likelihood (ML) decoding through the Viterbi algorithm, but suffers from a rate-loss particularly prominent in short blocks. …”
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Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

“…Moreover, we design the random forest-based ensemble TTI decision algorithm (RF-ETDA) to accomplish the TTI selection for each service. …”
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DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…To address these challenges, this paper proposes a lightweight dynamic block cipher (DynBlock) algorithm. DynBlock is specifically suitable for resource-limited devices, and features a dynamic block size (64-128 bits), which is adaptable to symmetric encryption key sizes. …”
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IMA-FLADRC-Based Electric-Driven High-Speed Maize Precision Seeding Control Strategy and System by Song Wang, Shujuan Yi, Bin Zhao, Yifei Li, Dongming Zhang, Tao Chen, Wensheng Sun

“…This study develops an electric-driven high-speed maize precision seeding control system, establishing kinematic models for the seeding and guiding motors relative to operating speed. An Improve Mayfly Algorithm-Fuzzy Linear Active Disturbance Rejection Control (IMA-FLADRC)-based control strategy is proposed, integrating a fuzzy algorithm to adaptively adjust the proportional coefficient of the Linear State Error Feedback (LSEF) and optimizing key parameters using an IMA, enhancing system adaptability and robustness. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…Therefore, an improved particle swarm algorithm (IPSO) is used to find the optimal solution of λ. …”
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Association between admission Braden Skin Score and delirium in surgical intensive care patients: an analysis of the MIMIC-IV database by Meiling Shang, Meiling Shang, Ailing Shang, Yu Xu, Yu Xu

“…Feature importance of BSS was initially assessed using a machine learning algorithm, while restricted cubic spline (RCS) models and multivariable logistic analysis evaluated the relationship between BSS and delirium. …”
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Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection by Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu

“…What is more, it shows better delay optimization for social vehicles than the algorithm with delay as the objective while declining bus delay appreciable quantity with 43.4 s in average. …”
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Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu, Kaiquan Cai

“…An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. …”
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Network capacity with probit-based stochastic user equilibrium problem. by Lili Lu, Jian Wang, Pengjun Zheng, Wei Wang

“…The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers' route choice. …”
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Investigation of a staggered dual-rotor wound field synchronous motor for offshore wind turbine full-scale testing platforms by Yang Xue, Shiyao Qin, Chen Qi, Ning Wang, Cong Liu, Wenliang Zhao

“…To enhance average torque and minimize torque ripple, the rotor structure undergoes further optimization through a multi-objective genetic algorithm. …”
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Prediction-Based Tip-Over Prevention for Planetary Exploration Rovers by Siddhant Shete, Raúl Domínguez, Ravisankar Selvaraju, Mariela De Lucas Álvarez, Frank Kirchner

“…The proposed system employs linear accelerations and angular velocities measured by the accelerometer and the gyroscope of the Inertial Measurements Unit (IMU) to monitor the rover’s dynamic behavior and stability while navigating the environment. By leveraging deep learning algorithms, the system evaluates predictions and true measurements in real time to identify potential tip-overs. …”
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Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study by Alyce S Adams, Catherine Lee, Gabriel Escobar, Elizabeth A Bayliss, Brian Callaghan, Michael Horberg, Julie A Schmittdiel, Connie Trinacty, Lisa K Gilliam, Eileen Kim, Nima S Hejazi, Lin Ma, Romain Neugebauer

“…Methods for early detection of individuals at high risk remain elusive. While data-driven diabetic polyneuropathy algorithms exist, high-performing, clinically useful tools to assess risk are needed to improve clinical care. …”
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SMART DShot: Secure Machine-Learning-Based Adaptive Real-Time Timing Correction by Hyunmin Kim, Zahid Basha Shaik Kadu, Kyusuk Han

“…Our approach addresses critical vulnerabilities in Electronic Speed Controller (ESC) interfaces by deploying four synergistic algorithms—Kalman Filter Timing Correction (KFTC), Recursive Least Squares Timing Correction (RLSTC), Fuzzy Logic Timing Correction (FLTC), and Hybrid Adaptive Timing Correction (HATC)—each optimized for specific error characteristics and attack scenarios. …”
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SpaceRL — A reinforcement learning-based knowledge graph driver by Miguel Bermudo, Daniel Ayala, Inma Hernández, David Ruiz, Miguel Toro

“…The generation of such agents is a complex task, even more so for a non-expert user.SpaceRL is meant to overcome these limitations by providing a flexible set of tools designed with a wide variety of customization options, in order to adapt to different users’ needs, while also including a variety of state-of-the-art RL algorithms and several embedding models that can be combined to optimize the agents performance. …”
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