Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis by XinPei Liu, SanXi Ai, RuiMing Yu, ChaoJi Zhang, Qi Miao

“…The optimal model was selected based on ROC curve AUC. …”
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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. …”
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MRI-based brain tumor ensemble classification using two stage score level fusion and CNN models by Oussama Bouguerra, Bilal Attallah, Youcef Brik

“…Nine deep learning models are then trained and tested on the enhanced dataset, experimenting with five optimizers. …”
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FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…To address these challenges, this study proposes an improved weed instance segmentation model based on YOLOv8s-Seg, named FCB-YOLOv8s-Seg, for targeted spraying operations in soybean fields. …”
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Comparative Analysis of Hybrid Model Performance Using Stacking and Blending Techniques for Student Drop Out Prediction In MOOC by Muhammad Ricky Perdana Putra, Ema Utami

“…The use of ensemble techniques to build models can improve performance, but previous research has not reviewed the most optimal ensemble technique for this case study. …”
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Secondary throughput maximization scheme for non-linear energy harvesting cognitive radio networks by Haijiang GE, Ning JIA, Kaikai CHI, Yunzhi CHEN

“…Aiming at a cognitive radio network (CRN) consisting of a pair of primary users and M pairs of secondary users, the secondary throughput maximization for CRN based on the non-linear energy harvesting model was studied.Specifically, in the case of considering secondary transmitter (ST) circuit power, the secondary throughput maximization (STM) problem with primary users’ throughput demands was first modeled as a non-linear optimization problem and then transformed into a convex optimization problem.Finally, a low-complexity algorithm combining the golden section and dichotomy was proposed.By applying this low-complexity algorithm, the optimal time allocation of the primary transmitter (PT)’s energy transmission and secondary users’ information transmission, and the optimal transmission power of PT were obtained.In addition, for the case of neglecting the ST circuit power, the convex property of the STM problem was first proved, and then a more efficient algorithm was designed to solve it.The simulation results show that compared with the equal time allocation method and the link gain priority method, the proposed design algorithm significantly improves the throughput of secondary users.…”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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Qualitative modification of geometrically oriented methods for constructing spatial curves in C3D FairCurveModeler by V. G. Mufteev, F. T. Ziganshina, V. I. Gumerov, R. I. Nabiev, G. M. Efimova

“…The article provides a detailed algorithm for improving the C3D FairCurveModeler commands for constructing a class F spatial curve with approximation by a rational cubic spline Bezier curve (NURBzS-curve) and with approximation by a highdegree B-spline curve. …”
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Generative Adversarial and Transformer Network Synergy for Robust Intrusion Detection in IoT Environments by Pardis Sadatian Moghaddam, Ali Vaziri, Sarvenaz Sadat Khatami, Francisco Hernando-Gallego, Diego Martín

“…Additionally, an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm is employed to fine-tune the hyper-parameters of the hybrid model, further enhancing learning stability and detection performance. …”
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A Novel Time Delay Nonsingular Fast Terminal Sliding Mode Control for Robot Manipulators with Input Saturation by Thanh Nguyen Truong, Anh Tuan Vo, Hee-Jun Kang

“…Manipulator systems are increasingly deployed across various industries to perform complex, repetitive, and hazardous tasks, necessitating high-precision control for optimal performance. However, the design of effective control algorithms is challenged by nonlinearities, uncertain dynamics, disturbances, and varying real-world conditions. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…In genomics, ML methods enabled nuanced disease subtype discovery and improved the accuracy of cancer risk assessment and pharmacogenomic modeling. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…Existing approaches lack adaptability to evolving terminologies and insufficiently address the complex interaction dynamics inherent in multi-disciplinary frameworks.MethodsTo address these limitations, we propose a Synergistic Collaboration Framework (SCF) integrated with an Adaptive Synergy Optimization Strategy (ASOS). SCF models IPC as a dynamic multi-agent system, where disciplines are represented as intelligent agents interacting within a weighted graph structure. …”
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Thermal Error Prediction in High-Power Grinding Motorized Spindles for Computer Numerical Control Machining Based on Data-Driven Methods by Quanhui Wu, Yafeng Li, Zhengfu Lin, Baisong Pan, Dawei Gu, Hailin Luo

“…The subsequent problem of thermal error compensation can be effectively solved by a suitable thermal error model, which is crucial for improving the machining accuracy of the actual machining process. …”
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Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Wen Yao Low, Nor Zaihar Yahaya, Ahmed Tijjani Dahiru, Temitope Ibrahim Amosa, Shehu Lukman Ayinla

“…Effective energy management is crucial in hybrid energy systems for optimal resource utilization and cost savings. This study integrates Deep Deterministic Policy Gradient (DDPG) with Particle Swarm Optimization (PSO) to enhance exploration and exploitation in the optimization process, aiming to improve energy resource utilization and reduce costs in hybrid energy systems. …”
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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

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Power-Yeoh: A Yeoh-Type Hyperelastic Model with Invariant I₂ for Rubber-like Materials by Subraya Krishna Bhat, Keerthan A.

“…In this paper, we improve the Yeoh model, a classical and popular I₁-based hyperelastic model with high versatility. …”
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Research on computer multi feature fusion SVM model based on remote sensing image recognition and low energy system by Yangming Wu, Hao Wu, Xin Tang, Jianwei Lv, Rufei Zhang

“…Aiming at the limitations of the traditional SVM model in processing high-dimensional data, an optimization algorithm is designed to reduce the computational complexity and improve the recognition accuracy of the model through dimensionality reduction and feature selection. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. …”
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A deep learning-based hybrid method for PM2.5 prediction in central and western China by Zuhan Liu, Zihai Fang, Yuanhao Hu

“…The model integrates the transformer and LSTM architectures and employs parameter optimization through the particle swarm optimization (PSO) algorithm. …”
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