An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis by Haien Wang, Xingxing Jiang, Wenjun Guo, Juanjuan Shi, Zhongkui Zhu

“…Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. …”
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Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning by Jon Alvarez Justo, Alexandru Ghita, Daniel Kovac, Joseph L. Garrett, Mariana-Iuliana Georgescu, Jesus Gonzalez-Llorente, Radu Tudor Ionescu, Tor Arne Johansen

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Latest Advancements in Credit Risk Assessment with Machine Learning and Deep Learning Techniques by Soni Umangbhai, Jethava Gordhan, Ganatra Amit

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Experimental Study on Compressive Capacity Behavior of Helical Anchors in Aeolian Sand and Optimization of Design Methods by Qingsheng Chen, Wei Liu, Linhe Li, Yijin Wu, Yi Zhang, Songzhao Qu, Yue Zhang, Fei Liu, Yonghua Guo

“…The XGBoost algorithm enabled the rigorous quantification of the governing geometric features of compressive capacity, culminating in a computational framework for the bearing capacity factor (<i>N</i>_q) and lateral earth pressure coefficient (<i>K</i>_u). …”
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QAR Data Imputation Using Generative Adversarial Network with Self-Attention Mechanism by Jingqi Zhao, Chuitian Rong, Xin Dang, Huabo Sun

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An AI-Enabled Framework for <i>Cacopsylla chinensis</i> Monitoring and Population Dynamics Prediction by Ruijun Jing, Deyan Peng, Jingtong Xu, Zhengjie Zhao, Xinyi Yang, Yihai Yu, Liu Yang, Ruiyan Ma, Zhiguo Zhao

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Reconstructing Fractional Holographic Dark Energy with scalar and gauge fields by Ayush Bidlan, Paulo Moniz, Oem Trivedi

“…In more detail, we methodically compute the corresponding Equation of State (EoS) parameters and field (kinetic and potential) features for the fractional parameter ( $$\alpha $$ α ) range, viz. $$1<\alpha \le 2$$ 1 < α ≤ 2 . …”
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A survey of models for automatic assessment of similarity of student's answer to the reference answer by Nadezhda S. Lagutina, Ksenia V. Lagutina

“…A large number of authors choose large language models to solve their problems, but standard features remain in demand. It is impossible to single out a universal approach; each subtask requires a separate choice of method and adjustment of its parameters. …”
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Evaluating multitemporal vegetation indices from Zhuhai-1 hyperspectral images for detecting a rapidly spreading invasive species - Spartina alterniflora by Yuanhui Zhu, Soe W. Myint, Jingjing Cao, Kai Liu, Mei Zeng, Chenxi Diao

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Dynamic Relevance-Weighting-Based Width-Adaptive Auto-Encoder by Malak Almejalli, Ouiem Bchir, Mohamed Maher Ben Ismail

“…Unlike traditional autoencoders with fixed architectures, the proposed method introduces a dynamic relevance weighting mechanism that assigns adaptive importance to each node in the hidden layer. This distinctive feature enables the simultaneous learning of both the model parameters and its structure. …”
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Prediction of Gait Neurodegenerative Diseases by Variational Mode Decomposition Using Machine Learning Algorithms by P. Visvanathan, P.M. Durai Raj Vincent

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Preliminary Design of Debris Removal Missions by Means of Simplified Models for Low-Thrust, Many-Revolution Transfers by Federico Zuiani, Massimiliano Vasile

“…This paper presents a novel approach for the preliminary design of Low-Thrust, many-revolution transfers. The main feature of the novel approach is a considerable reduction in the control parameters and a consequent gain in computational speed. …”
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Effective Gait Abnormality Detection in Parkinson&#x2019;s Patients for Multi-Sensors Surveillance System by Abdulwahab Alazeb, Mouazma Batool, Naif Al Mudawi, Mohammed S. Alshehri, Sultan Almakdi, Nouf Abdullah Almujally, Asaad Algarni

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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…Through first-order approximation, the number of iterations in model parameter updates is significantly reduced, thereby improving the computational efficiency of the algorithm. …”
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Impact of Tunnel Stern Design on Hydrodynamic Characteristics of Catamarans by Osmanov Osman, Aksu Erhan

“…This study investigates the influence of stern tunnel modifications on catamarans, emphasising their unique design and hydrodynamic features. Computational fluid dynamics (CFD) is used to assess resistance and flow around the hull. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…The proposed model builds upon the UNET3 + architecture and integrates multi-scale feature extraction with enhanced optimization strategies to improve segmentation accuracy while significantly reducing computational complexity. …”
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基于UG的直齿锥齿轮二次开发及误差分析 by 陈立新, 茅兴飞

“…The influence of the differences of the conical involutes and the spherical involutes on the accuracy error of the model of bevel gear is analyzed.The Accuracy of involutes determine that of the gear tooth profile,so the establishment of ideal involutes can ensure the tooth accuracy.In the secondary development environment of UG/NX Grip,using the spherical involute equation and the structural features of the straight tooth bevel gear,a secondary development program of the gear is completed and run successful,By changing the gear basic parameters of the gears though the program of human-computer interaction,the 3D model of the ideal bevel gear can be achieved.…”
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ZoomHead: A Flexible and Lightweight Detection Head Structure Design for Slender Cracks by Hua Li, Fan Yang, Junzhou Huo, Qiang Gao, Shusen Deng, Chang Guo

“…The results showed that the integration of ZoomHead effectively improved the model’s detection accuracy, reduced the number of parameters and computations, and increased the FPS, achieving a good balance between detection accuracy and speed. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Compared with traditional models like the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) and Support Vector Machine (SVM), the proposed framework significantly improves the sensitivity and generalization ability for detecting various types of attacks through dynamic feature selection and parameter optimization. Experimental results demonstrate that the hybrid algorithm exhibits superior real-time responsiveness in binary classification tasks, thanks to its lightweight design that reduces dependency on computational resources. …”
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Thematic Content Analysis of Studies Using Generalizability Theory by Gülşen Taşdelen Teker, Neşe Güler

“…While a small subset of studies features mixed design, a largegroup features crossed design, with individuals as the object of measurement.The computer program most commonly used in analyses is EduG. …”
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