SER Performance of Large Scale OFDM-SDMA Based Cognitive Radio Networks by Mostafa Hefnawi

“…This paper proposes an adaptive large scale multiple input multiple output-beamforming scheme (LSMIMO-BF) for uplink (UL) access in broadband wireless cognitive networks with multiple primary users (PUs) and secondary users (SUs) sharing the same spectrum and employing orthogonal frequency-division multiplexing (OFDM). The proposed algorithm seeks the optimal transmit/receive weight vectors that maximize the UL MIMO channel capacity for each cognitive user while controlling the interference levels to PUs. …”
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Hyperelastic behavior of cable gland silicon shroud: finite element analysis by Ganesh Bhoye, Ishant Jain

“…The results demonstrated the silicon shroud’s excellent radial expansion capacity, achieving a maximum observed displacement of 7.5 mm while maintaining induced stresses within acceptable limits. …”
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A variable threshold ring signature scheme for privacy protection in smart city blockchain applications by Guo Hongzhi, Qin Haowen

“…We further introduce an optimized batch-verification algorithm that cuts the number of expensive pairing checks per signature from O(n) to $$O(1) + n$$ O ( 1 ) + n , dramatically improving throughput. …”
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A data-driven, cloud-based approach for forest aboveground biomass mapping using GEDI and other earth observation data: an ecoregion-specific Investigation across the state of Alab... by Janaki Sandamali, Lana L. Narine

“…GEDI data preparation was performed locally, while the analysis was conducted within GEE using the Random Forest algorithm. …”
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DSGD++: Reducing Uncertainty and Training Time in the DSGD Classifier through a Mass Assignment Function Initialization Technique by Aik Tarkhanyan, Ashot Harutyunyan

“…We present a method for the Dempster-Shafer Gradient Descent (DSGD) algorithm that significantly reduces training time—by a factor of 1.6—and also reduces the uncertainty of each rule (a condition on features leading to a class label) by a factor of 2.1, while preserving accuracy comparable to other statistical classification techniques. …”
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Fluid Dynamics of Biomimetic Pectoral Fin Propulsion Using Immersed Boundary Method by Ningyu Li, Yumin Su

“…The results show that there is an optimal phase angle and Strouhal number for this complicated fin. …”
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Improved Hadamard Decomposition and Its Application in Data Compression in New-Type Power Systems by Zhi Ding, Tianyao Ji, Mengshi Li

“…Second, we develop an enhanced gradient descent algorithm incorporating adaptive regularization and early stopping mechanisms, achieving superior convergence performance in optimizing the Hadamard approximation. …”
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Research and application of flexible starting method for metro trains with permanent magnet motors based on PI control by LIU Zhicheng, CHEN Xijun, HE Ye, HU Hui

“…This solution focuses on optimizing cooperation among various subsystems during the starting process. …”
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Design and Performance Analysis of Fuzzy Logic Controller for Solar Photovoltaic System by Kumuthawathe Ananda-Rao, Steven Taniselass, Afifah Shuhada Rosmi, Aimi Salihah Abdul Nasir, Nor Hanisah Baharudin, Indra Nisja

“…The system is modeled and simulated using MATLAB/Simulink, incorporating the PV system, MPPT algorithm, and models for the PV module and boost converter. …”
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Research on Mine-Personnel Helmet Detection Based on Multi-Strategy-Improved YOLOv11 by Lei Zhang, Zhipeng Sun, Hongjing Tao, Meng Wang, Weixun Yi

“…In the complex environment of fully mechanized mining faces, the current object detection algorithms face significant challenges in achieving optimal accuracy and real-time detection of mine personnel and safety helmets. …”
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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

“…This can facilitate the inverse-free fast deep learning algorithm of AD-TSK while maintaining interpretability. …”
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Intelligent Office Lighting Control Using Natural Light and a GA-BP Neural Network-Based System by Rongmeng Zhang, Ruiqi Li, Junbai Lu, Haiqian E, Haotian Wang, Xinyu Zhao, Yingming Gao, Zhisheng Wang

“…This study addresses the issue of natural glare by proposing a method that uses a genetic algorithm (GA) to optimize a backpropagation (BP) neural network model. …”
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Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

“…The mean squared error (MSE) was used to evaluate the performance of models, which was 0.0535, 0.0704, and 0.0908 for the perceptron neural network in the Levenberg-Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, respectively. Also, the MSE value for the neuro-fuzzy model in the optimization and hybrid algorithms was 0.0190 and 0.0102, respectively. …”
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Financial Management of Innovative Activity by V. P. Shestak, E. I. Moreva, I. G. Tyutyunnik

“…A form of control functional was obtained on the sets of observable characteristics of the controlling and controlled subsystems while optimizing the results of innovative activity due to the feedback channel. …”
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Automation of reversible steganographic coding with nonlinear discrete optimisation by Ching-Chun Chang

“…Experimental results validate the near-optimality of the proposed optimisation algorithm when benchmarked against a brute-force method.…”
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Time-adaptive phase estimation by Brennan de Neeve, Andrey V. Lebedev, Vlad Negnevitsky, Jonathan P. Home

“…Phase estimation is known to be a robust method for single-qubit gate calibration in quantum computers, while Bayesian estimation is widely used in devising optimal methods for learning in quantum systems. …”
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Fourier Analysis of CMFD Method in Cylindrical Geometry by WEN Yuchen, HAO Chen, WANG Yizhen

“…The coarse mesh finite difference (CMFD) method has been widely adopted as an acceleration algorithm for neutron transport calculations, effectively reducing computational costs and improving convergence. …”

Machine learning approaches for predicting the link of the global trade network of liquefied natural gas. by Pei Zhao, Hao Song, Guang Ling

“…This study demonstrates that machine learning algorithms-specifically random forest and decision tree-outperform in predicting links within the global LNG trade network based on local information proximity, while the graph attention network, a deep learning model, exhibits stable optimization and effective feature learning. …”
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Unmanned aerial vehicle image stitching based on multi‐region segmentation by Weidong Pan, Anhu Li, Xingsheng Liu, Zhaojun Deng

“…Most existing image stitching methods based on optimal seamline searching algorithms can eliminate defects such as ghosting and distortion in stitched images, which unfortunately suffer from the problem that the seamline may cross those regions with significant geometric misalignment between different images. …”
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Dynamic Evacuation Shelter Allocation in Response to Human Mobility: A Case Study of Taipei City by Chang-Hung Shih, Cheng-Yun Wu, Shu-Ping Tseng, Yi-Lin Huang, Rong-Pu Jhuang, Yi-Chung Chen, Tien-Yi Yang, Wei-Ting Chen

“…Weighted Voronoi diagrams delineated regions to identify optimal evacuation points, while real-time SMS notifications through base station positioning disseminated evacuation information to the public. …”
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