De-speckling of medical ultrasound image using metric-optimized knowledge distillation by Mostafa Khalifa, Hanaa M. Hamza, Khalid M. Hosny

“…This noise varies with image intensity, which limits the effectiveness of traditional denoising methods. We introduce the Metric-Optimized Knowledge Distillation (MK) model, a deep-learning approach that utilizes Knowledge Distillation (KD) for denoising ultrasound images. …”
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Schur Complement Optimized Iterative EKF for Visual–Inertial Odometry in Autonomous Vehicles by Guo Ma, Cong Li, Hui Jing, Bing Kuang, Ming Li, Xiang Wang, Guangyu Jia

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Choosing the optimal dilution medium for pooled platelet concentrates, thawed after cryopreservation by M. S. Makarov, M. V. Storozheva, N. V. Borovkova, A. Yu. Bulanov, I. N. Ponomarev

“…Background. The current methods of cryopreservation, working with pooled platelet concentrates (PPC), require optimization. …”
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The Shrinking of Beijing and the Rising of Xiong’an: Optimize Population Migration in terms of Transport Service by Hongzhi Lin

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Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning by Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang

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Integrated Approach to Optimizing Selection and Placement of Water Pipeline Condition Monitoring Technologies by Diego Calderon, Mohammad Najafi

“…This article introduces a unified framework and methods for optimally selecting condition monitoring technologies while locating their deployment at the most vulnerable pipe segments. …”
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Research on process optimization and trajectory planning of EA4T axle robot grinding by Feng ZHANG, Zhongli FENG, Feng XU, Deming ZHANG, Xiangrui ZENG, Jianwei MA, Shilei ZHANG

“…Using this parameter combination, the post-grinding surface roughness reaches 0.338 μm, and the material removal depth is 1.67 μm, effectively improving surface quality while meeting specification requirements. (3) The off-line programming method is used to plan the grinding trajectory. …”
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Enhancing operational efficiency through overall equipment efficiency optimization and Kaizen initiatives. by Abu M Fuad, Nusra Akter Takia, Hasin Ahmad Zafir, Omar Farrok

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Structure Optimization in Deep Neural Networks with Synaptic Pruning Based on Connection Appraisal by Aghil Ahmadi, Reza Mahboobi Esfanjani

“…In this study, we propose a novel pruning method inspired by biological synaptic pruning that adaptively optimizes deep neural network structures. …”
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Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images by Rakoth Kandan Sambandam, Sasikala Jayaraman

“…The multilevel segmentation problem is formulated as an optimization problem and solved using the SADFO. The method optimizes the threshold values through effectively exploring the solution space in obtaining the global best solution. …”
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On Optimal Operator for Combining Left and Right Sole Pressure Data in Biometrics Security by Takahiro Takeda, Kei Kuramoto, Syoji Kobashi, Yutaka Hata

“…This paper describes optimal operator for combining left and right sole pressure data in a personal authentication method by dynamic change of sole pressure distribution while walking. …”
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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

“…The proposed model enhances the structural expressiveness of the sparse component while preserving the global low-rank structure. To solve the resulting optimization problem efficiently, we develop a tailored algorithm based on operator splitting techniques, significantly improving computational efficiency without sacrificing accuracy. …”
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Optimization of sludge recirculation for sustainable water treatment at Ait Massoud dam Morocco by Radouane El Amri, Rajaa Zahnoune, Otmane Boudouch, Reda Elkacmi

“…A techno-economic analysis revealed that applying this method on the scale of the plant (6 000 m3/h) would result in daily savings of around 3,715 euros, while reducing the disposal of almost 7,200 m3/day of sludge, thus helping to reduce the environmental footprint. …”
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Optimization for threat classification of various data types-based on ML model and LLM by Chaerim Hong, Taeyeon Oh

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Precision nitrogen management for optimal yield and cannabinoid profile in CBD hemp agronomy by Dinesh Panday, Bharat Sharma Acharya, Nikita Bhusal, Reza Keshavarz Afshar, Andrew Smith, Arash Ghalehgolabbehbahani

“…There was a significant interaction of N rate and application method, impacting biomass yield, while the N rate also influenced CBD concentration. …”
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Interpretable Machine Learning for Population Spatialization and Optimal Grid Scale Selection in Shanghai by Yuan Cao, Hefeng Wang, Lanxuan Guo, Anbing Zhang, Xiaohu Wu

“…However, when using machine learning methods for population spatialization, issues such as data overfitting and limited interpretability need to be addressed. …”
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Optimization of Surface Quality and Power Consumption in Machining Hardened AISI 4340 Steel by Dennis Ochengo, Li Liang, Zhao Wei, He Ning

“…The Taguchi method, based on the L18 orthogonal array, the variance analysis, the signal-to-noise ratios, and the response surface methodology have been used to optimize surface roughness (Ra) and cutting power (Cp). …”
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An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). …”
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An Operation Optimization Strategy of the Combined Power Generation System with Wind Power & Pumped Storage Based on Improved Whale Algorithm by LI Kecheng, YANG Ning

“…Simulation results show that the convergence, distribution and uniformity of the improved multi-objective whale optimization algorithm are better than the multi-objective particle swarm optimization algorithm and the basic multi-objective whale optimization algorithm, which verifies the effectiveness and superiority of the proposed improved multi-objective optimization method. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…PPO enhances policies in continuous action spaces to guarantee reliable performance in real-time, dynamic IoT settings. This method achieves an optimal equilibrium between policy learning and optimisation, rendering it suitable for contemporary IoT systems. …”
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