An Advanced Recomposition-Based Displaying Technique: Maximizing Image Reconstruction for Virtual Museum Applications by Jingjie Zhao, Xin Shi, Olga Yezhova, Qinchuan Zhan, Xijing Zhang

“…The approach effectively balances algorithmic precision with human-centered aesthetics, advancing AI-driven scene analysis and visual recomposition, while enhancing interactivity and immersion for a more engaging and adaptive user experience.…”
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Acute severe ulcerative colitis: using JAK-STAT inhibitors for improved clinical outcomes by Shruthi Karthikeyan, Chetan Ambastha, Kian Keyashian

“…Here we discuss methods to optimize the dosing of IFX to maximize its efficacy, while exploring recent work done on the safety and efficacy of JAK-STAT inhibitors as a salvage therapy, therefore suggesting a novel treatment algorithm to improve clinical outcomes in medically managed ASUC patients.…”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Combined with an Inner Generalized Intersection-over-Union (Inner-GIoU) loss function to optimize bounding box geometric consistency, MLD-DETR achieves 36.7% AP50% and 14.5% APs on the VisDrone2019 dataset, outperforming the baseline RT-DETR by 3.2% and 1.8% in accuracy while achieving 20% parameter reduction and maintaining computational efficiency suitable for UAV platforms equipped with modern edge computing hardware. …”
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Visual information perception system of coal mine comprehensive excavation working face for edge computing terminal by Dongyang Zhao, Guoyong Su, Pengyu Wang

“…Secondly, the pruning and distillation algorithm is used to lighten the FSBD‐YOLOv5s model, and the model complexity is greatly reduced while maintaining the model detection accuracy. …”
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A Reinforcement Learning-based Intelligent Learning Method for Anti-active Jamming in Frequency Agility Radar by J. Wei, L. Yu, Y. Wei, R. Xu

“…This model includes five submodules: signal processing, anti-jamming evaluation, target detection, optimization constraint design, and optimization algorithm design. …”
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A novel LSTPA methodology for managing energy in electrical/thermal microgrids through CHP, battery resources, thermal storage, and demand-side strategies by Elmira Akhavan Maroofi, Mahmoud Samiei Moghaddam, Azita Azarfar, Reza Davarzani, Mojtaba Vahedi

“…This study offers valuable insights for policymakers and system operators in optimizing microgrid energy management while balancing efficiency, cost, and reliability. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. …”
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Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems by Jun Zha, Xiaofei Peng, Zhiyan Cai, Fei Xue

“…To address this gap, this research proposes a novel method that integrates simulation with a data-driven optimization strategy. The core of our approach involves using the K-means clustering algorithm to optimize the selection of temperature measurement points on the hydrostatic screw nut, ensuring a more representative thermal characterization. …”
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Real-time urban regional route planning model for connected vehicles based on V2X communication by Pangwei Wang, Hui Deng, Juan Zhang, Mingfang Zhang

“…Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. …”
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A Heterogeneous Image Registration Model for an Apple Orchard by Dongfu Huang, Liqun Liu

“…Then, we used the Sinkhorn AutoDiff algorithm to iteratively optimize and solve the optimal transmission problem, achieving optimal matching between feature points. …”
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Analysis and Research on Intelligent Logistics Data under Internet of Things and Blockchain by Yige Li

“…Furthermore, the system efficiently manages high data volumes while upholding robust data processing capabilities, owing to the optimization of smart contracts and decentralized storage mechanisms. …”
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Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…Our results show that the Random Forest algorithm achieves the highest prediction accuracy, while a convolutional neural network demonstrates the best mitigation performance with accuracy. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…It utilizes independent modules to process high- and low-resolution features, adaptively adjusts receptive field sizes, and incorporates dynamic sparse attention mechanisms to optimize feature information at each resolution, by integrating optimal features across multiple scales into density maps for counting evaluation. …”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…Through a series of experimental analyses, it was evident that the performance of the Benthos-DETR network surpasses existing target detection algorithms, achieving an optimal equilibrium between high recognition precision and a trim network scale.…”
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Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…Different spectral similarity metrics, and weighted combinations of spectral and geographical similarity matrices were tested to optimize the selection of local training samples. As a result, the optimal modelling strategy, with partial least squares regression (PLSR) as the local fitting algorithm, consistently produced superior performances (R2: 0.66 to 0.82) than the conventional global modelling approach (R2: 0.59 to 0.77) for all three data types. …”
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Accuracy Assessment of Tomato Harvest Working Time Predictions from Panoramic Cultivation Images by Hiroki Naito, Tomohiko Ota, Kota Shimomoto, Fumiki Hosoi, Tokihiro Fukatsu

“…This study highlights the system’s potential to optimize harvesting plans and labor allocation, providing a novel tool for reducing labor costs while maintaining efficiency in large-scale tomato greenhouse production.…”
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Improved Block Element Method for Simulating Rock Failure by Yan Han, Qingwen Ren, Lei Shen, Yajuan Yin

“…As the innovation of this work, the iterative algorithm is combined with polygonal geometric features so that the area–perimeter fractal dimension can be introduced to optimize random Voronoi grids. …”
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An Adaptive Wireless Droop Control with Adaptive Virtual Resistance for Power Sharing Management in MTDC Grid by Hasan Alrajhi , Ahmed Al-Zahrani , Syed A. Raza , Fahad Al-Shareef 

“…Additionally, this communication-free scheme includes a power management algorithm that controls power sharing during peak hours of the inverters among the rectifiers as per mutual agreements between the operators to mitigate the risk of a system overload and optimize the power sharing. …”
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Recommendations on Chronic Constipation (Including Constipation Associated with Irritable Bowel Syndrome) Treatment by Pierre Paré, Ronald Bridges, Malcolm C Champion, Subhas C Ganguli, James R Gray, E Jan Irvine, Victor Plourde, Pierre Poitras, Geoffrey K Turnbull, Paul Moayyedi, Nigel Flook, Stephen M Collins

“…The myriad of treatment options available to Canadian physicians can be confusing; thus, the main aim of the recommendations and treatment algorithm is to optimize the approach in clinical care based on available evidence.…”
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Multi-exit Kolmogorov–Arnold networks: enhancing accuracy and parsimony by James Bagrow, Josh Bongard

“…This architecture provides deep supervision that improves training while discovering the right level of model complexity for each task. …”
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