NLP-Driven Analysis of Pneumothorax Incidence Following Central Venous Catheter Procedures: A Data-Driven Re-Evaluation of Routine Imaging in Value-Based Medicine by Martin Breitwieser, Vanessa Moore, Teresa Wiesner, Florian Wichlas, Christian Deininger

“…<b>Methods:</b> We analyzed electronic health records from four university hospitals in Salzburg, Austria, focusing on X-rays performed between 2012 and 2021 following CVC procedures. A custom-built NLP algorithm identified cases of pneumothorax from radiologists’ reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, or missing data. …”
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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Building upon the RT-DETR framework, this study proposes a Multiscale Separable Deformable (MSD) module that integrates depthwise convolution with deformable convolution to enhance feature extraction capabilities while reducing computational load. Additionally, a Deformable Agent Attention (DAA) mechanism is designed to optimize attention weights through sparse queries, effectively improving detection accuracy for small targets and enhancing inference speed in complex scenarios. …”
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Research on Credit Risk Prevention in Supply Chain Finance Driven by Blockchain by Lin Kejing

“…Distributed ledger technology is utilized through blockchain to ensure the transparency and traceability of information, while smart contracts optimize the credit execution and supervision process, playing a key role in preventing and controlling credit risks. …”
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A Collaborative Transit Signal Priority Method Considering Gaming among Traffic Participants by Bing Wu, Haishan Wang, Yanli Wang, Ben Zhai, TanXing Xue

“…Different from previous studies, Co-TSP uses game theory to realize collaborative optimization, instead of transforming the problem into a single objective optimization problem by weighting. …”
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Efficient Context-Preserving Encoding and Decoding of Compositional Structures Using Sparse Binary Representations by Roman Malits, Avi Mendelson

“…In addition, the proposed algorithms allow to optimize the amount of compute and memory needed to achieve the desired encoding/decoding performance.…”
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User preference–based QoS-aware service function placement in IoT-Edge cloud by Briytone Mutichiro, Younghan Kim

“…The proposed solutions are evaluated based on different metrics and the obtained results show the gap between the heuristic user preference placement algorithm and the optimal solution to be minimal.…”
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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…Finally, we employ the Adam optimization algorithm to improve network convergence speed. …”
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Analytical Designing of Optimum Controller for Linear-Quadratic Functional with the Given Limiting Restrictions by V. I. Timoshpolskii, V. B. Kovalevskii, G. Romadan, P. V. Ilyusenko

“…This methodology may be used in resource saving technologies while soaking metal in the furnace. The paper reveals new methods of optimization that do not have analogues.…”
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Investigating the Machining Behavior of the Additively Manufactured Polymer-Based Composite Using Adaptive Neuro-Fuzzy Learning by Anastasios Tzotzis, Dumitru Nedelcu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis

“…Multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) algorithm was employed to minimize both <i>Ra</i> and <i>T</i> simultaneously. …”
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Rate of penetration prediction in drilling operations: a comparative study of AI models and meta-heuristic approaches by Fatemeh Mohammadinia, Ali Ranjbar, Fatemeh Ghazi, Seyyed Taha Hosseini

“…To further enhance model performance, metaheuristic optimization strategies such as the Crow Search Algorithm (CSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) are integrated. …”
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Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance by Z. H. Lai, S. B. Wang, G. Q. Zhang, C. L. Zhang, J. W. Zhang

“…Furthermore, the influence of algorithm parameters on the optimization results is discussed, and the optimization results of the Langevin system and the Duffing system are compared. …”
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Iterative approach for photonic crystal devices design by Pavel V. Mokshin, Dimitriy L. Golovashkin, Vladimir S. Pavelyev

“…The proposed approach differs from known general-purpose optimization methods (e.g., genetic algorithm or gradient procedures) by using diffraction pattern information at different frequencies while optimizing an element designed to operate at the selected wavelength. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…By harnessing dynamic decision-making capabilities of reinforcement learning (RL), we design an optimization architecture centered on the Q-learning mechanism and dual-strategy pools, which is integrated into the honey badger algorithm to form the RL-enhanced honey badger algorithm (RLEHBA). …”
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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…A low-carbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm (ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. …”
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Three-Dimensional Temperature Field Reconstruction Based on Tucker Decomposition and Acoustic Thermometry by Jidong Yan, Liansuo An, Pengbo Yao, Guoqing Shen, Shiping Zhang

“…Our method achieves faster reconstruction speeds (approximately 4 s) and higher accuracy, reducing reconstruction errors by over 10% compared to traditional acoustic thermometry. Additionally, the algorithm demonstrates strong anti-noise capabilities and applicability to temperature fields beyond the a priori conditions, making it a valuable tool for combustion optimization and load adjustment in coal-fired power plants.…”
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Calculation method of line loss rate of substation areas considering tidal current variation with photovoltaic power generation access by Shengbo Sun, Chao Cheng, Shujun Ji, Wei Cui, Wei Ge, Shifang Hao

“…The proposed method employs an improved K-medoids clustering algorithm for substation area classification, optimized by an enhanced Cuckoo algorithm to minimize classification errors. …”
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Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…By leveraging machine learning algorithms for facility siting, this study aims to enhance the overall urban layout while mitigating the inherent subjectivity in planning and location decisions, offering valuable insights for the site selection of diverse facilities.…”
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Joint Allocation of Shared Yard Space and Internal Trucks in Sea–Rail Intermodal Container Terminals by Xiaohan Wang, Zhihong Jin, Jia Luo

“…Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. …”
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A Robust Tomato Counting Framework for Greenhouse Inspection Robots Using YOLOv8 and Inter-Frame Prediction by Wanli Zheng, Guanglin Dai, Miao Hu, Pengbo Wang

“…Accurate tomato yield estimation and ripeness monitoring are critical for optimizing greenhouse management. While manual counting remains labor-intensive and error-prone, this study introduces a novel vision-based framework for automated tomato counting in standardized greenhouse environments. …”
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Simulation analysis of path planning for workpiece clamping robots based on digital twin technology by Xin PAN, Min LIANG, Yanchao YIN, Zhong CHEN

“…Targeting feasible regions through elliptical constraints accelerates convergence toward optimal paths, while techniques such as redundant node elimination and initial path smoothing further improve path quality, resulting in shorter, smoother routes. …”
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