Tabu Search for Multi-Objective Hub Location Planning: A Case Study of the Northern Rail Line, Thailand by Nguyen Dang Nha, Pham Van Nam, Chanta Sunarin, Sangsawang Ornurai

“…This approach allows the model to handle large-scale problems within a reasonable time frame while generating Pareto fronts. The results demonstrate the effectiveness of multi-objective optimization in supporting rail hub location planning.…”
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Design of 3D Environment Combining Digital Image Processing Technology and Convolutional Neural Network by Xiaofei Lu, Shouwang Li

“…To enhance 3D reconstruction accuracy, this study proposes a digital image processing technology that combines binocular camera calibration, stereo correction, and a convolutional neural network (CNN) algorithm for optimization and improvement. By employing the refined stereo-matching algorithm, a 3D reconstruction model was developed to augment 3D environment design and reconstruction accuracy while optimizing the 3D reconstruction effect. …”
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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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Quantum circuit unoptimization by Yusei Mori, Hideaki Hakoshima, Kyohei Sudo, Toshio Mori, Kosuke Mitarai, Keisuke Fujii

“…In this paper, we define and construct a quantum algorithmic primitive called quantum circuit unoptimization, which makes a given quantum circuit complex by introducing some redundancies while preserving circuit equivalence, i.e., the inverse operation of circuit optimization. …”
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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…The improved detection algorithm maintains high accuracy while achieving faster inference speed and fewer model parameters. …”
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OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes by Runze Fang, Huamao Huang, Nuoyan Guo, Haichuan Wei, Shiyi Wang, Haiying Hu, Ming Liu

“…Channel pruning further reduces the decoder’s parameters, decreasing model size and computational requirements while maintaining precision. The enhanced algorithm achieved a mean average precision (mAP) of 89.4% ( $$\hbox {mAP}_{50}$$ ) and 78.3% ( $$\hbox {mAP}_{50:95}$$ ), while the number of model parameters was reduced to 9.9 M, the model size was reduced to 40.1 MB, and the number of floating point operations per second (FLOPs) was reduced to 31.2 G. …”
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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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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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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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Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…The results indicate that this framework preserves high accuracy while significantly reducing time requirements compared to Grid Search and Genetic Algorithm optimization.…”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…Empirical evidence demonstrates that this framework not only accurately captures the diverse characteristics of different data components but also significantly outperforms traditional benchmark models in predictive accuracy. By optimizing the GRU model with the grey wolf optimizer (GWO) algorithm, the framework enhances both prediction stability and adaptability, while the nonlinear integration approach effectively mitigates error accumulation. …”
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Computation Offloading and Resource Allocation for Energy-Harvested MEC in an Ultra-Dense Network by Dedi Triyanto, I Wayan Mustika, Widyawan

“…Subsequently, the MILP approach is employed to select the optimal offloading option while ensuring fairness-oriented resource allocation among users to improve overall system performance and user satisfaction. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Compared to RNNs and their variants, the LTCA–TCN algorithm yields superior prediction results while maintaining a simpler structure and requiring fewer computational resources. …”
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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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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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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Results: The results demonstrated that optimization algorithms reduced transportation costs and carbon emissions. …”
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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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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…These advancements also make education more inclusive, helping to bridge accessibility gaps for underserved communities. However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. …”
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Inflammation Biomarker-Driven Vertical Visualization Model for Predicting Long-Term Prognosis in Unstable Angina Pectoris Patients with Angiographically Intermediate Coronary Lesio... by Zhou B, Tan W, Duan S, Wang Y, Bian F, Zhao P, Wang J, Yao Z, Li H, Hu X, Wang J, Liu J

“…Various inflammatory markers are employed in clinical practice to predict patient prognosis and optimize clinical decision-making in the management of ACS. …”
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Assessing tafenoquine implementation in Brazil: a qualitative evaluation of perceptions of healthcare providers and Plasmodium vivax patients (QualiTRuST Study) by Alicia P. C. Santos, Marcelo A. M. Brito, Ana P. S. Oliveira, Rafaela N. Dávila, Hiran S. S. Gama, Evellyn A. R. T. Silva, Hélio A. Amazonas Jr., Patrícia C. S. Balieiro, Rosilene Rufatto, Penny Grewal Daumerie, Cássio R. L. Peterka, Dhélio Batista Pereira, Marcus V. G. Lacerda, Felipe L. G. Murta

“…The findings underscore the importance of adaptive training to optimize P. vivax radical cure implementation.…”
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