Tactical intent-driven autonomous air combat behavior generation method by Xingyu Wang, Zhen Yang, Shiyuan Chai, Jichuan Huang, Yupeng He, Deyun Zhou

“…Built around this, the decision-making process of pilot behavior is analyzed, and a reward mapping model from intent to behavior is established. Finally, to address the problems of poor stability and slow convergence speed of deep reinforcement learning algorithms in large-scale state-action spaces, the dueling-noisy-multi-step DQN algorithm is devised, which not only improves the accuracy of value function approximation but also enhances the efficiency of space exploration and network generalization. …”
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Modern aspects of diagnosis and treatment of patients with spontaneous coronary artery dissection by Sh. Sh. Zainobidinov, D. A. Khelimsky, A. A. Baranov, A. G. Badoyan, O. V. Krestyaninov

“…The angiographic classification of SCAD, the diagnostic algorithm and the choice of optimal treatment depending on clinical manifestations are also described.…”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…Logistic Regression and Multilayer Perceptron also showed robust results, but SGD was superior in most metrics. For the Rules classifiers, JRip outperformed others due to its iterative rule optimization, whereas OneR's simplicity resulted in the lowest performance. …”
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Preliminary analysis of acoustic detection of the Red-throated Caracara in northern Costa Rica by Roberto Vargas-Masís, Diego Quesada

“…Advances in automatic acoustic detection have transformed bird ecology, allowing researchers to analyze bird populations using pattern matching algorithms, machine learning, and random forest models. …”
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Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study by Hajin Kim, Bo Kyung Cha, Kyuseok Kim, Youngjin Lee

“…Computed tomography (CT) imaging using low-dose radiation effectively reduces radiation exposure; however, it introduces noise amplification in the resulting image. This study models an adaptive nonlocal total variation (NL-TV) algorithm that efficiently reduces noise in X-ray-based images and applies it to low-dose CT images. …”
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Numerical analysis method of stress wave transmission attenuation of coal and rock structural plane by Wenlong SHEN, Renren ZHU, Ziqiang CHEN, Guocang SHI

“…The simulation and machine learning of stress wave transmission in the experimental process of Split Hopkinson Pressure Bar (SHPB) were carried out by combining the Barton-Bandis nodal ontology model, UDEC discrete element simulation and Gray Wolf Algorithm optimized BP neural network technology. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…A hierarchical neural network structure is designed to address the characteristics of different scales in distinct layers. Key model parameters are optimized, and a sensitivity analysis is conducted. …”
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SwinFishNet: A Swin Transformer-based approach for automatic fish species classification using transfer learning. by Ebru Ergün

“…Images were preprocessed by resizing to 224 [Formula: see text] 224 pixels, normalizing, and converting to tensor format for compatibility with deep learning models. Transfer learning was applied using the ST, which was fine-tuned on these datasets and optimized with the AdamW algorithm. …”
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Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
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A New Routing Protocol for Heterogeneous Mobile Ad Hoc Networks by Bahareh Shafaie, Marjan Kuchaki Rafsanjani

“…Homogeneous Mobile Ad hoc Networks are networks in which all nodes have the same sources and capabilities, and this is in contrast with nature of MANETs because nodes are independent and have different sources, capabilities (such as battery lifetime, bandwidth, transmission range,...) and mobility. In this paper, we improve one of proactive routing protocols named OLSR (Optimized Link State Routing Protocol) so that this protocol becomes appropriate for HMANET and do not lose its capability and scalability. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. …”
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Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…<b>Methods</b>: This study investigates whether architectural design elements in Transformer-based generative models contribute to a measurable divergence from human reasoning. …”
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Performance Analysis of MVDR Beamformer Applied on an End-fire Microphone Array Composed of Unidirectional Microphones by Zoran ŠARIĆ, Miško SUBOTIĆ, Ružica BILIBAJKIĆ, Marko BARJAKTAROVIĆ, Nebojša ZDRAVKOVIĆ

“…Thirdly, we propose an adaptation of its adaptive algorithm during the pause of speech, which improves its robustness against the room reverberation and deviation from the optimal receiving direction. …”
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Automatic mosaic method of remote sensing images based on machine vision by S.P. Gao, M. Xia, S.J. Zhang

“…To address the above issues, this study proposes an improved remote sensing image mosaic model on the bias of the Scale Invariant Feature Transform (SIFT) algorithm. …”
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Risk identification and assessment of Internet public opinion on public emergencies based on Bayesian network and association rule mining by Mengjie You, Xuwei Pan, Chuwen Zhu

“…The core innovation lies in designing an improved scheme based on the CBA (Classification Based on Associations) algorithm to overcome the limitation of traditional association rule mining in handling non-Boolean data, thereby effectively extracting the correlations among public opinion risk factors to optimize the topological structure of the BN. …”
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AI Applications for Chronic Condition Self-Management: Scoping Review by Misun Hwang, Yaguang Zheng, Youmin Cho, Yun Jiang

“…Conversational AI (21/66, 32%) and multiple machine learning algorithms (16/66, 24%) were the most used AI technologies. …”
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Data and Knowledge Dual-Driven Creep Life Prediction for Austenitic Heat-Resistance Steel by Xiaochang Xie, Mutong Liu, Ping Yang, Zenan Yang, Chengbo Pan, Chenchong Wang, Xiaolu Wei

“…In this study, we collected 216 creep data of austenitic heat-resistant steel, selected a variety of different machine learning algorithms to establish creep life prediction models, calculated and introduced a large amount of physical metallurgy knowledge highly related to creep based on Thermo-Calc, and converted the creep life into the form of the Larson–Miller parameter to optimize the data distribution, which effectively improved the prediction accuracy and interpretability of the model. …”
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Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…Thus, Machine learning predictive algorithms have the potential to improve the quality of care and predict the needs of HIV patients by analyzing huge amounts of data, and enhancing prediction capabilities. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…Experimental results show that the validation loss of this method reaches 0.007, with a mean absolute error of 0.0148, outperforming other comparative models. This study enriches the theory of gray mold control and provides information technology for optimizing and selecting its inhibitors.…”
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