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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An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…However, test suites in open-source libraries often grow large, redundant, and difficult to maintain. Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
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Research on adaptive motion methods of flexible knee joints based on the artificial potential field by LUO Tianhong, LI Chaoyang, MA Xiangyu, FU Qiang, FANG Shangchen

“…ObjectiveConsidering the tracking error of the motion trajectory of the flexible knee joint and the influence of the flexibility on the joint motion, an adaptive impedance control method based on the artificial potential field (APF) was proposed.MethodsThe method took the pneumatic artificial muscle as the power source, and by establishing a kinetic model between the human-machine interaction moment and the knee joint motion angular velocity, the size of the impedance control parameter could be adjusted in real time, so as to realize the following of the motion of the exoskeleton knee joint and the human leg; the control parameter was optimized using the APF concept to enhance the effect of the motion following, and the effectiveness of the algorithm was verified by simulation and test.ResultsThe results show that the proposed APF-based adaptive impedance control method enables the exoskeleton to adaptively track the human motion trajectory and can reduce the error of trajectory tracking, thus improving the suppleness of the flexible knee joint control and enhancing the human-machine synergy of the system.…”
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Predicting Survival Rates in Brain Metastases Patients from Non‐Small Cell Lung Cancer Using Radiomic Signatures Associated with Tumor Immune Heterogeneity by Fuxing Deng, Gang Xiao, Guilong Tanzhu, Xianjing Chu, Jiaoyang Ning, Ruoyu Lu, Liu Chen, Zijian Zhang, Rongrong Zhou

“…Bidirectional stepwise logistic regression is employed to identify significant variables, facilitating the construction of a prognostic model, which is benchmarked against four machine learning algorithms. …”
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Predicted indirectly recognizable HLA epitopes scores and clinical outcomes after haploidentical stem cell transplantation in pediatric patients with relapsed neuroblastoma by Eun Seop Seo, Eun Seop Seo, In Hwa Jeong, In Hwa Jeong, Hee Young Ju, Ju Kyung Hyun, Ji Won Lee, Keon Hee Yoo, Won Young Heo, Ki Woong Sung, Hee Won Cho, Eun-Suk Kang

“…IntroductionThe Predicted Indirectly ReCognizable HLA Epitopes (PIRCHE) model is a recently developed algorithm that predicts indirect T-cell recognition by calculating the number of such epitopes in donor-recipient pairs.MethodsIn this study, the clinical significance of PIRCHE was evaluated in pediatric patients with relapsed/progressed neuroblastoma undergoing haploidentical stem cell transplantation (haplo-SCT).ResultsA higher PIRCHE-I score was associated with faster platelet recovery (P = 0.007) and lower incidence of hemorrhagic cystitis (13% vs. 41%, P = 0.028) and invasive fungal infections (0% vs. 18%, P = 0.045). …”
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A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

“…., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…We propose CWA-YOLO, a detection framework integrating multi-scale feature fusion and an enhanced small-object detection head into YOLOv8 to improve accuracy across variable conditions. Additionally, a federated learning (FL) system tailored for substations enables collaborative model training without centralized data sharing, addressing privacy concerns and data heterogeneity. …”
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Numerical Methodology for Enhancing Heat Transfer in a Channel with Arc-Vane Baffles by Piphatpong Thapmanee, Arnut Phila, Khwanchit Wongcharee, Naoki Maruyama, Masafumi Hirota, Varesa Chuwattanakul, Smith Eiamsa-ard

“…The calculations utilize the finite volume method, and the SIMPLE algorithm is executed with the QUICK scheme. For the analysis of turbulent flow, the finite volume method with the Renormalization Group (RNG) <i>k-ε</i> turbulence model was used. …”
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Methodological Tools for Evaluating Effectiveness of Capital Construction Projects of Oil Producing Enterprises by E. L. Chazov, V. P. Grakhov, O. L. Simchenko

“…Due to the fact that most of the large oil fields in Russia, characterized by high production costs, are at the final stage of development; the issue of cost optimization has become increasingly important in recent years. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…After the water conservation retrofit, non-saline soil increased by 326.5 km2, indicating improved soil conditions. The overall accuracy of the Gradient Boosting Tree classification model is 95.00 % and the Kappa coefficient is 0.93, which is the optimal model for land use type classification. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…To tackle these challenges, this article reformulates a novel image fusion model by incorporating Hankel tensor subspace representation (HTSR) for quality improvement of reconstruction images. …”
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Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning by Feng Lu, Yingying Liu, Zhen Chen, Shuning Chen, Weidong Liang, Fuzhou Hua, Maolin Zhong, Lifeng Wang

“…A total of 113 diagnostic models were developed through 12 machine learning algorithms, with the optimal model, “Lasso + Stepglm[both],” featuring six genes: Abca1, Cdh1, Glipr1, Glt8d2, Il10ra, and Pde5a. …”
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Artificial intelligence assisted wearable flexible sensors for sports: research progress in technology integration and application by Jie Wu, Zhiqi Mo, Xing Gao, Wanru Xin, Weiquan Shi, Jaeyoung Park

“…This article provides a comprehensive review of the latest advancements in artificial intelligence-assisted wearable flexible sensors for motion detection, focusing on the operational mechanisms, performance enhancements, and algorithm optimization of convolutional neural networks (CNN), temporal data modeling, multimodal fusion technology, and natural language generation. …”
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Numerical Investigation on Influential Factors for Quality of Smooth Blasting in Rock Tunnels by Baoping Zou, Zhipeng Xu, Jianxiu Wang, Zhanyou Luo, Lisheng Hu

“…As prerequisite for the evaluation of the blasting quality, effective identification of the influential factors affecting smooth blasting usually plays a significant role in the improvement of smooth blasting design. Compared to the expensive and time-consuming experiments including physical modelling and field tests, numerical modelling, as a cost-efficient approach, offers an attractive alternative to investigate the influential factors in terms of weight, which might be more applicable and reliable for the optimization of smooth blasting parameters. …”
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Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers by Vivek Singh, Shikha Chaganti, Matthias Siebert, Sowmya Rajesh, Andrei Puiu, Raj Gopalan, Jamie Gramz, Dorin Comaniciu, Ali Kamen

“…For most screening programs, age and clinical risk factors such as family history are part of the initial risk stratification algorithm. …”
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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…These features are then combined using a softmax-based attention mechanism to optimize the contribution of each component. To classify the reviews, we introduce a personalized multicentroid K-means algorithm, which improves traditional K-means by allowing a more precise clustering of false and genuine reviews. …”
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Virtual and Real Occlusion Processing Method of Monocular Visual Assembly Scene Based on ORB-SLAM3 by Hanzhong Xu, Chunping Chen, Qingqing Yin, Chao Ma, Feiyan Guo

“…The method proposes optimizing ORB-SLAM3 for matching and depth point reconstruction using the MNSTF algorithm. …”
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Hand–Eye Separation-Based First-Frame Positioning and Follower Tracking Method for Perforating Robotic Arm by Handuo Zhang, Jun Guo, Chunyan Xu, Bin Zhang

“…Additionally, the computational complexity of high-precision detection models limits deployment on resource-constrained edge devices, such as industrial controllers. …”
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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…In addition, the improved Channel Attention Concatenation (CAC) strategy adaptively learns channel-wise importance weights during feature concatenation, further optimizing multi-scale semantic feature fusion and enhancing the model’s sensitivity to critical crater features. …”
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The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa by F. Merk, T. Schaffhauser, F. Anwar, Y. Tuo, J.-M. Cohard, M. Disse

“…The comprehensive parameter set is then optimized using the shuffled complex evolution algorithm. …”
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