摘要：In response to the challenge of low detection accuracy and susceptibility to missed and false detections of small targets in unmanned aerial vehicles(UAVs)aerial images,an improved UAV image target detection algorithm based on YOLOv8 was proposed in this *** begin with,the CoordAtt attention mechanism was employed to enhance the feature extraction capability of the backbone network,thereby reducing interference from ***,the BiFPN feature fusion network with an added small object detection layer was used to enhance the model's ability to perceive for small ***,a multi-level fusion module was designed and proposed to effectively integrate shallow and deep *** use of an enhanced MPDIoU loss function further improved detection *** experimental results based on the publicly available VisDrone2019 dataset showed that the improved model outperformed the YOLOv8 baseline model,mAP@0.5 improved by 20%,and the improved method improved the detection accuracy of the model for small targets.

摘要：The correct identification of traffic signs plays an important role in automatic driving technology and road safety ***,to address the problems of misdetection and omission in traffic sign detection due to the variety of sign types,significant size differences and complex background information,an improved traffic sign detection model for RT-DETR was proposed in this ***,the HiLo attention mechanism was added to the Attention-based Intra-scale Feature Interaction,which further enhanced the feature extraction capability of the network and improved the detection efficiency on high-resolution ***,the CAFMFusion feature fusion mechanism was designed,which enabled the network to pay attention to the features in different regions in each *** on this,the model could better capture the remote dependencies and neighborhood feature correlation,improving the feature fusion capability of the ***,the MPDIoU was used as the loss function of the improved model to achieve faster convergence and more accurate regression *** experimental results on the TT100k-2021 traffic sign dataset showed that the improved model achieves the performance with a precision value of 90.2%,recall value of 88.1%and mAP@0.5 value of 91.6%,which are 4.6%,5.8%,and 4.4%better than the original RT-DETR model *** model effectively improves the problem of poor traffic sign detection and has greater practical value.

摘要：In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different *** OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed *** this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing ***,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation ***,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information ***,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion *** innovative structure helped the model to better focus on the target *** precision and robustness of oriented target detection were also *** results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original *** improvement is effective in detecting small targets and complex scenes.

摘要：Deep learning techniques are revolutionizing the developmentof medical image *** the advancement of Transformer models,especially ViT and Swin-Transformer,which enhances the remote-dependent modeling capability of the model through the self-attention mechanism,better segmentation performance can be ***,the high computational cost of Transformer has motivated researchers to explore more efficient models,such as the Mamba model based on state-space modeling(SSM),and for the field of medical segmentation,reducing the number of model parameters is also *** this study,a novel asymmetric model called LA-UMamba was proposed,which integrates visual Mamba module to efficiently capture complex visual features and remote *** classical design of U-Net was adopted in the upsampling phase to help reduce the number of references and recover more *** mitigate the information loss problem,an auxiliary U-Net downsampling layer was designed to focus on sizing without extracting features,thus enhancing the protection of input information while maintaining the efficiency of the *** experiments were conducted on the ACDC MRI cardiac segmentation dataset,and the results showed that the proposed LA-UMamba achieves proved performance compared to the baseline model in several evaluation metrics,such as IoU,Accuracy,Precision,HD and ASD,which improved that the model is successful in optimizing the detail processing and reducing the complexity of the model,providing a new perspective for further optimization of medical image segmentation techniques.

摘要：An EMU train with detailed cabin structural is established based on the finite element *** secondary impact between train driver and control desk is fully analysed and two measures are proposed to reduce the driver injury severity,such as the multi-objective optimization of the driver seat position and equipping the train with three-point seat *** results indicate that the driver seat position has a significant effect on the driver injury severity during a secondary *** to the multi-objective optimization,some Pareto solutions are suggested to design the driver seat *** that,it is also indicated although the chest and leg are well protected when the driver wears a two-point seat belt,it increases the head injure during a secondary *** the other hand,the three-point seat belt can supply the train driver with an overall protection against the secondary *** injury criteria(HIC,VC,TI)of the driver with the three-point seat belt is significantly lower than those of the driver without seat ***,according to the simulation analysis,the limited load of the three-point seat belt is suggested about 1.5 kN.

摘要：The evolution of temperature field of the continual motion induction cladding and the depth of heat affected zone are studied in this study.A three-dimensional finite element model for the point type continual induction cladding is established to investigate temperature distributions of fixed and motion induction cladding *** novel inductor is designed for cladding of curved *** modeling reliability is verified by the temperature *** influence of process parameters on the maximum temperature and the generation and transfer of heat are *** calculation is performed to its melting rate to verify the temperature distribution and *** results show that a good metallurgical bond can be formed between the cladding layer and *** melting rate gradually falls from the top of the cladding layer to the substrate,and the grain size in the substrate gradually *** heat affected zone is relatively small compared to integral heating.

摘要：Because of its high purity and excellent orientation, mesophase pitch is a superior precursor for high-performance car-bon materials. However, the preparation of top-notch mesophase pitch faces challenges. Catalytic polycondensation at low temperat-ures is more favorable for synthesizing mesophase pitch, because it circumvents the high-temperature free radical reaction of other thermal polycondensation approaches. The reaction is gentle and can be easily controlled. It has the potential to significantly im-prove the yield of mesophase pitch and easily introduce naphthenic characteristics into the molecules, catalytic polycondensation is therefore a preferred method of synthesizing highly spinnable mesophase pitch. This review provides a synopsis of the selective pre-treatment of the raw materials to prepare different mesophase pitches, and explains the reaction mechanism and associated research advances for different catalytic systems in recent years. Finally, how to manufacture high-quality mesophase pitch by using a cata-lyst-promoter system is summarized and proposed, which may provide a theoretical basis for the future design of high-quality pitch molecules.

摘要：随着人工智能在计算机视觉领域的飞速发展,越来越多的经典人工智能算法被应用于多人脸识别研究。其中,MTCNN算法在多人脸识别方面表现较好,但在识别精度上还有较大提升空间。本研究从经典的MTCNN算法框架出发,对其子算法NMS算法进行评估与改进,并对NMS算法与改进NMS算法在P-Net、R-Net、O-Net各个级联网络中的表现差异进行比较与理论分析。对改进后的NMS算法进行主观和客观相结合、横向比较与纵向比较相结合的多种维度方式的评估与鉴别。实验结果表明,本研究设计的模型在数据集LFW上的人脸识别准确率为94.56%,可为多人脸识别研究提供参考。

摘要：海岸带具有重要的生态系统服务价值,但是由于自然灾害以及人类不合理的开发利用,海岸带遭到严重侵蚀和破坏.传统的海岸硬质结构防御模式已经不足以面对不断变化的沿海条件甚至加剧海岸侵蚀,因此基于自然解决方案的“活力海岸”越来越受到人们的关注.本研究剖析了活力海岸内涵,提出了活力海岸核心要素,构建了活力海岸指标体系.采用德尔菲(Delphi)法开展2轮专家函询,通过计算专家积极性､专家权威程度､专家意见集中程度与协调系数,判断指标体系构建的可靠性;基于界值法筛选指标并结合专家意见构建活力海岸评价指标体系.活力海岸评价指标体系分为三个层次,即目标层、准则层和指标层,准则层分为“资源环境适宜性”､“资源环境可持续性”、“生态韧性”、“社会经济支撑性”4类,指标层包括一级指标13项和二级指标36项.活力海岸的核心特征是“基于自然元素”,通过采用自然材料或自然与人工材料相结合的技术保护、恢复和增强海岸带自然栖息地,最终促使海岸带资源环境条件和经济社会发展达到可持续发展的状态.我国目前活力海岸相关研究较少,本研究构建的活力海岸评价指标体系一定程度上填补了活力海岸管理模式的空白.

摘要：针对新能源发电的随机性和波动性对电力系统运行带来的挑战,本研究设计了一款智能电网综合能效管理平台。该平台通过物联网和数据分析技术,实现了电网数据的全面整合,提高了电网的能源效率和管理水平。通过实时监测和分析电网运行状态,平台能够精确评估电网运行状态、能源流向及负荷分布等关键参数。其核心功能包括高精度的能源需求预测以及对电网调度规划的优化。同时,为应对新能源接入电网带来的电网稳定性、安全性及能效管理的复杂挑战,平台采用了先进的数据处理和分析技术,如模式识别、深度学习以及优化算法,增强了预测模型的准确性以及调度系统的稳定性。