| ID | 原文 | 译文 |
| 24545 | 甲骨文的研究对历史探究和文化传承具有重要的意义。 | The study of Oracle-Bone inscriptions is of great significance to historical exploration and cultural inheritance. |
| 24546 | 但是要实现字符级别的甲骨字符图像标注，在现有技术环境下，只能通过资深甲骨学专家进行人工标注，不仅耗费人力资源，而且效率低下。 | However, in order to realize character-level Oracle-Bone image annotation, in the existing technical environment, only experienced experts in Oracle-Bone inscriptions can carry out manual annotation, which not only consumes human resources, but also is inefficient. |
| 24547 | 针对这一问题，在前期工作中的甲骨字符图像识别模型的基础上，本文提出了一种甲骨字符图像自动标注算法。 | Aiming at this problem, based on the Oracle-Bone image recognition model in the previous work, this paper proposes an automatic annotation algorithm for Oracle-Bone character images. |
| 24548 | 该算法通过先分列后切割的思想，先将甲骨拓片上的每一个字符图像归结到某一个特定列，再以锚点甲骨字为参考点，根据空间近邻关系找到甲骨原文中的字所对应的甲骨字符图像，从而实现了甲骨字符图像的自动标注。 | In this algorithm, each character image on the Oracle-Bone rubbings is first reduced to a specific column. Then, the Oracle-Bone character images corresponding to the characters in the original text are found by taking the anchor point as the reference point and according to the nearest neighbor relation of space, so as to realize the automatic labeling of the Oracle-Bone character images. |
| 24549 | 同时，将标注好的甲骨字符图像添加到样本数据集，并利用增广后的数据集（增加 6~10倍）重新训练甲骨字符图像识别模型，有利于提高基于深度学习的甲骨文识别算法的识别准确度。 | At the same time, the labeled Oracle-Bone images are added to the sample data set, and the original Oracle-Bone character image recognition model is retrained by using the augmented data set (6-10 times increase), which is conducive to improving the recognition accuracy of the Oracle-Bone character recognition algorithm based on deep learning. |
| 24550 | 以较小的成本大幅增加样本数量，也可以节约专家大量的时间和人力。 | In this way, the number of samples can be greatly increased at a small cost, and a lot of time and manpower of experts can be saved. |
| 24551 | 为了提高室内电力线通信和可见光通信（PLC-VLC）系统的吞吐量和用户体验的公平性，该文提出一种改进遗传算法优化用户配对联合子载波分配(IGA-JUPSA)方法。 | For improving the throughput and the fairness of user experience of indoor power line communications-visible light communications (PLC-VLC) system, an improved genetic algorithm-based joint user pairing and subcarrier allocation (IGA-JUPSA) method is proposed in the paper. |
| 24552 | 在 IGA-JUPSA 的用户配对阶段，设计了最优的非正交多址技术(NOMA)用户配对方法，提高 PLC-VLC 系统的吞吐量； | In the user pairing stage, a method of optimal non-orthogonal multipleaccess (NOMA) user pairing is designed to improve the throughput of PLC-VLC system. |
| 24553 | 在 IGA-JUPSA 的子载波分配阶段，设计 NOMA 与正交多址技术结合的子载波分配策略，设计改进的遗传算法优化不同NOMA组的子载波分配，提高系统的吞吐量和用户体验的公平性。 | During the process of the subcarrier allocation scheme combined NOMA with orthogonal multiple access (OMA) is proposed, and the improved genetic algorithm is used to optimize the subcarrier allocation for different NOMA groups for improving the system throughput and user fairness. |
| 24554 | 仿真结果表明，所提的用户配对和子载波联合方法可以提高PLC-VLC系统的吞吐量和用户体验的公平性。 | Simulation results show that the proposed IGA-JUPSA can improve the throughput of PLC-VLC cascaded system and the fairness experience of users. |