时尚特斯拉

在环境保护与能源短缺的双重压力下,近年来新能源车应运而生,全球各汽车公司争相开发新能源车,但真正成气候的不多。美国特斯拉公司的纯电动车一经问世,即产生了轰动效应,该车以其时尚的外观和先进的技术吸引了众多消费者的眼球。诞生于2003年的特斯拉汽车公司,迄今不过十余年历史,但在全世     

海洋吊机主动波浪补偿技术及国产化建议

采用波浪补偿技术可减轻或避免风、浪、流等作用对海洋吊机的影响,提高其安全性,增强其工作能力。在简述国内外主动波浪补偿技术现状的基础上,介绍了液压缸式和绞车式主动波浪补偿技术执行机构的工作原理,并从控制技术、数据采集技术、运动预报技术和节能技术等方面分析了主动波浪补偿技术的关键。建议我国走联合开发、集成创新的道路,采用由简单到复杂、循序渐进的研发思路,加强核心技术研究和关键零部件制造能力,以期早日研制出高性能的主动波浪补偿吊机,实现主动波浪补偿技术国产化。     

基于分数间隔的双模式盲均衡算法研究

针对MMMA存在的收敛速度慢的问题,提出一种改进算法。此算法将MCMA和改进型MMMA结合起来,并且应用于分数间隔均衡器中。该算法初期采用MCMA收敛均衡,根据判决区域切换到改进型MMMA中进一步收敛,由于分数间隔均衡器解决了波特间隔均衡器因抽样率不高带来的频谱混叠问题,从而进一步地提高了均衡效果。仿真结果表明,改进算法收敛速度快,剩余误差小而且能克服相位偏移。     

数字电路课程的翻转课堂教学及调研

以数字电路课程为例,介绍一个模板的翻转课堂实施过程和实施翻转课堂的经验,并提出几项挑战。     

浅析高中美术鉴赏课中的素质教育

文章通过对美术鉴赏课的重要性及其对素质教育的意义、方式和方法进行分析,意在建议广大美术教师,在带领学生鉴赏古今中外的美术作品和美术现象时,要让学生深入领会我国优秀的民族艺术传统,以提高学生的整体素质,发展学生的审美能力,培养学生的创新精神和实践能力,将素质教育贯穿于美术鉴赏教学。     

主动自加噪传输技术及其反通信侦察效能分析

虽然各种信息安全措施在通信系统的传输层、网络层和链路层广泛使用,使其安全等级得到了较大提升,但随着近年来通信侦察技术的不断进步与发展,通信传输物理层安全问题却日益突出。针对这一情况,提出了基于通信发射方自己主动添加噪声进行信号传输的方法,以此来有效阻止非合作的第三方对物理层信息的直接获取。根据不同的防护要求,设计了空间辐射自加噪与射频合路自加噪这2种主动自加噪传输模式,并分析了其不同的应用条件与反通信侦察的效能。最后通过仿真验证了上述方法的合理性与有效性,这对于提高通信传输物理层安全等级,推进通信电子防御工程建设具有重要参考意义。     

基于主动学习的离群点集成挖掘方法研究

离群点检测任务通常缺少可用的标注数据，且离群数据只占整个数据集的很小一部分，相较于其他的数据挖掘任务，离群点检测的难度较大，尚没有单一的算法适合于所有的场景。因此，结合多样性模型集成和主动学习思想，提出了一种基于主动学习的离群点集成检测方法OMAL（Outlier Mining based on Active Learning）。在主动学习框架指导下，根据各种基学习器的对比分析，选择了基于统计的、基于相似性的、基于子空间划分的三个无监督模型作为基学习器。将各基学习器评判的处于离群和正常边界的数据整合后呈现给人类专家进行标注，以最大化人类专家反馈的信息量；从标注的数据集和各基学习器投票产生的数据集中抽样，基于GBM（Gradient BoostingMachine）训练一个有监督二元分类模型，并将该模型应用于全数据集，得出最终的挖掘结果。实验表明，提出方法的AUC有了较为明显的提升，且具有良好的运行效率，具备较好的实用价值。     

Research on image segmentation of Miao costume patterns based on the RSKP-UNet model北大核心CSCD

The Miao nationality is the sixth largest ethnic group in China which has a history of thousands of years. It has created a unique material culture and spiritual culture in its development process and the Miao costume is a highly condensed collection of the material and spiritual culture of the Miao nationality. As one of the unique symbols of Miao culture the Miao costume has profound cultural heritage and cultural connotations. The patterns of the Miao costume are particularly eye-catching as they not only symbolize the wisdom of the Miao people in thousands of years of production and life but also symbolize the pursuit of the good spirit of the Miao people. However under the impact of modern pop culture and foreign culture these cultural symbols are gradually disappearing. In order to protect and inherit them the Miao costume pattern segmentation has become the most important work. However the Miao costume pattern segmentation is quite difficult. At present there are few studies on the extraction classification identification and preservation of the features of Miao costume pattern segmentation. With the excellent segmentation performance of the U-Net model and the advantages of easy deployment the paper improves the basic structure of the U-Net model and proposes a Miao costume pattern segmentation algorithm based on the RSKP-UNet Residual Selective-Kernel Parallel U-Net model. The algorithm adds Residual modules in the encoder part of the U-Net model to improve the feature extraction capability of the model and embeds the SKNet modules and ParNet modules in the decoder part to enhance the feature expression capability of the model. The paper uses evaluation metrics to measure the segmentation performance of the model and compares it with four segmentation models based on deep learning. The paper not only combines the current research focus-deep learning and attention mechanism but also introduces the Lovász-hinge loss function to effectively solve the problem of class imbalance in the Miao costume patterns. The RSKP-UNet model is better than other models in various segmentation indicators. Compared with the benchmark model U-Net the Dice coefficient IoU precision recall and accuracy are improved by 6. 98% 11. 07% 2. 89% 6. 75% and 3. 92% . The segmentation algorithm proposed in this paper realizes the extraction of the element content of the Miao costume patterns through image segmentation of Miao costume patterns which can be used to build the Miao costume pattern database in this way thus helping designers relevant researchers and organizations to provide research foundation and completing the protection and inheritance of the Miao costume culture. The paper also provides some reference for the segmentation research of other minority costume patterns. © 2022 Authors. All rights reserved.