深度视觉语音生成研究进展与展望

为了进一步推进深度学习技术驱动的视觉语音生成相关科学问题的研究进展,阐述了视觉语音生成的研究意义与基本定义,并深入剖析了该领域面临的难点与挑战;在此基础上,介绍了目前视觉语音生成研究的现状与发展水平,基于生成框架的区别对近期主流方法进行了梳理、归类和评述;最后探讨视觉语音生成研究潜在的问题和可能的研究方向。     

Undergraduate disarmament and nonproliferation education: gaps,opportunities, and new approaches

ABSTRACT

Despite living in a nuclear-weapon state, young Americans are generally ill-informed about weapons of mass destruction (WMD) and their means of control. The result is both widespread apathy toward nonproliferation and disarmament decision making among the general public and a looming personnel crisis within government sectors that enact policy in these domains. Considering that 67 percent of high school graduates in the United States go on to pursue a bachelor’s degree, exposing more undergraduates to nonproliferation and disarmament issues could contribute to addressing both of these challenges. The present study analyzes how these issues are already being taught at select US colleges and universities and explores ways to introduce them to more students that align with current priorities in higher education, such as interdisciplinary learning, digital humanities, and data-science learning. It also proposes concrete steps that the WMD policy community can take to help institutions of higher education integrate these topics more broadly into their curricula. The anticipated result is greater support for education in this important issue area across different stakeholders in academia, as well as increased engagement with these critical issues among a more diverse population of young people.     

面向蛋白质功能预测中有向无环图标记结构的多示例多标记学习

在多示例多标记学习问题中,标记之间往往是相互关联的,其中有向无环图结构是一种常见的层次关联结构,可见于蛋白质的基因本体学生物学功能预测的应用场景中。针对其标记间的有向无环图结构,提出了一种新的多示例多标记学习算法。算法从原始数据的特征空间训练出所有标记共享的低维子空间,通过随机梯度下降方法来降低模型排序损失,并融入标记间有向无环图结构关系对预测标记进行优化。将该算法应用于多个数据集的蛋白质功能预测中,实验结果表明,该算法具有更高的效率及预测性能。     

多约束强化学习最优智能滑翔制导方法

为提升复杂飞行任务下滑翔制导的自主性,提出一种基于最优制导与强化学习的多约束智能滑翔制导策略。引入三维最优制导以满足终端经纬度、高度以及速度倾角约束。提出基于侧向正弦机动的速度控制策略,研究考虑机动飞行的终端速度解析预测方法。针对速度控制中机动幅值无法离线确定的问题,研究基于强化学习的智能调参方法。该方法基于终端速度设计状态空间,以机动幅值设计动作空间,设计综合终端速度误差与滑翔制导任务的回报函数,采用Q-Learning实现机动幅值的智能调整。仿真结果表明,智能滑翔制导方法能够高精度满足终端多种约束,并能有效提升复杂任务下的自主决策能力。     

高性能互连网络中端口阻塞故障预测方法

随着系统规模、芯片功耗和链路速率的提升,高性能互连网络的整体故障率也不断上升,传统运维方式将难以为继,给高性能计算系统整体可靠性和可用性带来了巨大挑战。针对网络端口阻塞这类严重网络故障,提出无监督算法的预测模型。该模型从历史信息中挖掘征兆性规律并形成新的特征向量,应用K-means聚类算法对特征向量进行学习归类。在预测时,结合端口当前状态,利用二次指数平滑算法对未来状态进行预测,将得到的新特征向量使用K-means算法预判是否会发生阻塞故障。利用拓扑结构信息,分别对叶交换机和根交换机构建预测子模型,进而提升预测的精确率。结果表明,该预测模型能保持在召回率为88.2%的前提下,达到65.2%的准确率,可为运维人员提供有效的辅助。     

Visual-simulation region proposal and generative adversarial network based ground military target recognition

Ground military target recognition plays a crucial role in unmanned equipment and grasping the battlefield dynamics for military applications, but is disturbed by low-resolution and noisy-representation. In this paper, a recognition method, involving a novel visual attention mechanism-based Gabor region proposal sub-network (Gabor RPN) and improved refinement generative adversarial sub-network (GAN), is proposed. Novel central–peripheral rivalry 3D color Gabor filters are proposed to simulate retinal structures and taken as feature extraction convolutional kernels in low-level layer to improve the recognition accuracy and framework training efficiency in Gabor RPN. Improved refinement GAN is used to solve the problem of blurry target classification, involving a generator to directly generate large high-resolution images from small blurry ones and a discriminator to distinguish not only real images vs. fake images but also the class of targets. A special recognition dataset for ground military target, named Ground Military Target Dataset (GMTD), is constructed. Experiments performed on the GMTD dataset effectively demonstrate that our method can achieve better energy-saving and recognition results when low-resolution and noisy-representation targets are involved, thus ensuring this algorithm a good engineering application prospect.     

Ballistic response of armour plates using Generative Adversarial Networks

It is important to understand how ballistic materials respond to impact from projectiles such that informed decisions can be made in the design process of protective armour systems. Ballistic testing is a standards-based process where materials are tested to determine whether they meet protection, safety and performance criteria. For the V₅₀ ballistic test, projectiles are fired at different velocities to determine a key design parameter known as the ballistic limit velocity (BLV), the velocity above which projectiles perforate the target. These tests, however, are destructive by nature and as such there can be considerable associated costs, especially when studying complex armour materials and systems. This study proposes a unique solution to the problem using a recent class of machine learning system known as the Generative Adversarial Network (GAN). The GAN can be used to generate new ballistic samples as opposed to performing additional destructive experiments. A GAN network architecture is tested and trained on three different ballistic data sets, and their performance is compared. The trained networks were able to successfully produce ballistic curves with an overall RMSE of between 10 and 20 % and predicted the V₅₀ BLV in each case with an error of less than 5 %. The results demonstrate that it is possible to train generative networks on a limited number of ballistic samples and use the trained network to generate many new samples representative of the data that it was trained on. The paper spotlights the benefits that generative networks can bring to ballistic applications and provides an alternative to expensive testing during the early stages of the design process.     

刍议英文电影在大学英语课堂教学中的运用

在英语课堂教学中运用英文电影,可为学生提供丰富的语境化的语言和真实的跨文化信息,为学生创造在课堂上实践语言的机会,也更能激发学生的英语学习兴趣。分析在非英语专业学生课堂教学中选择英文电影的标准,探讨电影观前、观看和观后三个阶段的教学活动。     

真实性语言实践活动对大学生外语交际策略和听说能力的影响

外语交际能力是社会所需高水平复合应用型人才应具备的素养。本研究考察真实性语言应用实践活动对非英语专业大学生外语交际策略和听说能力的影响。通过对比研究发现,学生参加了真实性语言应用实践活动后,其交际策略使用情况得到改善,更倾向于使用积极交际策略,消极策略的使用频率明显减少;听说水平整体得到提高;寻找机会说英语的主动性增强。因此,真实性语言应用实践活动有助于大学生提高外语交际能力,提高社会所需整体应用能力素养。     

论高中《政治生活》实施探究性学习的一般模式

探究性学习的实质是要求教师转变教育观念,在教学中充分调动学生学习的主动性和积极性,激发学生学习的主人翁意识,真正使学生成为学习的主人。因此高中政治课的课堂教学应该充分渗透探究性学习的精神,同时教师又应在这一宗旨的指导下,根据教材的内容和特点的不同采用不同的模式,选用不同的方法,这样才能达到构建高效课堂的目的。