Building a transdisciplinary science of One Health with a global vision

One Health has been recognized as a cost-effectiveness approach that intricate connections between human health,animal health,and ecosystem health.This holistic perspective is crucial for addressing complex health challenges that arise at the intersection of these domains,such as emerging infectious diseases,antimicrobial resistance,food safety&food security,and environmental degradation.The beneficiaries of the One Health ap-proach have been demonstrated by many case studies worldwide,and summarized by The World Bank that not only support poverty alleviation in developing countries,but also can reduce pandemic risk globally.It is essential for us to understand the means of promoting the initiatives in building the transdisciplinary science of One Health that requires a global vision with integration of various disciplines,stakeholders,and resources.Therefore,we introduce the role of the transdisciplinary science of One Health,and the key steps and strategies necessary to implement One Health approach in the real world.We also propose three research priorities,including empha-sizing climate change and health,enhancing global health security,and promoting equity and inclusivity which is crucial for the success of One Health initiatives.Hence,building a transdisciplinary science of One Health will not only improve holistic health between human,animal,and environmental domains,but also contribute to the global health security and sustainable development.

A global vision system: using hue thresholds to exact feature and recognize

The fast paced nature of robotic soccer necessitates real time sensing coupled with quick behaving and decision making. In the field with real robots, it is important to well perceive the location of ball, team robots and opponent robots through the vision system in real time. In this paper the architecture of global vision system of our small size robotic team and the process of object recognition is described. According to the study on color distribution in different color space and quantitative investigation, a method which uses H (Hue) thresholds as the major thresholds to feature exact and recognize object in real time is presented.

The Belt and Road Initiative Working Towards a Global Vision

The Belt and Road Initiative is proposed as an international strategy in China. In the eyes of the Chinese people, the Belt and Road Initiative is an international strategy rather than a regional strategy, the goals of which are to coordinate an all-around opening of China to the world and promote further integration of the country into the global economy. So the strategy is talked in almost every field in China. However, Outside of China, the discussion about the Belt and Road initiative does not always provide encouragement and support and typically there are more disputes than agreements. Implementation of Belt and Road is going to reconstruct regional interests and balance powers throughout the world. There are many difficulties in achieving the goal, so China has to realize the true situation in neighboring countries and provide more chances for Non-Governmental Organizations as well as illustrating to the world how China will do in the future.

Global Vision

Innovative ZTE is a shining example of a Chinese company’s ongoing pursuit of excellence by Lu Qianwen EVERY autumn,28-year-old electronics fan Zhong Datong gets excited.It’s the time his favorite annual event,"P&T/ EXPO Comm China," the largest international information and communication technology exhibition in Asia,is held in Beijing. This year the dazzling new products at the booth of the ZTE Corp.were a contin-

基于Local-Global-VIT细粒度分类算法的蝴蝶识别

【目的】准确鉴别蝴蝶种类,动态观测蝴蝶群落多样性变化对生境质量评估、生态环境恢复等方面具有重要意义。针对现有蝴蝶识别方法仅依靠整体特征,忽略了局部特征导致识别生态图像能力不足的问题,本研究旨在开发一种Local-Global-VIT细粒度分类算法的蝴蝶识别方法。【方法】本研究以5科200种共计25 279张蝴蝶图像为识别对象,采用多种数据增强方法扩充图像数据;通过视觉Transformer(vision transformer, VIT)层级结构及自注意力机制逐层选择局部令牌并保留至最后一层学习蝴蝶局部判别部位信息;聚合高层全局令牌消除复杂背景干扰;通过对比损失拉大类间距提高区分度。除此之外,使用合理的学习率调整策略和迁移学习方法,优化了模型收敛过程,在不增加参数量的情况下提高了性能。【结果】Local-Global-VIT算法在大规模细粒度公开数据集Butterfly-200上识别准确率达91.20%,较改进前提升了1.15%,比最优的一般害虫识别算法EfficientNet_b0和细粒度分类算法TransFG准确率分别高了1.83%和0.64%,F1分值分别提高了1.89%和0.88%。【结论】Local-Global-VIT算法以细粒度识别方式有效解决了蝴蝶类内差异大、类间差异小的分类难题,能准确地识别蝴蝶种类,有助于高效评估生境质量。

Global Calibration Method for Monocular Multi-View System Using Rotational Dual-Target

To make the problems of existing high requirements of calibration tools, complex global calibration process addressed for monocular multi-view visual measurement system during measurement, in the paper, a global calibration method is proposed for the geometric properties of rotational correlation motion and the absolute orientation of the field of view without over lap. Firstly, a dual-camera system is constructed for photographing and collecting the rotating image sequence of two flat targets rigidly connected by a long rod at different positions, and based on the known parameters, such as, target feature image, world coordinates, camera internal parameters and so on, then the global PnP optimization method is used to solve the rotation axis and the reference point at different positions;Then, the absolute orientation matrix is constructed based on the parameters of rotation axis, reference point and connecting rod length obtained by this method. In the end, the singular value decomposition method is used to find the optimal rotation matrix, and then get the translation matrix. It’s shown based on simulation and actual tests that in comparison with the existing methods, the maximum attitude and pose errors is 0.0083˚ and 0.3657 mm, respectively, which improves the accuracy by 27.8% and 24.4%, respectively. The calibration device in this paper is simple, and there are no parallel, vertical and coplanar requirements between multiple rotating positions. At the same time, in view of the calibration accuracy, the accuracy requirements of most application scenarios can be met.

“Tsinghua Global Vision Lectures” Held

Since its launching on September 13, 2007, the Tsinghua Global Vision Lectures series, which has been incorporated into Tsinghua＇s elective course system, has received a warm welcome from students. In the past week, several famous university and company leaders delivered speeches in the series, including Professor Jeffery Lehman, Former President of Cornell University, Professor M.M. Salunkhe, Vice-Chancellor of Shivaji University in India, Mr. Maurice Greenberg, Former Chairman and CEO of American International Group （AIG）, Mr. Ronnie Chan, Chairman of the Hang Lung Group, and Mr. Joseph M. Tucci, Chairman, President and Chief Executive Officer of EMC Corporation.

University of Southern California Professor Kai Hwang Delivers Tsinghua Global Vision Lecture

University of Southern California （USC） Professor Kai Hwang delivered the Tsinghua Global Vision Lecture “Global Advances in Computer and Information Technology： Can China Take the Lead？” in the FIT Lecture Hall on January 6, 2009. During his lecture, Professor Hwang shared his ideas about several global advances in computer, networking, and information technology and discussed the great challenges yet to be confronted in information and technology in academia and in industry and the building of world-class universities. In his address,

How can home care realize people-based, local and global consciousness of the organic unity of vision

Under the background of China＇s aging population, home care service system in line with China＇s traditional family pension, pension also incorporates community features, is widely used in China at this stage of pension model. However, the home care service research stage and the organic unity of the people did not do standard, local awareness and global perspective, often blindly follow the tide of globalization. Article by home care services, people-based, local and global vision of the concept of consciousness and its relationship to reports, summarized the research stage of home care service should be how to achieve unity of the three.

Global Calibration Method of Multi-sensor Vision System Using Skew Laser Lines

Multi-sensor vision system plays an important role in the 3D measurement of large objects.However,due to the widely distribution of sensors,the problem of lacking common fields of view（FOV） arises frequently,which makes the global calibration of the vision system quite difficult.The primary existing solution relies on large-scale surveying equipments,which is ponderous and inconvenient for field calibrations.In this paper,a global calibration method of multi-sensor vision system is proposed and investigated.The proposed method utilizes pairs of skew laser lines,which are generated by a group of laser pointers,as the calibration objects.Each pair of skew laser lines provides a unique coordinate system in space which can be reconstructed in certain vision sensor＇s coordinates by using a planar pattern.Then the geometries of sensors are computed under rigid transformation constrains by taking coordinates of each skew lines pair as the intermediary.The method is applied on both visual cameras with synthetic data and a real two-camera vision system;results show the validity and good performance.The prime contribution of this paper is taking skew laser lines as the global calibration objects,which makes the method simple and flexible.The method need no expensive equipments and can be used in large-scale calibration.

从整合、多元到协商:安全共同体理念演化与全球安全治理

安全共同体是人类命运共同体思想中的重要一环。对安全共同体既有理论与实践进行回顾和反思,并基于人类命运共同体、中国的国际安全治理理念,对安全共同体理念、内涵与全球治理层面的演化进行新的探讨和诠释,有着重大的理论和现实意义。通过在结构、思想、身份认知和实践行动四个层面的解构与再建构,可以认为协商型安全共同体理念与实践是其演化的方向,其共同实践与共同体建构能够更好地适应当代国际关系和全球安全的复杂性、多样性与不确定性。全球经济与安全发展所处的历史阶段为新的规制、内化和秩序生成提出了要求,新的共同体理念和中国的全球安全治理实践对当代与未来安全治理提供了新的路径和可能。

坚持胸怀天下:从历史经验到世界观和方法论

党的二十大报告把坚持胸怀天下从“历史经验”升华为“世界观和方法论”,其主要依据在于它是马克思主义唯物辩证法的普遍联系原理及系统观念与中华优秀传统文化的天下情怀相结合而形成的理论成果,是一种实践中或运用中的马克思主义世界观和方法论。坚持胸怀天下,就是要坚持用世界眼光看待问题和解决问题,借鉴吸收人类一切优秀文明成果,为解决人类共同面对的问题作出中国贡献。未来继续坚持胸怀天下,必须积极培育和构建与坚持胸怀天下相适应的思想观念和社会心态;必须推进高水平对外开放;必须走和平发展道路,推动构建人类命运共同体。

中国式生态现代化“胸怀天下”的时代价值

中国式生态现代化“坚持胸怀天下”的世界观和方法论,在吸收和发展马克思主义人与自然关系思想和中华优秀传统生态智慧的基础上,深刻反思西方生态现代化发展模式的利与弊,紧密结合中国生态文明建设具体实际,有机融合中国特色社会主义现代化进程的其他方面内容,创造性地走出了具有中国特色、中国风格的生态文明建设道路。中国式生态现代化坚持“胸怀天下”深化了人与自然和谐共生关系的认识,助推了人与自然“双重解放”的实现,促进了人类文明新形态的发展。中国式生态现代化现代化“坚持胸怀天下”具有重要的时代价值,体现为胸怀自然与胸怀人民,“坚持绿水青山就是金山银山”理念,强调生态优先、推进绿色发展、注重生态民生。中国式生态现代化建立生态环境系统治理体系,构筑多元主体共治的生态治理格局,为实现人与自然和谐共生,为生态环境治理现代化提供了中国经验,为促进世界永续发展构建了中国方案。

我国体育高端智库建设的国际定位、现实困囿及推进策略

采用文献资料法、实地访谈法、对比分析法对我国体育高端智库的国际化定位、现实困囿与推进策略展开研究。研究表明,随着全球体育治理与体育事务国际化进程的加速推进,我国体育高端智库建设存在国际视野意识不强、国际战略研究程度不深、中国特色品牌尚未形成、成果国际传播不畅、国际议题设置实力较弱、智库人才的国际化培养不足等现实困囿。中国作为负责任大国应结合新时代体育全球化发展进程的现实需要,增强国际视野意识,深化国际战略研究程度,着力打造中国特色品牌,提高成果的国际传播能力,提升国际议题设置能力,加大体育智库国际化人才培养,为在国际上建设具有中国特色的体育高端智库提供理论和实践的战略支撑。

基于Pynq的半全局立体匹配算法实现

立体匹配算法作为双目立体视觉技术的核心算法,具有运算复杂度高、资源占用率高、实时性差的特点。而现有的基于FPGA实现方法多采用高性能FPGA芯片,利用其板卡丰富的资源进行纯verilog语言开发。这样做虽然实时性效果不错,但存在开发难度较大、周期较长、成本较高的弊端。论文针对该问题,提出了一种基于相对低廉的Pynq-z2开发板在PL+PS端协同开发的SGM立体匹配算法,将运算量大的部分在FPGA端进行硬件加速,部分代价优化算法在ARM端利用Python语言实现。实验表明,该算法可有效降低资源占用率,基本满足在相对低廉的嵌入式设备中实现的要求。

中国共产党“坚持胸怀天下”的辩证思考

坚持胸怀天下是中国共产党百年奋斗征程中形成的宝贵经验。中国共产党坚持胸怀天下始终贯穿着辩证思维,具体体现为:将坚持马克思主义与中华优秀传统文化相统一作为基因码,将坚持胸怀天下与心系祖国相统一作为视野观;将加强党的全面领导、全面加强党的建设与引领政党交流互鉴相统一作为引领力;将坚持全面推进与突出重点相统一作为方法论。

GNSS/SINS/视觉导航鲁棒算法

全球导航卫星系统(Global Navigation Satellite System, GNSS)、捷联惯性导航系统(Strapdown Inertial Navigation System, SINS)和视觉传感器优势互补,3者信息融合可获得高精度、无漂移的导航定位信息.针对GNSS/SINS/视觉融合导航易受运动速度、光照变化、遮挡等影响导致定位精度和鲁棒性降低问题,本文在图优化框架的代价函数中加入SoftLOne鲁棒核函数,设置量测值粗差检验程序,降低离群点带来的负面影响.进一步,对量测值计算残差进行卡方检验,对超限残差降权处理,提高系统精度和鲁棒性.实验结果表明,本文算法较不施加鲁棒核函数、不采用异常值剔除策略和卡方检验的传统算法,以及加入其他鲁棒核函数的算法精度更高、鲁棒性更好,能够较大程度提升GNSS/SINS/视觉导航定位精度和鲁棒性,在大尺度环境下,未出现较大漂移误差,绝对位姿均方根误差0.735 m,绝对位姿误差标准差0.336 m.

足球机器人全局视觉系统的快速标定方法

足球机器人全局视觉系统为决策系统提供机器人位姿信息,决策系统进行机器人的路径和动作规划;竞赛规则要求视觉系统必须现场安装调试,因此标定过程必须快速有效,且具有较高的精度;针对足球机器人全局视觉系统的特殊应用场景,提出了一种基于两步法简化标定模型的快速有效标定算法;利用近似欧拉角旋转矩阵建立摄像机标定模型,确定需要求取的摄像机内外参数,根据标定模型,对内外参数的求解过程进行了推导;借助场地上现有的一些标志点作为靶标,对模型的内外参数进行分步求取初始值,并利用L-M优化算法对摄像机内外参数进行分步优化求取精确值;通过实验分别从标定误差和机器人动作实现效率两个方面与其他标定算法进行对比,验证了该算法具有较高的标定精度;实验表明,本算法的优点在于不用借助专门的标定靶标,即可快速有效完成相机标定,标定精度可达±1 mm,完全能够满足决策系统的控制精度要求,且标定过程简单易实现。

基于实例分割的车间AGV精确定位研究

针对自动引导车(Automated Guided Vehicle,AGV)在复杂工业环境中定位误差大且准确率低的问题,本文提出了一种基于实例分割的车间AGV精确定位方法。通过SURF特征提取算法、最近邻匹配算法和随机一致性算法对双摄像头获取的图像进行实时拼接,使用动态加权融合算法消除接缝,利用RTMDet-Ins-x实例分割模型,获取AGV掩膜,结合AGV的特征进行定位,建立数学模型矫正定位误差。实验结果表明,在模拟车间环境下,该定位方法距离的最大误差为17.3 mm,平均误差为9.5 mm,角度最大误差为1.7°,平均误差为1.1°。与目标检测方法相比,该方法能够获取AGV的航向角度,距离误差缩小了64.4%,可实现车间AGV的精确定位,满足实际工程需要。

激光雷达SLAM下移动机器人双目视觉全局定位

移动机器人在未知环境中执行任务时,需精准感知地图环境和其他物体位置,确定其自身位置。为了提高移动机器人的全局定位精度,提出激光雷达SLAM下移动机器人双目视觉全局定位方法。依据双目视觉系统测距原理,选取双目摄像机中的任意一个相机建立主坐标系,构建双目摄像机模型,结合棋盘图与张正友标定法,标定双目摄像机中参数。在此基础上,计算单帧图像特征点的尺度,完成双目视觉初始化,利用权重函数计算任意一个特征点与线、与面之间的加权值和距离值,估计移动机器人的位置,引入非迭代畸变补偿方法,完成对移动机器人的全局定位。测试结果表明,所提方法的定位结果与实际运动位置之间的最小误差为0.1 m,该方法可以精准定位到移动机器人位置,指导移动机器人更好地执行作业任务。