英语原文共 12 页， 共享自动电动车队的运营:车辆和充电基础设施决策的影响 T. Donna Chen, Kara M. Kockelman，Josiah P. Hanna 摘 要：共享自动驾驶汽车(AV)车队和电动汽车(EV)技术之间存在着天然的协同效应，因为自动驾驶汽车车队解决了当今非自动电动汽车的实际限制，包括旅行里程焦虑、充电基础设施的接入和充电时间管理。如本文所示，车队管理的自动驾驶汽车可以缓解这些担忧，根据实时出行需求和已建立的充电站位置来管理里程和充电活动。本文研究探讨了在区域、离散时间、基于agent的模型下共享自动电动汽车车队(SAEV)的管理。该模拟研究了共享自动电动汽车车队在不同行驶里程和充电基础设施场景下的运行情况，该模型大致以德克萨斯州奥斯汀市的密度为模型。 基于2009年美国国家公路交通安全管理局行程距离和时间分�

英语原文共 16 页， 节省空间的堆垛仓库布局 Shahab Derhami, Jeffrey S. Smith amp; Kevin R. Gue 【关键词】：设施布局;仓库设计;块堆积,空间利用率;最优巷深度 【摘要】：在块堆叠仓库中，库存单元(sku)的托盘在仓库地板上的通道中一个接一个地堆叠。传统的布局是由通道分隔的多个车道组成的。存储槽的深度和通道数量决定了存储空间的利用率。通过分析模型，我们发现传统的车道深度模型低估了可达性浪费，因此不能提供最佳的车道深度。我们提出了一个新的浪费存储空间模型，并将其嵌入一个混合整数规划中，以求出最优的开间深度。该模型允许多个分区深度，并将sku分配到适当的分区，从而提高空间利用率。我们的计算研究表明，所提出的模型能够以相对较小的最优性间隙解决大规模问题。我们使用仿真来评估所提出的�

英语原文共 11 页， 碳纤维束与环氧树脂复合的性能表征与分析 范海超，顾奕卓，王绍凯，李敏，张佐光 北京航空航天大学材料科学与工程学院，航天先进材料与性能教育部重点实验室，北京，中国 摘要： 这次研究建立了碳纤维束复合环氧树脂的扭转试验方法，调查了几种不同环氧树脂基体的碳纤维的扭转性能，计算了抗扭强度和抗扭模量来表征抗扭性能，确定了样品长径比、测试速度、捆绑树脂含量等测试条件对扭转测试结果的影响，为选择合适的测试条件提供依据。通过对断裂试样的扫描电子显微镜(SEM)观察和单纤维拉拔试验，阐明了碳纤维的扭转性能与基体性能、界面性能的关系。实验结果表明，在优化的试验条件下，该方法能够获得较好的抗扭强度和抗扭模量，数据可靠性较好。碳纤维的伸长率越高，其扭

英语原文共 27 页， 组织信任的一个综合模型 结论与未来方向 本文提出了研究组织信任的若干问题。每一个问题都在组织环境二元模型的发展中被考虑和处理到了。本文提出的模型是第一个既明确考虑受信者特征又明确考虑信任者特征的模型。该模型清楚地区分了信任与促成信任的因素，也区分了信任与其在关系中承担风险的结果。目前的方法以一种不同于其他类似概念（合作、信心、可预测性）的方式定义信任，这些概念在文献中经常被与信任混淆。同样，风险的关键角色在这个模型中明确指定。这篇文章提出了一个通用的信任定义和一套简洁的决定因素。 导致信任的因素、信任本身和信任结果之间的差异是验证该模型的关键。为了全面测试模型，必须对这三个方面进行测量。对于受托人的能力、善行和正直的看法�

英语原文共 110 页， 原文： Chapter4 A Library for FPGA Implementation of Vision Algorithms. The ever-growing usage of computer vision in our daily livesrequires real-time and powerefficient implementations. FPGAs are very effective in accelerating various computer visionalgorithms.Unfortunately, developers may not be familiar with FPGA design, let alone efficient implementation. Even a CPU implementation of vision algorithms using programming languages such as C/C is time-consuming and error-prone. Moreover, despite advances in High-Level Synthesis (HLS) tools, they are still not able to generateefficient hardware implementation for visionalgorithms developed in general-purpose pro-gramming languages (e.g., C ). The main reason is that HLS tools do notincorporate specific optimization methods of vision algorithms, which are critical to the effi-cient implementation of such algorithms. On the other hand, popular vision libraries, such as

In the Web2.0 Era, Social Media Marketing Brings Business Opportunities to Enterprises Abstract In the web2.0 era, more and more companies use social media as a marketing tool. Based on the use of social media such as Facebook and YouTube, enter- prisersquo;s propaganda has become global and more widespread. Whatrsquo;s more, SME (small and medium-sized enterprises) which is not able to carry out large-scale publicity will also gain the capacity to use social platform to extend the number of audiences, bringing more opportunities for the enterprise development. Keywords Web2.0, Social Media, Marketing Strategy, Purchase Intention 1. Introduction Today, wersquo;re in the web2.0 era. Different from one-way information delivery mode with web1.0, the content of the web site in the web2.0 era is often the us- ers; users are the content of visitors and also site content makers. This also means that the web site provides users with more opportunities to participate

英语原文共 10 页， An Intelligent Non-Integer PID Controller-Based Deep Reinforcement Learning: Implementation and Experimental Results Meysam Gheisarnejad and Mohammad Hassan Khooban , Senior Member, IEEE Abstract—In this article, a noninteger proportional integral derivative (PID)-type controller based on the deep deterministic policy gradient algorithm is developed for the tracking problem of a mobile robot. This robot system is a typical case of nonholonomic plants and is exposed to the measurement noises and external disturbances. To accomplish the control methodology, two control mechanisms are established independently: a kinematic controller (which is designed based on the kinematic model of the vehicle),and a dynamic controller (which is realized according to the physical specifications of the vehicle dynamics). In particular, an optimal noninteger PID controller is initially designed as the primary dynamic controller for the tracking pr

英语原文共 7 页， 原文： （206页） Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 166 (2020) 206–212 3rd International Conference on Mechatronics and Intelligent Robotics (ICMIR-2019) Research and Application of Template Engine for Web Back-end Based on MyBatis-Plus Yao Zhang Li1 , Sheng Gao1,* , Jing Pan2, Bi Feng Guo1, Pei Feng Xie*1* 1Faculty of Mathematics and Computer Science, Guangdong Ocean University 2Faculty of Management, Guangdong Ocean University Abstract In web development, it takes much time to code for back-end including business logic and interface integration, which is machanized and high-repeated. In order to address the problem in back-end web coding, this paper analyzes the advantages and disadvantages of SSM(Spring, SpringMVC and MyBatis) framework and development pattern of the original and end separation. By integrating the template engine in P

Bjarke Felbo1, Alan Mislove2, Anders Soslash;gaard3, Iyad Rahwan1, Sune Lehmann4 1Media Lab, Massachusetts Institute of Technology 2College of Computer and Information Science, Northeastern University 3Department of Computer Science, University of Copenhagen 4DTU Compute, Technical University of Denmark Abstract NLP tasks are often limited by scarcity of manually annotated data. In social me- dia sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer representations. Through emoji prediction on a dataset of 1246 million tweets containing one of 64 ing the distant supervision to a more diverse set of noisy labels enables the models to learn richer rep- resentations of emotional content in text, thereby obtaining better performance on benchmarks for

英语原文共 9 页， 基于人群聚集模式和多列卷积神经网络的人群密度检测方法 刘 白，程 武，冯 谢，王一鸣 摘要 人群聚集场所经常发生人群拥堵和踩踏事件，这会造成大量人员伤亡和巨大的社会负面影响。传统的人群聚集安全动态评估研究主要依靠实时视频监控，但缺乏从不同来源、不同视角、不同粒度处理大量视频数据的可靠方法。本文以爱德华·霍尔的个人空间理论为基础，考虑了人群心理等因素，建立了人群聚集模式的静态基本模型。为了将实时多粒度监控视频与不同的视角结合在一起，利用了多列卷积神经网络（M-CNN）从低空视角提取人群的局部密度特征，从而建立了人群时间和空间的全息模型，并采用了一种新的人群聚集安全评估方法。该方法被应用于苏州地标城市生活喷泉广场人群聚集安全评价时取得了�