基于感兴趣区域的CNN-Squeeze交通标志图像识别

在公路交通中,针对复杂环境下交通标志识别率不高的问题,提出了一种基于 Kmeans对图像聚类,切割图像感兴趣区域(Regions of Interest, ROI),并利用方向梯度直方图特征(Histogram of Oriented Gradient, HOG)与卷积运算,特征加权(CNN-Squeeze)相结合的交通标志识别方法.首先,采用 K-means对交通标志图像进行三角形、圆形图像二聚类,并利用制作的切割模板切割 ROI 并提取 HOG 特征;然后,利用卷积神经网络 (Convolutional Neural Network, CNN)对 HOG特征进行过滤、降维,并通过 Squeeze网络对过滤后的二次特征进行重要性标定;最后,训练该网络模型并实现对交通标志的识别.仿真结果表明,与 BP网络、SVM 及CNN对比,本文方法在保证训练时间的同时,识别精度达到98.58%.     

高职学生英语学习策略培养与差异化教学

目前高职院校的英语教学,由于教学班型大,人数多,学生基础参差不齐,学生个性差异明显,多数学生学习比较被动,以往整齐划一的教学形式难以适应新时期英语教学目标的要求。通过实施差异化教学,将语言学习策略引入高职英语教学,对有效提高高职学生英语学习的积极性及英语实际应用能力,不失为解决高职英语教学难题,加强教学的针对性和时效性的新途径。     

高职院校学雷锋活动常态化调研分析

在高职院校推动学雷锋活动常态化、机制化,是促进高职院校践行雷锋精神、争当先进模范、形成我为人人、人人为我良好氛围的重要途径,更是匡正道德失范,矫正诚信缺失,提升社会道德水平的有效方法。本篇调研分析以阜新高等专科学校为例,调研并分析学生对学雷锋活动中的看法及思想动态,以便进一步为本校学雷锋活动常态化、机制化建设提供理论依据,进而形成具有推广价值和应用价值的课题报告。     

财产保险合同中保险利益原则探讨

保险是分散风险的一种制度,而保险利益作为保险法律制度的关键内容,在保险实务中起着举足轻重的作用。保险利益原则标准主要是保险主体与保险标的法律界定的利益关系。在我国现行保险法中,积极利用保险利益原则,规定投保人对合同标的具有法律保险利益,有助于推动我国财产保险法律制度的不断完善,实现我国保险业的可持续发展。本文主要结合当前保险利益原则的科学内涵,剖析当前财产保险利益原则在适用过程中存在的相关问题,并提出完善策略。     

Design of Reinforcement Learning Parameters for Seamless Application of Adaptive Traffic Signal Control

Adaptive traffic signal control (ATSC) is a promising technique to alleviate traffic congestion. This article focuses on the development of an adaptive traffic signal control system using Reinforcement Learning (RL) as one of the efficient approaches to solve such stochastic closed loop optimal control problem. A generic RL control engine is developed and applied to a multi-phase traffic signal at an isolated intersection in Downtown Toronto in a simulation environment. Paramics, a microscopic simulation platform, is used to train and evaluate the adaptive traffic control system. This article investigates the following dimensions of the control problem: 1) RL learning methods, 2) traffic state representations, 3) action selection methods, 4) traffic signal phasing schemes, 5) reward definitions, and 6) variability of flow arrivals to the intersection. The system was tested on three networks (i.e., small, medium, large-scale) to ensure seamless transferability of the system design and results. The RL controller is benchmarked against optimized pretimed control and actuated control. The RL-based controller saves 48% average vehicle delay when compared to optimized pretimed controller and fully-actuated controller. In addition, the effect of the best design of RL-based ATSC system is tested on a large-scale application of 59 intersections in downtown Toronto and the results are compared versus the base case scenario of signal control systems in the field which are mix of pretimed and actuated controllers. The RL-based ATSC results in the following savings: average delay (27%), queue length (28%), and l CO₂ emission factors (28%).     

当前宏观经济两难下的政策选择

传统的宏观经济两难是指经济增长与通货膨胀相伴,为了抑制通货膨胀所采取的提高利率的做法往往也抑制了经济增长．我国目前的宏观经济两难主要是指在投资拉动的经济增长情况下,虽然没有出现通货膨胀,但消费率处于很低的水平．为了抑制投资采取的提高利率和汇率的做法可能进一步抑制了消费,在这种情况下,宏观经济政策的选择应该以财政政策为主,并且主要是政府帮助居民增加消费的财政政策．     

SOM与HL融合的地铁异物分类算法

地铁站台门与列车门之间异物的检测和对异物的种类判别是保障乘客安全乘车和列车安全运行的基础。使用改进的Self-organizing Map(SOM)分别学习训练图片的数据分布和分类标签的数据分布,再通过Hebbian Learning(HL)学习图片SOM神经元和对应标签SOM神经元之间的数学关并编码在HL矩阵中,最后以查表方式完成异物分类。研究结果表明:改进的SOM+HL模型把分类准确率从原始模型的64.44%提高到72.6%;增加PCA(Principal components analysis)模块的SOM+HL模型使异物检测分类器的分类准确率从72.6%提高到86.2%,且其在NannoPC-T2嵌入式板上的检测速度从45FPS提高到60FPS,在满足分类精度的同时也实现了异物实时分类。且有PCA模块的模型在NannoPC-T2嵌入式板上检测速度为60FPS,移除PCA模块后其在NannoPC-T2嵌入式板上的检测速度为45FPS。     

On the electrification of road transportation – A review of the environmental,economic, and social performance of electric two-wheelers

Electrification is widely considered as a viable strategy for reducing the oil dependency and environmental impacts of road transportation. In pursuit of this strategy, most attention has been paid to electric cars. However, substantial, yet untapped, potentials could be realized in urban areas through the large-scale introduction of electric two-wheelers. Here, we review the environmental, economic, and social performance of electric two-wheelers, demonstrating that these are generally more energy efficient and less polluting than conventionally-powered motor vehicles. Electric two-wheelers tend to decrease exposure to pollution as their environmental impacts largely result from vehicle production and electricity generation outside of urban areas. Our analysis suggests that the price of e-bikes has been decreasing at a learning rate of 8%. Despite price differentials of 5000 ± 1800 EUR₂₀₁₂ kW h⁻¹ in Europe, e-bikes are penetrating the market because they appear to offer an apparent additional use value relative to bicycles. Mid-size and large electric two-wheelers do not offer such an additional use value compared to their conventional counterparts and constitute niche products at price differentials of 700 ± 360 EUR₂₀₁₂ kW⁻¹ and 160 ± 90 EUR₂₀₁₂ kW⁻¹, respectively. The large-scale adoption of electric two-wheelers can reduce traffic noise and road congestion but may necessitate adaptations of urban infrastructure and safety regulations. A case-specific assessment as part of an integrated urban mobility planning that accounts, e.g., for the local electricity mix, infrastructure characteristics, and mode-shift behavior, should be conducted before drawing conclusions about the sustainability impacts of electric two-wheelers.     

基于智能船厂的三维电子地图开发技术

研究基于智能船厂的三维电子地图开发技术，开发三维电子地图相关组件并实现地图瓦片化、动态加载、位置校准、地图缓存等功能，通过直观的地理实景模拟表现方式快速搭建智能船厂三维电子地图服务，为管理者提供设备、人员和中间产品等信息检索服务，有效提升船厂数字化、智能化、信息化程度，可为构建船厂资源管理和工装管理智能化提供技术支撑，进一步挖掘生产和管理环节潜力，推进船舶行业信息化建设。