对外汉语专业的英美文学选读课教学初探

英美文学选读课有助于对外汉语专业的学生全面掌握语言文字的魅力,领略不同文化的精神内涵,肩负起自身的文化使命。笔者通过两年多的教学实践,以教学活动过程为背景,从预热、选材、学习、反思四个阶段,总结出了几点经验。     

Road traffic conditions in Kenya: Exploring the policies and traffic cultures from unstructured user-generated data using NLP

Road traffic accidents (RTA) are a prevalent cause of fatality with African countries having the highest fatality index (25–34 per quota). The World Health Organization estimates Kenya's fatality rate due to RTA at 28 per quota. From literature, the country's fatality and injuries have increased by 26% and 46.5%, respectively, since the year 2015. The country is faced with incomplete RTA data capturing, hindering effective planning and policy adjustments to curb the menace. In this paper, we scrapped user-generated data (Twitter) and national transport and safety authority's (NTSA) reports to shed light on traffic safety, practices, and cultures in the country. To this end, we gathered 1,000,000 tweets and 8000 speeding entries between 2015 and 2021 and performed natural language processing (NLP) and quantitative study of the data. We applied NLP and n-gram search of keywords to categorize data into 8 topics: traffic, public service vehicle (PSVs), policing, accident, infrastructure, recklessness, robbery, and corruption. From the data, policing, which touches on all police and law-enforcement-related activity was found to be highly correlated with PSVs, recklessness, accidents, traffic congestion, robbery, infrastructure, and corruption with indices of r(76) = 0.92, 0. 91, 0.87, 0.82, 0.81, 0.76, and 0.70, respectively with p < 0.001. The topic modeling confirmed the identified topics to be the latent discussion issues affecting the public. From the study, PSVs, policing and traffic flow were isolated as key issues that ought to be addressed immediately. The research recommended the integration of driver monitoring systems to strengthen policing. The research, which utilized unstructured data, points to the utility of data mining which would greatly benefit traffic research, particularly African-based studies, that suffer from data inadequacy.     

Application of multi-criteria decision analysis methods for assessing walkability: A case study in Porto Alegre,Brazil

The concept of walkability refers to the extent to which a neighbourhood is walking-friendly. Several walkability indexes have been developed to quantify and evaluate the pedestrian environment. These indexes differ in terms of type of data, methods and goals. The indexes variables may present either uniform or distinct weights, defined by arbitrary, empirical or other diverse weighting methods. This paper pursues the determination of a weighted walkability index, constructed on the basis of the relative importance of their attributes. Weights were determined by the application of the Fuzzy Analytic Hierarchy Process (FAHP), a robust multi-criteria method which considers the experts’ uncertainty in decision making. Moreover, FAHP weights were compared with the attribute weights obtained from other simpler methods, and a chi-square test for homogeneity was computed to compare the obtained values. The three most important walkability attributes were: Public Security, Traffic Safety and Pavement Quality, similar results to the ones found in the literature. The application to a case study in the city of Porto Alegre, Brazil, allowed categorizing the studied neighbourhoods and to analyse the effect of changes on attributes in walkability.     

Field implementation feasibility study of cumulative travel‐time responsive (CTR) traffic signal control algorithm

The cumulative travel‐time responsive (CTR) algorithm determines optimal green split for the next time interval by identifying the maximum cumulative travel time (CTT) estimated under the connected vehicle environment. This paper enhanced the CTR algorithm and evaluated its performance to verify a feasibility of field implementation in a near future. Standard Kalman filter (SKF) and adaptive Kalman filter (AKF) were applied to estimate CTT for each phase in the CTR algorithm. In addition, traffic demand, market penetration rate (MPR), and data availability were considered to evaluate the CTR algorithm's performance. An intersection in the Northern Virginia connected vehicle test bed is selected for a case study and evaluated within vissim and hardware in the loop simulations. As expected, the CTR algorithm's performance depends on MPR because the information collected from connected vehicle is a key enabling factor of the CTR algorithm. However, this paper found that the MPR requirement of the CTR algorithm could be addressed (i) when the data are collected from both connected vehicle and the infrastructure sensors and (ii) when the AKF is adopted. The minimum required MPRs to outperform the actuated traffic signal control were empirically found for each prediction technique (i.e., 30% for the SKF and 20% for the AKF) and data availability. Even without the infrastructure sensors, the CTR algorithm could be implemented at an intersection with high traffic demand and 50–60% MPR. The findings of this study are expected to contribute to the field implementation of the CTR algorithm to improve the traffic network performance. Copyright © 2017 John Wiley & Sons, Ltd.     

Travel mode choices in small cities of China: A case study of Changting

The existing literature on urban transportation planning in China focuses primarily on large cities and neglects small cities. This paper aims to fill part of the knowledge gap by examining travel mode choice in Changting, a small city that has been experiencing fast spatial expansion and growing transportation problems. Using survey data collected from 1470 respondents on weekdays and weekends, the study investigates the relationship between mode choice and individuals’ socio-economic characteristics, trip characteristics, attitudes, and home and workplace built environments. While more than 35 percent of survey respondents are car owners, walk, bicycle, e-bike, and motorcycle still account for over 85 percent of trips made during peak hours. E-bike and motorcycle are the dominant means of travel on weekdays, but many people shift to walking and cycling on weekends, making non-motorized and semi-motorized travel especially important for non-commuting trips. Results of multinomial logistic regression show that: (1) job-housing balance might exert different effects on mode choice in different types of urban areas; (2) negative attitude towards e-bike and motorcycle is associated with more walking and cycling; and (3) land use diversity of workplace is related to commuting mode choice on weekdays, while land use diversities of both residential and activity places do not significantly affect mode choice on weekends. Our findings imply that planning and design for small cities needs to differentiate land use and transportation strategies in various types of areas, and to launch outreach programs to shift people’s mode choice from motorized travel to walking and cycling.     

面向动静态混合环境的智能车运动规划方法

针对存在动态和静态障碍物环境中的智能车运动规划问题，本文提出一种基于三维搜索的方法。该方法首先在笛卡尔坐标系中增加时间维度以建立时间-空间栅格，构建不同车速下的车辆运动基元；将智能车转化为多个圆心组成的线段，采用膨胀静态障碍物的方法进行不规则障碍物碰撞检测，运用时间间隔法将动态障碍物碰撞检测简化为线段交叉性检测；构建包含最大速度和加速度约束的速度启发式函数，用于引导搜索树在时空空间中快速到达目标位置和速度；最后基于启发式方法和局部运动规划方法在时空栅格中进行搜索，获取融合时间信息和“停止-等待”等决策信息的运动轨迹。实验结果表明：本文运动规划方法在动静态混合环境中能够引导智能车安全行驶，相比速度障碍方法，安全行驶的平均成功率提升23%；相比混合A*方法，平均成功率提升19%，行驶耗时缩短21%。     

网络环境下科技查新及其存在的问题研究

本文针对网络环境下科技查新工作,对科技查新与信息检索、信息分析、竞争情报之间的关系进行了辨析,剖析了影响科技查新的主要因素,并从提高查新人员的整体素质、制定查新工作统一标准、拓展文献检索手段、加强查新员与委托人之间的交流等方面提出了相应的提高科技查新质量的措施。     

花场湾自然条件及海床演变分析

通过对海南花场湾海域潮汐、潮流、泥沙、波浪以及底质沉积物等自然条件的分析,对该海区的水动力、泥沙环境及海床演变规律进行了研究,论证了花场湾海域略有冲刷的基本特征。     

高速列车研制中环境保护的几个问题

针对高速列车对环境危害最严重的噪声，振动和电磁干扰问题作了阐述，并提出了解决办法。     

捞雷机器人土力学特性研究

介绍了一种沿半埋鱼雷体表面爬行的捞雷机器人作业装置构成和原理，建立了捞雷机器人在水下泥土环境中作业的力学模型，对该模型和钻进状态进行了较为详细的分析。