学习动机和学习策略对英语学习的影响

本文通过对中学生和大学生英语学习的动机和策略的调查 ,揭示了动机、策略和学习成效的关系。     

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.     

Formal characterization of an efficient driving evaluation process for companies of the transport sector

Public institutions and private companies all around the world agree that road transport is one of the main sectors responsible for global warming. With this in mind, all of them have designed actions to increase efficiency and reduce fuel consumption and emissions. A favorite for the companies is eco-driving because it can improve the fleet performance without a great investment. However, although these programs have achieved promising results in the majority of the experiences, the figures are not so encouraging in the long term. In many cases this decrease is produced by fuzzy reward programs or the total lack of them. Nevertheless, any coherent reward program, in order to be effective, must be associated with a complete and fair evaluation process which takes into account all the different aspects and complexities related with driving. In this paper, we propose a formal characterization of an efficient driving evaluation process which starts with a review of many different driving recommendation systems. These recommendations are used as seeds to build a set of formal competences that any eco driver must have, as well as the learning outcomes associated with each competence. A set of patterns of driving behaviors are defined, that allow confirming any of the learning outcomes. The definition also comprises a set of Key Performance Indicators (KPIs) for each learning outcome. These KPIs allow measuring the progress associated with each competence. Finally, we also propose some relevant differences that must be taken into account for the goals associated with each KPI, depending on the domain of application: type and road geometry, vehicle type (automatic or manual, passengers, cargo or not, public or private), amount of traffic, weather. Some examples of this driver characterization have been included to demonstrate the process.     

基础会计教学中培养学生学习兴趣的研究与实践

学习兴趣在学生的学习过程中起着至关重要的作用．在基础会计教学中，如何培养学生的学习兴趣是教师非常重视的环节。文章结合基础会计教学实践经验，从赏识教育、灵活教法和互动教学三个方面探讨了培养和激发学生学习兴趣的途径．     

论航运企业的竞争策略

阐述了21世纪的航运市场出现的竞争形势,科技与人才、知识与信息、服务与质量的竞争已成为当今市场竞争的核心。我国航运企业应及时认清新的竞争形势,根据自己的实际情况,及时制定出新的竞争策略,提高市场竞争力。     

高职生英语应用文写作错误分析与对策

本文对高职学生在英语应用文写作中经常出现的错误进行了分析,根据二语习得理论和应用文的特点提出了英语应用文写作的对策,以提高学生的英语应用文写作水平。     

基于工作过程的项目课程教学实践与探索

基于工作过程的项目课程从学生就业的岗位出发,通过典型工作任务分析,形成综合能力领域,再遵循人类认知的规律和职业成长过程转换成系列项目课程。项目课程模糊了理论教学与实践教学的界限,在对学员进行专业知识与技能的培训外,更加注重学生组织、交往、合作、自主学习、独立思考等关键能力的培养,激发了教师教学和学生学习的积极性。文章对基于工作过程的项目课程的开发、建设、实施进行了探索。     

山区沿河公路路基水毁防治对策探讨

山区沿河公路路基水毁是公路主要的自然灾害之一,分布广泛、发生频繁和危害巨大的特点不但严重影响交通运输的营运与安全,而且也造成了重大经济损失。通过分析一些常见的公路水毁类型和机理,提出公路水毁防治的一些对策,并通过实际案例分析防护措施的运用效果,为公路养护管理部门提供技术参考。     

城市轨道交通乘客信息系统服务框架优化策略

介绍了目前城市轨道交通乘客信息系统的系统组成和信息服务原理.分析了日前国内乘客信息服务的内容和形式,以及国外乘客信息系统值得借鉴之处.针对目前城市轨道交通乘客信息系统存在的问题,设计了基于网络化的智能乘客信息服务框架.     

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公共交通是城市交通的重要组成部分,合理选择公交优先技术是提高公共交通效率最为有效的手段。对于多属性方案的选择问题,目前常用的比选方法基于AHP理论讨论权重具有较大不精确性和复杂性。本文采用了博弈论的理论,通过对公交优先系统中参与者集合N、战略集合S和收益函数u的确定,建立了一种基于博弈论的公交优先技术方案选择博弈模型来量化方案选择问题;在此基础上分析了NASH均衡的存在性,并且给出了一般情况下的重复剔除劣战略和特殊情况下的混合策略两种模型求解方法以及公交优先技术方案选择博弈模型的流程图;最后通过算例分析,验证了博弈模型应用于公交优先技术方案选择的可行性。