基于实训基地中职汽修专业教学模式构建探究

职业院校是培养专业技术人才的摇篮。而汽修专业是一门实践性很强的学科,要切实提高学生的汽车维修技术,大量的实践教学必不可少,这将有利于提高学生的专业素养以及实操能力,为学生夯实就业基础。因此,中职汽修专业实训基地的建设极为重要。尤其是如今人们生活水平大步提升,汽车已在我国获得普及应用。近年来私家车数量陡增,而汽修专业人才呈现较大缺口,这是中职汽修专业人才发展的良好契机,也是对汽修专业教学的一种挑战。如何培养出一批专业能力强、素养高的汽修人才,这是中职院校亟待解决的重要教育课题。     

以职业岗位能力为导向的教学模式研究和实践

文章通过以职业岗位能力为导向的教学模式研究和实践,从教改背景、理论依据、教学项目的选取、构建汽修岗位教学场景、项目实施等方面进行分析和实践,并在试点班级的实施中,充分发挥实践教学在职业教育中的核心作用,使学生快速达到企业岗位需求,并论证出该教学模式有利于提升教师教学业务能力,激发学生学习兴趣、提升学生职业岗位能力和职业素养。     

带中间渠道船闸运转方式的试验研究

带中间渠道的分散梯级船闸是高坝通航建筑物的布置型式之一,它具有调度灵活、通过能力大等特点。但其上下级船闸采用不同运转方式时,所产生的非恒定流水流条件十分复杂,严重时将影响船舶(队)停泊和航行条件,还会对船闸运转及人字闸门产生不利影响。通过1:40的水工概化模型试验,对断面为规则的矩形中间渠道进行了上下级船闸单独、同时与错时灌泄水3种运转方式渠道内的水力特性研究,否定了船闸同时运转方式;对渠长2 000 m和1 400 m在特定条件下的船闸错时运转方式,找出了最佳错开时间;对3种运转方式的水力要素进行综合对比后,最终推荐采用先泄后灌运转方式。     

Fast Mode Decision Method Based on Historical Information for H. 264/AVC

Mode decision based on rate-distortion optimization algorithm brings high compression efficiency to H.264/AVC. However, heavy computation load is also added to the encoder at the same time. In order to reduce the computation burden of mode decision, this paper presented a fast mode decision method based on mode information of the previously coded frame. Moreover, all coding modes were activated when scene change occurs and a scheme to detect scene change was proposed. The simulation results show that compared to the original encoder, the proposed method achieves a reduction of over 38% encoding time and keeps almost the same PSNR and bitrate for a wide range of quantization parameter.     

小半径弯梁桥的设计要点

由于弯梁桥的挠曲变形比一般相同跨径的直线桥大,且受弯矩及扭矩的共同作用、内梁和外梁受力不均等诸多问题困扰,使弯梁桥的设计存在一定难度。结合新疆某实际工程,从弯梁桥的跨径布置、截面选择、支承方式等方面,对小半径弯梁桥的设计要点进行了归纳,认为曲线梁桥采用整体性好、抗扭刚度大的就地浇注的连续箱梁比较好,最好采用普通钢筋混凝土结构,弯梁应在腹板侧面布置较多受力钢筋,除布设抗剪钢筋外,还要配置较多的抗扭箍筋。     

加强我军空中战略投送能力建设研究

针对我军空中战略投送能力薄弱的问题,结合我国国情、军情,研究提出了建立健全快速动员机制、增强民用运输机的军事适用性、发展军用运输机和创新战略投送模式等建议,可为我军空中战略投送能力建设提供参考。     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.     

A new logit‐artificial neural network ensemble for mode choice modeling: a case study for border transport

Logit model is one of the statistical techniques commonly used for mode choice modeling, while artificial neural network (ANN) is a very popular type of artificial intelligence technique used for mode choice modeling. Ensemble learning has evolved to be very effective approach to enhance the performance for many applications through integration of different models. In spite of this advantage, the use of ANN‐based ensembles in mode choice modeling is under explored. The focus of this study is to investigate the use of aforementioned techniques for different number of transportation modes and predictor variables. This study proposes a logit‐ANN ensemble for mode choice modeling and investigates its efficiency in different situations. Travel between Khobar‐Dammam metropolitan area of Saudi Arabia and Kingdom of Bahrain is selected for mode choice modeling. The travel on this route can be performed mainly by air travel or private vehicle through King Fahd causeway. The results show that the proposed ensemble gives consistently better accuracies than single models for multinomial choice problems irrespective of number of input variables. Copyright © 2015 John Wiley & Sons, Ltd.     

盾构法施工单机核算管理模式的应用

近年来盾构机越来越多地应用于各种隧道工程中,其中地铁应用的数量最多,约占80%。现代盾构已演变成为一种高度智能化的大型工程机械装备,对其控制的好坏将直接影响到整个工程的施工成本和企业的经营效益,而通过单机核算降低机械成本是降低施工成本、提高企业效益的有效手段,因此推行盾构法施工单机核算显得尤为重要。文章结合地铁2222标施工项目,重点介绍了盾构法单机核算管理模式及其在施工中的应用。