“多流程、多技能、多任务”式教学模式的研究与实践

基于"工作过程"教育教学理念,提出"多流程、多技能、多任务"的教育教学模式,将学生的学习课程进行分解、重组,按照"典型任务分析—学习领域设计—具体教学任务实施"的原则,研究了典型任务抽取、学习范围划分以及项目任务的情境教学与实施,并在实际教学过程中取得了良好的学习效果。     

The detection of drowsiness using a driver monitoring system

Abstract

Objective: Drowsiness is a major cause of driver impairment leading to crashes and fatalities. Research has established the ability to detect drowsiness with various kinds of sensors. We studied drowsy driving in a high-fidelity driving simulator and evaluated the ability of an automotive production-ready driver monitoring system (DMS) to detect drowsy driving. Additionally, this feature was compared to and combined with signals from vehicle-based sensors.

Methods: The National Advanced Driving Simulator was used to expose drivers to long, monotonous drives. Twenty participants drove for about 4?h in the simulator between 10 p.m. and 2 a.m. They were allowed to use cruise control and traffic was sparse and semirandom, with both slower- and faster-moving vehicles. Observational ratings of drowsiness (ORDs) were used as the ground truth for drowsiness, and several dependent measures were calculated from vehicle and DMS signals. Drowsiness classification models were created that used only vehicle signals, only driver monitoring signals, and a combination of the 2 sources.

Results: The model that used DMS signals performed better than the one that used only vehicle signals; however, the combination of the two performed the best. The models were effective at discriminating low levels of drowsiness from moderate to severe drowsiness; however, they were not effective at telling the difference between moderate and severe levels. A binary model that lumped drowsiness into 2 classes had an area under the receiver operating characteristic (ROC) curve of 0.897.

Conclusions: Blinks and saccades have been shown to be predictive of microsleeps; however, it may be that detection of microsleeps and lane departures occurs too late. Therefore, it is encouraging that the model was able to distinguish mild from moderate drowsy driving. The use of automation may make vehicle-based signals useless for characterizing driver states, providing further motivation for a DMS. Future improvements in impairment detection systems may be expected through a combination of improved hardware, physiological measures from unobtrusive sensors and wearables, and the intelligent integration of environmental variables like time of day and time on task.     

Inventory routing for dynamic waste collection

We consider the problem of collecting waste from sensor equipped underground containers. These sensors enable the use of a dynamic collection policy. The problem, which is known as a reverse inventory routing problem, involves decisions regarding routing and container selection. In more dense networks, the latter becomes more important. To cope with uncertainty in deposit volumes and with fluctuations due to daily and seasonal effects, we need an anticipatory policy that balances the workload over time. We propose a relatively simple heuristic consisting of several tunable parameters depending on the day of the week. We tune the parameters of this policy using optimal learning techniques combined with simulation. We illustrate our approach using a real life problem instance of a waste collection company, located in The Netherlands, and perform experiments on several other instances. For our case study, we show that costs savings up to 40% are possible by optimizing the parameters.     

城市交通道路氮氧化物浓度的CART回归树预测研究

提出了基于CART回归树的氮氧化物(NO_x)浓度预测模型,利用杭州市延安路路边空气质量监测站2016年6—9月空气污染物监测数据和同期延安路路段车辆抓拍识别数据,通过数据处理、影响因素分析及CART回归树构造,搭建了NO_x浓度预测模型.实验分析结果表明,相对于支持向量机和BP神经网络预测模型,基于CART回归树的NO_x浓度预测模型的预测精度有大幅度提升,可决系数在0.92以上;同时,对环境条件差异较大的G20会议期间NO_x浓度进行预测分析,结果表明,CART回归树方法的预测精度比其它方法更高,能够适应不同条件下的预测需求.     

在数学教学中如何培养学生能力

学生能力的培养是教学活动的中心,本文通过对数学教学过程的总结和分析,就如何培养学生能力问题谈了自己的一些见解,并针对学习能力和理解能力的培养提出了一些措施。     

Resource distributions and diet development by trial-and-error learning

We study interactions between resource distributions, grouping, and diet development in foragers who learn by trial-and-error. We do this by constructing an individual-based model where individuals move and forage in groups in a 2-D space with high resource diversity and learn what to eat. By comparing diet development in different resource distributions, and in gregarious and solitary individuals, we elucidate how these factors affect patterns of diet variation. Our results indicate that different resource distributions have profound effects on learning opportunities, and thereby lead to contrasting phenomena. In uniform environments, local resource depletion by gregarious individuals, in interaction with learning, leads to diet differentiation. In patchy environments, grouping leads to enhanced diet overlap within groups and leads to differences in diet between groups. Surprisingly, mixed environments can generate all these phenomena simultaneously. Our results predict relationships between diet variation, trial-and-error learning, and resource distributions. The phenomena we describe are not evolved strategies, but arise spontaneously when groups of individuals learn to forage in certain resource distributions. This suggests that describing diet specialization or diet homogenization as the result of behavioral strategies may not always be justified.     

Less is more: social learning of predator recognition requires a low demonstrator to observer ratio in Arctic charr (Salvelinus alpinus)

Reintroduction programs for conservation purposes suffer from low post-release survival of captive-bred animals, especially so with fish reintroductions. High mortality is most often due to weakened antipredator skills, which could be enhanced through direct experience with predators and social learning. As yet, the relative efficiency of these learning methods has not been tested, and the significance of the factors determining how efficiently antipredator responses are transmitted socially from experienced (demonstrator) to predator naive (observer) individuals is largely unknown. Using hatchery-bred stock of the endangered Saimaa Arctic charr (Salvelinus alpinus), we show for the first time that: (1) contrary to theoretical predictions, acquired predator recognition was only socially transmitted from predator-experienced to predator-naive fish in groups with a smaller proportion of experienced than naive individuals, and that (2) socially acquired avoidance of the predator odors was as strong as in those fish conditioned with a combination of odors and predator exposure. We conclude that using social transmission procedures in training fish for reintroduction programs may provide considerable ecological, economical and ethical advantages.Communicated by J. Krause     

The dynamics of social learning in an insect model,the bumblebee (<Emphasis Type="Italic">Bombus terrestris</Emphasis>)

Bumblebees (Bombus terrestris) are attracted to those particular inflorescences where other bees are already foraging, a process known as local enhancement. Here, we use a quantitative analysis of learning in a foraging task to illustrate that this attraction can lead bees to learn more quickly which flower species are rewarding if they forage in the company of experienced conspecifics. This effect can also be elicited by model bees, rather than live demonstrators. We also show that local enhancement in bumblebees most likely reflects a general attraction to conspecifics that is not limited to a foraging context. Based on the widespread occurrence of both local enhancement and associative learning in the invertebrates, we suggest that social influences on learning in this group may be more common than the current literature would suggest and that invertebrates may provide a useful model for understanding how learning processes based on social information evolve.     

Individual recognition of song repertoires in two wood warblers

We examined recognition of individual neighbors in hooded warblers (Wilsonia citrina) and Kentucky warblers (Oporornis formosus) by comparing responses to playbacks of neighbors' songs from appropriate and inappropriate boundaries of the subjects' territories. Kentucky warblers, which sing one song type each, responded more strongly to the songs of neighbors broadcast from incorrect than from correct boundaries. Hooded warblers use their repertoires of three to nine song types in two distinct modes of singing: repeat mode involves repeated presentation of one song type; mixed mode involves presentation of two or more song types in irregular sequence. Playbacks of neighbors' mixed-mode songs from appropriate and inappropriate boundaries indicated capabilities of individual recognition similar to those reported previously for repeat-mode songs (Godard 1991) and to those of Kentucky warblers. Repertoires of moderate size, therefore, have no pronounced influence on eventual recognition of individual neighbors in hooded warblers.