Impact of urban developments on the functional connectivity of forested habitats: a joint contribution of advanced urban models and landscape graphs

The impacts of urban growth on biodiversity vary according to the form and the intensity of urbanisation. However, there is a lack of knowledge about the consequences of the type of urban structure (e.g. monocentric vs polycentric), the shape of urban boundaries, the local density of residential development, on the habitats of wildlife species. In this context, this paper focuses on the relationship between forms of urbanisation and functional connectivity of ecological habitats. In the urban region of Besançon (eastern France), three emblematic protected species were selected to represent forest mammals. From the initial state describing current land cover, five prospective residential development scenarios were simulated, corresponding to the form currently most commonly found (e.g. compact development, transit-oriented development, polycentric development). For each scenario, we also simulate the volume of traffic on the road network to allow for the barrier effect of roads on habitat connectivity. Then, for each development scenario, we model the functional connectivity of habitats of the various target species using landscape graphs. Results show that compact city maintains more functional connectivity for all the species considered whereas urban sprawl leads to much more marked impacts. Moderately compact and regulated periurban scenarios have intermediate levels of impact. The transit-oriented development scenario produces specific impact values according to the species. An interesting point is that the decline in functional connectivity of forest habitats is more due to increased traffic than residential development proper. This outlines the relevance of integrated models for simulating both land use and transport at a fine scale.     

Government,enterprise and resident: Roles of local agents in regulating and simulating built-up land use and change in a mining city

Various agents are involved in decision-making when built-up land is allocated and regulated, but the roles of these agents must be clarified. To aid this process, the agents in Wu’an (a mining city in China) were classified as government, enterprise and resident, and then their roles were analyzed to establish a decision-making mechanism. The model of physical site selection for enterprises and residents was quantitatively simulated, taking into account the qualitative constraints from government and enterprises. Based on these rules, eight scenarios under economic development-driven scenario (EDdS) series and the environmental conservation-driven scenario (ECdS) series were set up, and vertical and horizontal comparisons were implemented for analysis. Our study showed that the established models could be well fitted for simulation, and that economic development could stimulate the allocation of more built-up land. The most important achievement is that the proposed comparison can effectively distinguish among the roles of various agents, as well as quantify government and enterprise incentives.     

《给排水处理仿真教学软件》的开发与应用

《给排水处理课程仿真教学软件》经过多年的开发成功,在给排水专业主干课程污水处理和给水处理的教学改革中取得了成效,符合高等职业教育教学规律,在社会上取得了良好的声誉。本文对该软件的技术开发与实践效果进行论述。     

基于电度表校验台用PWM电源失真问题的解决措施及MATLAB仿真分析

本文首先对电度表校验台用PWM电源的失真进行分析,指出在应用中存在的问题,并提出解决方案,并用MATLAB进行仿真。     

医药供应链需求不确定性仿真研究

针对医院主导型医药供应链提出了一个仿真模型,定量分析了需求不确定性对医院服务水平的影响,模型结果有助于医院在保证服务水平的前提下控制存储成本。     

仿真软件在电子技术设计型实验中的应用

介绍了仿真软件Proteus的功能及特点,结合电子电路实例阐述了该软件在电子技术设计型实验中的具体应用,及Proteus仿真实验与实际操作实验的优缺点,提出虚-实结合的电子技术设计型实验教学是最佳实验教学模式之一的观点.     

外部集卡到港控制优化研究

外部集卡到港失控是导致码头拥堵的重要原因之一。基于此,提出了将仿真和数学建模相结合的方法,应用仿真描述了外卡在码头的作业流程,应用数学建模方法描述了系统目标,并设计了相应的优化算法。     

Directional accuracy,forecasting error and the profitability of currency trading: model-based evidence

Three models (the flexible-price monetary model, PPP and a univariate ARIMA model) are estimated for 45 currency pairs to find out if the profitability of forecasting-based currency trading is more related to the ability of the underlying model to predict the direction of change than the magnitude of the forecasting error. Theoretical considerations show that a correct prediction of the direction of change is neither a necessary nor a sufficient condition for a profitable trade. The results of the exercise indicate that profitability is more strongly correlated with directional accuracy than with the magnitude of the error.     

How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market share variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.     

Analyzing airport security checkpoint performance using cognitive agent models

Modern airports operate under high demands and pressures, and strive to satisfy many diverse, interrelated, sometimes conflicting performance goals. Airport performance areas, such as security, safety, and efficiency are usually studied separately from each other. However, operational decisions made by airport managers often impact several areas simultaneously. Current knowledge on how different performance areas are related to each other is limited. This paper contributes to filling this gap by identifying and quantifying relations and trade-offs between the detection performance of illegal items and the average queuing time at airport security checkpoints. These relations and trade-offs were analyzed by simulations with a cognitive agent model of airport security checkpoint operations. By simulation analysis a security checkpoint performance curve with three different regions was identified. Furthermore, the importance of focus on accuracy for a security operator is shown. The results of the simulation studies were related to empirical research at an existing regional airport.