Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Arc routing problems to restore connectivity of a road network

After a disaster, restoring accessibility in the affected area is critical for response operations. We study two arc routing problems for clearing blocked roads. The first problem minimizes the time to reconnect the road network, while the second maximizes the total benefit gained by reconnecting network components within a time limit. For each problem, we develop a mixed integer programming formulation and two versions of a heuristic algorithm. We conduct computational experiments on Istanbul data and instances adapted from the literature. The heuristics achieve near-optimal or optimal solutions quickly in most of the tested instances.     

A contingent plan for disaster response

Natural and man-made disasters imply a great deal of uncertainty in terms of potential damage, though it is certain that there would be a huge spike in the demand for relief supplies causing shortages and/or delays in providing aid. Ruptures in the infrastructure (roads, utility, and communication lines) cause additional delays due to repairs. Therefore, the relief providers need to work in collaboration with retailers, and infrastructure service providers for improving responsiveness. The relief providers (government and non government) rely on acquiring and delivering supplies in real time because such actions accompany little risk of resource underutilization, though the cost of real time acquisitions can be high. In contrast, a proactive response, while minimizing acquisition cost, can be very ineffective if demand surges are high. We study a hybrid of reactive and proactive approaches, where the reactive response is contingent upon the disaster intensity exceeding a certain threshold. We show how the threshold value may impact capacity acquisitions and prices and establish the optimality of contingent response. Further, we establish how an infrastructure contract may help reducing the social cost of disaster.     

Local Venturing as Compassion Organizing in the Aftermath of a Natural Disaster: The Role of Localness and Community in Reducing Suffering

In contrast to models of compassion within existing organizations, this grounded theory study examines how ventures emerge relying on localness and community in direct response to ‘opportunities’ to alleviate suffering in the aftermath of a natural disaster. While a natural disaster is a surprising disruptive event devastating a local community, that local community is nested within a broader community, which can be a source of abundant resources. Ventures created in the aftermath of a natural disaster, given local knowledge and unencumbered by pre‐existing systems, procedures, and capabilities, are highly effective at connecting the broader community with the local community through customizing resources to meet victims' needs and to quickly delivering these resources to alleviate suffering.     

A true simulation study of three estimators at equal protection of respondents in randomized response sampling

In this study, three different estimators for estimating the proportion of a sensitive attribute in survey sampling are compared at equal protection of the respondents. The three estimators considered are due to Odumade and Singh (2009, Comm. Statist. Theory Methods) , Singh and Sedory (2011, Sociological Methods and Research) and a new estimator obtained by minimizing a chi‐squared distance. A SAS Macro is developed to compare these three estimators using a simulation study at equal protection of the respondents. A set of data from a real face‐to‐face interview was collected using two decks of cards and has been analyzed. The results are discussed.     

Volatility Relationship between Crude Oil and Petroleum Products

This paper utilizes calculated historical volatility and GARCH models to compare the historical price volatility behavior of crude oil, motor gasoline and heating oil in U.S. markets since 1990. We incorporate a shift variable in the GARCH/TARCH models to capture the response of price volatility to a change in OPEC’s pricing behavior. This study has three major conclusions. First, there was an increase in volatility as a result of a structural shift to higher crude oil prices after April 1999. Second, volatility shocks from current news are not important since GARCH effects dominate ARCH effects in the variance equation. Third, persistence of volatility in all commodity markets is quite transitory, with half-lives normally being a few weeks.

优化外商直接投资结构的研究——基于行业FDI数据的VAR模型

根据1990—2010年全国国内生产总值（GDP）、FDI在制造业的投资额（FM）、FDI在服务业的投资额（FS）、FDI在房地产业的投资额（FRE）及在教育领域的投资额（FE）的统计数据进行基于VAR模型的实证分析,认为长期看,外商在制造业的投资额（FM）和在服务业的投资额（FS）的增加导致全国GDP的增加,外商在房地产业的投资额（FRE）以及在教育领域的投资额（FE）与GDP反向变动;短期看,对全国经济发展的短期影响程度由高到低,依次是FDI在服务业的投资额（FS）、在制造业的投资额（FM）和在教育领域的投资额（FE）以及在房地产业的投资额（FRE）。建议以国务院颁布的《外商投资产业指导目录》为导向,积极利用外资及优化外商投资结构,在发挥外资对我国经济的积极推动作用的同时尽量减少外资的负面影响。     

基于VAR模型的江苏省投资、消费与经济增长实证分析

本文利用江苏省1980年到2007年经济数据,在VAR模型的基础上,运用协整检验、格兰杰因果检验、脉冲响应分析和方差分解的方法对江苏省的投资、消费与经济增长之间的关系进行实证分析。结果发现,投资、消费和经济增长之间具有长期均衡关系,江苏省地区生产总值的增长与投资和消费都具有双向因果关系,消费对经济增长的贡献度比投资更大。因此,通过提高居民收入水平,才能刺激消费,促进江苏经济健康发展。     

大学校园商业活动的利弊分析与管理应对

随着近年来全国各大学的扩招与大学城的扩建,大学校园商业活动的发展势头逐渐呈上升趋势。大学校园商业活动对于大学的发展以及大学师生的学习生活具有非常积极的意义,但同时也存在一些消极隐患。针对这些隐患,只有采取相关有效的应对策略,才能真正实现大学校园商业活动的良性发展进而营造学校、师生与商家的共赢局面。