Ecological Risk Assessment Framework for Low-Altitude Aircraft Overflights: I. Planning the Analysis and Estimating Exposure

An ecological risk assessment framework for low-altitude aircraft overflights was developed, with special emphasis on military applications. The problem formulation and exposure analysis phases are presented in this article; an analysis of effects and risk characterization is presented in a companion article. The intent of this article is threefold: (1) to illustrate the development of a generic framework for the ecological risk assessment of an activity, (2) to show how the U.S. Environmental Protection Agency's ecological risk assessment paradigm can be applied to an activity other than the release of a chemical, and (3) to provide guidance for the assessment of ecological risks from low-altitude aircraft overflights. The key stressor for low-altitude aircraft overflights is usually sound, although visual and physical (collision) stressors may also be significant. Susceptible and regulated wildlife populations are the major assessment endpoint entities, although plant communities may be impacted by takeoffs and landings. The exposure analysis utilizes measurements of wildlife locations, measurements of sound levels at the wildlife locations, measurements of slant distances from aircraft to wildlife, models that extrapolate sound from the source aircraft to the ground, and bird-strike probability models. Some of the challenges to conducting a risk assessment for aircraft overflights include prioritizing potential stressors and endpoints, choosing exposure metrics that relate to wildlife responses, obtaining good estimates of sound or distance, and estimating wildlife locations.     

A Heuristic Risk Assessment Technique for Birdstrike Management at Airports

Collisions between birds and aircraft (birdstrikes) have caused the loss of at least 88 aircraft and 243 lives in world civil aviation. Conservative estimates suggest that more routine damage and delays following birdstrikes cost the industry and its insurers US$1.2-1.5 billion per year. The majority of strikes happen close to airports and most countries have regulations that require airport managers to control the birdstrike risk on their property. Birdstrike prevention has, however, lagged behind other aspects of flight safety in the development and implementation of risk assessment protocols, possibly because of the inherent difficulty in quantifying the variability in the populations and behavior of the various bird species involved. This article presents a technique that uses both national and airport-specific data to evaluate risk by creating a simple probability-times-severity matrix. It uses the frequency of strikes reported for different bird species at a given airport over the preceding five years as a measure of strike probability, and the proportion of strikes with each species that result in damage to aircraft, in the national birdstrike database, as a measure of likely severity. Action thresholds for risk levels for particular bird species are then defined, above which the airport should take action to reduce the risk further. The assessment is designed for airports where the reporting and collation of birdstrike events is reasonably consistent over time and where a bird hazard management program of some sort is already in place. This risk assessment is designed to measure risk to the airport as a business rather than risk to the traveling passenger individually. It therefore takes no account of aircraft movement rate in the calculations and is aimed at minimizing the number of damaging incidents rather than concentrating on catastrophic events. Once set up at an airport, the technique is simple to implement for nonexperts, and it allows managers to focus bird control resources on the species causing the greatest risk, hence maximizing the return on investment. This protocol is now being successfully used at major airports in the United Kingdom and elsewhere in the world.     

基于协同救助的海上救助报酬合理分配方法

海上救助报酬是为鼓励人们冒险参与海上救援,由受益人给予救助人的补偿和回报,具有射幸性,奉行“无效果、无报酬”的给付原则。本文以救助方成本性和非成本性投入对救助效果的贡献为依据,首先对各方的成本性投入进行补偿;然后从资源要素的关键性和参与人的重要性两个维度对各救助方的贡献进行综合评价,并按贡献度对“剩余”部分进行二次分配,两次分配之和即为各救助方所获得的分配总额。通过运用“重购成本”和Shapley值法分别对资源要素的关键性和参与人的重要性进行客观度量,该方法可同时解决共同救助报酬的外部分配与内部分配问题,不仅避免了目前各国司法实践中按成本投入比例进行分配的不合理性,也更能体现相关国际公约和国内立法有关救助报酬分配的原则。     

Modelling process robustness: a case study of centrifugal casting

A robust process minimises the effect of the noise factors on the performance of a product or process. The variation of the performance of a robust process can be measured through modelling and analysis of process robustness. In this paper, a comprehensive methodology for modelling and analysis of process robustness is developed considering a number of relevant tools and techniques such as multivariate regression, control charting and simulation within the broad framework of Taguchi method. The methodology as developed considers, in specific terms, process modelling using historical data pertaining to responses, inputs variables and parameters as well as simulated noise variables data, identification of the model responses at each experimental setting of the controllable variables, estimation of multivariate process capability indices and control of their variability using control charting for determining optimal settings of the process variables using design of experiment-based Taguchi Method. The methodology is applied to a centrifugal casting process that produces worm-wheels for steam power plants in view of its critical importance of maintaining consistent performance in various under controllable situations (input conditions). The results show that the process settings as determined ensure minimum in-control variability with maximum performance of the centrifugal casting process, indicating improved level of robustness.     

存在保证域的模糊非径向偏好DEA模型——基于中科院24个研究所的实证分析

数据包络分析（DEA）是一种非参数化的方法,用于评价具有类似输入和输出的决策单元的效率。传统的非径向DEA模型假设输入和输出数据均为准确值,且对权重变量不加以限制,本文构建了存在保证域的模糊非径向偏好DEA模型,并给出了一种基于模糊数截集的模型求解方法,有效地解决了输入和输出全部或部分为模糊数的决策单元评价问题。最后给出了一个中科院研究所效率评价的实例说明了方法的有效性。     

Integrated framework for robustness analysis using ratio-based efficiency model with application to evaluation of Polish airports

We consider a problem of evaluating efficiency of Decision Making Units (DMUs) based on their deterministic performance on multiple consumed inputs and multiple produced outputs. We apply a ratio-based efficiency measure, and account for the Decision Maker׳s preference information representable with linear constraints involving input/output weights. We analyze the set of all feasible weights to answer various robustness concerns by deriving: (1) extreme efficiency scores and (2) extreme efficiency ranks for each DMU, (3) possible and necessary efficiency preference relations for pairs of DMUs, (4) efficiency distribution, (5) efficiency rank acceptability indices, and (6) pairwise efficiency outranking indices. The proposed hybrid approach combines and extends previous results from Ratio-based Efficiency Analysis and the SMAA-D method. The practical managerial implications are derived from the complementary character of accounted perspectives on DMUs׳ efficiencies. We present an innovative open-source software implementing an integrated framework for robustness analysis using a ratio-based efficiency model on the diviz platform. The proposed approach is applied to a real-world problem of evaluating efficiency of Polish airports. We consider four inputs related to the capacities of a terminal, runways, and an apron, and to the airport׳s catchment area, and two outputs concerning passenger traffic and number of aircraft movements. We present how the results can be affected by integrating the weight constraints and eliminating outlier DMUs.     

Comparison of Sensitivity Analysis Methods Based on Applications to a Food Safety Risk Assessment Model

Sensitivity analysis (SA) methods are a valuable tool for identifying critical control points (CCPs), which is one of the important steps in the hazard analysis and CCP approach that is used to ensure safe food. There are many SA methods used across various disciplines. Furthermore, food safety process risk models pose challenges because they often are highly nonlinear, contain thresholds, and have discrete inputs. Therefore, it is useful to compare and evaluate SA methods based upon applications to an example food safety risk model. Ten SA methods were applied to a draft Vibrio parahaemolyticus (Vp) risk assessment model developed by the Food and Drug Administration. The model was modified so that all inputs were independent. Rankings of key inputs from different methods were compared. Inputs such as water temperature, number of oysters per meal, and the distributional assumption for the unrefrigerated time were the most important inputs, whereas time on water, fraction of pathogenic Vp, and the distributional assumption for the weight of oysters were the least important inputs. Most of the methods gave a similar ranking of key inputs even though the methods differed in terms of being graphical, mathematical, or statistical, accounting for individual effects or joint effect of inputs, and being model dependent or model independent. A key recommendation is that methods be further compared by application on different and more complex food safety models. Model independent methods, such as ANOVA, mutual information index, and scatter plots, are expected to be more robust than others evaluated.     

Responsive Pricing Newsvendor Networks with Discretionary Commonality

Discretionary commonality is a form of operational flexibility used in multi‐product manufacturing environments. Consider a case where a firm produces and sells two products. Without discretionary commonality, each product is made through a unique combination of input and production capacity. With discretionary commonality, one of the inputs could be used for producing both products, and one of the production capacities could be used to process different inputs for producing one of the products. In the latter case, the manager can decide, upon the realization of uncertainty, not only the quantities for different products (outputs) but also the means of transforming inputs into outputs. The objective of this study is to understand how the firm's value, its inventory levels for inputs and capacity levels for resources are affected by the demand characteristics and market conditions. In pursuing this research, we extend Van Mieghem and Rudi ( 2002 )'s newsvendor network model to allow for the modeling of product interdependence, demand functions, random shocks, and firm's ex post pricing decision. Applying the general framework to the network with discretionary commonality, we discover that inventory and capacity management can be quite different compared to a network where commonality is non‐discretionary. Among other results, we find that as the degree of product substitution increases, the relative need for discretionary commonality increases; as the market correlation increases, while the firm's value may increase for complementary products, the discretionary common input decreases but the dedicated input increases. Numerical study shows that discretionary flexibility and responsive pricing are strategic substitutes.     

A Nerlovian cost inefficiency two-stage DEA model for modeling banks’ production process: Evidence from the Turkish banking system

By developing a two-stage model the paper examines the cost inefficiency levels of Turkish banks during the period from 2007 to 2016. Using the notion of Koopmans input efficiency we deconstruct the estimated Nerlovian cost inefficiency to the sum of slack-based allocative and technical inefficiency levels. Alongside the traditional inputs, intermediates and outputs used to model banks’ performance measure we additionally use their labor education quality factor as a non-discretionary input. This allows us to model how human capital factors affect a bank's revenue generation stage. Our findings suggest that cost inefficiency levels are driven mainly by a bank's ability to control its allocative inefficiency levels. The empirical evidence also shows that foreign banks perform better, suggesting that bank ownership structures matter when measuring cost performance. Finally, it is evident that the Global Financial Crisis (GFC) had a negative effect on banks’ ability to minimize their cost inefficiency levels. However, the post-crisis findings demonstrate that Turkish banks have started to recover from its negative effects, mainly by improving their allocative performance.     

Additive manufacturing’s impact and future in the aviation industry

Additive manufacturing (AM) is a technology that has the potential to change the future of aviation supply chains and how the aviation industry designs, manufactures and repairs aircraft in the future. The purpose of this research was to shed light on the current and future states of AM in the aviation industry. From focus groups with nearly 50 aviation professionals from aircraft original equipment manufacturers (OEMs), suppliers, maintenance repair overhaul providers, and AM service providers and AM production firms, we found that the adoption of AM will be triggered by the accumulated AM experience in the industry, the stability of AM technology and the development of new aircraft generations. For AM to be finally adopted, aircraft OEMs must actively manage several success factors and monitor numerous control factors identified and discussed in this research. AM will supplement traditional manufacturing processes at least in the short to midterm, likely grow exponentially and offer benefits for players in the aviation supply chain.     

The use of period batch control (PBC) in the implosive industries

Period batch control (PBC) is a just-in-time (JIT) production control system of the flow control, single cycle type. It was developed in the UK before the Second World War, by the late R. J. Gigli, who installed it in 30 different factories and used it to regulate the manufacture of Spitfire fighter aircraft for the Battle of Britain. Implosive industries are those—such as foundries, glass works, spinning mills and potteries, among others—which produce a wide variety of different products from a very small number of material items. The paper shows how PBC is used in implosive industries, and explains why it is normally the best method to adopt in such factories.     

Informing Ex Ante Event Studies with Macro‐Econometric Evidence on the Structural and Policy Impacts of Terrorism

Economic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event‐specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates of return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or ex ante surveys. This article explores a new method. We elucidate the magnitude of CGE‐relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future ex ante event assessments. Ex post econometric studies of terrorism by Blomberg et al . yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the United States. This allows us to: (i) compare values for these shifts with input assumptions in earlier ex ante CGE studies; and (ii) discuss how future ex ante studies can be informed by our analysis.     

电子商务与企业竞争优势

本文运用进化博弈理论和企业竞争战略理论对于企业运用电子商务的过程进行了分析,指出获取长期竞争优势是企业运用电子商务的根本动机,并对电子商务给企业带来竞争优势的机制做了细致的探讨,最后根据国内外企业电子商务发展的规律,给出我国企业发展电子商务所应采取的策略。     

A Neural Network-Based Method for Risk Factor Analysis of West Nile Virus

There is a lack of knowledge about which risk factors are more important in West Nile virus (WNV) transmission and risk magnitude. A better understanding of the risk factors is of great help in developing effective new technologies and appropriate prevention strategies for WNV infection. A contribution analysis of all risk factors in WNV infection would identify those major risk factors. Based on the identified major risk factors, measures to control WNV proliferation could be directed toward those significant risk factors, thus improving the effectiveness and efficiency in developing WNV control and prevention strategies. Neural networks have many generally accepted advantages over conventional analytical techniques, for instance, ability to automatically learn the relationship between the inputs and outputs from training data, powerful generalization ability, and capability of handling nonlinear interactions. In this article, a neural network model was developed for analysis of risk factors in WNV infection. To reveal the relative contribution of the input variables, the neural network was trained using an algorithm called structural learning with forgetting. During the learning, weak neural connections are forced to fade away while a skeletal network with strong connections emerges. The significant risk factors can be identified by analyzing this skeletal network. The proposed approach is tested with the dead bird surveillance data in Ontario, Canada. The results demonstrate the effectiveness of the proposed approach.     

非参数计量经济联立模型的局部线性广义矩估计

联立方程模型在经济政策制定、经济结构分析和经济预测方面起重要作用。本文在随机设计(模型中所有变量为随机变量)下,提出了非参数计量经济联立模型的局部线性广义矩估计并利用概率论中大数定理和中心极限定理在内点处研究了它的大样本性质,证明了它的一致性和渐近正态性。它在内点处的收敛速度达到了非参数函数估计的最优收敛速度。     

Board characteristics and the value relevance of fair values

This study investigates whether board characteristics affect the value relevance of fair value estimates in financial firms under International Financial Reporting Standard (IFRS) 13. Specifically, the study will focus on whether a better and more efficient monitoring of managers, after the adoption of this new regulation, has an effect on the information quality of fair values. IFRS 13 requires firms to disclose a fair value hierarchy containing three levels: Level 1 (quoted prices in active markets), Level 2 (inputs other than quoted prices that are observable either directly or indirectly) and Level 3 (unobservable inputs generated by entities). The results indicate that, in a post IFRS 13 era, board independence and gender diversity have a positive effect on the value relevance of fair value estimates (Level 3). In addition, firms with larger boards have lower information quality of firm-generated fair value estimates. Moreover, initial analysis shows that all fair values are value relevant to investors and the adoption of IFRS 13 has blurred the lines between the three levels in the fair value hierarchy. Hence, IFRS 13 has successfully reduced the information asymmetry related to fair value estimates.     

Efficiency and Equilibrium with Dynamic Increasing Aggregate Returns due to Demand Complementarities

When do dynamic nonconvexities at the disaggregate level translate into dynamic nonconvexities at the aggregate level? We address this question in a framework where the production of differentiated intermediate inputs is subject to dynamic nonconvexities, and we show that the answer depends on the degree of Hicks-Allen complementarity (substitutability) between differentiated inputs. In our simplest model, a generalization of Judd (1985) and Grossman and Helpman (1991) among many others, there are dynamic nonconvexities at the aggregate level if and only if differentiated inputs are Hicks-Allen complements. We also compare dynamic equilibrium and optimal allocations in the presence of aggregate dynamic nonconvexities due to Hicks-Allen complementarities between differentiated inputs.     

Ecological Risk Assessment Framework for Low-Altitude Aircraft Overflights: II. Estimating Effects on Wildlife

An ecological risk assessment framework for aircraft overflights has been developed, with special emphasis on military applications. This article presents the analysis of effects and risk characterization phases; the problem formulation and exposure analysis phases are presented in a companion article. The framework addresses the effects of sound, visual stressors, and collision on the abundance and production of wildlife populations. Profiles of effects, including thresholds, are highlighted for two groups of endpoint species: ungulates (hoofed mammals) and pinnipeds (seals, sea lions, walruses). Several factors complicate the analysis of effects for aircraft overflights. Studies of the effects of aircraft overflights previously have not been associated with a quantitative assessment framework; therefore no consistent relations between exposure and population-level response have been developed. Information on behavioral effects of overflights by military aircraft (or component stressors) on most wildlife species is sparse. Moreover, models that relate behavioral changes to abundance or reproduction, and those that relate behavioral or hearing effects thresholds from one population to another are generally not available. The aggregation of sound frequencies, durations, and the view of the aircraft into the single exposure metric of slant distance is not always the best predictor of effects, but effects associated with more specific exposure metrics (e.g., narrow sound spectra) may not be easily determined or added. The weight of evidence and uncertainty analyses of the risk characterization for overflights are also discussed in this article.     

A Grasp for Aircraft Routing in Response to Groundings and Delays

This paper presents a greedy randomized adaptive search procedure (GRASP) to reconstruct aircraft routings in response to groundings and delays experienced over the course of the day. Whenever the schedule is disrupted, the immediate objective of the airlines is to minimize the cost of reassigning aircraft to flights taking into account available resources and other system constraints. Associated costs are measured by flight delays and cancellations.In the procedure, the neighbors of an incumbent solution are generated and evaluated, and the most desirable are placed on a restricted candidate list. One is selected randomly and becomes the incumbent. The heuristic is polynomial with respect to the number of flights and aircraft. This is reflected in our computational experience with data provided by Continental Airlines. Empirical results demonstrate the ability of the GRASP to quickly explore a wide range of scenarios and, in most cases, to produce an optimal or near-optimal solution.     

U.S. Aviation Regulations Increase Probability of Midair Collisions

A purely stochastic Monte Carlo model is used to compare the relative midair collision course probabilities and mean closing velocities of four systems of rules for aircraft cruising altitudes as a function of altitude error: (1) current U.S. federal rules, (2) random altitudes, and (3) two proposed alternatives to the current rules. This model increments error while: (1) counting collisions among cruising pairs of aircraft following the four rules being tested on random headings between randomly placed airports, and (2) calculating mean closing velocities for each rule. The calculations verify that: (1) federal rules increase collision course probabilities by about four times more than for a chaotic system of aircraft cruising at randomly selected altitudes, (2) risk is directly proportional to the level of compliance, and (3) mean closing velocities resulting from the current rule are slightly less than for random altitudes, while being almost twice as high as for the proposed rules. High closing velocities are shown to increase the collision probability.