Search

Estimation of bicycling volumes is essential for the strategic implementation of infrastructure and related transport elements and policies. Link-level volume estimation models (models that estimate volumes on individual street segments) allow for understanding variation in bicycling volumes across an entire network at higher spatial resolution than area-level models. Such models assist transport planners to efficiently monitor network usage, to identify opportunities to enhance safety and to evaluate the impact of policy and infrastructure interventions. However, given the sparsity and scarcity of bicycling data as compared to its motorised counterparts, link-level bicycling volume estimation literature is relatively limited. This paper conducts a scoping review of link-level bicycling volume estimation methods by implementing systematic search strategies across relevant databases, thereby identifying appropriate studies for the review. The review resulted in some interesting findings. Among all the methods implemented, direct demand modelling was the predominant one. Not a single study implemented multiple modelling approaches in the same study area, thereby not allowing for comparison of these approaches. Most studies were conducted in the United States. It was also observed that there exists a lot of heterogeneity in the reporting of basic study characteristics and validation results, sometimes to the extent of not reporting these at all. The study presents the different types of data used in modelling (count, travel survey, GPS data) along with an array of popular explanatory variables that can inform future studies about data collection and variable selection for modelling. The study discusses the strengths and limitations of different methods and finally presents recommendations for future research. [ABSTRACT FROM AUTHOR]

Natural disasters affect structural health of buildings, thus directly impacting public safety. Continuous structural monitoring can be achieved by deploying an Internet of things network of distributed sensors in buildings to capture floor movement. These sensors can be used to compute the displacements of each floor, which can then be employed to assess building damage after a seismic event. The peak relative floor displacement is computed, which is directly related to damage level according to the United States federal agencies standards. With this information, the building inventory can be classified into immediate occupancy, life safety, or collapse prevention categories. In this paper, we propose a zero velocity update technique to minimize displacement estimation error. Theoretical derivation and experimental validation are presented. In addition, we investigate modeling sensor error and interstory drift ratio distribution. Moreover, we discuss the impact of sensor error on the achieved building classification accuracy. [ABSTRACT FROM AUTHOR]

Right-of-way (R/W) acquisition, one of the most basic of preconstruction activities on a highway project, is an important subject by many state DOTs because the failure to make timely acquisitions of R/W causes significant delays and conflicts. Various management practices and strategies have been designed and implemented to deliver R/W acquisition on schedule but completing this preconstruction process is still not an easy activity for many state DOTs. The Texas DOT (TXDOT) is no exception. The research reported in this paper has identified all drivers that can be considered influential in the determination of durations for R/W acquisition; it was undertaken to improve the R/W duration-prediction capabilities of practitioners involved in regional districts of TXDOT. In the research process, each driver's importance level was evaluated by such practitioners. The practitioners, all of whom had different levels of accuracy at estimating durations, showed significantly different perceptions of the identified duration-drivers. Based on this observation, the research reported in this paper suggests that all drivers which show such significantly different levels of importance should be determined when predicting durations for R/W acquisition in a project's early-planning phase. The research reported in this paper demonstrates that determining the influential drivers is critical to accurately estimate durations for R/W acquisition on highway projects. [ABSTRACT FROM AUTHOR]

Over 70 million individuals are infected with hepatitis C virus (HCV) worldwide. Yet most prevalence data are in the adult population, with little focus on paediatrics, partially due to the scarcity of public data. The objective of this paper is to examine HCV prevalence in children by estimating prevalence rates among women, given the assumption that most cases are vertically transmitted. Between 2001 and 2017, maternal HCV infection affected ~ 0.24% of all births, with prevalence increasing by at least 261%. On average, approximately 0.01% of the total number of live births were infected with HCV, with a 245% increase in the number of children born with the infection. HCV epidemiology has evolved, with women of childbearing age representing a greater proportion of infected individuals in the United States, and infants born to infected mothers being at risk. We therefore recommend a greater public health focus of HCV on the paediatric population. [ABSTRACT FROM AUTHOR]

Vehicle inspection in an outbound automotive supply chain is a manual process performed in challenging conditions at various nodes along the transportation network. This paper describes the application of a statistical technique called 'capture-recapture (CR) modelling' (traditionally used in animal ecology estimation) to estimate the dealer claims based on the vehicle defects detected during inspection. Current industry practice in the USA permits the dealers to file the claims up to nine months after receiving the vehicles. The outcome of this research can be used to estimate the dealer claims at a one-month delay. Hence, the output of this model can be used to evaluate the progress made in the quality of the service in a finished vehicle supply chain without having to wait for the claims to be filed. On applying the CR technique to two assembly plants of a leading automotive manufacturer in the USA, the results were found to be statistically similar. Hence, the principles outlined in this paper can be used to estimate the claims in automotive supply chains more generally. [ABSTRACT FROM AUTHOR]

While digital map has been applied to many advanced driver assistance system applications, one critical attribute - road/lane curvature—is not available in the existing digital maps. Curvature derivation using splines is a well-known method in the computer graphics modelling community; however, it was also found that the direct application of the spline method is often not appropriate for real-time safety applications due to the resultant discontinuities in the curvature estimates and the lack of robustness against map data errors [CAMP, Enhanced digital mapping project final report, United States Department of Transportation, Washington, DC, 2004]. This paper presents a method to reconstruct road curvature attributes in real time using digital map data based on the proposed circle centre search and circle selection algorithms. Simulation and experimental results demonstrated that the proposed method can deliver curvature estimates that meet the desired accuracy. The method was also applied to the curve over-speed warning system in an on-going research project: Vehicle Infrastructure Integration—California. Some preliminary experimental results are also presented in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of making inferences about a population of infrastructure facilities from a subset that is a biased sample. We consider the case in which the sample is biased toward facilities in worse condition or requiring more expensive repair. Two methods are developed that incorporate a model of the process through which the sample is selected. One of the methods is based on well-known truncated distributions, whereas the other assumes that the bias operates continuously. The methods are applied to a class of facilities under the Federal Aviation Administration’s jurisdiction known as “unstaffed facilities.” These consist of structures housing radars, navigation aids, radio beacons, and other ground-based equipment, and no previous system-wide evaluation has been attempted for these facilities. We present and discuss the estimates obtained from both the methods, and examine their goodness-of-fit with the sample. Given the premise that bias exists, the continuous bias model proved more suitable. However, the continuous bias model did not surpass the truncation models in terms of goodness-of-fit. [ABSTRACT FROM AUTHOR]

The draft ICH E9(R1) addendum stipulates that an estimator should align with its associated estimand and yield an estimate that facilitates reliable interpretations. The addendum further stipulates that assumptions should be justifiable and plausible, and that the extent of assumptions is an important consideration for whether an estimate will be robust because assumptions are often unverifiable. The draft addendum specifies 5 strategies for dealing with intercurrent events. The intent of this paper is to provide conceptual considerations and technical details for various estimators that align with these strategies. We include focus on how the nature and extent of assumptions influences the potential robustness of the various estimators. The content reflects the knowledge, experience, and opinions of the Drug Information Association's Scientific Working Group on Missing Data. This group includes experienced statisticians from across industry and academia, primarily in the US and European Union. [ABSTRACT FROM AUTHOR]

The prevention of infectious diseases is a global health priority area. The early detection of possible epidemics is the first and important defense line against infectious diseases. However, conventional surveillance systems, e.g., the Centers for Disease Control and Prevention (CDC), rely on clinical data. The CDC publishes the surveillance results weeks after epidemic outbreaks. To improve the early detection of epidemic outbreaks, we designed a syndromic surveillance system to predict the epidemic trends based on disease-related Google search volume. Specifically, we first represented the epidemic trend with multiple alert levels to reduce the noise level. Then, we predicted the epidemic alert levels using a continuous density HMM, which incorporated the intrinsic characteristic of the disease transmission for alert level estimation. Respective models are built to monitor both national and regional epidemic alert levels of the U.S. The proposed system can provide real-time surveillance results, which are weeks before the CDC’s reports. This paper focusses on monitoring the infectious disease in the U.S., however, we believe similar approach may be used to monitor epidemics for the developing countries as well. [ABSTRACT FROM PUBLISHER]

Purpose - The purpose of this paper is to review issues pertaining to estimating market potential for consumer services which may cause underestimates of market potential and result in inappropriate marketing strategies. Particular attention is paid to the issue of double counting disqualified individuals. Design/methodology/approach - The process of estimating market potential for consumer services is described. Attention is paid to the role of factors that disqualify groups of individuals from inclusion in the relevant market and the problem of double counting disqualified individuals. Secondary data for enlistees in the United States Army are used to illustrate the process. Findings - The United States Armys estimate of its market potential was approximately twice as large as previous estimates when the double- counting of disqualified individuals was eliminated. Research implications/limitations - This is the first study appearing in the academic literature that directly addresses the issue of double-counting disqualified individuals when estimating market potential. It is intended to raise awareness of the issue and lead to a more thorough coverage of the topic in marketing textbooks and other practitioner-related materials. Practical implications - The process of estimating market potential applies to a broad range of service industries in which the double counting of disqualified individuals is an important issue. More accurate estimates of market potential can lead to more effective marketing strategies and improved allocation of marketing resources. Originality/value - A review of the literature indicates that, surprisingly, no previous studies have addressed these important issues. This article helps to fill that void. [ABSTRACT FROM AUTHOR]

Piracy is one of the most challenging problems faced by the motion picture industry. The Motion Picture Association of America estimates that US studios lose more than $3 billion annually in box office revenue from piracy. They have launched a major effort to prevent these losses. Yet their efforts are hampered by the ex post, counterfactual, and indirect methods by which losses are usually estimated. This paper addresses these issues directly. We develop and estimate a statistical model of the effects of piracy on the box-office performance of a widely-released movie. The model discredits the argument that piracy increases sales, showing unambiguously that Internet piracy diminished the box-office revenues of a widely released motion picture. The model overcomes a major weakness of counterfactual or “but for piracy” methods widely used to estimate damages. These counterfactual methods violate the “nobody knows” principle because they forecast what the movie would have earned in the absence piracy. The model we present does not violate this basic principle of motion picture uncertainty. We estimate that pre-release and contemporaneous Internet downloads of a major studio movie accelerated its box-office revenue decline and caused the picture to lose about $40 million in revenue. [ABSTRACT FROM AUTHOR]

Learning to estimate a linear measurement is critical in becoming a successful measurer. Research indicates that the teaching of the estimation of linear measurement is quite open and that instruction does not make explicit to students how to carry out estimation work. Because written curriculum has been identified as one of the main sources affecting teachers' instruction and students' learning, this study examined how estimation of linear measurement tasks were presented to students in three US elementary mathematics curricula to see how much and in what ways these tasks were presented in an open manner. The principal result was that the length estimation tasks were frequently not explicit about which attribute of the object to measure and the requested level of precision of the estimate. Length estimation tasks were also left more open than other measurement tasks like measuring length with rulers. [ABSTRACT FROM AUTHOR]

Implementation of the Federal Communications Commission's (FCC) E-911 Phase-2 requirements and commercial location-based services in urban environments requires mobile station (MS) localization capabilities in non-line-of-sight (NLOS) propagation conditions. This work addresses the problem of MS localization in urban environments characterized by the NLOS propagation conditions and limited Global Positioning System (GPS) services. We propose a single-base-station-based localization approach that uses a statistical model of urban propagation conditions in the framework of target classification. The proposed localization approach involves no data collection during the training process, requires no modifications of the MS hardware, is not location specific, and requires no identification and mitigation of the NLOS conditions. The performance of the proposed localization approach was evaluated using collected and ray-traced measurements. [ABSTRACT FROM PUBLISHER]

Classical threshold models assume that threshold values are constant and stable, which appears overly restrictive and unrealistic. In this article, we extend Hansen's (2000) constant threshold regression model by allowing for a time‐varying threshold which is approximated by a Fourier function. Least‐square estimation of regression slopes and the time‐varying threshold is proposed, and test statistics for the existence of threshold effect and threshold constancy are constructed. We also develop the asymptotic distribution theory for the time‐varying threshold estimator. Through Monte Carlo simulations, we show that the proposed estimation and testing procedures work reasonably well in finite samples, and there is little efficiency loss by the allowance for Fourier approximation in the estimation procedure even when there is no time‐varying feature in the threshold. On the contrary, the slope estimates are seriously biased when the threshold is time‐varying but being treated as a constant. The model is illustrated with an empirical application to a nonlinear Taylor rule for the United States. [ABSTRACT FROM AUTHOR]

In response to the strategic plan required by the Agricultural Act of 2014, the USDA Forest Service Forest Inventory and Analysis (FIA) program is initiating a strategic inventory of the nation's urban forests. The inventory is designed to provide timely and credible data on urban forests, thereby meeting an expanding need for information on trees located in communities where more than 80% of people live. The program monitors the status and trends of trees in urban settings (i.e. urban forests), enabling assessment of their composition and structure, ecosystem services and values, health, and risk from pests and disease. At full implementation with funding, resources, and partnerships in place, the program as designed would provide annual updates of urban forest conditions on approximately 68 million acres of land and for 100 of the most populous cities in the United States. The traditional forestland inventory of FIA continues and is complemented by the new urban inventory providing the means for a more complete assessment of the tree and forest resources across the United States. [ABSTRACT FROM AUTHOR]

Given the fact that more than 1 million crimes happened in USA every year, public safety becomes one of the most important concerns. Although many public safety related applications have been commercialized, how to guarantee safely walking to a destination especially in an unfamiliar city is still challenging. To provide a safe walking navigation in smart cities, we design a novel application SPATH (the Safest PATH). To support this service, wireless cameras, existing cellular infrastructure, and vehicles with underutilized computing resources are utilized to process and transmit surveillance videos, which can be viewed by users to check the current safety status of walking paths. Noting the long-distance transmission of a large volume of videos may cause network congestion; video summarizing technology, which is realized by utilizing the underutilized computing capability in vehicles, is applied to extract valuable information from a video file while effectively compressing its data size. Since the quality of service for this application is strongly correlated with the latency of delivering videos, we formulate a latency minimization problem by jointly considering the computing resource allocation and computing task assignment. A fast iterative matching is proposed with low complexity to effectively solve the optimization problem. Simulation results demonstrated the effectiveness and efficiency of our solution. [ABSTRACT FROM AUTHOR]

Dam reservoir capacity estimation is an important issue for operation, design and safety assessments of dam structures. In this study, the reservoir capacity of the Stony Brook dam in the USA was estimated by Generalized Regression Neural Network (GRNN), Support Vector Machines (SVM) and M5 Tree Model (M5T) methods with using 3726 data taken from United States Geological Survey Institute (USGS) for 2012-2015 years. Listed soft computing techniques give opportunities to researchers working on non-linear problems. Based on the non-linear approach, models are generated by using precipitation, flow, temperature hydrological parameters. The models were compared with each other according to the three statistical criteria, namely, mean absolute error (MAE), root mean square error (RMSE), and determination coefficient. As a result of the study, it is seen that Support Vector Machines (SVM) models have better performance in predicting dam reservoir level than the other used soft computing models. [ABSTRACT FROM AUTHOR]

A sample frame is the listing of the units from which a sample is to be selected. When deciding upon a file to serve as a source for a sample frame for a survey, perhaps the most important consideration is the extent to which the target population will be covered by the frame. However, other issues also come into play such as the accuracy of contact and other information appearing on the file as well as its cost. The American Medical Association Masterfile has long been considered the preferred choice for surveys of physicians, although it does have drawbacks. Here we consider two alternative files, discussing their relative advantages and disadvantages. For surveys of physician practices (or other organizations that employ physicians), there have been no files that are obvious choices to serve as the basis for a sample frame. Here we discuss data collection on physician practices from an analytic perspective and consider how sampling physicians to obtain practice level data may be a desirable approach. [ABSTRACT FROM AUTHOR]

The probable maximum precipitation (PMP), an estimate of the upper limit to storm rainfall, is determined using a catalog of extreme rainstorms. The effect of a recent extreme rainstorm—the northeastern Illinois storm of July 17–18, 1996—on PMP estimates for the Chicago area, is evaluated using standard PMP moisture maximization procedures. The results show that although the storm is a record rainfall event, its maximized precipitation is still below the PMP estimates for the Chicago area. Instead, a storm that occurred in Oklahoma, or perhaps another in Iowa, established the 24-h, 26-km2 (10-mi2) PMP estimate for Chicago. In either case, the higher maximized precipitation can be attributed to the combination of a larger storm rainfall amount, and a larger in-place moisture maximization factor. The case study also illustrates potential limitations with using standard PMP procedures. For instance, it is difficult to obtain an objective index to represent the mean moisture availability for this storm, since it has multiple rain periods. In addition, the estimated precipitable water based on standard PMP assumptions is much greater than that observed with upper-air soundings. Finally, for the same storm to occur under climatological maximum moisture conditions, a fundamental assumption in moisture maximization, dew points in the atmospheric profile would need to be increased beyond the observed air temperatures for the storm, a situation that is physically impossible. [ABSTRACT FROM AUTHOR]

With the elimination of the long-form questionnaire from future decennial censuses and its replacement by a much smaller continuous monthly sampling survey (the American Community Survey), students of territorial mobility may find it necessary to deal with inadequate, missing, or inaccurate sample data on migration by adopting an approach that “improves” such data using information from different geographical areas, time periods, and data sources. We develop such an approach in this article and illustrate it with interregional migration flow data reported by the U.S. decennial censuses of 1980 and 1990 and by the 1985 Current Population Survey. [ABSTRACT FROM AUTHOR]

Abstract: This study provides population-based normative data for healthy, community-dwelling American elderly on the Spot-the-Word test (STW). The effects of age, education, and gender on STW performance are also investigated. Given previously limited normative data for the elderly, the current norms expand the clinical utility of STW as an estimate of premorbid intelligence. Significant but small effects were found for age on STW performance. Significant and moderate effects were found for education. Therefore, normative adjustments are provided for education. Consistent with previous research, no effect was found for gender. [ABSTRACT FROM PUBLISHER]

Rates of change in final summer densities of two desert annuals, Eriogonum abertianum and Haplopappus gracilis , as constrained by their initial winter germination densities were estimated with regression quantiles and compared with mechanistic fits based on a self-thinning rule proposed by Guo et al. (1998); Oikos 83: 237–245). The allometric relation used was equivalent to S =N f (N i )-1=c f (N i )-1, where S is the ratio of final to initial densities (survivorship), c f is a constant that is a final density specific to the species and environment, N i is the initial plant density, and N f is final plant density. We used regression quantiles to estimate c f assuming the exponent of -1 was fixed (model 1, N f (N i )-1=c f (N i )-1) and also obtained estimates by treating the exponent as a parameter to estimate (model 2, N f (N i )-1=c f (N i )λ). Regression quantiles allow rates of change to be estimated through any part of a data distribution conditional on some linear function of covariates. We focused on estimates for upper (90–99th) quantiles near the boundary of the summer density distributions where we expected effects of self-thinning to operate as the primary constraint on plant performance. Allometric functions estimated with regression quantiles were similar to functions fit by Guo et al. (1998) when the exponent was constrained to -1. However, the data were more consistent with estimates for model (2), where exponents were closer to -0.4 than -1, although model fit was not as good at higher initial plant densities as when the exponent was fixed at -1. An exponential form (model 3, N f (N i )-1=c f (N i )λ eγNi) that is a generalization of the discrete logistic growth function, where estimates of λ were -0.23 to -0.28 and estimates of γ were -0.003 to -0.006, provided better fit from low to high initial germination densities. Model 3 predictions were consistent with an interpretation that final summer densities were constrained by initial germination densities when these were low (<40 per 0.25 m2 for Eriogonum and <100 per 0.25 m2 for Haplopappus ) and were constrained by the self-thinning process at higher germination densities. Our exponential model (3) estimated with regression quantiles had similar form to the mechanistic relation of Guo et al. (1998) when plotted as a survivorship function, but avoided the unrealistic assumption that all populations attained a similar final density, and was based on a statistical model that has formal rules for estimation and inference. [ABSTRACT FROM AUTHOR]