Nonlinear models and small sample performance of the generalized method of moments

In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models.

Evaluation of oviposition traps as an entomological surveillance method for Aedes aegypti (Diptera, Culicidae)

This study aimed to describe the behavior of oviposition traps for Aedes aegypti over time, to compare it with the larval survey and to investigate the association with climatic variables. It was conducted in São José do Rio Preto city, São Paulo. Daily climatic data and fortnightly measurements for oviposition traps and larval infestation were collected from October 2003 to September 2004. Three different periods were identified in the behavior of oviposition traps' positivity and mean number of eggs: increase, plateau and decrease in values. These measurements followed the variation of climatic data from the first and third periods. High correlation was obtained between the positivity and the mean number of eggs. The oviposition traps showed higher capacity to detect the vector than did larval survey. It was observed that the first (October to December) and third (May to September) periods were considered to be the most suitable to use oviposition traps than larval surveys.

What risks do people perceive in everyday life? A perspective gained from the experience sampling method (ESM)

The experiential sampling method (ESM) was used to collect data from 74 parttimestudents who described and assessed the risks involved in their current activitieswhen interrupted at random moments by text messages. The major categories ofperceived risk were short-term in nature and involved loss of time or materials relatedto work and physical damage (e.g., from transportation). Using techniques of multilevelanalysis, we demonstrate effects of gender, emotional state, and types of risk onassessments of risk. Specifically, females do not differ from males in assessing thepotential severity of risks but they see these as more likely to occur. Also, participantsassessed risks to be lower when in more positive self-reported emotional states. Wefurther demonstrate the potential of ESM by showing that risk assessments associatedwith current actions exceed those made retrospectively. We conclude by notingadvantages and disadvantages of ESM for collecting data about risk perceptions.

Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

Spatial evaluation of larvae of Culicidae (Diptera) from different breeding sites: application of a geospatial method and implications for vector control

Spatial evaluation of Culicidae (Diptera) larvae from different breeding sites: application of a geospatial method and implications for vector control. This study investigates the spatial distribution of urban Culicidae and informs entomological monitoring of species that use artificial containers as larval habitats. Collections of mosquito larvae were conducted in the São Paulo State municipality of Santa Bárbara d' Oeste between 2004 and 2006 during house-to-house visits. A total of 1,891 samples and nine different species were sampled. Species distribution was assessed using the kriging statistical method by extrapolating municipal administrative divisions. The sampling method followed the norms of the municipal health services of the Ministry of Health and can thus be adopted by public health authorities in disease control and delimitation of risk areas. Moreover, this type of survey and analysis can be employed for entomological surveillance of urban vectors that use artificial containers as larval habitat.

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

New method for rearing Spodoptera frugiperda in laboratory shows that larval cannibalism is not obligatory

New method for rearing Spodoptera frugiperda in laboratory shows that larval cannibalism is not obligatory. Here we show, for the first time, that larvae of the fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera, Noctuidae), can be successfully reared in a cohort-based manner with virtually no cannibalism. FAW larvae were reared since the second instar to pupation in rectangular plastic containers containing 40 individuals with a surprisingly ca. 90% larval survivorship. Adult females from the cohort-based method showed fecundity similar to that already reported on literature for larvae reared individually, and fertility higher than 99%, with the advantage of combining economy of time, space and material resources. These findings suggest that the factors affecting cannibalism of FAW larvae in laboratory rearings need to be reevaluated, whilst the new technique also show potential to increase the efficiency of both small and mass FAW rearings.

Buffer Capacity Allocation: A method to QoS support on MPLS networks

This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network

The profiling of false identity documents: a promising method to fight identity fraud

Under the influence of intelligence-led policing models, crime analysis methods have known of important developments in recent years. Applications have been proposed in several fields of forensic science to exploit and manage various types of material evidence in a systematic and more efficient way. However, nothing has been suggested so far in the field of false identity documents.This study seeks to fill this gap by proposing a simple and general method for profiling false identity documents which aims to establish links based on their visual forensic characteristics. A sample of more than 200 false identity documents including French stolen blank passports, counterfeited driving licenses from Iraq and falsified Bulgarian driving licenses was gathered from nine Swiss police departments and integrated into an ad hoc developed database called ProfID. Links detected automatically and systematically through this database were exploited and analyzed to produce strategic and tactical intelligence useful to the fight against identity document fraud.The profiling and intelligence process established for these three types of false identity documents has confirmed its efficiency, more than 30% of documents being linked. Identity document fraud appears as a structured and interregional criminality, against which material and forensic links detected between false identity documents might serve as a tool for investigation.

A noninvasive method for measuring the velocity of diffuse hydrothermal flow by tracking moving refractive index anomalies

Diffuse flow velocimetry (DFV) is introduced as a new, noninvasive, optical technique for measuring the velocity of diffuse hydrothermal flow. The technique uses images of a motionless, random medium (e.g.,rocks) obtained through the lens of a moving refraction index anomaly (e.g., a hot upwelling). The method works in two stages. First, the changes in apparent background deformation are calculated using particle image velocimetry (PIV). The deformation vectors are determined by a cross correlation of pixel intensities across consecutive images. Second, the 2-D velocity field is calculated by cross correlating the deformation vectors between consecutive PIV calculations. The accuracy of the method is tested with laboratory and numerical experiments of a laminar, axisymmetric plume in fluids with both constant and temperaturedependent viscosity. Results show that average RMS errors are ∼5%–7% and are most accurate in regions of pervasive apparent background deformation which is commonly encountered in regions of diffuse hydrothermal flow. The method is applied to a 25 s video sequence of diffuse flow from a small fracture captured during the Bathyluck’09 cruise to the Lucky Strike hydrothermal field (September 2009). The velocities of the ∼10°C–15°C effluent reach ∼5.5 cm/s, in strong agreement with previous measurements of diffuse flow. DFV is found to be most accurate for approximately 2‐D flows where background objects have a small spatial scale, such as sand or gravel

A new maximum likelihood method for luminosity calibrations

A new statistical parallax method using the Maximum Likelihood principle is presented, allowing the simultaneous determination of a luminosity calibration, kinematic characteristics and spatial distribution of a given sample. This method has been developed for the exploitation of the Hipparcos data and presents several improvements with respect to the previous ones: the effects of the selection of the sample, the observational errors, the galactic rotation and the interstellar absorption are taken into account as an intrinsic part of the formulation (as opposed to external corrections). Furthermore, the method is able to identify and characterize physically distinct groups in inhomogeneous samples, thus avoiding biases due to unidentified components. Moreover, the implementation used by the authors is based on the extensive use of numerical methods, so avoiding the need for simplification of the equations and thus the bias they could introduce. Several examples of application using simulated samples are presented, to be followed by applications to real samples in forthcoming articles.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Modelling of weather radar echoes from anomalous propagation using a hybrid parabolic equation method and NWP model data

Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.