Extracting statistically dominant modes of a steel truss bridge from vehicle-induced vibrations

This study is intended to investigate the validity of the stability diagram (SD) aided multivariate autoregressive (MAR) analysis for identifying modal parameters of a real truss bridge. The MAR models are adopted to fit the time series of the dynamic accelerations recorded from a number of observation points on the bridge; then the modal parameters are extracted from the MAR model coefficient matrix. The SD is adopted to determine statistically dominant modes. In plotting the SD, a number of stability criteria are further adopted for filtering out those modes with unstable modal parameters. By the present method, the first five modal frequencies and mode shapes are identified with very high precision, while the damping ratios are identified with high precision for the 1st mode but with poorer precision for higher modes. Moreover, the ability of the SD in selecting structural modes without getting involved in any model-order optimization problem is highlighted through a comparison study.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

A practical taxonomy of methods and literature for managing uncertain spatial data in geographic information systems

Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.

Spectacle design preferences among Chinese primary and secondary students and their parents: A qualitative and quantitative study

Purpose: To identify the specific characteristics making glasses designs, particularly those compatible with adjustable glasses, more or less appealing to Chinese children and their parents. Patients and Methods: Primary and secondary school children from urban and rural China with < = -1.00 diopters of bilateral myopia and their parents ranked four conventional-style frames identified by local optical shops as popular versus four child-specific frames compatible with adjustable spectacles. Scores based on the proportion of maximum possible ranking were computed for each style. Selected children and their parents also participated in Focus Groups (FGs) discussing spectacle design preference. Recordings were transcribed and coded by two independents reviewers using NVivo software. Results: Among 136 urban primary school children (age range 9-11 years), 290 rural secondary school children (11-17 years) and 16 parents, all adjustable-style frames (scores on 0-100 scale 25.7-62.4) were ranked behind all conventional frames (63.0-87.5). For eight FGs including 12 primary children, 26 secondary children and 16 parents, average kappa values for NVivo coding were 0.81 (students) and 0.70 (parents). All groups agreed that the key changes to make adjustable designs more attractive were altering the round lenses to rectangular or oval shapes and adding curved earpieces for more stable wear. The thick frames of the adjustable designs were considered stylish, and children indicated they would wear them if the lens shape were modified. Conclusions: Current adjustable lens designs are unattractive to Chinese children and their parents, though this study identified specific modifications which would make them more appealing.

Development and Validation of a Procedure for Numerical Vibration Analysis of an Oscillating Wave Surge Converter

During extreme sea states so called impact events can be observed on the wave energy converter Oyster. In small scale experimental tests these impact events cause high frequency signals in the measured load which decrease confidence in the data obtained. These loads depend on the structural dynamics of the model. Amplification of the loads can occur and is transferred through the structure from the point of impact to the load cell located in the foundation. Since the determination of design data and load cases for Wave Energy Converters originate from scale experiments, this lack of confidence has a direct effect on the development.

Numerical vibration analysis is a valuable tool in the research of the structural load response of Oyster to impact events, but must take into account the effect of the surrounding water. This can be done efficiently by adding an added mass distribution, computed with a linearised potential boundary element method. This paper presents the development and validation of a numerical procedure, which couples the OpenSource boundary element code NEMOH with the Finite Element Analysis tool CodeAster. Numerical results of the natural frequencies and mode shapes of the structure under the influence of added mass due to specific structural modes are compared with experimental results.

k-fold Subsampling based Sequential Backward Feature Elimination

We present a new wrapper feature selection algorithm for human detection. This algorithm is a hybrid featureselection approach combining the benefits of filter and wrapper methods. It allows the selection of an optimalfeature vector that well represents the shapes of the subjects in the images. In detail, the proposed featureselection algorithm adopts the k-fold subsampling and sequential backward elimination approach, while thestandard linear support vector machine (SVM) is used as the classifier for human detection. We apply theproposed algorithm to the publicly accessible INRIA and ETH pedestrian full image datasets with the PASCALVOC evaluation criteria. Compared to other state of the arts algorithms, our feature selection based approachcan improve the detection speed of the SVM classifier by over 50% with up to 2% better detection accuracy.Our algorithm also outperforms the equivalent systems introduced in the deformable part model approach witharound 9% improvement in the detection accuracy

Holidays in the Danger Zone: Entanglements of War and Tourism

A timely, and uniquely historical, look at how war turns soldiers, and all of us, into tourists. Holidays in the Danger Zone exposes the mundane and everyday entanglements between two seemingly opposed worlds—warfare and tourism. Debbie Lisle shows how a tourist sensibility shapes the behavior of soldiers in warespecially the experiences of Western military forces in “exotic” settings. This includes not only R&R but also how battlefields themselves become landscapes of leisure and tourism. It further explores how a military sensibility shapes the development of tourism in the postwar context, from “Dark Tourism” (engaging with displays of conflict and atrocity) to exhibitions of conflict in museums and at memorial sites, as well as in advertising, film, journals, guidebooks, blogs, and photography. Focused on how war and tourism reinforce prevailing modes of domination, Holidays in the Danger Zone critically examines the long historical arc of the war-tourism nexus from nineteenth-century imperialism to World War I and World War II, from the Cold War to globalization and the War on Terror.

Measuring the shape of degree distributions

Degree distribution is a fundamental property of networks. While mean degree provides a standard measure of scale, there are several commonly used shape measures. Widespread use of a single shape measure would enable comparisons between networks and facilitate investigations about the relationship between degree distribution properties and other network features. This paper describes five candidate measures of heterogeneity and recommends the Gini coefficient. It has theoretical advantages over many of the previously proposed measures, is meaningful for the broad range of distribution shapes seen in different types of networks, and has several accessible interpretations. While this paper focusses on degree, the distribution of other node based network properties could also be described with Gini coefficients.