World emissions and economic growth: Application of non-parametric methods

The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

Topological localization using optical flow descriptors

We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.

A Study of feature extraction algorithms for optical flow tracking

Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

Fire performance of LSF wall panels using numerical parametric studies

Light Gauge Steel Framing (LSF) walls made of cold-formed and thin-walled steel lipped channel studs with plasterboard linings on both sides are commonly used in commercial, industrial and residential buildings. However, there is limited data about their structural and thermal performances under fire conditions. Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing LSF wall systems. In this research a series of full scale fire tests was conducted first to evaluate the performance of LSF wall systems with eight different wall configurations under standard fire conditions. Finite element models of LSF walls were then developed, analysed under transient and steady state conditions, and validated using full scale fire tests. This paper presents the details of an investigation into the fire performance of LSF wall panels based on an extensive finite element analysis based parametric study. The LSF wall panels with eight different plasterboard-insulation configurations were considered under standard fire conditions. Effects of varying steel grades, steel thicknesses, screw spacing, plasterboard restraint, insulation materials and load ratio on the fire performance of LSF walls were investigated and the results of extensive fire performance data are presented in the form of load ratio versus time and critical hot flange (failure) temperature curves.

Very high resolution optical satellites for DEM generation : a review

The advent of very high resolution (VHR) optical satellites capable of producing stereo images led to a new era in extracting digital elevation model which commenced with the launch of IKONOS. The special specifications of VHR optical satellites besides, the significant economic profit stimulated other countries and companies to have their constellations such as EROS-A1 and EROS-B1 as the cooperation between Israel and ImageSat. QuickBird, WorldView-1 and WorldVew-2 were launched by DigitalGlobe. ALOS and GeoEye-1 were offered by Japan and GeoEye Respectively. In addition to aforementioned satellites, Indian and South Korea initiated their own constellation by launching CartoSat-1 and KOPOSAT-2 respectively.The availability of all so-called satellites make a huge market of stereo images for extracting of digital elevation model and other correspondent applications such as, producing orthorectifcatin images and updating maps. Therefore, there is a need for a comprehensive comparison for scientific and commercial clients to choose appropriate satellite images and methods of generating digital elevation model to obtain optimum results. This paper will thus give a review about the specifications of VHR optical satellites. Then it will discuss the automatic elaborating of digital elevation model. Finally an overview of studies and corresponding results is reported.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Validation of a container ship model for parametric rolling

The objective of this work is to formulate a nonlinear, coupled model of a container ship during parametric roll resonance, and to validate the model using experimental data.

Functionalized Ag nanoparticles with tunable optical properties for selective protein analysis

We present a preparation procedure for small sized biocompatibly coated Ag nanoparticles with tunable surface plasmon resonances. The conditions were optimised with respect to the resonance Raman signal enhancement of heme proteins and to the preservation of the native protein structure....

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Exact parametric confidence intervals for Bland-Altman limits of agreement

Purpose The previous literature on Bland-Altman analysis only describes approximate methods for calculating confidence intervals for 95% Limits of Agreement (LoAs). This paper describes exact methods for calculating such confidence intervals, based on the assumption that differences in measurement pairs are normally distributed. Methods Two basic situations are considered for calculating LoA confidence intervals: the first where LoAs are considered individually (i.e. using one-sided tolerance factors for a normal distribution); and the second, where LoAs are considered as a pair (i.e. using two-sided tolerance factors for a normal distribution). Equations underlying the calculation of exact confidence limits are briefly outlined. Results To assist in determining confidence intervals for LoAs (considered individually and as a pair) tables of coefficients have been included for degrees of freedom between 1 and 1000. Numerical examples, showing the use of the tables for calculating confidence limits for Bland-Altman LoAs, have been provided. Conclusions Exact confidence intervals for LoAs can differ considerably from Bland and Altman’s approximate method, especially for sample sizes that are not large. There are better, more precise methods for calculating confidence intervals for LoAs than Bland and Altman’s approximate method, although even an approximate calculation of confidence intervals for LoAs is likely to be better than none at all. Reporting confidence limits for LoAs considered as a pair is appropriate for most situations, however there may be circumstances where it is appropriate to report confidence limits for LoAs considered individually.

Visual field coordinates of pupillary circular axis and optical axis

Purpose: We term the visual field position from which the pupil appears most nearly circular as the pupillary circular axis (PCAx). The aim was to determine and compare the horizontal and vertical co-ordinates of the PCAx and optical axis from pupil shape and refraction information for only the horizontal meridian of the visual field. Method: The PCAx was determined from the changes with visual field angle in the ellipticity and orientation of pupil images out to ±90° from fixation along the horizontal meridian for the right eyes of 30 people. This axis was compared with the optical axis determined from the changes in the astigmatic components of the refractions for field angles out to ±35° in the same meridian. Results: The mean estimated horizontal and vertical field coordinates of the PCAx were (‒5.3±1.9°, ‒3.2±1.5°) compared with (‒4.8±5.1°, ‒1.5±3.4°) for the optical axis. The vertical co-ordinates of the two axes were just significantly different (p =0.03) but there was no significant correlation between them. Only the horizontal coordinate of the PCAx was significantly related to the refraction in the group. Conclusion: On average, the PCAx is displaced from the line-of-sight by about the same angle as the optical axis but there is more inter-subject variation in the position of the optical axis. When modelling the optical performance of the eye, it appears reasonable to assume that the pupil is circular when viewed along the line-of-sight.

Optical Characterization of the Hole Polaron in a Series of Diketopyrrolopyrrole Polymers Used for Organic Photovoltaics

Abstract: A strategy that is often used for designing low band gap polymers involves the incorporation of electron-rich (donor) and electron-deficient (acceptor) conjugated segments within the polymer backbone. In this paper we investigate such a series of Diketopyrrolopyrrole (DPP)-based co-polymers. The co-polymers consisted of a DPP unit attached to a phenylene, naphthalene, or anthracene unit. Additionally, polymers utilizing either the thiophene-flanked DPP or the furan-flanked DPP units paired with the naphthalene comonomer were compared. As these polymers have been used as donor materials and subsequent hole transporting materials in organic solar cells, we are specifically interested in characterizing the optical absorption of the hole polaron of these DPP based copolymers. We employ chemical doping, electrochemical doping, and photoinduced absorption (PIA) studies to probe the hole polaron absorption spectra. While some donor-acceptor polymers have shown an appreciable capacity to generate free charge carriers upon photoexcitation, no polaron signal was observed in the PIA spectrum of the polymers in this study. The relations between molecular structure and optical properties are discussed. Keywords: organic solar cell; organic photovoltaic; diketopyrrolopyrrole; chemical doping; spectroelectrochemistry; photoinduced absorption; hole polaron

On the use of optical flow for scene change detection and description

We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.