Drought Severity Assessment Based on Bivariate Probability Analysis

Conventionally drought severity is assessed based on drought indices. Recently the Reconnaissance Drought Index (RDI) was proposed to assess drought severity based on the precipitation to potential evapotranspiration ratio (P/PET). In this paper RDI is studied as a bivariate index under a set of assumptions and simplifications. The paper presents a simple computational procedure for estimating the P/PET ratio for selected reference periods varying from 3 to 12 months, for any return period of drought. Alternatively, based on this procedure, the severity of any drought episode is rationally assessed. A bivariate probability analysis is employed based on the assumption that P and PET values are normally distributed and often negatively correlated. Examples for the application of the proposed procedure are presented using data from several meteorological stations in Greece. It is shown that the assumption of normality of both P and PET holds for long periods at all examined stations.     

Laminated paper-based analytical devices (LPAD): fabrication, characterization, and assays

Paper-based microfluidic devices have recently garnered an increasing interest in the literature. The majority of these devices were produced by patterning hydrophobic zones in hydrophilic paper via photoresist or wax. Others were created by cutting paper using a laser. Here, we present a fabrication method for producing devices by simple craft-cutting and lamination, in a way similar to making an identification (ID) card. The method employs a digital craft cutter and roll laminator to produce laminated paper-based analytical devices (LPAD). Lamination with a plastic backing provides the mechanical strength for a paper device. The approach of using a craft cutter and laminator makes it possible to rapid-prototype LPAD with no more difficulty than producing a typical ID card, at very low cost. Devices constructed using this method have been exploited for simultaneous detection of bovine serum albumin (BSA) and glucose in synthetic urine with colorimetric assays. Both BSA and glucose are detectable at clinically relevant concentrations, with the detection limit at 2.5 μM for BSA and 0.5 mM for glucose.     

RoadCompass: following rural roads with vision + ladar using vanishing point tracking

We present a vision- and ladar-based approach to autonomous driving on rural and desert roads that has been tested extensively in a closed-loop system. The vision component uses Gabor wavelet filters for texture analysis to find ruts and tracks from which the road vanishing point can be inferred via Hough-style voting, yielding a direction estimate for steering control. The ladar component projects detected obstacles along the road direction onto the plane of the front of the vehicle and tracks the 1-D obstacle “gap” presumed due to the road to yield a lateral offset estimate. Several image- and state-based tests to detect failure conditions such as off-road poses (i.e., there is no road to follow) and poor lighting due to sun glare or distracting shadows are also explained. The system’s efficacy is demonstrated with analysis of diverse logged data including from the 2005 DARPA Grand Challenge, as well as tests with full control of a vehicle over 15 km of difficult roads at up to 37 km/h with no waypoints.

A Managed IPv6 Transitioning Architecture for Large Network Deployments

With IPv6 transitioning still in a relative state of flux, the need has emerged for methods to control this crucial aspect of IPv6 deployments. This article makes the case for transitioning architectures as a realistic solution to this issue, specifically within large-scale networks. The Site Transitioning Architecture (STA) supports the deployment, operation, and management of IPv6 transitioning mechanisms. The authors provide an overview of the STA's design and operation, noting that its flexible, simple, and secure architecture is suitable for the duration of the IPv6 deployment process, regardless of the underlying network environment.     

Quantile map: Simultaneous visualization of patterns in many distributions with application to tandem mass spectrometry

High-throughput experiments have become more and more prevalent in biomedical research. The resulting high-dimensional data have brought new challenges. Effective data reduction, summarization and visualization are important keys to initial exploration in data mining. In this paper, we introduce a visualization tool, namely a quantile map, to present information contained in a probabilistic distribution. We demonstrate its use as an effective visual analysis tool through the application of a tandem mass spectrometry data set. Information of quantiles of a distribution is presented in gradient colors by concentric doughnuts. The width of the doughnuts is proportional to the Fisher information of the distribution to present unbiased visualization effect. A parametric empirical Bayes (PEB) approach is shown to improve the simple maximum likelihood estimate (MLE) approach when estimating the Fisher information. In the motivating example from tandem mass spectrometry data, multiple probabilistic distributions are to be displayed in two-dimensional grids. A hierarchical clustering to reorder rows and columns and a gradient color selection from a Hue-Chroma-Luminance model, similar to that commonly applied in heatmaps of microarray analysis, are adopted to improve the visualization. Both simulations and the motivating example show superior performance of the quantile map in summarization and visualization of such high-throughput data sets.     

Infinitesimal Perturbation Analysis in Networks of Stochastic Flow Models: General Framework and Case Study of Tandem Networks with Flow Control

This paper presents a general algorithmic framework for computing the IPA derivatives of sample performance functions defined on networks of fluid queues. The underlying network-model consists of bi-layered hybrid dynamical systems with continuous-time dynamics at the lower layer and discrete-event dynamics at the upper layer. The linearized system, computed from the sample path via a discrete-event process, yields fairly simple algorithms for the IPA derivatives. As an application-example, the paper discusses loss and workload performance functions in a tandem network with congestion control, subjected to signal delays.     

A Biologically-Inspired Micro Aerial Vehicle

This paper introduces a novel framework for the design, modeling and control of a Micro Aerial Vehicle (MAV). The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). We have taken inspiration from the flight mechanism features of the dragonfly and have developed indigenous designs in creating a novel version of a Flapping Wing MAV (FWMAV). The MAV design incorporates a complex mechanical construction and a sophisticated multi-layered, hybrid, linear/non-linear controller to achieve extended flight times and improved agility compared to other rotary wing and FWMAV Vertical Take Off and Landing (VTOL) designs. The first MAV prototype will have a ballpark weight including sensor payload of around 30 g. The targeted lifting capability is about twice the weight. The MAV features state of the art sensing and instrumentation payload, which includes integrated high-power on-board processors, 6DoF inertial sensors, 3DoF compasses, GPS, embedded camera and long-range telemetry capability. A 3-layer control mechanism has been developed to harness the dynamics and attain complete navigational control of the MAV. The inner-layer is composed of a ‘quad hybrid-energy controller’ and two higher layers are at present, implementing a linear controller; the latter will be replaced eventually with a dynamic adaptive non-linear controller. The advantages of the proposed design compared to other similar ones include higher energy efficiency and extended flight endurance. The design features elastic storage and re-use of propulsion energy favoring energy conservation during flight. The design/modeling of the MAV and its kinematics & dynamics have been tested under simulation to achieve desired performance. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance and reconnaissance in cluster and swarm formations. The efficacy of the design is demonstrated through a simulation environment. The dynamics are verified through simulations and a general linear controller coupled with an energy based non-linear controller is shown to operate the vehicle in a stable regime. In accordance with specified objectives a prototype is being developed for flight-testing and demonstration purposes.     

Application of functionalised carbon nanotubes immobilised into chitosan films in amperometric enzyme biosensors

A new approach for building a bio-conductive interface for enzyme immobilisation is described. This strategy permits very simple preparation of the enzyme biosensor and also reveals direct electron transfer features. A graphite-epoxy resin composite (GrEC) electrode modified with functionalised multi-wall carbon nanotubes (MWCNTs) immobilised by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide together with N-hydroxysuccinimide (EDC–NHS) in a chitosan (Chit) matrix was prepared and characterised by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) in the presence of hexaammineruthenium (III) chloride. It was then used as a base for glucose oxidase (GOx) immobilisation by the simple method of crosslinking with glutaraldehyde (GA) with bovine serum albumin (BSA) as carrier protein. The resulting mediator-free biosensor was applied to the determination of glucose in amperometric mode at different applied potentials and the mechanism of reaction was also investigated by cyclic voltammetry, with and without dissolved oxygen in solution. Analytical parameters, as well as reproducibility, repeatability and stability were determined. Interferences were assessed using different compounds usually present in natural samples, such as wines, juices or blood, in order to evaluate the selectivity of the developed biosensor. The novel combination of carbon nanotubes immobilised with chitosan crosslinked with EDC–NHS and glucose oxidase immobilised by crosslinking with glutaraldehyde offers an excellent, easy to make biosensor for glucose determination without interferences.