Bed morphology, flow structure, and sediment transport at the outlet of Lake Huron and in the upper St. Clair River

An integrated multibeam echo sounder and acoustic Doppler current profiler field survey was conducted in July 2008 to investigate the morphodynamics of the St. Clair River at the outlet of Lake Huron. The principal morphological features of the upper St. Clair River included flow-transverse bedforms that appear weakly mobile, erosive bedforms in cohesive muds, thin non-cohesive veneers of weakly mobile sediment that cover an underlying cohesive (till or glacio-lacustrine) surface, and vegetation that covers the bed. The flow was characterized by acceleration as the banks constrict from Lake Huron into the St. Clair River, an approximately 1500-m long region of flow separation downstream from the Blue Water Bridge, and secondary flow connected to: i) channel curvature; ii) forcing of the flow by local bed topography, and iii) flow wakes in the lee side of ship wrecks. Nearshore, sand-sized, sediment from Lake Huron was capable of being transported into, and principally along, the banks of the upper St. Clair River by the measured flow. A comparison of bathymetric surveys conducted in 2007 and 2008 identifies that the gravel bed does undergo slow downstream movement, but that this movement does not appear to be generated by the mean flow, and could possibly be caused by ship-propeller-induced turbulence. The study results suggest that the measured mean flow and dredging within the channel have not produced major scour of the upper St. Clair River and that the recent fall in the level of Lake Huron is unlikely to have been caused by these mechanisms.     

Application of the Soil and Water Assessment Tool for six watersheds of Lake Erie: Model parameterization and calibration

The Soil and Water Assessment Tool (SWAT), a physically-based watershed-scale model, holds promise as a means to predict tributary sediment and nutrient loads to the Laurentian Great Lakes. In the present study, model performance is compared across six watersheds draining into Lake Erie to determine the applicability of SWAT to watersheds of differing characteristics. After initial model parameterization, the Huron, Raisin, Maumee, Sandusky, Cuyahoga, and Grand SWAT models were calibrated (1998-2001) and confirmed, or validated (2002-2005), individually for stream water discharge, sediment loads, and nutrient loads (total P, soluble reactive P, total N, and nitrate) based on available datasets. SWAT effectively predicted hydrology and sediments across a range of watershed characteristics. SWAT estimation of nutrient loads was weaker although still satisfactory at least two-thirds of the time across all nutrient parameters and watersheds. SWAT model performance was most satisfactory in agricultural and forested watersheds, and was less so in urbanized settings. Model performance was influenced by the availability of observational data with high sampling frequency and long duration for calibration and confirmation evaluation. In some instances, it appeared that parameter adjustments that improved calibration of hydrology negatively affected subsequent sediment and nutrient calibration, suggesting trade-offs in calibrating for hydrologic vs. water quality model performance. Despite these considerations, SWAT accurately predicted average stream discharge, sediment loads, and nutrient loads for the Raisin, Maumee, Sandusky, and Grand watersheds such that future use of these SWAT models for various scenario testing is reasonable and warranted.     

Evaporation from Lake Superior: 1. Physical controls and processes

The surface energy balance of Lake Superior was measured using the eddy covariance method at a remote, offshore site at 0.5-h intervals from June 2008 through November 2010. Pronounced seasonal patterns in the surface energy balance were observed, with a five-month delay between maximum summer net radiation and maximum winter latent and sensible heat fluxes. Late season (winter) evaporation and sensible heat losses from the lake typically occurred in two- to three-day-long events, and were associated with significant release of stored heat from the lake. The majority of the evaporative heat loss (70-88%) and sensible heat loss (97-99%) occurred between October and March, with 464 mm (2008-2009) and 645 mm (2009-2010) of evaporative water loss occurring over the water year starting October 1. Evaporation was proportional to the horizontal wind speed, inversely proportional to the ambient vapor pressure, and was well described by the ratio of wind speed to vapor pressure. This ratio remained relatively constant between the two water years, so the differences in evaporative water loss between years were largely associated with differences in lake surface conditions (e.g. water temperature, ice cover, and ice duration). Since late-season water temperature decline is driven by evaporative and sensible heat loss, the potential for a negative feedback mechanism between evaporation and ice cover is discussed.     

Characterization of Sky‐region Morphological‐temporal Airborne Collision Detection

Automated airborne collision‐detection systems are a key enabling technology for facilitating the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety‐critical systems must be sensitive enough to provide timely warnings of genuine airborne collision threats, but not so sensitive as to cause excessive false alarms. Hence, an accurate characterization of detection and false‐alarm sensitivity is essential for understanding performance tradeoffs, and system designers can exploit this characterization to help achieve a desired balance in system performance. In this paper, we experimentally evaluate a sky‐region, image‐based, aircraft collision‐detection system that is based on morphological and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter background.) A novel collection methodology for collecting realistic airborne collision‐course target footage in both head‐on and tail‐chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540 m in three flight test cases with no false‐alarm events in 14.14 h of nontarget data (under cloudy conditions, the system achieved detection ranges greater than 1170 m in four flight test cases with no false‐alarm events in 6.63 h of nontarget data). Importantly, this paper is the first documented presentation of detection range versus false‐alarm curves generated from airborne target and nontarget image data. © 2012 Wiley Periodicals, Inc.     

Adiabatic quantum optimization with qudits

Most realistic solid state devices considered as qubits are not true two-state systems. If the energy separation of the upper energy levels from the lowest two levels is not large, then these upper states may affect the evolution of the ground state over time and therefore cannot be neglected. In this work, we study the effect of energy levels beyond the lowest two energy levels on adiabatic quantum optimization in a device with a double-well potential as the basic logical element. We show that the extra levels can be modeled by adding additional ancilla qubits coupled to the original logical qubits, and that the presence of upper levels has no effect on the final ground state. We also study the influence of upper energy levels on the minimum gap for a set of 8-qubit spin glass instances.     

Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet

We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like “large”, “huge” and “gigantic” with respect to their attribute (“size”). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.     

Performance models of storage contention in cloud environments

We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. Model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same server. We first propose a trace-driven approach that evaluates a queueing network with fair share scheduling using simulation. The model parameters consider Virtual Machine Monitor level disk access optimizations and rely on a calibration technique. We further present a measurement-based approach that allows a distinct characterization of read/write performance attributes. In particular, we define simple linear prediction models for I/O request mean response times, throughputs and read/write mixes, as well as a simulation model for predicting response time distributions. We found our models to be effective in predicting such quantities across a range of synthetic and emulated application workloads.     

Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. These maps were used to assign all blocks (18.5 by 18.5 km) partitioning the boreal biome into strata of high, medium and low likelihood of forest cover loss. A stratified random sample of 118 blocks was interpreted for forest cover and forest cover loss using high spatial resolution Landsat imagery from 2000 and 2005. Area of forest cover gross loss from 2000 to 2005 within the boreal biome is estimated to be 1.63% (standard error 0.10%) of the total biome area, and represents a 4.02% reduction in year 2000 forest cover. The proportion of identified forest cover loss relative to regional forest area is much higher in North America than in Eurasia (5.63% to 3.00%). Of the total forest cover loss identified, 58.9% is attributable to wildfires. The MODIS pan-boreal change hotspot estimates reveal significant increases in forest cover loss due to wildfires in 2002 and 2003, with 2003 being the peak year of loss within the 5-year study period. Overall, the precision of the aggregate forest cover loss estimates derived from the Landsat data and the value of the MODIS-derived map displaying the spatial and temporal patterns of forest loss demonstrate the efficacy of this protocol for operational, cost-effective, and timely biome-wide monitoring of gross forest cover loss.     

Analyzing clusters of class characteristics in OO applications

The transition from Java 1.4 to Java 1.5 has provided the programmer with more flexibility due to the inclusion of several new language constructs, such as parameterized types. This transition is expected to increase the number of class clusters exhibiting different combinations of class characteristics. In this paper we investigate how the number and distribution of clusters are expected to change during this transition. We present the results of an empirical study were we analyzed applications written in both Java 1.4 and 1.5. In addition, we show how the variability of the combinations of class characteristics may affect the testing of class members.     

Konzeptuelle Modellierung von Geodiensten

Zusammenfassung  Navigationssysteme, ortsbezogene Suchdienste wie Google Maps, interaktive Augmented-Reality-Spiele, Handy-basierte FindMe-Dienste – diese wenige Beispiele zeigen bereits, wie direkt oder indirekt raumbezogene Dienste unser Alltagsleben immer mehr durchdringen. Wir beobachten, wie sich die Nutzung von Geodaten schrittweise vom pers?nlichen Desktop-Geoinformationssystem (GIS) über hausinternen Zugriff auf die Geodatenbank bis zum Webzugriff durch Clients und Servern unterschiedlicher Provenienz ausweitet (,,Web-GIS“). Klassische Aufgaben wie Kartenproduktion und Beauskunftung treten dabei gegenüber komplexen, situationsbezogenen Verknüpfungen von Geo- mit anderen Daten eher in den Hintergrund. Damit geht offensichtlich ein Paradigmenwechsel von der einfachen, passiven Geodatenbereitstellung via WWW zu funktional komplexeren Geodiensten einher. Sollen solche Mehrwertdienste offen und flexibel orchestrierbar sein, so müssen Geodaten systemübergreifend ad hoc abgefragt werden k?nnen. Unabdingbar sind dafür offene Standards, nicht nur auf der Ebene von Datenaustauschformaten, sondern auch bei den Zugriffsdiensten; diese Geoservice-Standardisierung leistet das Open GeoSpatial Consortium (OGC). Im vorliegenden Beitrag geben wir einen überblick über die Modellierung von Web-basierten Geodiensten auf Basis ausgew?hlter OGC-Standards. Modellierung bedeutet in diesem Kontext die Gestaltung von Funktionalit?t und Schnittstellen eines potenziell komplexen Dienstes auf Basis offener Standards und ihrer Basisdienste und -operationen. Diskutiert werden Standards für den Meta-, Vektor- und Rasterdatenzugriff sowie ein anwendungsorientierter Standard für Sensordaten.