Contributions to time series data mining departing from the problem of road travel time modeling

194 p.

Comparison of habitat-based indices of abundance with fishery-independent biomass estimates from bottom trawl surveys

Rockfish species are notoriously difficult to sample with multispecies bottom trawl survey methods. Typically, biomass estimates have high coefficients of variation and can fluctuate outside the bounds of biological reality from year to year. This variation may be due in part to their patchy distribution related to very specific habitat preferences. We successfully modeled the distribution of five commercially important and abundant rockf ish species. A two-stage modeling method (modeling both presence-absence and abundance) and a collection of important habitat variables were used to predict bottom trawl survey catch per unit of effort. The resulting models explained between 22% and 66% of the variation in rockfish distribution. The models were largely driven by depth, local slope, bottom temperature, abundance of coral and sponge, and measures of water column productivity (i.e., phytoplankton and zooplankton). A year-effect in the models was back-transformed and used as an index of the time series of abundance. The abundance index trajectories of three of five species were similar to the existing estimates of their biomass. In the majority of cases the habitat-based indices exhibited less interannual variability and similar precision when compared with stratified survey-based biomass estimates. These indices may provide for stock assessment models a more stable alternative to current biomass estimates produced by the multispecies bottom trawl survey in the Gulf of Alaska.

Age validation, growth modeling, and mortality estimates for striped trumpeter (Latris lineata) from southeastern Australia: making the most of patchy data

Age estimates for striped trumpeter (Latris lineata) from Tasmanian waters were produced by counting annuli on the transverse section of sagittal otoliths and were validated by comparison of growth with known-age individuals and modal progression of a strong recruitment pulse. Estimated ages ranged from one to 43 years; fast growth rates were observed for the first five years. Minimal sexual dimorphism was shown to exist between length, weight, and growth characteristics of striped trumpeter. Seasonal growth variability was strong in individuals up to at least age four, and growth rates peaked approximately one month after the observed peak in sea surface temperature. A modified two-phase von Bertalanffy growth function was fitted to the length-at-age data, and the transition between growth phases was linked to apparent changes in physiological and life history traits, including offshore movement as fish approach maturity. The two-phase curve was found to represent the mean length at age in the data better than the standard von Bertalanffy growth function. Total mortality was estimated by using catch curve analysis based on the standard and two-phase von Bertalanffy growth functions, and estimates of natural mortality were calculated by using two empirical models, one based on longevity and the other based on the parameters L∞ and k from both growth functions. The interactions between an inshore gillnet fishery targeting predominately juveniles and an offshore hook fishery targeting predominately adults highlight the need to use a precautionary approach when developing harvest strategies.

Modeling the Potential Spread of the Recently Identified Non-Native Panther Grouper (Chromileptes altivelis)in the Atlantic Using a Cellular Automaton Approach

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species

Optical waveguides and switches based on periodic arrays of carbon nanotubes

This document presents the modeling and characterization of novel optical devices based on periodic arrays of multiwalled carbon nanotubes. Vertically aligned carbon nanotubes can be grown in the arrangement of two-dimensional arrays of precisely determined dimensions. Having their dimensions comparable to the wavelength of light makes carbon nanotubes good candidates for utilization in nano-scale optical devices. We report that highly dense periodic arrays of multiwalled carbon nanotubes can be utilized as sub-wavelength structures for establishing advanced optical materials, such as metamaterials and photonic crystals. We demonstrate that when carbon nanotubes are grown close together at spacing of the order of few hundred nanometers, they display artificial optical properties towards the incident light, acting as metamaterials. By utilizing these properties we have established micro-scaled plasmonic high pass filter which operates in the optical domain. Highly dense arrays of multiwalled also offer a periodic dielectric constant to the incident light and display interesting photonic band gaps, which are frequency domains within which on wave propagation can take place. We have utilized these band gaps displayed by a periodic nanotube array, having 400 nm spacing, to construct photonic crystals based optical waveguides and switches. © 2011 IEEE.

Modeling seabird group size: implications for ecological impact assessments

The purpose of this project is to model seabird flock size data to provide recommendations to the Bureau of Ocean and Energy Management for offshore wind turbine placement. Our hypothesis is that ecological characteristics influence which statistical distribution will provide the best fit to seabird flock size data. To test this, seabird species can be grouped based on shared ecological traits, such as foraging mechanism or diet.

Characterizing Jobos Bay, Puerto Rico: a watershed modeling analysis and monitoring plan

Land-based pollution is commonly identified as a major contributor to the observed deterioration of shallow-water coral reef ecosystem health. Human activity on the coastal landscape often induces nutrient enrichment, hypoxia, harmful algal blooms, toxic contamination and other stressors that have degraded the quality of coastal waters. Coral reef ecosystems throughout Puerto Rico, including Jobos Bay, are under threat from coastal land uses such as urban development, industry and agriculture. The objectives of this report were two-fold: 1. To identify potentially harmful land use activities to the benthic habitats of Jobos Bay, and 2. To describe a monitoring plan for Jobos Bay designed to assess the impacts of conservation practices implemented on the watershed. This characterization is a component of the partnership between the U.S. Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) established by the Conservation Effects Assessment Project (CEAP) in Jobos Bay. CEAP is a multi-agency effort to quantify the environmental benefits of conservation practices used by private landowners participating in USDA programs. The Jobos Bay watershed, located in southeastern Puerto Rico, was selected as the first tropical CEAP Special Emphasis Watershed (SEW). Both USDA and NOAA use their respective expertise in terrestrial and marine environments to model and monitor Jobos Bay resources. This report documents NOAA activities conducted in the first year of the three-year CEAP effort in Jobos Bay. Chapter 1 provides a brief overview of the project and background information on Jobos Bay and its watershed. Chapter 2 implements NOAA’s Summit to Sea approach to summarize the existing resource conditions on the watershed and in the estuary. Summit to Sea uses a GIS-based procedure that links patterns of land use in coastal watersheds to sediment and pollutant loading predictions at the interface between terrestrial and marine environments. The outcome of Summit to Sea analysis is an inventory of coastal land use and predicted pollution threats, consisting of spatial data and descriptive statistics, which allows for better management of coral reef ecosystems. Chapters 3 and 4 describe the monitoring plan to assess the ecological response to conservation practices established by USDA on the watershed. Jobos Bay is the second largest estuary in Puerto Rico, but has more than three times the shoreline of any other estuarine area on the island. It is a natural harbor protected from offshore wind and waves by a series of mangrove islands and the Punta Pozuelo peninsula. The Jobos Bay marine ecosystem includes 48 km² of mangrove, seagrass, coral reef and other habitat types that span both intertidal and subtidal areas. Mapping of Jobos Bay revealed 10 different benthic habitats of varying prevalence, and a large area of unknown bottom type covering 38% of the entire bay. Of the known benthic habitats, submerged aquatic vegetation, primarily seagrass, is the most common bottom type, covering slightly less than 30% of the bay. Mangroves are the dominant shoreline feature, while coral reefs comprise only 4% of the total benthic habitat. However, coral reefs are some of the most productive habitats found in Jobos Bay, and provide important habitat and nursery grounds for fish and invertebrates of commercial and recreational value.

Coupling ecology and economy: modeling optimal release scenarios for summer flounder (Paralichthys dentatus) stock enhancement

Increasing interest in the use of stock enhancement as a management tool necessitates a better understanding of the relative costs and benefits of alternative release strategies. We present a relatively simple model coupling ecology and economic costs to make inferences about optimal release scenarios for summer flounder (Paralichthys dentatus), a subject of stock enhancement interest in North Carolina. The model, parameterized from mark-recapture experiments, predicts optimal release scenarios from both survival and economic standpoints for varyious dates-of-release, sizes-at-release, and numbers of fish released. Although most stock enhancement efforts involve the release of relatively small fish, the model suggests that optimal results (maximum survival and minimum costs) will be obtained when relatively large fish (75–80 mm total length) are released early in the nursery season (April). We investigated the sensitivity of model predictions to violations of the assumption of density-independent mortality by including density-mortality relationships based on weak and strong type-2 and type-3 predator functional responses (resulting in depensatory mortality at elevated densities). Depending on postrelease density, density-mortality relationships included in the model considerably affect predicted postrelease survival and economic costs associated with enhancement efforts, but do not alter the release scenario (i.e. combination of release variables) that produces optimal results. Predicted (from model output) declines in flounder over time most closely match declines observed in replicate field sites when mortality in the model is density-independent or governed by a weak type-3 functional response. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement of summer flounder and provides a template for model creation for additional species that are subjects of stock enhancement interest, but for which limited empirical data exist.

Nonparametric Bayesian sparse factor models with application to gene expression modeling

A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially infinite number of hidden factors, $\mathbf{X}$. The Indian Buffet Process (IBP) is used as a prior on $\mathbf{G}$ to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity.

Intermittency transport modeling of separated flow transition

An intermittency transport model is proposed for modeling separated-flow transition. The model is based on earlier work on prediction of attached flow bypass transition and is applied for the first time to model transition in a separation bubble at various degrees of free-stream turbulence. The model has been developed so that it takes into account the entrainment of the surrounding fluid. Experimental investigations suggest that it is this phenomena which ultimately determines the extent of the separation bubble. Transition onset is determined via a boundary layer correlation based on momentum thickness at the point of separation. The intermittent flow characteristic of the transition process is modeled via an intermittency transport equation. This accounts for both normal and streamwise variation of intermittency and hence models the entrainment of surrounding flow in a more accurate manner than alternative prescribed intermittency models. The model has been validated against the well established T3L semicircular leading edge flat plate test case for three different degrees of free-stream turbulence characteristic of turbomachinery blade applications.

Deposition and characterisation of ultralow-stress ZnO thin films for application in FBAR-based gravimetric biosensors

Zinc oxide (ZnO) thin films were deposited at high rates ( > 50 nm min-1) using a unique technique known as high target utilisation sputtering (HiTUS). The films obtained possess good crystallographic orientation, low surface roughness, very low stress and excellent piezoelectric properties. We have utilised the films to develop highly sensitive biosensors based on thickness longitudinal mode (TLM) thin film bulk acoustic resonators (FBARs). The FBARs have the fundamental TLM at a frequency near 1.5 GHz and quality factor Q higher than 1,000, which is one of the largest values ever reported for ZnO-based FBARs. Bovine Serum Albumin (BSA) solutions with different concentrations were placed on the top of different sets of identical FBARs and their responses to mass-loading from physically adsorbed protein coatings were investigated. These resonators demonstrated a high sensitivity and thus have a great potential as gravimetric sensors for biomedical applications. © 2011 Inderscience Enterprises Ltd.

Modular risk modeling and management of water infrastructure disaster incidents

Water supply and wastewater control are critical elements of society's infrastructure. The objective of this study will be to provide a generic risk assessment tool to provide municipalities and the nation as a whole with a quantifiable assessment of their vulnerability to water infrastructure threats. The approach will prioritize countermeasures and identify where research and development is required to further minimize risk. This paper outlines the current context, primary concerns and state-of-the art in critical infrastructure risk management for the water sector and proposes a novel approach to resolve existing questions in the field. The proposed approach is based on a modular framework that derives a quantitative risk index for varied domains of interest. The approach methodology is scaleable and based on formal definitions of event probability and severity. The framework is equally applicable to natural and human-induced hazard types and can be used for analysis of compound risk events.

AlN-based BAW resonators with CNT electrodes for gravimetric biosensing

Solidly mounted resonators (SMRs) with a top carbon nanotubes (CNTs) surface coating that doubles as an electrode and as a sensing layer have been fabricated. The influence of the CNTs on the frequency response of the resonators was studied by direct comparison to identical devices with a top metallic electrode. It was found that the CNTs introduced significantly less mass load on the resonators and these devices exhibited a greater quality factor, Q (>2000, compared to ∼1000 for devices with metal electrodes), which increases the gravimetric sensitivity of the devices by allowing the tracking of smaller frequency shifts. Protein solutions with different concentrations were loaded on the top of the resonators and their responses to mass-load from physically adsorbed coatings were investigated. Results show that resonators using CNTs as the top electrode exhibited a higher frequency change for a given load (∼0.25 MHz cm2 ng-1) compared to that of a metal thin film electrode (∼0.14 MHz cm2 ng-1), due to the lower mass of the CNT electrodes and their higher active surface area compared to that of a thin film metal electrode. It is therefore concluded that the use of CNT electrodes on resonators for their use as gravimetric biosensors is a significant improvement over metallic electrodes that are normally employed. © 2011 Elsevier B.V. All rights reserved.

Switching characteristics of diamond-based m-i-p+ diodes in power electronic applications

Modeling and numerical analysis of diamond m-i-p+ diode have been performed for static and transient analysis using TCAD Sentaurus platform. The simulation results are compared with experimental measurements. Prediction of transient turn-off characteristics of diamond m-i-p+ diode at high temperature is performed for the first time. It was found that unlike conventional Si diode, peak reverse current in diamond m-i-p+ diode reduces with increasing temperature while on-state voltage drop increases. © 2011 IEEE.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.