Predicting Lodging Manager Annual Salary Based on Metropolitan Statistical Area Attributes and Lodging Industry Performance: Exploring the Concept

Using multiple regression analysis, lodging managers’ annual mean salaries in 143 Metropolitan Statistical Areas (MSA) within the U.S. were analyzed to identify what relationships existed with variables related to general MSA characteristics, along with the lodging industry’s size and performance. By examining the relationship between these variables, the authors predict the long-term possibility of predicting lodging industry managers’ salaries. These predictions may have an impact on financial performance of an individual lodging property or organization. Through this paper, this concept was applied and explored within U.S. MSAs. These findings may have value for a variety of stakeholders, including human resources practitioners, the hospitality education community, and individuals considering lodging management careers.

An automatic method of above-water iceberg 3-D profiling based on autonomous surface craft (ASC) using surface images and LIDAR

This thesis reports on a novel method to build a 3-D model of the above-water portion of icebergs using surface imaging. The goal is to work towards the automation of iceberg surveys, allowing an Autonomous Surface Craft (ASC) to acquire shape and size information. After collecting data and images, the core software algorithm is made up of three parts: occluding contour finding, volume intersection, and parameter estimation. A software module is designed that could be used on the ASC to perform automatic and fast processing of above-water surface image data to determine iceberg shape and size measurement and determination. The resolution of the method is calculated using data from the iceberg database of the Program of Energy Research and Development (PERD). The method was investigated using data from field trials conducted through the summer of 2014 by surveying 8 icebergs during 3 expeditions. The results were analyzed to determine iceberg characteristics. Limitations of this method are addressed including its accuracy. Surface imaging system and LIDAR system are developed to profile the above-water iceberg in 2015.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Ultrahigh Purcell factor in low-threshold nanolaser based on asymmetric hybrid plasmonic cavity

A low-threshold nanolaser with all three dimensions at the subwavelength scale is proposed and investigated. The nanolaser is constructed based on an asymmetric hybrid plasmonic F-P cavity with Ag-coated end facets. Lasing characteristics are calculated using finite element method at the wavelength of 1550 nm. The results show that owing to the low modal loss, large modal confinement factor of the asymmetric plasmonic cavity structure, in conjunction with the high reflectivity of the Ag reflectors, a minimum threshold gain of 240 cm−1 is predicted. Furthermore, the Purcell factor as large as 2518 is obtained with optimized structure parameters to enhance rates of spontaneous and stimulated emission.

Synthesis and characterization of nanocomposites based on PANI and carbon nanostructures prepared by electropolymerization

Nanocomposites based on polyaniline (PANI) and carbon nanostructures (CNSs) (graphene (G) and multiwall carbon nanotubes (MWCNTs)) were prepared by in situ electrochemical polymerization. CNSs were inserted into the PANI matrix by dispersing them into the electrolyte before the electropolymerization. Electrochemical characterization by means of cyclic voltammetry and steady state polarization were performed in order to determine conditions for electro- polymerization. Electro-polymerization of the PANI based nanocomposites was carried out at 0.75 V vs. saturated calomel electrode (SCE) for 40 and 60 minutes. The morphology and structural characteristics of the obtained nanocomposites were studied by scanning electron microscopy (SEM) and Raman spectroscopy, while thermal stability was determined using thermal gravimetric analysis (TGA). According to the morphological and structural study, fibrous and porous structure of PANI based nanocomposites was detected well embedding both G and MWCNTs. Also, strong interaction between quinoidal structure of PANI with carbon nanostructures via π–π stacking was detected by Raman spectroscopy. TGA showed the increased thermal stability of composites reinforced with CNSs, especially those reinforced with graphene.

Spring snowmelt and midwinter thaw and refreeze north of 60°N based on Seawinds QuikScat 2000-2009

The scatterometer SeaWinds on QuikSCAT provided regular measurements at Ku-band from 1999 to 2009. Although it was designed for ocean applications, it has been frequently used for the assessment of seasonal snowmelt patterns aside from other terrestrial applications such as ice cap monitoring, phenology and urban mapping. This paper discusses general data characteristics of SeaWinds and reviews relevant change detection algorithms. Depending on the complexity of the method, parameters such as long-term noise and multiple event analyses were incorporated. Temporal averaging is a commonly accepted preprocessing step with consideration of diurnal, multi-day or seasonal averages.

Variability of marine climate on the North Icelandic Shelf in a 1357-year proxy archive based on growth increments in the bivalve Arctica islandica

A multicentennial and absolutely-dated shell-based chronology for the marine environment of the North Icelandic Shelf has been constructed using annual growth increments in the shell of the long-lived bivalve clam Arctica islandica. The region from which the shells were collected is close to the North Atlantic Polar Front and is highly sensitive to the varying influences of Atlantic and Arctic water masses. A strong common environmental signal is apparent in the increment widths, and although the correlations between the growth increment indices and regional sea surface temperatures are significant at the 95% confidence level, they are low (r ~ 0.2), indicating that a more complex combination of environmental forcings is driving growth. Remarkable longevities of individual animals are apparent in the increment-width series used in the chronology, with several animals having lifetimes in excess of 300 years and one, at 507 years, being the longest-lived non-colonial animal so far reported whose age at death can be accurately determined. The sample depth is at least three shells after AD 1175, and the time series has been extended back to AD 649 with a sample depth of one or two by the addition of two further series, thus providing a 1357-year archive of dated shell material. The statistical and spectral characteristics of the chronology are investigated by using two different methods of removing the age-related trend in shell growth. Comparison with other proxy archives from the same region reveals several similarities in variability on multidecadal timescales, particularly during the period surrounding the transition from the Medieval Climate Anomaly to the Little Ice Age.

Ecological classification of Herschel Island based on supervised classification of multispectral satellite imagery

Permafrost landscapes experience different disturbances and store large amounts of organic matter, which may become a source of greenhouse gases upon permafrost degradation. We analysed the influence of terrain and geomorphic disturbances (e.g. soil creep, active-layer detachment, gullying, thaw slumping, accumulation of fluvial deposits) on soil organic carbon (SOC) and total nitrogen (TN) storage using 11 permafrost cores from Herschel Island, western Canadian Arctic. Our results indicate a strong correlation between SOC storage and the topographic wetness index. Undisturbed sites stored the majority of SOC and TN in the upper 70 cm of soil. Sites characterised by mass wasting showed significant SOC depletion and soil compaction, whereas sites characterised by the accumulation of peat and fluvial deposits store SOC and TN along the whole core. We upscaled SOC and TN to estimate total stocks using the ecological units determined from vegetation composition, slope angle and the geomorphic disturbance regime. The ecological units were delineated with a supervised classification based on RapidEye multispectral satellite imagery and slope angle. Mean SOC and TN storage for the uppermost 1?m of soil on Herschel Island are 34.8 kg C/m**2 and 3.4 kg N/m**2, respectively.

An R-package for the Estimation and Testing of Multiple Covariates and Biomarker Interactions for Survival Data Based on Local Partial Likelihood

When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.

Assessment of the EEE-4 oral test: a discourse analysis based on complex networks.

With the development of information technology, the theory and methodology of complex network has been introduced to the language research, which transforms the system of language in a complex networks composed of nodes and edges for the quantitative analysis about the language structure. The development of dependency grammar provides theoretical support for the construction of a treebank corpus, making possible a statistic analysis of complex networks. This paper introduces the theory and methodology of the complex network and builds dependency syntactic networks based on the treebank of speeches from the EEE-4 oral test. According to the analysis of the overall characteristics of the networks, including the number of edges, the number of the nodes, the average degree, the average path length, the network centrality and the degree distribution, it aims to find in the networks potential difference and similarity between various grades of speaking performance. Through clustering analysis, this research intends to prove the network parameters’ discriminating feature and provide potential reference for scoring speaking performance.

New Method for the Estimation of Viscosity of Pure and Mixtures of Ionic Liquids Based on the UNIFAC–VISCO Model

A modified UNIFAC–VISCO group contribution method was developed for the correlation and prediction of viscosity of ionic liquids as a function of temperature at 0.1 MPa. In this original approach, cations and anions were regarded as peculiar molecular groups. The significance of this approach comes from the ability to calculate the viscosity of mixtures of ionic liquids as well as pure ionic liquids. Binary interaction parameters for selected cations and anions were determined by fitting the experimental viscosity data available in literature for selected ionic liquids. The temperature dependence on the viscosity of the cations and anions were fitted to a Vogel–Fulcher–Tamman behavior. Binary interaction parameters and VFT type fitting parameters were then used to determine the viscosity of pure and mixtures of ionic liquids with different combinations of cations and anions to ensure the validity of the prediction method. Consequently, the viscosities of binary ionic liquid mixtures were then calculated by using this prediction method. In this work, the viscosity data of pure ionic liquids and of binary mixtures of ionic liquids are successfully calculated from 293.15 K to 363.15 K at 0.1 MPa. All calculated viscosity data showed excellent agreement with experimental data with a relative absolute average deviation lower than 1.7%.

Irish Credit Unions: Differential Regulation based on Business Model Complexity

This study examines the business model complexity of Irish credit unions using a latent class approach to measure structural performance over the period 2002 to 2013. The latent class approach allows the endogenous identification of a multi-class framework for business models based on credit union specific characteristics. The analysis finds a three class system to be appropriate with the multi-class model dependent on three financial viability characteristics. This finding is consistent with the deliberations of the Irish Commission on Credit Unions (2012) which identified complexity and diversity in the business models of Irish credit unions and recommended that such complexity and diversity could not be accommodated within a one size fits all regulatory framework. The analysis also highlights that two of the classes are subject to diseconomies of scale. This may suggest credit unions would benefit from a reduction in scale or perhaps that there is an imbalance in the present change process. Finally, relative performance differences are identified for each class in terms of technical efficiency. This suggests that there is an opportunity for credit unions to improve their performance by using within-class best practice or alternatively by switching to another class.

Synthesis, Characterization and Properties of Conductive Elastomeric Composites Based on Polypyrrole and Short Nylon-6 Fiber

The search for new materials especially those possessing special properties continues at a great pace because of ever growing demands of the modern life. The focus on the use of intrinsically conductive polymers in organic electronic devices has led to the development of a totally new class of smart materials. Polypyrrole (PPy) is one of the most stable known conducting polymers and also one of the easiest to synthesize. In addition, its high conductivity, good redox reversibility and excellent microwave absorbing characteristics have led to the existence of wide and diversified applications for PPy. However, as any conjugated conducting polymer, PPy lacks processability, flexibility and strength which are essential for industrial requirements. Among various approaches to making tractable materials based on PPy, incorporating PPy within an electrically insulating polymer appears to be a promising method, and this has triggered the development of blends or composites. Conductive elastomeric composites of polypyrrole are important in that they are composite materials suitable for devices where flexibility is an important parameter. Moreover these composites can be moulded into complex shapes.

Death by Suicide: A Report Based on the Northern Ireland Coroner’s Database

Funded by HSC R&D Division, Public Health Agency Why did we start? Potentially new information, especially relating to the characteristics of those who had died by suicide was made available through the Coroner’s Office.  The information made available to us covered deaths that occurred in the years 2005 to the end of 2011. What did we do? First we addressed the descriptive characteristics associated with this group of individuals. These descriptive characteristics included information relating to (1) means by which the death occurred (2) gender, age and employment status of the person (3) prior attempts (4)  alcohol and prescription use around time of death (5) adverse events (6) use of health services and (7) mental and physical health problems. Second we examined area level residential location in terms of Local Government Districts, and Wards within Northern Ireland. To address this area level of analysis, standardised mortality ratios (SMRs) were used.      

Generic wind estimation and compensation based on residual generators and higher-order sliding mode schemes

This master thesis proposes a solution to the approach problem in case of unknown severe microburst wind shear for a fixed-wing aircraft, accounting for both longitudinal and lateral dynamics. The adaptive controller design for wind rejection is also addressed, exploiting the wind estimation provided by suitable estimators. It is able to successfully complete the final approach phase even in presence of wind shear, and at the same time aerodynamic envelope protection is retained. The adaptive controller for wind compensation has been designed by a backstepping approach and feedback linearization for time-varying systems. The wind shear components have been estimated by higher-order sliding mode schemes. At the end of this work the results are provided, an autonomous final approach in presence of microburst is discussed, performances are analyzed, and estimation of the microburst characteristics from telemetry data is examined.