Timeshare Owner Preferences - An Analysis of Program and Service Relationships during Recessionary Times

Since the 1970s various industry studies have indicated that the vacation ownership industry has enjoyed unprecedented growth in unit sales, resort growth, and the number of owners (American Resort Devleopment Association [ARDA], 2007; ARDA, 2009a; ARDA, 2009b). However, due to the recent economic downturn these growth metrics are no longer obtainable. This external impact has caused developers to retrench and therefore reflect upon their existing product and service offerings, financial metrics, and consumer markets (ARDA, 2010a; ARDA 2010b). The crux of these findings indicates that the industry has shifted to maintaining and enhancing product and service offerings as a reaction to changing economic conditions. The findings reported in the body of this manuscript represent product and service preferences as collected from a random data pull of their existing ownership base. The study also revealed current preferences of timeshare owners with relation to services provided and products/amenities offered. Management implications and limitations of the current study are discussed.

European Leaf Physiognomic Approach ELPA

Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.

Multiple classification analysis ; a report on a computer program for multiple regression using categorical predictors /

Bibliographical footnotes.

Multivariate statistical analysis of hydrochemical data to assess alluvial aquifer–stream connectivity during drought and flood : Cressbrook Creek, southeast Queensland, Australia

A catchment-scale multivariate statistical analysis of hydrochemistry enabled assessment of interactions between alluvial groundwater and Cressbrook Creek, an intermittent drainage system in southeast Queensland, Australia. Hierarchical cluster analyses and principal component analysis were applied to time-series data to evaluate the hydrochemical evolution of groundwater during periods of extreme drought and severe flooding. A simple three-dimensional geological model was developed to conceptualise the catchment morphology and the stratigraphic framework of the alluvium. The alluvium forms a two-layer system with a basal coarse-grained layer overlain by a clay-rich low-permeability unit. In the upper and middle catchment, alluvial groundwater is chemically similar to streamwater, particularly near the creek (reflected by high HCO3/Cl and K/Na ratios and low salinities), indicating a high degree of connectivity. In the lower catchment, groundwater is more saline with lower HCO3/Cl and K/Na ratios, notably during dry periods. Groundwater salinity substantially decreased following severe flooding in 2011, notably in the lower catchment, confirming that flooding is an important mechanism for both recharge and maintaining groundwater quality. The integrated approach used in this study enabled effective interpretation of hydrological processes and can be applied to a variety of hydrological settings to synthesise and evaluate large hydrochemical datasets.

Representation of the Weddell Sea deep water masses in the ocean component of the NCAR-CCSM model

We examine Weddell Sea deep water mass distributions with respect to the results from three different model runs using the oceanic component of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM). One run is inter-annually forced by corrected NCAR/NCEP fluxes, while the other two are forced with the annual cycle obtained from the same climatology. One of the latter runs includes an interactive sea-ice model. Optimum Multiparameter analysis is applied to separate the deep water masses in the Greenwich Meridian section (into the Weddell Sea only) to measure the degree of realism obtained in the simulations. First, we describe the distribution of the simulated deep water masses using observed water type indices. Since the observed indices do not provide an acceptable representation of the Weddell Sea deep water masses as expected, they are specifically adjusted for each simulation. Differences among the water masses` representations in the three simulations are quantified through their root-mean-square differences. Results point out the need for better representation (and inclusion) of ice-related processes in order to improve the oceanic characteristics and variability of dense Southern Ocean water masses in the outputs of the NCAR-CCSM model, and probably in other ocean and climate models.

Multivariate statistical analysis of highway accident and highway conditions. Final report.

Transportation Department, Office of University Research, Washington, D.C.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Regression and hypothesis tests for multivariate GNSS state time series

A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

How to increase the accuracy of analysis and reduce the computational time in ANSYS in the case of deformation study of orthopedic bone plates

Currently, finite element analyses are usually done by means of commercial software tools. Accuracy of analysis and computational time are two important factors in efficiency of these tools. This paper studies the effective parameters in computational time and accuracy of finite element analyses performed by ANSYS and provides the guidelines for the users of this software whenever they us this software for study on deformation of orthopedic bone plates or study on similar cases. It is not a fundamental scientific study and only shares the findings of the authors about structural analysis by means of ANSYS workbench. It gives an idea to the readers about improving the performance of the software and avoiding the traps. The solutions provided in this paper are not the only possible solutions of the problems and in similar cases there are other solutions which are not given in this paper. The parameters of solution method, material model, geometric model, mesh configuration, number of the analysis steps, program controlled parameters and computer settings are discussed through thoroughly in this paper.

The use of phospholipid fatty acid analysis to measure impact of acid rock drainage on microbial communities in sediments

The impact of acid rock drainage (ARD) and eutrophication on microbial communities in stream sediments above and below an abandoned mine site in the Adelaide Hills, South Australia, was quantified by PLFA analysis. Multivariate analysis of water quality parameters, including anions, soluble heavy metals, pH, and conductivity, as well as total extractable metal concentrations in sediments, produced clustering of sample sites into three distinct groups. These groups corresponded with levels of nutrient enrichment and/or concentration of pollutants associated with ARD. Total PLFA concentration, which is indicative of microbial biomass, was reduced by >70% at sites along the stream between the mine site and as far as 18 km downstream. Further downstream, however, recovery of the microbial abundance was apparent, possibly reflecting dilution effect by downstream tributaries. Total PLFA was >40% higher at, and immediately below, the mine site (0-0.1 km), compared with sites further downstream (2.5-18 km), even after accounting for differences in specific surface area of different sediment samples. The increased microbial population in the proximity of the mine source may be associated with the presence of a thriving iron-oxidizing bacteria community as a consequence of optimal conditions for these organisms while the lower microbial population further downstream corresponded with greater sediments' metal concentrations. PCA of relative abundance revealed a number of PLFAs which were most influential in discriminating between ARD-polluted sites and the rest of the sites. These PLFA included the hydroxy fatty acids: 2OH12:0, 3OH12:0, 2OH16:0; the fungal marker: 18:2ω6; the sulfate-reducing bacteria marker 10Me16:1ω7; and the saturated fatty acids 12:0, 16:0, 18:0. Partial constrained ordination revealed that the environmental parameters with the greatest bearing on the PLFA profiles included pH, soluble aluminum, total extractable iron, and zinc. The study demonstrated the successful application of PLFA analysis to rapidly assess the toxicity of ARD-affected waters and sediments and to differentiate this response from the effects of other pollutants, such as increased nutrients and salinity.

Phosphorus concentrations in the leaves of cotton in tropical Australia are determined by temperature.

Previous research on P leaf analysis for detecting deficiencies in cotton (Gossypium hirsutum L.) has not considered temperature as a determining factor. This is despite correlations between leaf P content and temperature being observed in other crops. As part of research into a new cotton farming system for the semi-arid tropics of Australia, we conducted two P fertiliser rate experiments on recently cleared un-cropped (bicarbonate P < 5 mg kg- 1) and previously cropped (bicarbonate P 26 mg kg- 1) soil. They aimed to develop P requirements and more importantly to determine if temperature affects the leaf P concentrations used to diagnose P deficiencies. In 2002, optimal yield on un-cropped, low P soil was achieved with a 60 kg P ha- 1 rate. In 2003, residual P from the 40 kg P ha- 1 treatment produced optimal yield. On cropped, high P soil there was no yield response to treatments up to 100 kg P ha- 1. On low P soil, a positive correlation was observed between P concentration in the youngest fully-unfurled leaf (YFUL), fertiliser rate, and mean diurnal temperature in the seven days prior to sampling. On high P soil, a positive correlation was observed between the YFUL and mean diurnal temperature however there was no correlation with fertiliser rate. These results show that YFUL analysis can be used to diagnose P deficiencies in cotton, provided the temperature prior to sampling is considered.

Declining trends in annual catch rates of the tiger shark (Galeocerdo cuvier) in Queensland, Australia

Suitable long term species-specific catch rate and biological data are seldom available for large shark species, particularly where historical commercial logbook reporting has been poor. However, shark control programs can provide suitable data from gear that consistently fishes nearshore waters all year round. We present an analysis of the distribution of 4757 . Galeocerdo cuvier caught in surface nets and on drumlines across 9 of the 10 locations of the Queensland Shark Control Program (QSCP) between 1993 and 2010. Standardised catch rates showed a significant decline (p<. 0.0001) in southern Queensland locations for both gear types, which contrasts with studies at other locations where increases in tiger shark catch per unit effort (CPUE) have been reported. Significant temporal declines in the average size of tiger sharks occurred at four of the nine locations analysed (p<. 0.05), which may be indicative of fishing reducing abundance in these areas. Given the long term nature of shark control programs along the Australian east coast, effects on local abundance should have been evident many years ago, which suggests that factors other than the effects of shark control programs have also contributed to the decline. While reductions in catch rate are consistent with a decline in tiger shark abundance, this interpretation should be made with caution, as the inter-annual CPUE varies considerably at most locations. Nevertheless, the overall downward trend, particularly in southern Queensland, indicates that current fishing pressures on the species may be unsustainable. © 2012 Elsevier B.V.