Analysis of a negatively buoyant jet

The behavior of plane fountains, resulting from the injection of dense fluid (water) upwards into a large container of homogeneous fluid of lower density (air),was investigated. In this study the behavior of fountains was examined numerically and experimentally for different Froude and Reynolds numbers. The flow rate and nozzle diameter of the inlet of the fountain was varied to cover a wide range of Reynolds and Froude numbers. The effect of inclination angle of the inlet for different nozzle diameter and flow rate on fountain behavior was observed. It was found that the height of the fountain greatly depends on Froude number. An empirical correlation was developed for non-dimensional fountain height with Froude number. However the non-dimensional fountain height can more accurately be represented when regressed with both Reynolds and Froude number by the following relationship H/r=exp(5.94)*Re^-0.72*Fr^2.26. The result are compared with previous numerical and experimental results and found to be consistent.

Heat transfer measurements on the first experimental layer of the FIRE II reentry vehicle in expansion tubes

The present study focused on simulating a trajectory point towards the end of the first experimental heatshield of the FIRE II vehicle, at a total flight time of 1639.53s. Scale replicas were sized according to binary scaling and instrumented with thermocouples for testing in the X1 expansion tube, located at The University of Queensland. Correlation of flight to experimental data was achieved through the separation, and independent treatment of the heat modes. Preliminary investigation indicates that the absolute value of radiant surface flux is conserved between two binary scaled models, whereas convective heat transfer increases with the length scale. This difference in the scaling techniques result in the overall contribution of radiative heat transfer diminishing to less than 1% in expansion tubes from a flight value of approximately 9-17%. From empirical correlation's it has been shown that the St √Re number decreases, under special circumstances, in expansion tubes by the percentage radiation present on the flight vehicle. Results obtained in this study give a strong indication that the relative radiative heat transfer contribution in the expansion tube tests is less than that in flight, supporting the analysis that the absolute value remains constant with binary scaling.

The relation between work motivation and project management success : an empirical investigation

The content and context of work significantly influences an employees’ satisfaction. While managers see work motivation as a tool to engage the employees so that they perform better, academicians value work motivation for its contribution to human behaviour. Though the relationship between employee motivation and project success has been extensively covered in the literature, more research focusing on the nature of job design on project success may have been wanting. We address this gap through this study. The present study contributes to the extant literature by suggesting an operational framework of work motivation for project—based organizations. We are also advancing the conceptual understanding of this variable by understanding how the different facets of work motivation have a differing impact of the various parameters of project performance. A survey instrument using standardized scales of work motivation and project success was used. 199 project workers from various industries completed the survey. We first ‘operationalized’ the definition of work motivation for the purpose of our study through a principal component analysis of work motivation items. We obtained a five factor structure that had items pertaining to employee development, work climate, goal clarity, and job security. We then performed a Pearson’s correlation analysis which revealed moderate to significant relationship between project outcomes ad work climate; project outcomes & employee development. In order to establish a causality between work motivation and project management success, we employed linear regression analysis. The results show that work climate is a significant predictor of client satisfaction, while it moderately influences the project quality. Further, bringing in objectivity to project work is important for a successful implementation.

Forecasting volatility and correlation : the role of option implied measures

Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.

Empirical study to identify the key business activities contributing to manufacturing business performance

Purpose: Within the context of high global competitiveness, knowledge management (KM) has proven to be one of the major factors contributing to enhanced business outcomes. Furthermore, knowledge sharing (KS) is one of the most critical of all KM activities. From a manufacturing industry perspective, supply chain management (SCM) and product development process (PDP) activities, require a high proportion of company resources such as budget and manpower. Therefore, manufacturing companies are striving to strengthen SCM, PDP and KS activities in order to accelerate rates of manufacturing process improvement, ultimately resulting in higher levels of business performance (BP). A theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, factor and path analyses. Design/methodology/approach: A questionnaire survey was administered to a sample of electronic manufacturing companies operating in Taiwan to facilitate testing the proposed relationships. More than 170 respondents from 83 organisations responded to the survey. The study identified top management commitment and employee empowerment, supplier evaluation and selection, and design simplification and modular design as the key business activities that are strongly associated with the business performance. Findings: The empirical study supports that key manufacturing business activities (i.e., SCM, PDP, and KS) are positively associated with BP. The findings also evealed that some specific business activities such as SCMF1,PDPF2, and KSF1 have the strongest influencing power on particular business outcomes (i.e., BPF1 and BPF2) within the context of electronic manufacturing companies operating in Taiwan. Practical implications: The finding regarding the relationship between SCM and BP identified the essential role of supplier evaluation and selection in improving business competitiveness and long term performance. The process of forming knowledge in companies, such as creation, storage/retrieval, and transfer do not necessarily lead to enhanced business performance; only through effectively applying knowledge to the right person at the right time does. Originality/value: Based on this finding it is recommended that companies should involve suppliers in partnerships to continuously improve operations and enhance product design efforts, which would ultimately enhance business performance. Business performance depends more on an employee’s ability to turn knowledge into effective action.

Empirical approach to understand the knowledge management process

Knowledge Management (KM) is a process that focuses on knowledge-related activities to facilitate knowledge creation, capture, transformation and use, with the ultimate aim of leveraging organisations’ intellectual capital to achieve organisational objectives. The KM process receives input from its context (e.g. internal business environment), and produces output (i.e. knowledge). It is argued that the validity of such knowledge should be justified by business performance. The study, this paper reports on, provides enhanced empirical understanding of such an input-process-output relationship through investigating the interactions among different KM activities in the context of how construction organisations in Hong Kong manage knowledge. To this end, a theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, regression and path analyses. A questionnaire survey was administered to a sample of construction contractors operating in Hong Kong to facilitate testing the proposed relationships. More than 140 respondents from 99 organisations responded to the survey. The study findings demonstrate that both organisational and technical environments have the potential to predict the intensity of KM activities. Furthermore, different categories of KM activities interact with each other, and collectively they could be used to predict business performance.

An IEEE 802.11p empirical performance model for cooperative systems applications

IEEE 802.11p is the new standard for Inter-Vehicular Communications (IVC) using the 5.9 GHz frequency band, as part of the DSRC framework; it will enable applications based on Cooperative Systems. Simulation is widely used to estimate or verify the potential benefits of such cooperative applications, notably in terms of safety for the drivers. We have developed a performance model for 802.11p that can be used by simulations of cooperative applications (e.g. collision avoidance) without requiring intricate models of the whole IVC stack. Instead, it provide a a straightforward yet realistic modelisation of IVC performance. Our model uses data from extensive field trials to infer the correlation between speed, distance and performance metrics such as maximum range, latency and frame loss. Then, we improve this model to limit the number of profiles that have to be generated when there are more than a few couples of emitter-receptor in a given location. Our model generates realistic performance for rural or suburban environments among small groups of IVC-equipped vehicles and road side units.

Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Representation of facial expression categories in continuous arousal-valence space: Feature and correlation

Representation of facial expressions using continuous dimensions has shown to be inherently more expressive and psychologically meaningful than using categorized emotions, and thus has gained increasing attention over recent years. Many sub-problems have arisen in this new field that remain only partially understood. A comparison of the regression performance of different texture and geometric features and investigation of the correlations between continuous dimensional axes and basic categorized emotions are two of these. This paper presents empirical studies addressing these problems, and it reports results from an evaluation of different methods for detecting spontaneous facial expressions within the arousal-valence dimensional space (AV). The evaluation compares the performance of texture features (SIFT, Gabor, LBP) against geometric features (FAP-based distances), and the fusion of the two. It also compares the prediction of arousal and valence, obtained using the best fusion method, to the corresponding ground truths. Spatial distribution, shift, similarity, and correlation are considered for the six basic categorized emotions (i.e. anger, disgust, fear, happiness, sadness, surprise). Using the NVIE database, results show that the fusion of LBP and FAP features performs the best. The results from the NVIE and FEEDTUM databases reveal novel findings about the correlations of arousal and valence dimensions to each of six basic emotion categories.

Analysing the similarity of proteins based on a new approach to empirical mode decomposition

The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

Testing against changing correlation

A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.