An identification of factors influencing police workplace motivation

Police work tasks are diverse and require the ability to take command, demonstrate leadership, make serious decisions and be self directed (Beck, 1999; Brunetto & Farr-Wharton, 2002; Howard, Donofrio & Boles, 2002). This work is usually performed in pairs or sometimes by an officer working alone. Operational police work is seldom performed under the watchful eyes of a supervisor and a great amount of reliance is placed on the high levels of motivation and professionalism of individual officers. Research has shown that highly motivated workers produce better outcomes (Whisenand & Rush, 1998; Herzberg, 2003). It is therefore important that Queensland police officers are highly motivated to provide a quality service to the Queensland community. This research aims to identify factors which motivate Queensland police to perform quality work. Researchers acknowledge that there is a lack of research and knowledge in regard to the factors which motivate police (Beck, 1999; Bragg, 1998; Howard, Donofrio & Boles, 2002; McHugh & Verner, 1998). The motivational factors were identified in regard to the demographic variables of; age, sex, rank, tenure and education. The model for this research is Herzberg’s two-factor theory of workplace motivation (1959). Herzberg found that there are two broad types of workplace motivational factors; those driven by a need to prevent loss or harm and those driven by a need to gain personal satisfaction or achievement. His study identified 16 basic sub-factors that operate in the workplace. The research utilised a questionnaire instrument based on the sub-factors identified by Herzberg (1959). The questionnaire format consists of an initial section which sought demographic information about the participant and is followed by 51 Likert scale questions. The instrument is an expanded version of an instrument previously used in doctoral studies to identify sources of police motivation (Holden, 1980; Chiou, 2004). The questionnaire was forwarded to approximately 960 police in the Brisbane, Metropolitan North Region. The data were analysed using Factor Analysis, MANOVAs, ANOVAs and multiple regression analysis to identify the key sources of police motivation and to determine the relationships between demographic variables such as: age, rank, educational level, tenure, generation cohort and motivational factors. A total of 484 officers responded to the questionnaire from the sample population of 960. Factor analysis revealed five broad Prime Motivational Factors that motivate police in their work. The Prime Motivational Factors are: Feeling Valued, Achievement, Workplace Relationships, the Work Itself and Pay and Conditions. The factor Feeling Valued highlighted the importance of positive supportive leaders in motivating officers. Many officers commented that supervisors who only provided negative feedback diminished their sense of feeling valued and were a key source of de-motivation. Officers also frequently commented that they were motivated by operational police work itself whilst demonstrating a strong sense of identity with their team and colleagues. The study showed a general need for acceptance by peers and an idealistic motivation to assist members of the community in need and protect victims of crime. Generational cohorts were not found to exert a significant influence on police motivation. The demographic variable with the single greatest influence on police motivation was tenure. Motivation levels were found to drop dramatically during the first two years of an officer’s service and generally not improve significantly until near retirement age. The findings of this research provide the foundation of a number of recommendations in regard to police retirement, training and work allocation that are aimed to improve police motivation levels. The five Prime Motivational Factor model developed in this study is recommended for use as a planning tool by police leaders to improve motivational and job-satisfaction components of police Service policies. The findings of this study also provide a better understanding of the current sources of police motivation. They are expected to have valuable application for Queensland police human resource management when considering policies and procedures in the areas of motivation, stress reduction and attracting suitable staff to specific areas of responsibility.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Virtual diasporas and the dilemma of multiple belongings in cyberspace

One of the most celebrated qualities of the Internet is its enabling of simultaneity and multiplicity. By allowing users to open as many windows into the world as they (and their computers) can withstand, the Internet is understood to have brought places and cultures together on a scale and in a manner unprecedented. Yet, while the Internet has enabled many to reconnect with cultures and places long distanced and/or lost, it has also led to the belief that these reconnections are established with little correspondent cost to existent ties of belonging. In this paper, I focus on the dilemma multiple belongings engender for the ties of national belonging and question the sanguinity of multiple belongings as practised online. In particular, I use Lefebvre's notion of lived space to unpack the problems and contradictions of what has been called 'Greater China' for the ethnic Chinese minority in nations like Malaysia, Singapore and Australia.

Immunogenicity and protective efficacy of an anti-Streptococcus pyogenes vaccine candidate in multiple animal species

Streptococcus pyogenes, also known as Group A Streptococcus (GAS) has been associated with a range of diseases from the mild pharyngitis and pyoderma to more severe invasive infections such as streptococcal toxic shock. GAS also causes a number of non-suppurative post-infectious diseases such as rheumatic fever, rheumatic heart disease and glomerulonephritis. The large extent of GAS disease burden necessitates the need for a prophylactic vaccine that could target the diverse GAS emm types circulating globally. Anti-GAS vaccine strategies have focused primarily on the GAS M-protein, an extracellular virulence factor anchored to GAS cell wall. As opposed to the hypervariable N-terminal region, the C-terminal portion of the protein is highly conserved among different GAS emm types and is the focus of a leading GAS vaccine candidate, J8-DT/alum. The vaccine candidate J8-DT/alum was shown to be immunogenic in mice, rabbits and the non-human primates, hamadryas baboons. Similar responses to J8-DT/alum were observed after subcutaneous and intramuscular immunization with J8-DT/alum, in mice and in rabbits. Further assessment of parameters that may influence the immunogenicity of J8-DT demonstrated that the immune responses were identical in male and female mice and the use of alum as an adjuvant in the vaccine formulation significantly increased its immunogenicity, resulting in a long-lived serum IgG response. Contrary to the previous findings, the data in this thesis indicates that a primary immunization with J8-DT/alum (50ƒÊg) followed by a single boost is sufficient to generate a robust immune response in mice. As expected, the IgG response to J8- DT/alum was a Th2 type response consisting predominantly of the isotype IgG1 accompanied by lower levels of IgG2a. Intramuscular vaccination of rabbits with J8-DT/alum demonstrated that an increase in the dose of J8-DT/alum up to 500ƒÊg does not have an impact on the serum IgG titers achieved. Similar to the immune response in mice, immunization with J8-DT/alum in baboons also established that a 60ƒÊg dose compared to either 30ƒÊg or 120ƒÊg was sufficient to generate a robust immune response. Interestingly, mucosal infection of naive baboons with a M1 GAS strain did not induce a J8-specific serum IgG response. As J8-DT/alum mediated protection has been previously reported to be due to the J8- specific antibody formed, the efficacy of J8-DT antibodies was determined in vitro and in vivo. In vitro opsonization and in vivo passive transfer confirmed the protective potential of J8-DT antibodies. A reduction in the bacterial burden after challenge with a bioluminescent M49 GAS strain in mice that were passively administered J8-DT IgG established that protection due to J8-DT was mediated by antibodies. The GAS burden in infected mice was monitored using bioluminescent imaging in addition to traditional CFU assays. Bioluminescent GAS strains including the ‘rheumatogenic’ M1 GAS could not be generated due to limitations with transformation of GAS, however, a M49 GAS strain was utilized during BLI. The M49 serotype is traditionally a ‘nephritogenic’ serotype associated with post-streptococcal glomerulonephritis. Anti- J8-DT antibodies now have been shown to be protective against multiple GAS strains such as M49 and M1. This study evaluated the immunogenicity of J8-DT/alum in different species of experimental animals in preparation for phase I human clinical trials and provided the ground work for the development of a rapid non-invasive assay for evaluation of vaccine candidates.