Web-based and traditional public participation in comprehensive planning : a comparative study

The present paper examines whether the potential advantages of the expanding practice of web-based public participation only complement the benefits of the traditional techniques, or are empowering enough to replace them. The question is examined in a real-world case of neighbourhood revitalization, in which both techniques were practiced simultaneously. Comparisons are made at four major planning junctions, in order to study the contributions of each technique to the qualities of involvement, trust, and empowerment. The results show that web-based participants not only differ from the participants of traditional practices, but they also differ from each other on the basis of their type of web participation. The results indicate that web-based participation is an effective and affective complementary means of public participation, but it cannot replace the traditional unmediated techniques.

Synthesis and thermal analysis of Indium based hydrotalcites of formula Mg6In2(CO3)(OH)16•4H2O

Insight into the unique structure of layered double hydroxides has been obtained using a combination of X-ray diffraction and thermal analysis. Indium containing hydrotalcites of formula Mg4In2(CO3)(OH)12•4H2O (2:1 In-LDH) through to Mg8In2(CO3)(OH)18•4H2O (4:1 In-LDH) with variation in the Mg:In ratio have been successfully synthesised. The d(003) spacing varied from 7.83 Å for the 2:1 LDH to 8.15 Å for the 3:1 indium containing layered double hydroxide. Distinct mass loss steps attributed to dehydration, dehydroxylation and decarbonation are observed for the indium containing hydrotalcite. Dehydration occurs over the temperature range ambient to 205 °C. Dehydroxylation takes place in a series of steps over the 238 to 277 °C temperature range. Decarbonation occurs between 763 and 795 °C. The dehydroxylation and decarbonation steps depend upon the Mg:In ratio. The formation of indium containing hydrotalcites and their thermal activation provides a method for the synthesis of indium oxide based catalysts.

Modelling the process of dialogic communication in public relations: a role-based approach

This paper takes Kent and Taylor’s (2002) call to develop a dialogic theory of public relations and suggests that a necessary first step is the modelling of the process of dialogic communication in public relations. In order to achieve this, extant literature from a range of fields is reviewed, seeking to develop a definition of dialogic communication that is meaningful to the practice of contemporary public relations. A simple transmission model of communication is used as a starting point. This is synthesised with concepts relating specifically to dialogue, taken here in its broadest sense rather than defined as any one particular outcome. The definition that emerges from this review leads to the conclusion that dialogic communication in public relations involves the interaction of three roles – those of sender, receiver, and responder. These three roles are shown to be adopted at different times by both participants involved in dialogic communication. It is further suggested that variations occur in how these roles are conducted: the sender and receiver roles can be approached in a passive or an active way, while the responder role can be classified as being either resistant or responsive to the information received in dialogic communication. The final modelling of the definition derived provides a framework which can be tested in the field to determine whether variations in the conduct of the roles in dialogic communication actually exist, and if so, whether they can be linked to the different types of outcome from dialogic communication identified previously in the literature.

Description and evaluation of a Newton-based electronic appetite rating system for temporal tracking of appetite in human subjects

This study assessed the reliability and validity of a palm-top-based electronic appetite rating system (EARS) in relation to the traditional paper and pen method. Twenty healthy subjects [10 male (M) and 10 female (F)] — mean age M=31 years (S.D.=8), F=27 years (S.D.=5); mean BMI M=24 (S.D.=2), F=21 (S.D.=5) — participated in a 4-day protocol. Measurements were made on days 1 and 4. Subjects were given paper and an EARS to log hourly subjective motivation to eat during waking hours. Food intake and meal times were fixed. Subjects were given a maintenance diet (comprising 40% fat, 47% carbohydrate and 13% protein by energy) calculated at 1.6×Resting Metabolic Rate (RMR), as three isoenergetic meals. Bland and Altman's test for bias between two measurement techniques found significant differences between EARS and paper and pen for two of eight responses (hunger and fullness). Regression analysis confirmed that there were no day, sex or order effects between ratings obtained using either technique. For 15 subjects, there was no significant difference between results, with a linear relationship between the two methods that explained most of the variance (r2 ranged from 62.6 to 98.6). The slope for all subjects was less than 1, which was partly explained by a tendency for bias at the extreme end of results on the EARS technique. These data suggest that the EARS is a useful and reliable technique for real-time data collection in appetite research but that it should not be used interchangeably with paper and pen techniques.

No energy compensation at the meal following exercise indietary restrained and unrestrained women

The objective of this investigation was to compare the acute effects of exercise and diet manipulations on energy intake, between dietary restrained and unrestrained females. Comparisons of two studies using an identical 2 x 2 repeated-measures design (level of activity (rest or exercise) and lunch type (high-fat or low-fat)) including thirteen dietary unrestrained and twelve restrained females were performed. Energy expenditure during the rest session was estimated and the energy cost of exercise was measured by indirect calorimetry. Relative energy intake was calculated by subtracting the energy expenditure of the exercise session from the energy intake of the test meal. Post-meal hedonic ratings were completed after lunch. Energy intake and relative energy intake increased during high-fat conditions compared with the low-fat, independently of exercise (P < 0.001). There was a positive relationship between dietary restraint scores and energy intake or relative energy intake in the rest conditions only (r 0.54, P < 0.01). The decrease of relative energy intake between the rest and exercise conditions was higher in restrained than in unrestrained eaters (P < 0.01). These results confirm that a high-fat diet reversed the energy deficit due to exercise. There was no energy compensation in response to an acute bout of exercise during the following meal. In restrained eaters, exercise was more effective in creating an energy deficit than in unrestrained eaters. Exercise may help restrained eaters to maintain control over appetite.

Improved power sharing among distributed generators using web based communication

This paper investigates the possibility of power sharing improvements amongst distributed generators with low cost, low bandwidth communications. Decentralized power sharing or power management can be improved significantly with low bandwidth communication. Utility intranet or a dedicated web based communication can serve the purpose. The effect of network parameter such line impedance, R/X ratio on decentralized power sharing can be compensated with correction in the decentralized control reference quantities through the low bandwidth communication. In this paper, the possible improvement is demonstrated in weak system condition, where the micro sources and the loads are not symmetrical along the rural microgrid with high R/X ratio line, creates challenge for decentralized control. In those cases the web based low bandwidth communication is economic and justified than costly advance high bandwidth communication.

Knowledge-based approach for planning healthy cities : the case of Logan-Beaudesert, Australia

Introduction - The planning for healthy cities faces significant challenges due to lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges for planning healthy cities have been magnified by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and knowledge-based decisions. Some studies have suggested that the use of a ‘knowledge-based’ approach to planning will enhance the accuracy and quality decision-making by improving the availability of data and information for health service planners and may also lead to increased collaboration between stakeholders and the community. A knowledge-based or evidence-based approach to decision-making can provide an ‘out-of-the-box’ thinking through the use of technology during decision-making processes. Minimal research has been conducted in this area to date, especially in terms of evaluating the impact of adopting knowledge-based approach on stakeholders, policy-makers and decision-makers within health planning initiatives. Purpose – The purpose of the paper is to present an integrated method that has been developed to facilitate a knowledge-based decision-making process to assist health planning Methodology – Specifically, the paper describes the participatory process that has been adopted to develop an online Geographic Information System (GIS)-based Decision Support System (DSS) for health planners. Value – Conceptually, it is an application of Healthy Cities and Knowledge Cities approaches which are linked together. Specifically, it is a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This setting-based initiative is named as the Logan-Beaudesert Health Coalition (LBHC). Practical implications - The paper outlines the application of a knowledge-based approach to the development of a healthy city. Also, it focuses on the need for widespread use of this approach as a tool for enhancing community-based health coalition decision making processes.

An environmental assessment model for knowledge-based urban development

Purpose – In recent years, knowledge-based urban development (KBUD) has introduced as a new strategic development approach for the regeneration of industrial cities. It aims to create a knowledge city consists of planning strategies, IT networks and infrastructures that achieved through supporting the continuous creation, sharing, evaluation, renewal and update of knowledge. Improving urban amenities and ecosystem services by creating sustainable urban environment is one of the fundamental components for KBUD. In this context, environmental assessment plays an important role in adjusting urban environment and economic development towards a sustainable way. The purpose of this paper is to present the role of assessment tools for environmental decision making process of knowledge cities. Design/methodology/approach – The paper proposes a new assessment tool to figure a template of a decision support system which will enable to evaluate the possible environmental impacts in an existing and future urban context. The paper presents the methodology of the proposed model named ‘ASSURE’ which consists of four main phases. Originality/value –The proposed model provides a useful guidance to evaluate the urban development and its environmental impacts to achieve sustainable knowledge-based urban futures. Practical implications – The proposed model will be an innovative approach to provide the resilience and function of urban natural systems secure against the environmental changes while maintaining the economic development of cities.

GIS-based mapping and statistical analysis of air pollution and mortality in Brisbane, Australia

In this thesis, the relationship between air pollution and human health has been investigated utilising Geographic Information System (GIS) as an analysis tool. The research focused on how vehicular air pollution affects human health. The main objective of this study was to analyse the spatial variability of pollutants, taking Brisbane City in Australia as a case study, by the identification of the areas of high concentration of air pollutants and their relationship with the numbers of death caused by air pollutants. A correlation test was performed to establish the relationship between air pollution, number of deaths from respiratory disease, and total distance travelled by road vehicles in Brisbane. GIS was utilized to investigate the spatial distribution of the air pollutants. The main finding of this research is the comparison between spatial and non-spatial analysis approaches, which indicated that correlation analysis and simple buffer analysis of GIS using the average levels of air pollutants from a single monitoring station or by group of few monitoring stations is a relatively simple method for assessing the health effects of air pollution. There was a significant positive correlation between variable under consideration, and the research shows a decreasing trend of concentration of nitrogen dioxide at the Eagle Farm and Springwood sites and an increasing trend at CBD site. Statistical analysis shows that there exists a positive relationship between the level of emission and number of deaths, though the impact is not uniform as certain sections of the population are more vulnerable to exposure. Further statistical tests found that the elderly people of over 75 years age and children between 0-15 years of age are the more vulnerable people exposed to air pollution. A non-spatial approach alone may be insufficient for an appropriate evaluation of the impact of air pollutant variables and their inter-relationships. It is important to evaluate the spatial features of air pollutants before modeling the air pollution-health relationships.

Probability based data analysis for road asset management

Road agencies require comprehensive, relevan and quality data describing their road assets to support their investment decisions. An investment decision support system for raod maintenance and rehabilitation mainly comprise three important supporting elements namely: road asset data, decision support tools and criteria for decision-making. Probability-based methods have played a crucial role in helping decision makers understand the relationship among road related data, asset performance and uncertainties in estimating budgets/costs for road management investment. This paper presents applications of the probability-bsed method for road asset management.

Testing a belief-based intervention encouraging sun safety among adolescents in a high risk area

Objective. To provide a preliminary test of a Theory of Planned Behavior (TPB) belief-based intervention to increase adolescents’ sun protective behaviors in a high risk area, Queensland, Australia. Methods. In the period of October-November, 2007 and May-June, 2008, 80 adolescents (14.53 ± 0.69 years) were recruited from two secondary schools (one government and one private) in Queensland after obtaining student, parental, and school informed consent. Adolescents were allocated to either a control or intervention condition based on the class they attended. The intervention comprised three, one hour in-school sessions facilitated by Cancer Council Queensland employees with sessions covering the belief basis of the TPB (i.e., behavioral, normative, and control [barrier and motivator] sun-safe beliefs). Participants completed questionnaires assessing sun-safety beliefs, intentions, and behavior pre- and post-intervention. Repeated Measures Multivariate Analysis of Variance was used to test the effect of the intervention across time on these constructs. Results. Students completing the intervention reported stronger sun-safe normative and motivator beliefs and intentions and the performance of more sun-safe behaviors across time than those in the control condition. Conclusion. Strengthening beliefs about the approval of others and motivators for sun protection may encourage sun-safe cognitions and actions among adolescents.

Speech recognition using ad-hoc microphone arrays

While close talking microphones give the best signal quality and produce the highest accuracy from current Automatic Speech Recognition (ASR) systems, the speech signal enhanced by microphone array has been shown to be an effective alternative in a noisy environment. The use of microphone arrays in contrast to close talking microphones alleviates the feeling of discomfort and distraction to the user. For this reason, microphone arrays are popular and have been used in a wide range of applications such as teleconferencing, hearing aids, speaker tracking, and as the front-end to speech recognition systems. With advances in sensor and sensor network technology, there is considerable potential for applications that employ ad-hoc networks of microphone-equipped devices collaboratively as a virtual microphone array. By allowing such devices to be distributed throughout the users’ environment, the microphone positions are no longer constrained to traditional fixed geometrical arrangements. This flexibility in the means of data acquisition allows different audio scenes to be captured to give a complete picture of the working environment. In such ad-hoc deployment of microphone sensors, however, the lack of information about the location of devices and active speakers poses technical challenges for array signal processing algorithms which must be addressed to allow deployment in real-world applications. While not an ad-hoc sensor network, conditions approaching this have in effect been imposed in recent National Institute of Standards and Technology (NIST) ASR evaluations on distant microphone recordings of meetings. The NIST evaluation data comes from multiple sites, each with different and often loosely specified distant microphone configurations. This research investigates how microphone array methods can be applied for ad-hoc microphone arrays. A particular focus is on devising methods that are robust to unknown microphone placements in order to improve the overall speech quality and recognition performance provided by the beamforming algorithms. In ad-hoc situations, microphone positions and likely source locations are not known and beamforming must be achieved blindly. There are two general approaches that can be employed to blindly estimate the steering vector for beamforming. The first is direct estimation without regard to the microphone and source locations. An alternative approach is instead to first determine the unknown microphone positions through array calibration methods and then to use the traditional geometrical formulation for the steering vector. Following these two major approaches investigated in this thesis, a novel clustered approach which includes clustering the microphones and selecting the clusters based on their proximity to the speaker is proposed. Novel experiments are conducted to demonstrate that the proposed method to automatically select clusters of microphones (ie, a subarray), closely located both to each other and to the desired speech source, may in fact provide a more robust speech enhancement and recognition than the full array could.

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.