Asset specificity and behavioural uncertainty as moderators of the sales growth : employment growth relationship in emerging ventures

Sales growth and employment growth are the two most widely used growth indicators for new ventures; yet, sales growth and employment growth are not interchangeable measures of new venture growth. Rather, they are related, but somewhat independent constructs that respond differently to a variety of criteria. Most of the literature treats this as a methodological technicality. However, sales growth with or without accompanying employment growth has very different implications for managers and policy makers. A better understanding of what drives these different growth metrics has the potential to lead to better decision making. To improve that understanding we apply transaction cost economics reasoning to predict when sales growth will be or will not be accompanied by employment growth. Our results indicate that our predictions are borne out consistently in resource-constrained contexts but not in resource-munificent contexts.

Investment decision-making under risk (reliability) and uncertainty for infrastructure asset management

Risks and uncertainties are inevitable in engineering projects and infrastructure investments. Decisions about investment in infrastructure such as for maintenance, rehabilitation and construction works can pose risks, and may generate significant impacts on social, cultural, environmental and other related issues. This report presents the results of a literature review of current practice in identifying, quantifying and managing risks and predicting impacts as part of the planning and assessment process for infrastructure investment proposals. In assessing proposals for investment in infrastructure, it is necessary to consider social, cultural and environmental risks and impacts to the overall community, as well as financial risks to the investor. The report defines and explains the concept of risk and uncertainty, and describes the three main methodology approaches to the analysis of risk and uncertainty in investment planning for infrastructure, viz examining a range of scenarios or options, sensitivity analysis, and a statistical probability approach, listed here in order of increasing merit and complexity. Forecasts of costs, benefits and community impacts of infrastructure are recognised as central aspects of developing and assessing investment proposals. Increasingly complex modelling techniques are being used for investment evaluation. The literature review identified forecasting errors as the major cause of risk. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. For risks that cannot be readily quantified, assessment techniques commonly include classification or rating systems for likelihood and consequence. The report outlines the system used by the Australian Defence Organisation and in the Australian Standard on risk management. After each risk is identified and quantified or rated, consideration can be given to reducing the risk, and managing any remaining risk as part of the scope of the project. The literature review identified use of risk mapping techniques by a North American chemical company and by the Australian Defence Organisation. This literature review has enabled a risk assessment strategy to be developed, and will underpin an examination of the feasibility of developing a risk assessment capability using a probability approach.

Framework for investment decision-making under risk and uncertainty for infrastructure asset management

A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.

Uncertainty avoidance: public sector clients and procurement selection

Purpose: Choosing the appropriate procurement system for construction projects is a complex and challenging task for clients particularly when professional advice has not been sought. To assist with the decision making process, a range of procurement selection tools and techniques have been developed by both academic and industry bodies. Public sector clients in Western Australia (WA) remain uncertain about the pairing of procurement method to bespoke construction project and how this decision will ultimately impact upon project success. This paper examines ‘how and why’ a public sector agency selected particular procurement methods. · Methodology/Approach: An analysis of two focus group workshops (with 18 senior project and policy managers involved with procurement selection) is reported upon · Findings: The traditional lump sum (TLS) method is still the preferred procurement path even though alternative forms such as design and construct, public-private-partnerships could optimize the project outcome. Paradoxically, workshop participants agreed that alternative procurement forms should be considered, but an embedded culture of uncertainty avoidance invariably meant that TLS methods were selected. Senior managers felt that only a limited number of contractors have the resources and experience to deliver projects using the nontraditional methods considered. · Research limitations/implications: The research identifies a need to develop a framework that public sector clients can use to select an appropriate procurement method. A procurement framework should be able to guide the decision-maker rather than provide a prescriptive solution. Learning from previous experiences with regard to procurement selection will further provide public sector clients with knowledge about how to best deliver their projects.

A forward and backward secure key management in wireless sensor networks for PCS/SCADA

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Visualisation of Information Uncertainty : Progress and Challenges

Information uncertainty which is inherent in many real world applications brings more complexity to the visualisation problem. Despite the increasing number of research papers found in the literature, much more work is needed. The aims of this chapter are threefold: (1) to provide a comprehensive analysis of the requirements of visualisation of information uncertainty and their dimensions of complexity; (2) to review and assess current progress; and (3) to discuss remaining research challenges. We focus on four areas: information uncertainty modelling, visualisation techniques, management of information uncertainty modelling, propagation and visualisation, and the uptake of uncertainty visualisation in application domains.

Bearing-only SLAM : a vision-based navigation system for autonomous robots

To navigate successfully in a previously unexplored environment, a mobile robot must be able to estimate the spatial relationships of the objects of interest accurately. A Simultaneous Localization and Mapping (SLAM) sys- tem employs its sensors to build incrementally a map of its surroundings and to localize itself in the map simultaneously. The aim of this research project is to develop a SLAM system suitable for self propelled household lawnmowers. The proposed bearing-only SLAM system requires only an omnidirec- tional camera and some inexpensive landmarks. The main advantage of an omnidirectional camera is the panoramic view of all the landmarks in the scene. Placing landmarks in a lawn field to define the working domain is much easier and more flexible than installing the perimeter wire required by existing autonomous lawnmowers. The common approach of existing bearing-only SLAM methods relies on a motion model for predicting the robot’s pose and a sensor model for updating the pose. In the motion model, the error on the estimates of object positions is cumulated due mainly to the wheel slippage. Quantifying accu- rately the uncertainty of object positions is a fundamental requirement. In bearing-only SLAM, the Probability Density Function (PDF) of landmark position should be uniform along the observed bearing. Existing methods that approximate the PDF with a Gaussian estimation do not satisfy this uniformity requirement. This thesis introduces both geometric and proba- bilistic methods to address the above problems. The main novel contribu- tions of this thesis are: 1. A bearing-only SLAM method not requiring odometry. The proposed method relies solely on the sensor model (landmark bearings only) without relying on the motion model (odometry). The uncertainty of the estimated landmark positions depends on the vision error only, instead of the combination of both odometry and vision errors. 2. The transformation of the spatial uncertainty of objects. This thesis introduces a novel method for translating the spatial un- certainty of objects estimated from a moving frame attached to the robot into the global frame attached to the static landmarks in the environment. 3. The characterization of an improved PDF for representing landmark position in bearing-only SLAM. The proposed PDF is expressed in polar coordinates, and the marginal probability on range is constrained to be uniform. Compared to the PDF estimated from a mixture of Gaussians, the PDF developed here has far fewer parameters and can be easily adopted in a probabilistic framework, such as a particle filtering system. The main advantages of our proposed bearing-only SLAM system are its lower production cost and flexibility of use. The proposed system can be adopted in other domestic robots as well, such as vacuum cleaners or robotic toys when terrain is essentially 2D.

Uncertainty budget in the measurement of typical airborne number, surface area and mass particle distributions

The effects of particulate matter on environment and public health have been widely studied in recent years. A number of studies in the medical field have tried to identify the specific effect on human health of particulate exposure, but agreement amongst these studies on the relative importance of the particles’ size and its origin with respect to health effects is still lacking. Nevertheless, air quality standards are moving, as the epidemiological attention, towards greater focus on the smaller particles. Current air quality standards only regulate the mass of particulate matter less than 10 μm in aerodynamic diameter (PM10) and less than 2.5 μm (PM2.5). The most reliable method used in measuring Total Suspended Particles (TSP), PM10, PM2.5 and PM1 is the gravimetric method since it directly measures PM concentration, guaranteeing an effective traceability to international standards. This technique however, neglects the possibility to correlate short term intra-day variations of atmospheric parameters that can influence ambient particle concentration and size distribution (emission strengths of particle sources, temperature, relative humidity, wind direction and speed and mixing height) as well as human activity patterns that may also vary over time periods considerably shorter than 24 hours. A continuous method to measure the number size distribution and total number concentration in the range 0.014 – 20 μm is the tandem system constituted by a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). In this paper, an uncertainty budget model of the measurement of airborne particle number, surface area and mass size distributions is proposed and applied for several typical aerosol size distributions. The estimation of such an uncertainty budget presents several difficulties due to i) the complexity of the measurement chain, ii) the fact that SMPS and APS can properly guarantee the traceability to the International System of Measurements only in terms of number concentration. In fact, the surface area and mass concentration must be estimated on the basis of separately determined average density and particle morphology. Keywords: SMPS-APS tandem system, gravimetric reference method, uncertainty budget, ultrafine particles.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.

Evolutionary optimisation methods with uncertainty for modern multidisciplinary design in aeronautical engineering

One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.

Cost effectiveness of antimicrobial catheters in the intensive care unit : Addressing uncertainty in the decision

Introduction: Some types of antimicrobial-coated central venous catheters (A-CVC) have been shown to be cost-effective in preventing catheter-related bloodstream infection (CR-BSI). However, not all types have been evaluated, and there are concerns over the quality and usefulness of these earlier studies. There is uncertainty amongst clinicians over which, if any, antimicrobial-coated central venous catheters to use. We re-evaluated the cost-effectiveness of all commercially available antimicrobialcoated central venous catheters for prevention of catheter-related bloodstream infection in adult intensive care unit (ICU) patients. Methods: We used a Markov decision model to compare the cost-effectiveness of antimicrobial-coated central venous catheters relative to uncoated catheters. Four catheter types were evaluated; minocycline and rifampicin (MR)-coated catheters; silver, platinum and carbon (SPC)-impregnated catheters; and two chlorhexidine and silver sulfadiazine-coated catheters, one coated on the external surface (CH/SSD (ext)) and the other coated on both surfaces (CH/SSD (int/ext)). The incremental cost per qualityadjusted life-year gained and the expected net monetary benefits were estimated for each. Uncertainty arising from data estimates, data quality and heterogeneity was explored in sensitivity analyses. Results: The baseline analysis, with no consideration of uncertainty, indicated all four types of antimicrobial-coated central venous catheters were cost-saving relative to uncoated catheters. Minocycline and rifampicin-coated catheters prevented 15 infections per 1,000 catheters and generated the greatest health benefits, 1.6 quality-adjusted life-years, and cost-savings, AUD $130,289. After considering uncertainty in the current evidence, the minocycline and rifampicin-coated catheters returned the highest incremental monetary net benefits of $948 per catheter; but there was a 62% probability of error in this conclusion. Although the minocycline and rifampicin-coated catheters had the highest monetary net benefits across multiple scenarios, the decision was always associated with high uncertainty. Conclusions: Current evidence suggests that the cost-effectiveness of using antimicrobial-coated central venous catheters within the ICU is highly uncertain. Policies to prevent catheter-related bloodstream infection amongst ICU patients should consider the cost-effectiveness of competing interventions in the light of this uncertainty. Decision makers would do well to consider the current gaps in knowledge and the complexity of producing good quality evidence in this area.