Learned stochastic mobility prediction for planning with control uncertainty on unstructured terrain

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.

Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.

Impacts of introduced aquaculture species on markets for native marine aquaculture products : the case of edible oysters in Australia

Economic competition between introduced and native aquaculture species is of interest for industry stakeholders since increased production can affect price formation if both aquaculture species are part of the same market or even substitutes. In this study, we focus on the Australian edible oyster industry, which is dominated by two major species—the native Sydney rock oyster (grown mainly in Queensland and New South Wales) and the non-native Pacific oyster (grown mainly in South Australia and Tasmania). We examine the integration of the Australian oyster market to determine if there exists a single or several markets. Short- and long-run own, cross-price and income flexibilities of demand are estimated for both species using an inverse demand system of equations. The results suggest that the markets for the two species are integrated. We found evidence that the development of the Pacific oyster industry has had an adverse impact on Sydney rock oyster prices. However, our results show that both species are not perfect substitutes. Demand for Sydney rock oysters is relatively inelastic in the long run, yet no long-run relationships can be identified for Pacific oysters, reflecting the developing nature of this sector.

Stochastic output feedback model predictive control

This paper addresses the issue of output feedback model predictive control for linear systems with input constraints and stochastic disturbances. We show that the optimal policy uses the Kalman filter for state estimation, but the resultant state estimates are not utilized in a certainty equivalence control law

Do Big-Four affilitates earn audit fee premiums in emerging markets?

The paper investigates whether Big-Four affiliated (B4A) firms earn audit premiums in an emerging economy context, using Bangladesh as a case. The joint determination of audit and non-audit service fees is also examined using a sample of 122 companies listed in the Dhaka Stock Exchange. Our findings reveal that although the B4A firms do not generally earn a fee premiumin Bangladesh, they charge higher audit fees for clients not purchasing non-audit services. This suggests that the B4A firms may actually lower audit fees to attract non-audit services, and cross subsidizes audit fees through non-audit-services fees. The lack of a B4A premium implies that there is lack of quality audit in emerging markets. We also document that audit and non-audit service fees are jointly determined in Bangladesh. Thus, we provide evidence of joint determination of audit and non-audit service fees in an emerging economy context.

Cryptic marketing : strategic targeting of subculture markets

This research aims to understand what factors influence consumers' behaviour to subculture marketing and how companies can strategically overcome potential brand alienation. Findings validate cryptic marketing as a strategy for organizations to communicate effectively with their chosen market through the use of cryptic cues, symbols and messages while circumventing negative responses from non-target audiences. The thesis contributes to extending current understanding of marketing communication through the use of covert strategies, employing covert tactics on the non-target, wider market instead of the target, subculture market.

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study