A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Computational aspects of probabilistic assessment of UAS robust autonomy

As the level of autonomy in Unmanned Aircraft Systems (UAS) increases, there is an imperative need for developing methods to assess robust autonomy. This paper focuses on the computations that lead to a set of measures of robust autonomy. These measures are the probabilities that selected performance indices related to the mission requirements and airframe capabilities remain within regions of acceptable performance.

Tensor-based item recommendation using probabilistic ranking in social tagging systems

A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.

Building macroscale models from microscale probabilistic models : a general probabilistic approach for nonlinear diffusion and multispecies phenomena

A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

Exploring the effect of political risks in large infrastructure projects in politically unstable countries using a probabilistic modelling approach

This research aims to explore and identify political risks on a large infrastructure project in an exaggerated environment to ascertain whether sufficient objective information can be gathered by project managers to utilise risk modelling techniques. During the study, the author proposes a new definition of political risk; performs a detailed project study of the Neelum Jhelum Hydroelectric Project in Pakistan; implements a probabilistic model using the principle of decomposition and Bayes probabilistic theorem and answers the question: was it possible for project managers to obtain all the relevant objective data to implement a probabilistic model?

The effect of recording situation on the echolocation calls of the New Zealand Lesser short-tailed bat (Mystacina tuberculata Gray).

Using a broad‐band recording system (150 Hz‐100 kHz) the echolocation calls of the lesser short‐tailed bat (Mystacina tuberculata) were recorded under three very different situations: free‐flying, flying within a flight cage, and on release from the hand. Calls of bats landing and feeding on a platform in Wellington Zoo were also recorded. Both the lowest frequency and frequency of peak amplitude of calls were significantly affected by the situation under which calls were recorded. Although the calls of free‐flying bats are different from those produced by bats foraging on the ground, it is unlikely that M. tuberculata uses echolocation to locate prey on the ground. No significant differences could be found between the calls emitted by male and female bats, and no consistent relationships were obvious between temporal and spectral call characteristics. There was some evidence to suggest that individual bats could be identified by their echolocation calls.

Probabilistic power system contingency analysis considering wind

This thesis was a step forward in developing probabilistic assessment of power system response to faults subject to intermittent generation by renewable energy. It has investigated the wind power fluctuation effect on power system stability, and the developed fast estimation process has demonstrated the feasibility for real-time implementation. A better balance between power network security and efficiency can be achieved based on this research outcome.

Therapeutic options for metastatic castration resistant prostate cancer : has the situation improved?

Limited treatment options for Castration Resistant Prostate Cancer (CRPC) still remain a major challenge. Despite therapeutic advances, most patients with malignant PCa have a poor prognosis. Since the year 2000, we have rapidly expanded our understanding of the molecular mechanisms underlying CRPC and this has led to an unprecedented number of new drug approvals within a short span of time. Recently, four new agents namely Abiraterone Acetate, Enzalutamide, Cabazitaxel, and Radium-223 have been shown to be effective in the post-chemotherapy setting in CRPC. The continued dependency of CRPC on androgen synthesis has seen the development of a number of new anti-androgen therapies, with abiraterone acetate and Enzalutamide being the most promising discoveries. Immunotherapeutic approaches have also found their niche in PCa with Sipuleucel-T shown to be effective in minimally asymptomatic CRPC. Research focussed on bone-targeting therapies has witnessed the arrival of promising new drugs with Denosumab and Radium-223 displaying improved survival of patients with CRPC. This review briefly discusses the findings and limitations from ongoing and completed clinical trials of novel treatments and regimens. In addition, potential mechanisms of therapy resistance and future challenges are discussed.

From the bush to the burbs : a comparison of driver situation awareness at rural and urban railway level crossings

The problem of collisions between road users and trains at rail level crossings (RLXs) remains resistant to current countermeasures. One factor underpinning these collisions is poor Situation Awareness (SA) on behalf of the road user involved (i.e. not being aware of an approaching train). Although this is a potential threat at any RLX, the factors influencing SA may differ depending on whether the RLX is located in a rural or urban road environment. Despite this, there has been no empirical investigation regarding how road user SA might differ across distinct RLX environments. This knowledge is needed to establish the extent to which a uniform approach to RLX design and safety is acceptable. The aim of this paper is to investigate the differences in driver SA at rural versus urban RLXs. We present analyses of driver SA in both rural and urban RLX environments based on two recent on-road studies undertaken in Victoria, Melbourne. The findings demonstrate that driver SA is markedly different at rural and urban RLXs, and also that poor SA regarding approaching trains may be caused by different factors. The implications for RLX design and safety are discussed.

The effect of autonomy transparency in human-robot interactions : a preliminary study on operator cognitive workload and situation awareness in multiple heterogeneous UAV management

The autonomous capabilities in collaborative unmanned aircraft systems are growing rapidly. Without appropriate transparency, the effectiveness of the future multiple Unmanned Aerial Vehicle (UAV) management paradigm will be significantly limited by the human agent’s cognitive abilities; where the operator’s CognitiveWorkload (CW) and Situation Awareness (SA) will present as disproportionate. This proposes a challenge in evaluating the impact of robot autonomous capability feedback, allowing the human agent greater transparency into the robot’s autonomous status - in a supervisory role. This paper presents; the motivation, aim, related works, experiment theory, methodology, results and discussions, and the future work succeeding this preliminary study. The results in this paper illustrates that, with a greater transparency of a UAV’s autonomous capability, an overall improvement in the subjects’ cognitive abilities was evident, that is, with a confidence of 95%, the test subjects’ mean CW was demonstrated to have a statistically significant reduction, while their mean SA was demonstrated to have a significant increase.

Design of a tablet sized human-computer interface and its effect on situation awareness

Emergency Response Teams increasingly use interactive technology to help manage information and communications. The challenge is to maintain a high situation awareness for different interactive devices sizes. This research specifically compared a handheld interactive device in the form of an iPad with a large interactive multi-touch tabletop. A search and rescue inspired simulator was designed to test operator situation awareness for the two sized devices. The results show that operators had better situation awareness on the tabletop device when the operation related to detecting of moving targets, searching target locations, distinguishing target types, and comprehending displayed information.