Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views

This paper presents a long-term experiment where a mobile robot uses adaptive spherical views to localize itself and navigate inside a non-stationary office environment. The office contains seven members of staff and experiences a continuous change in its appearance over time due to their daily activities. The experiment runs as an episodic navigation task in the office over a period of eight weeks. The spherical views are stored in the nodes of a pose graph and they are updated in response to the changes in the environment. The updating mechanism is inspired by the concepts of long- and short-term memories. The experimental evaluation is done using three performance metrics which evaluate the quality of both the adaptive spherical views and the navigation over time.

Prevalence of risk factors for undiagnosed obstructive sleep apnoea is high in truck drivers on UK roads

Objectives To determine the prevalence of symptoms and risk factors of obstructive sleep apnoea (OSA) in truck drivers at a UK large truck stop. Methods Over a 5 day period, truck drivers completed a short questionnaire at a major UK ‘truck stop’. The questionnaire asked about OSA rist factors and symptoms, and included the Epworth Sleepiness Scale (ESS). Additionally, measurements of height, weight and collar size were taken. 148 truck drivers participated and within this random group the risk factors of OSA that were looked for were:men age over 40 y, obesity, parge neck circumference, smoking, high ESS and bed partner reporting snoring with witnessed apnoeas. Results Our sample were all men, with 82% aged over 40 y. 47% were obese (compared with 23% for UK men in general) and average neck circumference was 42 cm (compared with 38 cm for UK men in general – Martin et al 1997). 31% smoked (vs 21% for general population), and ESS averaged 2.1 points higher than expected for a healthy population (Johns et al 1997). Snoring was quite evident at 57% (compared wth 40% for men in general) and witnessed apnoeas were almost double (7%) compared with 3.8% given by Ohayon et al (1997) generally for men. Conclusion 8 key symptoms and risk factors of OSA have been found to be prevalent in a sample of truck drivers on UK roads, and to greater extent that for estimates in the general male population. Bed partners of truck drivers reporting witnessed apnoeas strongly suggests this group has a high potential for undiagnosed OSA. OSA sufferers are known to be at high risk of causing road traffi c accidents. This, together with the large size of trucks, then the potential for serious road crashes is great. Truck drivers, especially those who are obese, ought to be a high priority population for OSA screening.

Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques

This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

Spatiotemporal patterns of Aedes aegyptipopulations in Cairns, Australia : assessing drivers of dengue transmission

OBJECTIVES To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia. METHODS Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns. RESULTS Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach. CONCLUSION Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.