Topic dependent language modelling for spoken term detection

This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.

Phonetic spoken term search using topic information

The aim of spoken term detection (STD) is to find all occurrences of a specified query term in a large audio database. This process is usually divided into two steps: indexing and search. In a previous study, it was shown that knowing the topic of an audio document would help to improve the accuracy of indexing step which results in a better performance for STD system. In this paper, we propose the use of topic information not only in the indexing step, but also in the search step. Results of our experiments show that topic information could also be used in search step to improve the STD accuracy.

A Study of feature extraction algorithms for optical flow tracking

Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

Reduced resting skeletal muscle protein synthesis is rescued by resistance exercise and protein ingestion following short-term energy deficit

The myofibrillar protein synthesis (MPS) response to resistance exercise (REX) and protein ingestion during energy deficit (ED) is unknown. We determined, in young men (n=8) and women (n=7), protein signaling, resting post-absorptive MPS during energy balance [EB: 45 kcal∙(kg FFM∙d)-1] and after 5d of ED [30 kcal∙(kg FFM∙d)-1] as well as MPS while in ED after acute REX in the fasted state and with the ingestion of whey protein (15 and 30 g). Post-absorptive rates of MPS were 27% lower in ED than EB (P<0.001), but REX stimulated MPS to rates equal to EB. Ingestion of 15 and 30 g of protein after REX in ED increased MPS ~16 and ~34% above resting EB, (P<0.02). p70 S6Kthr389 phosphorylation increased above EB only with combined exercise and protein intake (~2-7 fold; P<0.05). In conclusion, short-term ED reduces post-absorptive MPS, however, a bout of REX in ED restores MPS to values observed at rest in EB. The ingestion of protein after REX further increases MPS above resting EB in a dose-dependent manner. We conclude that combining REX with increased protein availability after exercise enhances rates of skeletal muscle protein synthesis during short term ED and could, in the long term, preserve muscle mass.

An iterative speaker re-diarization scheme for improving speaker-based entity extraction in multimedia archives

In this paper we present a novel scheme for improving speaker diarization by making use of repeating speakers across multiple recordings within a large corpus. We call this technique speaker re-diarization and demonstrate that it is possible to reuse the initial speaker-linked diarization outputs to boost diarization accuracy within individual recordings. We first propose and evaluate two novel re-diarization techniques. We demonstrate their complementary characteristics and fuse the two techniques to successfully conduct speaker re-diarization across the SAIVT-BNEWS corpus of Australian broadcast data. This corpus contains recurring speakers in various independent recordings that need to be linked across the dataset. We show that our speaker re-diarization approach can provide a relative improvement of 23% in diarization error rate (DER), over the original diarization results, as well as improve the estimated number of speakers and the cluster purity and coverage metrics.

Effect of temperature and moisture on high pressure lipid/oil extraction from microalgae

Commercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 ºC, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 ºC. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values.

Assessment of Geogenic Contaminants in Water Co-Produced with Coal Seam Gas Extraction in Queensland, Australia : Implications for Human Health Risk

Organic compounds in Australian coal seam gas produced water (CSG water) are poorly understood despite their environmental contamination potential. In this study, the presence of some organic substances is identified from government-held CSG water-quality data from the Bowen and Surat Basins, Queensland. These records revealed the presence of polycyclic aromatic hydrocarbons (PAHs) in 27% of samples of CSG water from the Walloon Coal Measures at concentrations <1 µg/L, and it is likely these compounds leached from in situ coals. PAHs identified from wells include naphthalene, phenanthrene, chrysene and dibenz[a,h]anthracene. In addition, the likelihood of coal-derived organic compounds leaching to groundwater is assessed by undertaking toxicity leaching experiments using coal rank and water chemistry as variables. These tests suggest higher molecular weight PAHs (including benzo[a]pyrene) leach from higher rank coals, whereas lower molecular weight PAHs leach at greater concentrations from lower rank coal. Some of the identified organic compounds have carcinogenic or health risk potential, but they are unlikely to be acutely toxic at the observed concentrations which are almost negligible (largely due to the hydrophobicity of such compounds). Hence, this study will be useful to practitioners assessing CSG water related environmental and health risk.

Clinically-based automatic implant fitting for shape optimization of fracture fixation plates

Complex bone contour and anatomical variations between individual bones complicate the process of deriving an implant shape that fits majority of the population. This thesis proposes an automatic fitting method for anatomically-precontoured plates based on clinical requirements, and investigated if 100% anatomical fit for a group of bone is achievable through manual bending of one plate shape. It was found that, for the plate used, 100% fit is impossible to achieve through manual bending alone. Rather, newly-developed shapes are also required to obtain anatomical fit in areas with more complex bone contour.

Fischer rats consume 20% ethanol in a long-term intermittent-access two-bottle-choice paradigm

The 20% ethanol intermittent-access (IAE) two-bottle-choice drinking procedure has been shown to produce high voluntary ethanol consumption in a number of rat strains. For this study, we applied this procedure to male Fischer (F344) rats, a strain previously reported to exhibit low levels of ethanol consumption. We also subjected these animals to a two-week ethanoldeprivation- period to see if they would exhibit an alcohol deprivation effect (ADE) signified by a transient increase in alcohol consumption following deprivation. Our data show a separation between high and low consuming animals within this strain, with high-consumers exhibiting an escalation in consumption. In contrast, Fischer rats did not show a significant separation between high and low consumers or any significant escalation in consumption, using the 20% ethanol continuous-access two-bottle-choice drinking protocol. Following the two-week deprivation period, animals in the high (but not the low) IAE group exhibited the transient increase in ethanol consumption and preference typically associated with an ADE. Together, the data suggest that the intermittent access protocol is a useful protocol for increasing ethanol consumption.

Influence of polymorphisms of GSTM1 and GSTT1 for risk of renal cell cancer in workers with long-term high occupational exposure to trichloroethene

Suspected nephrocarcinogenic effects of trichloroethene (TRI) in humans are attributed to metabolites derived from the glutathione transferase (GST) pathway. The influence of polymorphisms of GSTM1 and GSTT1 isoenzymes on the risk of renal cell cancer in subjects having been exposed to high levels of TRI over many years was investigated. GSTM1 and GSTT1 genotypes were determined by internal standard controlled polymerase chain reaction. Fourty-five cases with histologically verified renal cell cancer and a history of long-term occupational exposure to high concentrations of TRI were studied. A reference group consisted of 48 workers from the same geographical region with similar histories of occupational exposures to TRI but not suffering from any cancer. Among the 45 renal cell cancer patients, 27 carried at least one functional GSTM1 (GSTM1 +) and 18 at least one functional GSTT1 (GSTT1 +). Among the 48 reference workers, 17 were GSTM1 + and 31 were GSTT1 +. Odds ratios for renal cell cancer were 2.7 for GSTM1 + individuals (95% CI, 1.18-6.33; P < 0.02) and 4.2 for GSTT1 + individuals (95% CI, 1.16-14.91; P < 0.05), respectively. The data support the present concept of the nephrocarcinogenicity of TRI.

A convolutional neural network for automatic analysis of aerial imagery

This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.