Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

A cognitive processing framework for learning analytics

Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.

Firmicutes dominate the bacterial taxa within sugar-cane processing plants

Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Significant variation (p , 0.05) in community structure occurred between samples collected from ‘floor dump sediment’, ‘cooling tower water’, and ‘bagasse leachate’. Many bacterial Classes contributed to these differences, however most were of low numerical abundance. Separation in community composition was also linked to Classes of Firmicutes, particularly Bacillales, Lactobacillales and Clostridiales, whose dominance is likely to be linked to their physiology as ‘lactic acid bacteria’, capable of fermenting the sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria.

Processing biases towards gain-framed messages may lead reward sensitive individuals to adopt safer driving behaviours

Using Gray and McNaughton’s revised RST, this study investigated the extent to which the Behavioural Approach System (BAS) and the Fight-Flight-Freeze System (FFFS) influence the processing of gain-framed and loss-framed road safety messages and subsequent message acceptance. It was predicted that stronger BAS sensitivity and FFFS sensitivity would be associated with greater processing and acceptance of the gain-framed messages and loss-framed messages, respectively. Young drivers (N = 80, aged 17–25 years) viewed one of four road safety messages and completed a lexical decision task to assess message processing. Both self-report (e.g., Corr-Cooper RST-PQ) and behavioural measures (i.e., CARROT and Q-Task) were used to assess BAS and FFFS traits. Message acceptance was measured via self-report ratings of message effectiveness, behavioural intentions, attitudes and subsequent driving behaviour. The results are discussed in the context of the effect that differences in reward and punishment sensitivities may have on message processing and message acceptance.

A Triple Bottom Line Planning Tool for Measuring Sustainability : A Systems Approach to Sustainability Using the Australian Dairy Industry as a Case Study

Sustainability is a key driver for decisions in the management and future development of organisations and industries. However, quantifying and comparing sustainability across the triple bottom line (TBL) of economy, environment and social impact, has been problematic. There is a need for a tool which can measure the complex interactions within and between the environmental, economic and social systems which affect the sustainability of an industry in a transparent, consistent and comparable way. The authors acknowledge that there are currently numerous ways in which sustainability is measured and multiple methodologies in how these measurement tools were designed. The purpose of this book is to showcase how Bayesian network modelling can be used to identify and measure environmental, economic and social sustainability variables and to understand their impact on and interaction with each other. This book introduces the Sustainability Scorecard, and describes it through a case study on sustainability of the Australian dairy industry. This study was conducted in collaboration with the Australian dairy industry.

Developmentally and transgene regulated nuclear processing of primary transcripts of chalcone synthase A in petunia

The introduction of chalcone synthase A transgenes into petunia plants can result in degradation of chalcone synthase A RNAs and loss of chalcone synthase, a process called cosuppression or post-transcriptional gene silencing. Here we show that the RNA degradation is associated with changes in premRNA processing, i.e. loss of tissue specificity in transcript cleavage patterns, accumulation of unspliced molecules, and use of template-specific secondary poly(A) sites. These changes can also be observed at a lower level in leaves but not flowers of nontransgenic petunias. Based on this, a model is presented of how transgenes may disturb the carefully evolved, developmentally controlled post-transcriptional regulation of chalcone synthase gene expression by influencing the survival rate of the endogenous and their own mRNA.

Calcium influx inhibits MT1-MMP processing and blocks MMP-2 activation

We have previously reported that concanavalin A (ConA)-induced MMP-2 activation involves both transcriptional and non-transcriptional mechanisms. Here we examined the effects of calcium influx on MT1-MMP expression and MMP-2 activation in MDA-MB-231 cells. The calcium ionophore ionomycin caused a dose-dependent inhibition of ConA-induced MMP-2 activation, but had no effect on MT1-MMP mRNA levels. However, Western analysis revealed an accumulation of pro-MT1-MMP (63 kDa), indicating that ionomycin blocked the conversion of pro-MT1-MMP protein to the active 60 kDa form. This suggests that increased calcium levels inhibit the processing of MT1-MMP. This finding may help to elucidate the mechanism(s) which regulates MT1-MMP activation.

Low-temperature plasma processing for Si photovoltaics

There has been a recent rapid expansion of the range of applications of low-temperature plasma processing in Si-based photovoltaic (PV) technologies. The desire to produce Si-based PV materials at an acceptable cost with consistent performance and reproducibility has stimulated a large number of major research and research infrastructure programs, and a rapidly increasing number of publications in the field of low-temperature plasma processing for Si photovoltaics. In this article, we introduce the low-temperature plasma sources for Si photovoltaic applications and discuss the effects of low-temperature plasma dissociation and deposition on the synthesis of Si-based thin films. We also examine the relevant growth mechanisms and plasma diagnostics, Si thin-film solar cells, Si heterojunction solar cells and silicon nitride materials for antireflection and surface passivation. Special attention is paid to the low-temperature plasma interactions with Si materials including hydrogen interaction, wafer cleaning, masked or mask-free surface texturization, the direct formation of p-n junction, and removal of phosphorus silicate glass or parasitic emitters. The chemical and physical interactions in such plasmas with Si surfaces are analyzed. Several examples of the plasma processes and techniques are selected to represent a variety of applications aimed at the improvement of Si-based solar cell performance. © 2014 Elsevier B.V.

Nanopore processing in dielectric materials and dielectric template-assisted nanoarray synthesis : using pulsed bias to enhance process throughput and precision

An effective technique to improve the precision and throughput of energetic ion condensation through dielectric nanoporous templates and reduce nanopore clogging by using finely tuned pulsed bias is proposed. Multiscale numerical simulations of ion deposition show the possibility of controlling the dynamic charge balance on the upper template's surface to minimize ion deposition on nanopore sidewalls and to deposit ions selectively on the substrate surface in contact with the pore opening. In this way, the shapes of nanodots in template-assisted nanoarray fabrication can be effectively controlled. The results are applicable to various processes involving porous dielectric nanomaterials and dense nanoarrays.

Self-assembled low-dimensional nanomaterials via low-temperature plasma processing

Examples of successful fabrication of low-dimensional semiconducting nanomaterials in the Integrated Plasma-Aided Nanofabrication Facility are shown. Self-assembled size-uniform ZnO nanoparticles, ultra-high-aspect ratio Si nanowires, vertically aligned cadmium sulfide nanostructures, and quarternary semiconducting SiCAlN nanomaterial have been synthesized using inductively coupled plasma-assisted RF magnetron sputtering deposition. The observed increase in crystallinity and growth rates of the nanostructures are explained by using a model of plasma-enhanced adatom surface diffusion under conditions of local energy exchange between the ion flux and the growth surface. Issues related to plasma-based growth of low-dimensional semiconducting nanomaterials are discussed as well. © 2007 Elsevier B.V. All rights reserved.

The role of the posterior superior temporal sulcus in audiovisual processing

In this study we investigate previous claims that a region in the left posterior superior temporal sulcus (pSTS) is more activated by audiovisual than unimodal processing. First, we compare audiovisual to visual-visual and auditory-auditory conceptual matching using auditory or visual object names that are paired with pictures of objects or their environmental sounds. Second, we compare congruent and incongruent audiovisual trials when presentation is simultaneous or sequential. Third, we compare audiovisual stimuli that are either verbal (auditory and visual words) or nonverbal (pictures of objects and their associated sounds). The results demonstrate that, when task, attention, and stimuli are controlled, pSTS activation for audiovisual conceptual matching is 1) identical to that observed for intramodal conceptual matching, 2) greater for incongruent than congruent trials when auditory and visual stimuli are simultaneously presented, and 3) identical for verbal and nonverbal stimuli. These results are not consistent with previous claims that pSTS activation reflects the active formation of an integrated audiovisual representation. After a discussion of the stimulus and task factors that modulate activation, we conclude that, when stimulus input, task, and attention are controlled, pSTS is part of a distributed set of regions involved in conceptual matching, irrespective of whether the stimuli are audiovisual, auditory-auditory or visual-visual.

Dissociating verbal and nonverbal audiovisual object processing

This fMRI study investigates how audiovisual integration differs for verbal stimuli that can be matched at a phonological level and nonverbal stimuli that can be matched at a semantic level. Subjects were presented simultaneously with one visual and one auditory stimulus and were instructed to decide whether these stimuli referred to the same object or not. Verbal stimuli were simultaneously presented spoken and written object names, and nonverbal stimuli were photographs of objects simultaneously presented with naturally occurring object sounds. Stimulus differences were controlled by including two further conditions that paired photographs of objects with spoken words and object sounds with written words. Verbal matching, relative to all other conditions, increased activation in a region of the left superior temporal sulcus that has previously been associated with phonological processing. Nonverbal matching, relative to all other conditions, increased activation in a right fusiform region that has previously been associated with structural and conceptual object processing. Thus, we demonstrate how brain activation for audiovisual integration depends on the verbal content of the stimuli, even when stimulus and task processing differences are controlled.