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.

Experimental verification of the modified spring-mass theory of fiber Bragg grating accelerometers using transverse forces

A fiber Bragg grating (FBG) accelerometer using transverse forces is more sensitive than one using axial forces with the same mass of the inertial object, because a barely stretched FBG fixed at its two ends is much more sensitive to transverse forces than axial ones. The spring-mass theory, with the assumption that the axial force changes little during the vibration, cannot accurately predict its sensitivity and resonant frequency in the gravitational direction because the assumption does not hold due to the fact that the FBG is barely prestretched. It was modified but still required experimental verification due to the limitations in the original experiments, such as the (1) friction between the inertial object and shell; (2) errors involved in estimating the time-domain records; (3) limited data; and (4) large interval ∼5 Hz between the tested frequencies in the frequency-response experiments. The experiments presented here have verified the modified theory by overcoming those limitations. On the frequency responses, it is observed that the optimal condition for simultaneously achieving high sensitivity and resonant frequency is at the infinitesimal prestretch. On the sensitivity at the same frequency, the experimental sensitivities of the FBG accelerometer with a 5.71 gram inertial object at 6 Hz (1.29, 1.19, 0.88, 0.64, and 0.31 nm/g at the 0.03, 0.69, 1.41, 1.93, and 3.16 nm prestretches, respectively) agree with the static sensitivities predicted (1.25, 1.14, 0.83, 0.61, and 0.29 nm/g, correspondingly). On the resonant frequency, (1) its assumption that the resonant frequencies in the forced and free vibrations are similar is experimentally verified; (2) its dependence on the distance between the FBG’s fixed ends is examined, showing it to be independent; (3) the predictions of the spring-mass theory and modified theory are compared with the experimental results, showing that the modified theory predicts more accurately. The modified theory can be used more confidently in guiding its design by predicting its static sensitivity and resonant frequency, and may have applications in other fields for the scenario where the spring-mass theory fails.

Comparing skin biopsy with confocal microscopy : diagnostic yield of nerve fiber density

Background and aims: The assessment of intra-epidermal nerve fiber density (IENFD) in skin biopsies and corneal nerve fiber density (CNFD) using corneal confocal microscopy (CCM) provides promising techniques to detect small nerve fiber damage in patients with peripheral neuropathy. To help define the clinical utility of each of these techniques in patients with diabetic neuropathy we have assessed sensitivity and specificity of IENFD and CNFD in predicting the following: 1) diabetic polyneuropathy (DPN); 2) risk of foot ulceration (RFU); 3) initial small fiber neuropathy (iSFN); 4) severe small fiber neuropathy (sSFN)...

Detecting and Analyzing Linear Structures in Biomedical Images : A Case Study Using Corneal Nerve Fibers

Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.

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.

Damage evaluation based on a wave energy flow map using multiple PZT sensors

A new wave energy flow (WEF) map concept was proposed in this work. Based on it, an improved technique incorporating the laser scanning method and Betti’s reciprocal theorem was developed to evaluate the shape and size of damage as well as to realize visualization of wave propagation. In this technique, a simple signal processing algorithm was proposed to construct the WEF map when waves propagate through an inspection region, and multiple lead zirconate titanate (PZT) sensors were employed to improve inspection reliability. Various damages in aluminum and carbon fiber reinforced plastic laminated plates were experimentally and numerically evaluated to validate this technique. The results show that it can effectively evaluate the shape and size of damage from wave field variations around the damage in the WEF map.

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.