Hardware Acceleration of Background Modeling in the Compressed Domain

In intelligent video surveillance systems, scalability (of the number of simultaneous video streams) is important. Two key factors which hinder scalability are the time spent in decompressing the input video streams, and the limited computational power of the processor. This paper demonstrates how a combination of algorithmic and hardware techniques can overcome these limitations, and significantly increase the number of simultaneous streams. The techniques used are processing in the compressed domain, and exploitation of the multicore and vector processing capability of modern processors. The paper presents a system which performs background modeling, using a Mixture of Gaussians approach. This is an important first step in the segmentation of moving targets. The paper explores the effects of reducing the number of coefficients in the compressed domain, in terms of throughput speed and quality of the background modeling. The speedups achieved by exploiting compressed domain processing, multicore and vector processing are explored individually. Experiments show that a combination of all these techniques can give a speedup of 170 times on a single CPU compared to a purely serial, spatial domain implementation, with a slight gain in quality.

A co-operative formation-based collision avoidance approach for a group of autonomous vehicles (Special Issue on Adaptive Control and Signal Processing in Marine System)

This paper employs a unique decentralised cooperative control method to realise a formation-based collision avoidance strategy for a group of autonomous vehicles. In this approach, the vehicles' role in the formation and their alert and danger areas are first defined, and the formation-based intra-group and external collision avoidance methods are then proposed to translate the collision avoidance problem into the formation stability problem. The extension–decomposition–aggregation formation control method is next employed to stabilise the original and modified formations, whilst manoeuvring, and subsequently solve their collision avoidance problem indirectly. Simulation study verifies the feasibility and effectiveness of the intra-group and external collision avoidance strategy. It is demonstrated that both formation control and collision avoidance problems can be simultaneously solved if the stability of the expanded formation including external obstacles can be satisfied.

Information processing in the transcriptional regulatory network of yeast: Functional robustness

Background: Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism.

Echolocation signal structure in the Megachiropteran bat Rousettus aegyptiacus Geoffroy 1810

Rousettus aegyptiacus Geoffroy 1810 is a member of the only genus of Megachiropteran bats to use vocal echolocation, but the structure of its brief, click-like signal is poorly described. Although thought to have a simple echolocation system compared to that of Microchiroptera, R. aegyptiacus is capable of good obstacle avoidance using its impulse sonar. The energy content of the signal was at least an order of magnitude smaller than in Microchiropteran bats and dolphins (approximately 4 X 10(-8) J m(-2)). Measurement of the duration, amplitude and peak frequency demonstrate that the signals of this animal are broadly similar in structure and duration to those of dolphins. Gabor functions were used to model signals and to estimate signal parameters, and the quality of the Gabor function fit to the early part of the signal demonstrates that the echolocation signals of R. aegyptiacus match the minimum spectral spread for their duration and amplitude and are thus well matched to its best hearing sensitivity. However, the low energy content of the signals and short duration should make returning echoes difficult to detect. The performance of R. aegyptincus in obstacle avoidance experiments using echolocation therefore remains something of a conundrum.

Speed of processing in the primary motor cortex: A continuous theta burst stimulation study

‘Temporally urgent’ reactions are extremely rapid, spatially precise movements that are evoked following discrete stimuli. The involvement of primary motor cortex (M1) and its relationship to stimulus intensity in such reactions is not well understood. Continuous theta burst stimulation (cTBS) suppresses focal regions of the cortex and can assess the involvement of motor cortex in speed of processing. The primary objective of this study was to explore the involvement of M1 in speed of processing with respect to stimulus intensity. Thirteen healthy young adults participated in this experiment. Behavioral testing consisted of a simple button press using the index finger following median nerve stimulation of the opposite limb, at either high or low stimulus intensity. Reaction time was measured by the onset of electromyographic activity from the first dorsal interosseous (FDI) muscle of each limb. Participants completed a 30 min bout of behavioral testing prior to, and 15 min following, the delivery of cTBS to the motor cortical representation of the right FDI. The effect of cTBS on motor cortex was measured by recording the average of 30 motor evoked potentials (MEPs) just prior to, and 5 min following, cTBS. Paired t-tests revealed that, of thirteen participants, five demonstrated a significant attenuation, three demonstrated a significant facilitation and five demonstrated no significant change in MEP amplitude following cTBS. Of the group that demonstrated attenuated MEPs, there was a biologically significant interaction between stimulus intensity and effect of cTBS on reaction time and amplitude of muscle activation. This study demonstrates the variability of potential outcomes associated with the use of cTBS and further study on the mechanisms that underscore the methodology is required. Importantly, changes in motor cortical excitability may be an important determinant of speed of processing following high intensity stimulation.

A statistical framework for channel availability modelling in the polarisation domain

Cognitive radio has been proposed as a means of improving the spectrum utilisation and increasing spectrum efficiency of wireless systems. This can be achieved by allowing cognitive radio terminals to monitor their spectral environment and opportunistically access the unoccupied frequency channels. Due to the opportunistic nature of cognitive radio, the overall performance of such networks depends on the spectrum occupancy or availability patterns. Appropriate knowledge on channel availability can optimise the sensing performance in terms of spectrum and energy efficiency. This work proposes a statistical framework for the channel availability in the polarization domain. A Gaussian Normal approximation is used to model real-world occupancy data obtained through a measurement campaign in the cellular frequency bands within a realistic scenario.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Use of data dependence graphs in the design of bit-level systolic arrays

The use of bit-level systolic array circuits as building blocks in the construction of larger word-level systolic systems is investigated. It is shown that the overall structure and detailed timing of such systems may be derived quite simply using the dependence graph and cut-set procedure developed by S. Y. Kung (1988). This provides an attractive and intuitive approach to the bit-level design of many VLSI signal processing components. The technique can be applied to ripple-through and partly pipelined circuits as well as fully systolic designs. It therefore provides a means of examining the relative tradeoff between levels of pipelining, chip area, power consumption, and throughput rate within a given VLSI design.

Constant scale factor, on-line CORDIC algorithm in the circular coordinate system

Real time digital signal processing requires the development of high performance arithmetic algorithms suitable for VLSI design. In this paper, a new online, circular coordinate system CORDIC algorithm is described, which has a constant scale factor. This algorithm was developed using a new Angular Representation (AR) model A radix 2 version of the CORDIC algorithm is presented, along with an architecture suitable for VLSI implementation.

Terminal nerve-derived neuropeptide Y modulates physiological responses in the olfactory epithelium of hungry axolotls (Ambystoma mexicanum).

The vertebrate brain actively regulates incoming sensory information, effectively filtering input and focusing attention toward environmental stimuli that are most relevant to the animal's behavioral context or physiological state. Such centrifugal modulation has been shown to play an important role in processing in the retina and cochlea, but has received relatively little attention in olfaction. The terminal nerve, a cranial nerve that extends underneath the lamina propria surrounding the olfactory epithelium, displays anatomical and neurochemical characteristics that suggest that it modulates activity in the olfactory epithelium. Using immunocytochemical techniques, we demonstrate that neuropeptide Y (NPY) is abundantly present in the terminal nerve in the axolotl (Ambystoma mexicanum), an aquatic salamander. Because NPY plays an important role in regulating appetite and hunger in many vertebrates, we investigated the possibility that NPY modulates activity in the olfactory epithelium in relation to the animal's hunger level. We therefore characterized the full-length NPY gene from axolotls to enable synthesis of authentic axolotl NPY for use in electrophysiological experiments. We find that axolotl NPY modulates olfactory epithelial responses evoked by L-glutamic acid, a food-related odorant, but only in hungry animals. Similarly, whole-cell patch-clamp recordings demonstrate that bath application of axolotl NPY enhances the magnitude of a tetrodotoxin-sensitive inward current, but only in hungry animals. These results suggest that expression or activity of NPY receptors in the olfactory epithelium may change with hunger level, and that terminal nerve-derived peptides modulate activity in the olfactory epithelium in response to an animal's changing behavioral and physiological circumstances.

Hydraulic Subsurface Measurements and Hydrodynamic Modeling as Indicators for Groundwater Flow Systems in the Rotondo Granite, Central Alps (Switzerland)

Regional groundwater flow in high mountainous terrain is governed by a multitude of factors such as geology, topography, recharge conditions, structural elements such as fracturation and regional fault zones as well as man-made underground structures. By means of a numerical groundwater flow model, we consider the impact of deep underground tunnels and of an idealized major fault zone on the groundwater flow systems within the fractured Rotondo granite. The position of the free groundwater table as response to the above subsurface structures and, in particular, with regard to the influence of spatial distributed groundwater recharge rates is addressed. The model results show significant unsaturated zones below the mountain ridges in the study area with a thickness of up to several hundred metres. The subsurface galleries are shown to have a strong effect on the head distribution in the model domain, causing locally a reversal of natural head gradients. With respect to the position of the catchment areas to the tunnel and the corresponding type of recharge source for the tunnel inflows (i.e. glaciers or recent precipitation), as well as water table elevation, the influence of spatial distributed recharge rates is compared to uniform recharge rates. Water table elevations below the well exposed high-relief mountain ridges are observed to be more sensitive to changes in groundwater recharge rates and permeability than below ridges with less topographic relief. In the conceptual framework of the numerical simulations, the model fault zone has less influence on the groundwater table position, but more importantly acts as fast flow path for recharge from glaciated areas towards the subsurface galleries. This is in agreement with a previous study, where the imprint of glacial recharge was observed in the environmental isotope composition of groundwater sampled in the subsurface galleries. Copyright © 2012 John Wiley & Sons, Ltd.