Scene invariant crowd counting

This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd counting across a wide range of environments. The use of local features allows the proposed algorithm to calculate local occupancy statistics, and Gaussian process regression is used to scale to conditions which are unseen in the training data, also providing confidence intervals for the crowd size estimate. A new crowd counting database is introduced to the computer vision community to enable a wider evaluation over multiple scenes, and the proposed algorithm is tested on seven datasets to demonstrate scene invariance and high accuracy. To the authors' knowledge this is the first system of its kind due to its ability to scale between different scenes and viewpoints.

A visual description of early-number counting, addition and subtraction knowledge

Early-number is a rich fabric of interconnected ideas that is often misunderstood and thus taught in ways that do not lead to rich understanding. In this presentation, a visual language is used to describe the organisation of this domain of knowledge. This visual language is based upon Piaget’s notion of reflective abstraction (Dubinsky, 1991; Piaget, 1977/2001), and thus captures the epistemological associations that link the problems, concepts and representations of the domain. The constructs of this visual language are introduced and then applied to the early-number domain. The introduction to this visual language may prompt reflection upon its suitability and significance to the description of other domains of knowledge. Through such a process of analysis and description, the visual language may serve as a scaffold for enhancing pedagogical content knowledge and thus ultimately improve learning outcomes.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

A small molecule that walks non-directionally along a track without external intervention

Charge of the light brigade: A molecule is able to walk back and forth upon a five-foothold pentaethylenimine track without external intervention. The 1D random walk is highly processive (mean step number 530) and exchange takes place between adjacent amine groups in a stepwise fashion. The walker performs a simple task whilst walking: quenching of the fluorescence of an anthracene group sited at one end of the track. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The magic of numbers and the amazing disappearing act : the politics of counting youth homelessness

No-one wants to see young people who are no longer able to stay at home with their parents living in situations that are neither stable nor safe. Most Australians also appreciate that youth homelessness is typically a result of factors beyond the control of young people like poverty, lack of affordable housing, parental divorce or separation, family conflict and violence, sexual abuse, or mental health problems.1 Since the Burdekin Report of 1989 first put the issue on the national agenda, youth homelessness has been a point of some political sensitivity as the numbers of young homeless stayed stubbornly high through the 1990s and into the 2000s.

Increased charge transfer of Poly (ethylene oxide) based electrolyte by addition of small molecule and its application in dye-sensitized solar cells

A Poly (ethylene oxide) based polymer electrolyte impregnated with 2-Mercapto benzimidazole was comprehensively characterized by XRD, UV–visible spectroscopy, FTIR as well as electrochemical impedance spectroscopy. It was found that the crystallization of PEO was dramatically reduced and the ionic conductivity of the electrolyte was increased 4.5 fold by addition of 2-Mercapto benzimidazole. UV–visible and FTIR spectroscopes indicated the formation of charge transfer complex between 2-Mercapto benzimidazole and iodine of the electrolyte. Dye-sensitized solar cells with the polymer electrolytes were assembled. It was found that both the photocurrent density and photovoltage were enhanced with respect to the DSC without 2-Mercapto benzimidazole, leading to a 60% increase of the performance of the cell.

Ion transport in small-molecule electrolytes based on LiI/3-hydroxypropionitrile with high salt contents

Abnormal “polymer-in-salt” conduction behavior is observed in a solid electrolyte composed of lithium iodide (LiI) and 3-hydroxypropionitrile (HPN). Based on comprehensive investigations by X-ray diffraction (XRD) and Raman and infrared spectroscopy, this abnormal conduction behavior is attributed to the formation of new ionic associates [Lim +In−]· · ·N C (m> n) and the reinforced hydrogen bonding of I· · ·HO in the electrolyte at high LiI concentrations.

Results of a phase IIa clinical trial of an anti-inflammatory molecule, chaperonin 10, in multiple sclerosis

Background Chaperonin 10 (Cpn10) is a mitochondrial molecule involved in protein folding. The aim of this study was to determine the safety profile of Cpn10 in patients with multiple sclerosis (MS). Methods A total of 50 patients with relapse-remitting or secondary progressive MS were intravenously administered 5 mg or 10 mg of Cpn10 weekly for 12 weeks in a double-blind, randomized, placebo controlled, phase II trial. Clinical reviews, including Expanded Disability Status Scale and magnetic resonance imaging (MRI) with Gadolinium, were undertaken every 4 weeks. Stimulation of patient peripheral blood mononuclear cells with lipopolysaccharide ex vivo was used to measure the in vivo activity of Cpn10. Results No significant differences in the frequency of adverse events were seen between treatment and placebo arms. Leukocytes from both groups of Cpn10-treated patients produced significantly lower levels of critical proinflammatory cytokines. A trend toward improvement in new Gadolinium enhancing lesions on MRI was observed, but this difference was not statistically significant. No differences in clinical outcome measures were seen. Conclusions Cpn10 is safe and well tolerated when administered to patients with MS for 3 months, however, a further extended phase II study primarily focused on efficacy is warranted.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

The molecular basis for selective inhibition of unconventional mRNA splicing by an IRE1-binding small molecule

IRE1 couples endoplasmic reticulum unfolded protein load to RNA cleavage events that culminate in the sequence-specific splicing of the Xbp1 mRNA and in the regulated degradation of diverse membrane-bound mRNAs. We report on the identification of a small molecule inhibitor that attains its selectivity by forming an unusually stable Schiff base with lysine 907 in the IRE1 endonuclease domain, explained by solvent inaccessibility of the imine bond in the enzyme-inhibitor complex. The inhibitor (abbreviated 4μ8C) blocks substrate access to the active site of IRE1 and selectively inactivates both Xbp1 splicing and IRE1-mediated mRNA degradation. Surprisingly, inhibition of IRE1 endonuclease activity does not sensitize cells to the consequences of acute endoplasmic reticulum stress, but rather interferes with the expansion of secretory capacity. Thus, the chemical reactivity and sterics of a unique residue in the endonuclease active site of IRE1 can be exploited by selective inhibitors to interfere with protein secretion in pathological settings.

Inferring diffusion in single live cells at the single-molecule level

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

Does counting still count? Revisiting the security of counting based user authentication protocols against statistical attacks

At NDSS 2012, Yan et al. analyzed the security of several challenge-response type user authentication protocols against passive observers, and proposed a generic counting based statistical attack to recover the secret of some counting based protocols given a number of observed authentication sessions. Roughly speaking, the attack is based on the fact that secret (pass) objects appear in challenges with a different probability from non-secret (decoy) objects when the responses are taken into account. Although they mentioned that a protocol susceptible to this attack should minimize this difference, they did not give details as to how this can be achieved barring a few suggestions. In this paper, we attempt to fill this gap by generalizing the attack with a much more comprehensive theoretical analysis. Our treatment is more quantitative which enables us to describe a method to theoretically estimate a lower bound on the number of sessions a protocol can be safely used against the attack. Our results include 1) two proposed fixes to make counting protocols practically safe against the attack at the cost of usability, 2) the observation that the attack can be used on non-counting based protocols too as long as challenge generation is contrived, 3) and two main design principles for user authentication protocols which can be considered as extensions of the principles from Yan et al. This detailed theoretical treatment can be used as a guideline during the design of counting based protocols to determine their susceptibility to this attack. The Foxtail protocol, one of the protocols analyzed by Yan et al., is used as a representative to illustrate our theoretical and experimental results.

Ion-molecule reactions reveal facile radical migration in peptides

Ion-molecule reactions between molecular oxygen and peptide radicals in the gas phase demonstrate that radical migration occurs easily within large biomolecules without addition of collisional activation energy.