Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

EPG monitoring of the probing behaviour of the common brown leafhopper Orosius orientalis on artificial diet and selected host plants

The common brown leafhopper Orosius orientalis (Hemiptera: Cicadellidae) is a polyphagous vector of a range of economically important pathogens, including phytoplasmas and viruses, which infect a diverse range of crops. Studies on the plant penetration behaviour by O. orientalis were conducted using the electrical penetration graph (EPG) technique to assist in the characterisation of pathogen acquisition and transmission. EPG waveforms representing different probing activities were acquired from adult O. orientalis probing in planta, using two host species, tobacco Nicotiana tabacum and bean Phaseolus vulgaris, and in vitro using a simple sucrose-based artificial diet. Five waveforms (O1–O5) were evident when O. orientalis fed on bean, whereas only four waveforms (O1–O4) and three waveforms (O1–O3) were observed when the leafhopper fed on tobacco and on the artificial diet, respectively. Both the mean duration of each waveform and waveform type differed markedly depending on the food substrate. Waveform O4 was not observed on the artificial diet and occurred relatively rarely on tobacco plants when compared with bean plants. Waveform O5 was only observed with leafhoppers probing on beans. The attributes of the waveforms and comparative analyses with previously published Hemipteran data are presented and discussed, but further characterisation studies will be needed to confirm our suggestions.

Non-intrusive continuous user behaviour analysis using computerized systems

There are different ways to authenticate humans, which is an essential prerequisite for access control. The authentication process can be subdivided into three categories that rely on something someone i) knows (e.g. password), and/or ii) has (e.g. smart card), and/or iii) is (biometric features). Besides classical attacks on password solutions and the risk that identity-related objects can be stolen, traditional biometric solutions have their own disadvantages such as the requirement of expensive devices, risk of stolen bio-templates etc. Moreover, existing approaches provide the authentication process usually performed only once initially. Non-intrusive and continuous monitoring of user activities emerges as promising solution in hardening authentication process: iii-2) how so. behaves. In recent years various keystroke dynamic behavior-based approaches were published that are able to authenticate humans based on their typing behavior. The majority focuses on so-called static text approaches, where users are requested to type a previously defined text. Relatively few techniques are based on free text approaches that allow a transparent monitoring of user activities and provide continuous verification. Unfortunately only few solutions are deployable in application environments under realistic conditions. Unsolved problems are for instance scalability problems, high response times and error rates. The aim of this work is the development of behavioral-based verification solutions. Our main requirement is to deploy these solutions under realistic conditions within existing environments in order to enable a transparent and free text based continuous verification of active users with low error rates and response times.

Numerical Modelling of Mechanical Behaviour of Graphene

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of element carbon, is a monolayer of honeycomb lattice of carbon atoms, which was discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking work on the two-dimensional (2D) graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its intriguing electrical, mechanical and thermal properties. It has been confirmed that grapheme possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene also has exceptional mechanical properties. It is one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Due to these exceptional properties, graphene has demonstrated its potential for broad applications in micro and nano devices, various sensors, electrodes, solar cells and energy storage devices and nanocomposites. In particular, the excellent mechanical properties of graphene make it more attractive for development next generation nanocomposites and hybrid materials...

A hybrid association rule mining approach for characterizing network traffic behaviour

Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.

Robust recognition of human behaviour in challenging environments

Novel techniques have been developed for the automatic recognition of human behaviour in challenging environments using information from visual and infra-red camera feeds. The techniques have been applied to two interesting scenarios: Recognise drivers' speech using lip movements and recognising audience behaviour, while watching a movie, using facial features and body movements. Outcome of the research in these two areas will be useful in the improving the performance of voice recognition in automobiles for voice based control and for obtaining accurate movie interest ratings based on live audience response analysis.

Investigation on Temperature-Dependent Electrical Conductivity of Carbon Nanotube/Epoxy Composites for Sustainable Energy Applications

Composites with carbon nanotubes are becoming increasingly used in energy storage and electronic devices, due to incorporated excellent properties from carbon nanotubes and polymers. Although their properties make them more attractive than conventional smart materials, their electrical properties are found to be temperature-dependent which is important to consider for the design of devices. To study the effects of temperature in electrically conductive multi-wall carbon nanotube/epoxy composites, thin films were prepared and the effect of temperature on the resistivity, thermal properties and Raman spectral characteristics of the composite films was evaluated. Resistivity-temperature profiles showed three distinct regions in as-cured samples and only two regions in samples whose thermal histories had been erased. In the vicinity of the glass transition temperature, the as-cured composites exhibited pronounced resistivity and enthalpic relaxation peaks, which both disappeared after erasing the composites’ thermal histories by temperature cycling. Combined DSC, Raman spectroscopy, and resistivity-temperature analyses indicated that this phenomenon can be attributed to the physical aging of the epoxy matrix and that, in the region of the observed thermal history-dependent resistivity peaks, structural rearrangement of the conductive carbon nanotube network occurs through a volume expansion/relaxation process. These results have led to an overall greater understanding of the temperature-dependent behaviour of conductive carbon nanotube/epoxy composites, including the positive temperature coefficient effect.

Agent-based modelling simulation case study : assessment of airport check-in and evacuation process by considering group travel behaviour of air passengers

Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Lung recruitment and endotracheal suction in ventilated preterm infants measured with electrical impedance tomography

Aims Although suctioning is a standard airway maintenance procedure, there are significant associated risks, such as loss of lung volume due to high negative suction pressures. This study aims to assess the extent and duration of change in end-expiratory level (EEL) resulting from endotracheal tube (ETT) suction and to examine the relationship between EEL and regional lung ventilation in ventilated preterm infants with respiratory distress syndrome. Methods A prospective observational clinical study of the effect of ETT suction on 20 non-muscle-relaxed preterm infants with respiratory distress syndrome (RDS) on conventional mechanical ventilation was conducted in a neonatal intensive care unit. Ventilation distribution was measured with regional impedance amplitudes and EEL using electrical impedance tomography. Results ETT suction resulted in a significant increase in EEL post-suction (P < 0.01). Regionally, anterior EEL decreased and posterior EEL increased post-suction, suggesting heterogeneity. Tidal volume was significantly lower in volume-guarantee ventilation compared with pressure-controlled ventilation (P = 0.04). Conclusions ETT suction in non-muscle-relaxed and ventilated preterm infants with RDS results in significant lung volume increase that is maintained for at least 90 min. Regional differences in distribution of ventilation with ETT suction suggest that the behaviour of the lung is heterogeneous in nature.

Demonstration of nonlinear absorption in Au semi-continuous film by electrical measurement

We have demonstrated the nonlinear absorption at 532 nm wavelength in an Au semi-continuous film (SF) resulting from smearing of the Fermi distribution and diffusion of conduction electrons into the substrate. The Au SF was irradiated by a pulsed laser with 8 ns pulse width at 532 nm in near resonance with the interband transition of the Au. We determined the temperature increase in the SF for different intensities by electrical measurement. We calculated the temperature increase by using a 1D heat transport equation; comparing the results of the calculation with measured values for the temperature increase, revealed the nonlinear absorption in the Au SF. We employed this deviation from linear behaviour to determine the nonlinear absorption coefficient.

Synthesis and study of conductivity behaviour of blended conducting polymer films irradiated with swift heavy ions of silicon

In recent times, blended polymers have shown a lot of promise in terms of easy processability in different shapes and forms. In the present work, polyaniline emeraldine base (PANi-EB) was doped with camphor sulfonic acid (CSA) and combined with the conducting polymer polyfluorene (PF) as well as the insulating polymer polyvinyl chloride (PVC) to synthesize CSA doped PANi-PF and PANi-PVC blended polymers. It is well known that PANi when doped with CSA becomes highly conducting. However, its poor mechanical properties, such as low tensile, compressive, and flexural strength render PANi a non-ideal material to be processed for its various practical applications, such as electromagnetic shielding, anti-corrosion shielding, photolithography and microelectronic devices etc. Thus the search for polymers which are easily processable and are capable of showing high conductivity still continues. PANi-PVC blend was prepared, which showed low conductivity which is limiting factor for certain applications. Therefore, another processable polymer PF was chosen as conducting matrix. Conducting PF can be easily processed into various shapes and forms. Therefore, a blend mixture was prepared by using PANi and PF through the use of CSA as a counter ion which forms a "bridge" between the two polymeric components of the inter-polymer complex. Two blended polymers have been synthesized and investigated for their conductivity behaviour. It was observed that the blended film of CSA doped PANi-PVC showed a room temperature electrical conductivity of 2.8 × 10-7 S/cm where as the blended film made by CSA doped PANi with conducting polymer PF showed a room temperature conductivity of 1.3 × 10-5 S/cm. Blended films were irradiated with 100 MeV silicon ions with a view to increase their conductivity with a fluence ranging from 1011 ions to 1013 per cm2 from 15 UD Pelletron accelerator at NSC, New Delhi.

Analysis of passenger group behaviour and its impact on passenger flow using an agent-based model

Group interaction within crowds is a common phenomenon and has great influence on pedestrian behaviour. This paper investigates the impact of passenger group dynamics using an agent-based simulation method for the outbound passenger process at airports. Unlike most passenger-flow models that treat passengers as individual agents, the proposed model additionally incorporates their group dynamics as well. The simulation compares passenger behaviour at airport processes and discretionary services under different group formations. Results from experiments (both qualitative and quantitative) show that incorporating group attributes, in particular, the interactions with fellow travellers and wavers can have significant influence on passengers activity preference as well as the performance and utilisation of services in airport terminals. The model also provides a convenient way to investigate the effectiveness of airport space design and service allocations, which can contribute to positive passenger experiences. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Temporal and environmental influences on the vocal behaviour of a nocturnal bird

Temporal and environmental variation in vocal activity can provide information on avian behaviour and call function not available to short-term experimental studies. Intersexual differences in this variation can provide insight into selection effects. Yet factors influencing vocal behaviour have not been assessed in many birds, even those monitored by acoustic methods. This applies to the New Zealand kiwi (Apterygidae), for which call censuses are used extensively in conservation monitoring, yet which have poorly understood acoustic ecology. We investigated little spotted kiwi Apteryx owenii vocal behaviour over 3 yr, measuring influences on vocal activity in both sexes from time of night, season, weather conditions and lunar cycle. We tested hypotheses that call rate variation reflects call function, foraging efficiency, historic predation risk and variability in sound transmission, and that there are inter-sexual differences in call function. Significant seasonal variation showed that vocalisations were important in kiwi reproduction, and inter-sexual synchronisation of call rates indicated that contact, pair-bonding or resource defence were key functions. All weather variables significantly affected call rates, with elevated calling during increased humidity and ground moisture indicating a relation between vocal activity and foraging conditions. A significant decrease in calling activity on cloudy nights, combined with no moonlight effect, suggests an impact of light pollution in this species. These influences on vocal activity provide insight into kiwi call function, have direct consequences for conservation monitoring of kiwi, and have wider implications in understanding vocal behaviour in a range of nocturnal birds

Electrical Conductivity and Magneto-Resistance Studies on Polyaniline-Pmma Blends at Very Low Temperature

D.C. electrical conductivity of polyaniline (33%,40%) blended with PMMA was measured from 5K to 300mK. The conductivity behaviour is consistent with fluctuation induced tunneling. Magneto-resistance (MR) was measured between 300K and 2K. From 20K to 2K, a large positive MR was observed. At 2K, for low magnetic fields (<1 Tesla), a deviation from the normal H-2 behaviour was observed.

Electrical and mechanical properties of diluted magnetic semiconductor Zn1-xMnxS nanocrystalline films

Nanostructured Zn1-xMnxS films (0 less-than-or-equals, slant x less-than-or-equals, slant 0.25) were deposited on glass substrates by simple resistive thermal evaporation technique. All the films were deposited at 300 K in a vacuum of 2*10-6 m bar. All the films temperature dependence of resistivity revealed semiconducting behaviour of the samples. Hot probe test revealed that all the samples exhibited n-type conductivity. The nanohardness of the films ranges from 4.7 to 9.9 GPa, Young's modulus value ranging 69.7-94.2 GPa.