Emotion Recognition in Human-Computer Interaction

The authors are concerned with the development of computer systems that are capable of using information from faces and voices to recognise people's emotions in real-life situations. The paper addresses the nature of the challenges that lie ahead, and provides an assessment of the progress that has been made in the areas of signal processing and analysis techniques (with regard to speech and face), and the psychological and linguistic analyses of emotion. Ongoing developmental work by the authors in each of these areas is described.

The use of Raman microscopy to determine and localize vitamin E in biological samples

Alpha-tocopherol (aT), the predominant form of vitamin E in mammals, is thought to prevent oxidation of polyunsaturated fatty acids. In the lung, aT is perceived to be accumulated in alveolar type II cells and secreted together with surfactant into the epithelial lining fluid. Conventionally, determination of aT and related compounds requires extraction with organic solvents. This study describes a new method to determine and image the distribution of aT and related compounds within cells and tissue sections using the light-scattering technique of Raman microscopy to enable high spatial as well as spectral resolution. This study compared the nondestructive analysis by Raman microscopy of vitamin E, in particular aT, in biological samples with data obtained using conventional HPLC analysis. Raman spectra were acquired at spatial resolutions of 2-0.8 microm. Multivariate analysis techniques were used for analyses and construction of corresponding maps showing the distribution of aT, alpha-tocopherol quinone (aTQ), and other constituents (hemes, proteins, DNA, and surfactant lipids). A combination of images enabled identification of colocalized constituents (heme/aTQ and aT/surfactant lipids). Our data demonstrate the ability of Raman microscopy to discriminate between different tocopherols and oxidation products in biological specimens without sample destruction. By enabling the visualization of lipid-protein interactions, Raman microscopy offers a novel method of investigating biological characterization of lipid-soluble compounds, including those that may be embedded in biological membranes such as aT.

Viscoelastic Material Models of Polypropylene for Thermoforming Applications

Polypropylene (PP), a semi-crystalline material, is typically solid phase thermoformed at temperatures associated with crystalline melting, generally in the 150° to 160°Celsius range. In this very narrow thermoforming window the mechanical properties of the material rapidly decline with increasing temperature and these large changes in properties make Polypropylene one of the more difficult materials to process by thermoforming. Measurement of the deformation behaviour of a material under processing conditions is particularly important for accurate numerical modelling of thermoforming processes. This paper presents the findings of a study into the physical behaviour of industrial thermoforming grades of Polypropylene. Practical tests were performed using custom built materials testing machines and thermoforming equipment at Queen′s University Belfast. Numerical simulations of these processes were constructed to replicate thermoforming conditions using industry standard Finite Element Analysis software, namely ABAQUS and custom built user material model subroutines. Several variant constitutive models were used to represent the behaviour of the Polypropylene materials during processing. This included a range of phenomenological, rheological and blended constitutive models. The paper discusses approaches to modelling industrial plug-assisted thermoforming operations using Finite Element Analysis techniques and the range of material models constructed and investigated. It directly compares practical results to numerical predictions. The paper culminates discussing the learning points from using Finite Element Methods to simulate the plug-assisted thermoforming of Polypropylene, which presents complex contact, thermal, friction and material modelling challenges. The paper makes recommendations as to the relative importance of these inputs in general terms with regard to correlating to experimentally gathered data. The paper also presents recommendations as to the approaches to be taken to secure simulation predictions of improved accuracy.

Label-free detection of nanomolar unmodified single- and double-stranded dna by using surface-enhanced raman spectroscopy on Ag and Au colloids

Unlabelled single- and double-stranded DNA (ssDNA and dsDNA, respectively) has been detected at concentrations =10-9?M by surface-enhanced Raman spectroscopy. Under appropriate conditions the sequences spontaneously adsorbed to the surface of both Ag and Au colloids through their nucleobases; this allowed highly reproducible spectra with good signal-to-noise ratios to be recorded on completely unmodified samples. This eliminated the need to promote absorption by introducing external linkers, such as thiols. The spectra of model ssDNA sequences contained bands of all the bases present and showed systematic changes when the overall base composition was altered. Initial tests also showed that small but reproducible changes could be detected between oligonucleotides with the same bases arranged in a different order. The spectra of five ssDNA sequences that correspond to different strains of the Escherichia coli bacterium were found to be sufficiently composition-dependent so that they could be differentiated without the need for any advanced multivariate data analysis techniques.

Modeling of subsurface pulsed radar for nondestructive testing of structures

The use of pulsed radar for investigating the integrity of structural elements is gaining popularity and becoming firmly established as a nondestructive test method in civil engineering. Difficulties can often arise in the interpretation of results obtained, particularly where internal details are relatively complex. One approach that can be used to understand and evaluate radar results is through numerical modeling of signal propagation and reflection. By comparing the results of a numerical modeling with those from field measurements, engineers can gain valuable insight into the probable features embedded beneath the surface of a structural element. This paper discusses a series of numerical techniques for modeling subsurface radar and compares the precision of the results with those taken from real field data. It is found that more complex problems require more sophisticated analysis techniques to obtain realistic results, with a consequential increase in the computational resources to carry out the modeling.

Behaviours in video

With a significant increment of the number of digital cameras used for various purposes, there is a demanding call for advanced video analysis techniques that can be used to systematically interpret and understand the semantics of video contents, which have been recorded in security surveillance, intelligent transportation, health care, video retrieving and summarization. Understanding and interpreting human behaviours based on video analysis have observed competitive challenges due to non-rigid human motion, self and mutual occlusions, and changes of lighting conditions. To solve these problems, advanced image and signal processing technologies such as neural network, fuzzy logic, probabilistic estimation theory and statistical learning have been overwhelmingly investigated.

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Risky decision making in younger and older adults:The role of learning.

Are older adults risk seeking or risk averse? Answering this question might depend on both the task used and the analysis performed. By modeling responses to the Balloon Analogue Risk Task (BART), our results illustrate the value of modeling as compared to relying on common analysis techniques. While analysis of overall measures suggested initially that older and younger adults do not differ in their risky decisions, our modeling results indicated that younger adults were at first more willing to take greater risks. Furthermore, older adults may be more cautious when their decision making is based on initial perceptions of risk, rather than learning following some experience with a task.

Arsenic in groundwater and its influence on exposure risks through traditionally cooked rice in Prey Vêng Province, Cambodia

Arsenic (As) contamination of communal tubewells in Prey Vêng, Cambodia, has been observed since 2000. Many of these wells exceed the WHO As in drinking water standard of 10 µg/L by a factor of 100. The aim of this study was to assess how cooking water source impacts dietary As intake in a rural community in Prey Vêng. This aim was fulfilled by (1) using geostatistical analysis techniques to examine the extent of As contaminated groundwater in Prey Vêng and identify a suitable study site, (2) conducting an on-site study in two villages to measure As content in cooked rice prepared with water collected from tubewells and locally harvested rainwater, and (3) determining the dietary intake of As from consuming this rice. Geostatistical analysis indicated that high risk tubewells (>50 µg As/L) are concentrated along the Mekong River's east bank. Participants using high risk tubewells are consuming up to 24 times more inorganic As daily than recommended by the previous FAO/WHO provisional tolerable daily intake value (2.1 µg/kgBW/day). However, As content in rice cooked in rainwater was significantly reduced, therefore, it is considered to be a safer and more sustainable option for this region.

Secure Virtualised Environment

Cloud computing is a technological advancementthat provide resources through internet on pay-as-you-go basis.Cloud computing uses virtualisation technology to enhance theefficiency and effectiveness of its advantages. Virtualisation isthe key to consolidate the computing resources to run multiple instances on each hardware, increasing the utilization rate of every resource, thus reduces the number of resources needed to buy, rack, power, cool, and manage. Cloud computing has very appealing features, however, lots of enterprises and users are still reluctant to move into cloud due to serious security concerns related to virtualisation layer. Thus, it is foremost important to secure the virtual environment.In this paper, we present an elastic framework to secure virtualised environment for trusted cloud computing called Server Virtualisation Security System (SVSS). SVSS provide security solutions located on hyper visor for Virtual Machines by deploying malicious activity detection techniques, network traffic analysis techniques, and system resource utilization analysis techniques.SVSS consists of four modules: Anti-Virus Control Module,Traffic Behavior Monitoring Module, Malicious Activity Detection Module and Virtualisation Security Management Module.A SVSS prototype has been deployed to validate its feasibility,efficiency and accuracy on Xen virtualised environment.

Microneedle characterisation: the need for universal acceptance criteria and GMP specifications when moving towards commercialisation

With interest in microneedles as a novel drug transdermal delivery system increasing rapidly since the late 1990s (Margetts and Sawyer Contin Educ Anaesthesia Crit Care Pain. 7(5):171-76, 2007), a diverse range of microneedle systems have been fabricated with varying designs and dimensions. However, there are still very few commercially available microneedle products. One major issue regarding microneedle manufacture on an industrial scale is the lack of specific quality standards for this novel dosage form in the context of Good Manufacturing Practice (GMP). A range of mechanical characterisation tests and microneedle insertion analysis techniques are used by researchers working on microneedle systems to assess the safety and performance profiles of their various designs. The lack of standardised tests and equipment used to demonstrate microneedle mechanical properties and insertion capability makes it difficult to directly compare the in use performance of candidate systems. This review highlights the mechanical tests and insertion analytical techniques used by various groups to characterise microneedles. This in turn exposes the urgent need for consistency across the range of microneedle systems in order to promote innovation and the successful commercialisation of microneedle products.

Reflection of Qualitative Methods: “memoring” fieldwork experience in organisational research with photographs

The paper is a reflection on the use of photographs in multiple case study research. It explores the crossovers between interpreting visual artefacts, the qualitative approach to case study research in organisations, and the move from cases to theory guided by the grounded theory tenets. The paper proposes an additional use of photographs as a visual method to those in the literature, as a device for data analysis. Photograph-based analysis techniques are explored, using e sequence of individual images and photo collages on case data, moving from interpretation of single to multiple case themes. This makes the case of using photograph analysis as an interpretation device for case research to illuminate theory development.

Using geotechnical and LIDAR spatial monitoring to determine key environmental slope instability thresholds of a Jurassic coastal landslide: Straidkilly Point, Northern Ireland, UK.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland to the famous Giant’s Causeway in the North has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). At various locations along the route, fluid interactions between the problematic geology, Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability within the vadose zone. During such instances of instability, debris flows and composite mudflows encroach on the carriageway posing a hazard to road users. This paper examines the site investigative, geotechnical and spatial analysis techniques currently being implemented to monitor slope stability for one site at Straidkilly Point, Glenarm, Northern Ireland. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration dynamic data.
Terrestrial LiDAR (TLS) was applied to the slope for the monitoring of failures, with surveys carried out on a bi-monthly basis. TLS monitoring allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, erosion and deposition. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters are characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDARi datasets were used for the spatio-morphological characterisation of the slope on a macro scale. Results from the geotechnical and environmental monitoring were compared with spatial data obtained through Terrestrial and Airborne LiDAR, providing a multi-faceted approach to slope stability characterization, which facilitates more informed management of geotechnical risk by the Northern Ireland Roads Service.