Designing for video: investigating the contextual cues within viewing situations

The viewing of video increasingly occurs in a wide range of public and private environments via a range of static and mobile devices. The proliferation of content on demand and the diversity of the viewing situations means that delivery systems can play a key role in introducing audiences to contextually relevant content of interest whilst maximising the viewing experience for individual viewers. However, for video delivery systems to do this, they need to take into account the diversity of the situations where video is consumed, and the differing viewing experiences that users desire to create within them. This requires an ability to identify different contextual viewing situations as perceived by users. This paper presents the results from a detailed, multi-method, user-centred field study with 11 UK-based users of video-based content. Following a review of the literature (to identify viewing situations of interest on which to focus), data collection was conducted comprising observation, diaries, interviews and self-captured video. Insights were gained into whether and how users choose to engage with content in different public and private spaces. The results identified and validated a set of contextual cues that characterise distinctive viewing situations. Four archetypical viewing situations were identified: ‘quality time’, ‘opportunistic planning’, ‘sharing space but not content’ and ‘opportunistic self-indulgence’. These can be differentiated in terms of key contextual factors: solitary/shared experiences, public/private spaces and temporal characteristics. The presence of clear contextual cues provides the opportunity for video delivery systems to better tailor content and format to the viewing situation or additionally augment video services through social media in order to provide specific experiences sensitive to both temporal and physical contexts.     

Geographic Variation in Alkaloid Production in <Emphasis Type="Italic">Conium maculatum</Emphasis> Populations Experiencing Differential Herbivory by <Emphasis Type="Italic">Agonopterix alstroemeriana</Emphasis>

Conium maculatum, a Eurasian weed naturalized in North America, contains high concentrations of piperidine alkaloids that act as chemical defenses against herbivores. C. maculatum was largely free from herbivory in the United States, until approximately 30 yr ago, when it was reassociated via accidental introduction with a monophagous European herbivore, the oecophorid caterpillar Agonopterix alstroemeriana. At present, A. alstroemeriana is found in a continuum of reassociation time and intensities with C. maculatum across the continent; in the Pacific Northwest, A. alstroemeriana can cause severe damage, resulting in some cases in complete defoliation. Studies in biological control and invasion biology have yet to determine whether plants reassociated with a significant herbivore from the area of indigeneity increase their chemical defense investment in areas of introduction. In this study, we compared three locations in the United States (New York, Washington, and Illinois) where C. maculatum experiences different levels of herbivory by A. alstroemeriana to determine the association between the intensity of the interaction, as measured by damage, and chemical defense production. Total alkaloid production in C. maculatum was positively correlated with A. alstroemeriana herbivory levels: plants from New York and Washington, with higher herbivory levels, invested two and four times more N to alkaloid synthesis than did plants from Illinois. Individual plants with lower concentrations of alkaloids from a single location in Illinois experienced more damage by A. alstroemeriana, indicative of a preference on the part of the insect for plants with less chemical defense. These results suggest that A. alstroemeriana may act either as a selective agent or inducing agent for C. maculatum and increase its toxicity in its introduced range.     

Separation of crude palm oil components by semipreparative supercritical fluid chromatography

Successful separation of triglycerides, diglycerides, free fatty acids, carotenes, tocopherol, and tocotrienols from crude palm oil has been achieved by supercritical fluid chromatography (SFC) with a combination of a C18 and a silica gel column. The separation was carried out by the programmed extraction elution method. Free fatty acids were separated into five components by gas-liquid chromatography; tocopherol and tocotrienols were also separated into four components by SFC analysis, and the pure fractionated carotenes were obtained by preparative SFC. Thus, by using supercritical fluid chromatography, crude palm oil components can be separated and fractionated, based on differences in their functional groups.     

Determining Geographic Vulnerabilities Using a Novel Impact Based Resilience Metric

Various natural and man-made disasters as well as major political events (like riots) have increased the importance of understanding geographic failures and how correlated failures impact networks. Since mission critical networks are overlaid as virtual networks over a physical network infrastructure forming multilayer networks, there is an increasing need for methods to analyze multilayer networks for geographic vulnerabilities. In this paper, we present a novel impact-based resilience metric. Our new metric uses ideas borrowed from performability to combine network impact with state probability to calculate a new metric called Network Impact Resilience. The idea is that the highest impact to the mission of a network should drive its resilience metric. Furthermore, we present a state space analysis method that analyzes multilayer networks for geographic vulnerabilities. To demonstrate the methods, the inability to provision a given number of upper layer services is used as the criteria for network failure. Mapping techniques for multilayer network states are presented. Simplifying geographic state mapping techniques to reduce enumeration costs are also presented and tested. Finally, these techniques are tested on networks of varying sizes.     

Approximate factorization of multivariate polynomials using singular value decomposition

We describe the design, implementation and experimental evaluation of new algorithms for computing the approximate factorization of multivariate polynomials with complex coefficients that contain numerical noise. Our algorithms are based on a generalization of the differential forms introduced by W. Ruppert and S. Gao to many variables, and use singular value decomposition or structured total least squares approximation and Gauss–Newton optimization to numerically compute the approximate multivariate factors. We demonstrate on a large set of benchmark polynomials that our algorithms efficiently yield approximate factorizations within the coefficient noise even when the relative error in the input is substantial (10⁻³).     

The movement patterns and the experiential components of virtual environments

Human movement in virtual environments (VEs) is a largely unstudied area, and there are no well-established methods of measuring it in VEs. Consequently, it is unclear how movement affects the experiential side of VEs. We introduce a novel method of measuring and modelling human movement. A specific information entropy-based modelling method enabled us to identify different movement patterns and analyse the experiential components related to them. The data was collected by registering the movement patterns of 68 participants who were in a virtual house doing a search task. The experiential side of the VE was measured with the Experimental Virtual Environment Questionnaire (EVEQ). Four movement patterns were identified. In addition, fluent movement in VEs was related to a high sense of presence. Moreover, the participants who moved fluently in the environment assessed their skills high. The results show how movement is related the way in which people experience the VE. The movement analysis method introduced here is applicable to other related research areas as well.     

Prediction of urban stormwater quality using artificial neural networks

There are a vast number of complex, interrelated processes influencing urban stormwater quality. However, the lack of measured fundamental variables prevents the construction of process-based models. Furthermore, hybrid models such as the buildup-washoff models are generally crude simplifications of reality. This has created the need for statistical models, capable of making use of the readily accessible data. In this paper, artificial neural networks (ANN) were used to predict stormwater quality at urbanized catchments located throughout the United States. Five constituents were analysed: chemical oxygen demand (COD), lead (Pb), suspended solids (SS), total Kjeldhal nitrogen (TKN) and total phosphorus (TP). Multiple linear regression equations were initially constructed upon logarithmically transformed data. Input variables were primarily selected using a stepwise regression approach, combined with process knowledge. Variables found significant in the regression models were then used to construct ANN models. Other important network parameters such as learning rate, momentum and the number of hidden nodes were optimized using a trial and error approach. The final ANN models were then compared with the multiple linear regression models. In summary, ANN models were generally less accurate than the regression models and more time consuming to construct. This infers that ANN models are not more applicable than regression models when predicting urban stormwater quality.     

Postural support strategies of disabled drivers and the effectiveness of postural support aids

The paper discusses a series of driving trials that were conducted to investigate postural stability of disabled drivers and to assess the effectiveness of a representative sample of support aids. Twenty-three disabled drivers with varying levels of physical disability and seven non disabled drivers participated in the study. The test car was equipped with transducers to measure vehicle velocity and acceleration (longitudinal and lateral), steering wheel movement and torque, and the bracing forces exerted by the driver on the steering wheel. Video cameras were installed to record postural support strategies and displacement of the driver and to record deviation of the car from the specified path. Subjective data regarding driver attitudes and acceptance were also collected through the administration of questionnaires. Findings from the study showed that support aids significantly improved driving performance and reduced physical exertion to maintain an upright driving position for disabled drivers. However, ergonomics design aspects regarding the ease of use and acceptance of the support aids by the end users were identified as obstacles to their sustained use in everyday driving.     

Measurements of the photocurrent enhancement of reverse-biased silicon photodiodes in the 0.05-1.5-keV photon-energy range

The measured photocurrents from two different p-n-junction silicon photodiodes at 170-? (73-eV) and at 8.34-? (1480-eV) light are presented. One is a standard extreme-UV photodiode fabricated on low resistivity silicon (70-100 Ω cm), and the other is fabricated on high-resistivity silicon (> 2 × 10(4) Ω cm). The photocurrents from the diode on high-resistivity silicon are at least an order of magnitude greater than the photocurrents from the diode on low-resistivity silicon when a reverse bias of 40 V is applied to each. This photocurrent enhancement is 15.4 ± 4 at 8.34 ? and 12.5 ± 2 at 170 ?.