Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments

Since the advent of the internet in every day life in the 1990s, the barriers to producing, distributing and consuming multimedia data such as videos, music, ebooks, etc. have steadily been lowered for most computer users so that almost everyone with internet access can join the online communities who both produce, consume and of course also share media artefacts. Along with this trend, the violation of personal data privacy and copyright has increased with illegal file sharing being rampant across many online communities particularly for certain music genres and amongst the younger age groups. This has had a devastating effect on the traditional media distribution market; in most cases leaving the distribution companies and the content owner with huge financial losses. To prove that a copyright violation has occurred one can deploy fingerprinting mechanisms to uniquely identify the property. However this is currently based on only uni-modal approaches. In this paper we describe some of the design challenges and architectural approaches to multi-modal fingerprinting currently being examined for evaluation studies within a PhD research programme on optimisation of multi-modal fingerprinting architectures. Accordingly we outline the available modalities that are being integrated through this research programme which aims to establish the optimal architecture for multi-modal media security protection over the internet as the online distribution environment for both legal and illegal distribution of media products.

Host plant recognition by the root feeding clover weevil, Sitona lepidus (Coleoptera : Curculionidae)

This study investigated the ability of neonatal larvae of the root-feeding weevil, Sitona lepidus Gyllenhal, to locate white clover Trifolium repens L. (Fabaceae) roots growing in soil and to distinguish them from the roots of other species of clover and a co-occurring grass species. Choice experiments used a combination of invasive techniques and the novel technique of high resolution X-ray microtomography to non-invasively track larval movement in the soil towards plant roots. Burrowing distances towards roots of different plant species were also examined. Newly hatched S. lepidus recognized T. repens roots and moved preferentially towards them when given a choice of roots of subterranean clover, Trifolium subterraneum L. (Fabaceae), strawberry clover Trifolium fragiferum L. (Fabaceae), or perennial ryegrass Lolium perenne L. (Poaceae). Larvae recognized T. repens roots, whether released in groups of five or singly, when released 25 mm (meso-scale recognition) or 60 mm (macro-scale recognition) away from plant roots. There was no statistically significant difference in movement rates of larvae.

Cross-modal preference acquisition: evaluative conditioning of pictures by affective olfactory and auditory cues

In this research, a cross-model paradigm was chosen to test the hypothesis that affective olfactory and auditory cues paired with neutral visual stimuli bearing no resemblance or logical connection to the affective cues can evoke preference shifts in those stimuli. Neutral visual stimuli of abstract paintings were presented simultaneously with liked and disliked odours and sounds, with neutral-neutral pairings serving as controls. The results confirm previous findings that the affective evaluation of previously neutral visual stimuli shifts in the direction of contingently presented affective auditory stimuli. In addition, this research shows the presence of conditioning with affective odours having no logical connection with the pictures.

Modeling the user knowledge by belief networks

This paper describes the user modeling component of EPIAIM, a consultation system for data analysis in epidemiology. The component is aimed at representing knowledge of concepts in the domain, so that their explanations can be adapted to user needs. The first part of the paper describes two studies aimed at analysing user requirements. The first one is a questionnaire study which examines the respondents' familiarity with concepts. The second one is an analysis of concept descriptions in textbooks and from expert epidemiologists, which examines how discourse strategies are tailored to the level of experience of the expected audience. The second part of the paper describes how the results of these studies have been used to design the user modeling component of EPIAIM. This module works in a two-step approach. In the first step, a few trigger questions allow the activation of a stereotype that includes a "body" and an "inference component". The body is the representation of the body of knowledge that a class of users is expected to know, along with the probability that the knowledge is known. In the inference component, the learning process of concepts is represented as a belief network. Hence, in the second step the belief network is used to refine the initial default information in the stereotype's body. This is done by asking a few questions on those concepts where it is uncertain whether or not they are known to the user, and propagating this new evidence to revise the whole situation. The system has been implemented on a workstation under UNIX. An example of functioning is presented, and advantages and limitations of the approach are discussed.

User interface standards for expert systems: are they appropriate?

In recent years there has been a growing debate over whether or not standards should be produced for user system interfaces. Those in favor of standardization argue that standards in this area will result in more usable systems, while those against argue that standardization is neither practical nor desirable. The present paper reviews both sides of this debate in relation to expert systems. It argues that in many areas guidelines are more appropriate than standards for user interface design.

Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

Less-is-more effects without the recognition heuristic

Inferences consistent with “recognition-based” decision-making may be drawn for various reasons other than recognition alone. We demonstrate that, for 2-alternative forced-choice decision tasks, less-is-more effects (reduced performance with additional learning) are not restricted to recognition-based inference but can also be seen in circumstances where inference is knowledge-based but item knowledge is limited. One reason why such effects may not be observed more widely is the dependence of the effect on specific values for the validity of recognition and knowledge cues. We show that both recognition and knowledge validity may vary as a function of the number of items recognized. The implications of these findings for the special nature of recognition information, and for the investigation of recognition-based inference, are discussed

Nitrogen management is essential to prevent tropical oil palm plantations from causing ozone pollution

More than half the world's rainforest has been lost to agriculture since the Industrial Revolution. Among the most widespread tropical crops is oil palm (Elaeis guineensis): global production now exceeds 35 million tonnes per year. In Malaysia, for example, 13% of land area is now oil palm plantation, compared with 1% in 1974. There are enormous pressures to increase palm oil production for food, domestic products, and, especially, biofuels. Greater use of palm oil for biofuel production is predicated on the assumption that palm oil is an “environmentally friendly” fuel feedstock. Here we show, using measurements and models, that oil palm plantations in Malaysia directly emit more oxides of nitrogen and volatile organic compounds than rainforest. These compounds lead to the production of ground-level ozone (O3), an air pollutant that damages human health, plants, and materials, reduces crop productivity, and has effects on the Earth's climate. Our measurements show that, at present, O3 concentrations do not differ significantly over rainforest and adjacent oil palm plantation landscapes. However, our model calculations predict that if concentrations of oxides of nitrogen in Borneo are allowed to reach those currently seen over rural North America and Europe, ground-level O3 concentrations will reach 100 parts per billion (109) volume (ppbv) and exceed levels known to be harmful to human health. Our study provides an early warning of the urgent need to develop policies that manage nitrogen emissions if the detrimental effects of palm oil production on air quality and climate are to be avoided.

Syk-Dependent Cytokine Induction by Dectin-1 Reveals a Novel Pattern Recognition Pathway for C Type Lectins

Pattern-recognition receptors (PRRs) detect molecular signatures of microbes and initiate immune responses to infection. Prototypical PRRs such as Toll-like receptors (TLRs) signal via a conserved pathway to induce innate response genes. In contrast, the signaling pathways engaged by other classes of putative PRRs remain ill defined. Here, we demonstrate that the β-glucan receptor Dectin-1, a yeast binding C type lectin known to synergize with TLR2 to induce TNFα and IL-12, can also promote synthesis of IL-2 and IL-10 through phosphorylation of the membrane proximal tyrosine in the cytoplasmic domain and recruitment of Syk kinase. syk−/− dendritic cells (DCs) do not make IL-10 or IL-2 upon yeast stimulation but produce IL-12, indicating that the Dectin-1/Syk and Dectin-1/TLR2 pathways can operate independently. These results identify a novel signaling pathway involved in pattern recognition by C type lectins and suggest a potential role for Syk kinase in regulation of innate immunity.

Effect of replacing calcium salts of palm oil distillate with rapeseed oil, milled or whole rapeseeds on milk fatty-acid composition in cows fed maize silage-based diets

Inclusion of rapeseed feeds in dairy cow diets has the potential to reduce milk fat saturated fatty acid (SFA) and increase cis-monounsaturated fatty acid (cis-MUFA) content but effectiveness may depend on the form in which the rapeseed is presented. Four mid-lactation Holstein dairy cows were allocated to four maize silage-based dietary treatments according to a 4 x 4 Latin Square design, with 28-day experimental periods. Treatments consisted of a control diet (C containing 49 g/kg dry matter (DM) of calcium salts of palm oil distillate (CPO), or 49 g/kg DM of oil supplied as whole rapeseeds (WR), rapeseeds milled with wheat (MR) or rapeseed oil (RO). Replacing CPO with rapeseed feeds had no effect (P > 0.05) on milk fat and protein content, while milk yields were higher (P < 0.05) for RO and MR compared with WR (37.1, 38.1 and 34.3 kg/day, respectively). Substituting CPO with RO or MR reduced (P < 0.05) milk fat total SFA content (69.6, 55.6, 71.7 and 61.5 g/100g fatty acids for C, RO, WR and MR, respectively) and enhanced (P < 0.05) milk cis-9 18:1 MUFA concentrations (corresponding values 18.6, 24.3, 17.0 and 23.0 g/100g fatty acids) compared with C and WR. Treatments RO and MR also increased (P < 0.05) milk trans-MUFA content (4.4, 6.8, 10.5 g/100g fatty acids, C MR and RO, respectively). A lack of significant changes in milk fat composition when replacing CPO with WR suggests limited bioavailability of fatty acids in intact rapeseeds. In conclusion, replacing a commercial palm oil-based fat supplement in the diet with milled rapeseeds or rapeseed oil represented an effective strategy to alter milk fatty acid composition with the potential to improve human health. Inclusion of processed rapeseeds offered a good compromise for reducing milk SFA and increasing cis-MUFA, whilst minimising milk trans-MUFA and negative effects on animal performance.

Effect of replacing calcium salts of palm oil distillate with extruded linseeds on milk fatty acid composition in Jersey and Holstein cows

Clinical and biomedical studies have provided evidence for the critical role of n-3 fatty acids on the reduction of chronic disease risk in humans, including cardiovascular disease. In the current experiment, the potential to enhance milk n-3 content in two breeds with inherent genetic differences in mammary lipogenesis and de novo fatty acid synthesis was examined using extruded linseeds. Six lactating cows (three Holstein and three Jersey) were used in a two-treatment switchback design with 3 × 21-day experimental periods to evaluate the effect of iso-energetic replacement of calcium salts of palm oil distillate (CPO) in the diet (34 g/kg dry matter (DM)) with 100 g/kg DM extruded linseeds (LIN). For both breeds, replacing CPO with LIN had no effect (P > 0.05) on DM intake or milk yield, but reduced (P < 0.05) milk fat and protein yield (on average, from 760 to 706 and 573 to 552 g/day, respectively). Relative to CPO, the LIN treatment reduced (P < 0.01) total saturated fatty acid content and enhanced (P < 0.001) 18:3n-3 in milk, whereas breed by diet interactions were significant for milk fat 16:0, total trans fatty acid and conjugated linoleic acid concentrations. Increases in 18:3n-3 intake derived from LIN in the diet were transferred into milk with a mean marginal transfer efficiency of 1.8%. Proportionate changes in milk fatty acid composition were greater in the Jersey, highlighting the importance of diet–genotype interactions on mammary lipogenesis. More extensive studies are required to determine the role of genotype on milk fat composition responses to oilseeds in the diet.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.