VALENCE: affective visualisation using EEG

VALENCE is an interactive visualisation controlled by live brainwave monitoring. We used a wireless EEG headset to monitor the player's alpha waves (an indicator of relaxation) and valence (an indicator of emotion or arousal). The game world is an emergent system of attractive and repulsive forces responding to EEG input.     

FAO’s AVHRR-based Agricultural Stress Index System (ASIS) for global drought monitoring

Agricultural production is highly dependent on climate variability in many parts of the world. In particular, drought may severely reduce crop yields, potentially affecting food availability at local, regional, and global scales. The Food and Agriculture Organization of the United Nations (FAO) operates the Global Early Warning System (GIEWS), which monitors global food supply and demand. One of the key challenges is to obtain synoptic information on a recurrent and timely basis about drought-affected agricultural zones. This is needed to quickly identify areas requiring immediate attention. The Agricultural Stress Index System (ASIS), based on imagery from the Advanced Very High Resolution Radiometer (AVHRR) sensors on board the National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational Satellite (METOP) satellites, was specifically developed to meet this need. The system is based on a methodology developed by Rojas, Vrieling, and Rembold over the African continent. This approach has been modified and adapted to the global scale to produce an agricultural stress index (ASI) representing, per administrative unit, the percentage of cropland (or pasture) areas affected by drought over the growing season. The vegetation health index (VHI), based on normalized difference vegetation index (NDVI) and temperature anomalies, is used as a drought indicator. A fused time series of AVHRR data from METOP and NOAA was used to produce a consistent time series of VHI at 1 km resolution. Global phenology maps, indicating the number of growing seasons and their start and end dates, were derived from a multi-annual image set of SPOT-Vegetation (1999–2011). The VHI time series and phenology maps were then combined to produce the ASI for the years 1984 to the present. This allowed evaluation of the suitability of the ASIS to identify drought using historical reports and ancillary data. As a result of this analysis, ASIS was positively evaluated to support the FAO early warning system.     

Model-driven assessment of system dependability

Designers of complex real-time systems need to address dependability requirements early on in the development process. This paper presents a model-based approach that allows developers to analyse the dependability of use cases and to discover more reliable and safe ways of designing the interactions of the system with the environment. The hardware design and the dependability of the hardware to be used also needs to be considered. We use a probabilistic extension of statecharts to formally model the interaction requirements defined in the use cases. The model is then evaluated analytically based on the success and failure probabilities of events. The analysis may lead to further refinement of the use cases by introducing detection and recovery measures to ensure dependable system interaction. A visual modelling environment for our extended statecharts formalism supporting automatic probability analysis has been implemented in AToM³, A Tool for Multi-formalism and Meta-Modelling. Our approach is illustrated with an elevator control system case study.

Early design stage exploration of fixed-length block structured architectures

An important challenge concerning the design of future microprocessors is that current design methodologies are becoming impractical due to long simulation runs and due to the fact that chip layout considerations are not incorporated in early design stages. In this paper, we show that statistical modeling can be used to speed up the architectural simulations and is thus viable for early design stage explorations of new microarchitectures. In addition, we argue that processor layouts should be considered in early design stages in order to tackle the growing importance of interconnects in future technologies. In order to show the applicability of our methodology which combines statistical modeling and processor layout considerations in an early design stage, we have applied our method on a novel architectural paradigm, namely a fixed-length block structured architecture. A fixed-length block structured architecture is an answer to the scalability problem of current architectures. Two important factors prevent contemporary out-of-order architectures from being scalable to higher levels of parallelism in future deep-submicron technologies: the increased complexity and the growing domination of interconnect delays. In this paper, we show by using statistical modeling and processor layout considerations, that a fixed-length block structured architecture is a viable architectural paradigm for future microprocessors in future technologies thanks to the introduction of decentralization and a reduced register file pressure.     

Meta-modelling and graph grammars for multi-paradigm modelling in AToM<Superscript>3</Superscript>

This paper presents the combined use of meta-modelling and graph grammars for the generation of visual modelling tools for simulation formalisms. In meta-modelling, formalisms are described at a meta-level. This information is used by a meta-model processor to generate modelling tools for the described formalisms. We combine meta-modelling with graph grammars to extend the model manipulation capabilities of the generated modelling tools: edit, simulate, transform into another formalism, optimize and generate code. We store all (meta-)models as graphs, and thus, express model manipulations as graph grammars.We present the design and implementation of these concepts in AToM³ (A_To_ol for M_ulti-formalism, M_eta-M_odelling). AToM³ supports modelling of complex systems using different formalisms, all meta-modelled in their own right. Models in different formalisms may be transformed into a single common formalism for further processing. These transformations are specified by graph grammars. Mosterman and Vangheluwe [18] introduced the term multi-paradigm modelling to denote the combination of multiple formalisms, multiple abstraction levels, and meta-modelling. As an example of multi-paradigm modelling we present a meta-model for the Object-Oriented Continuous Simulation Language OOCSMP, in which we combine ideas from UML class diagrams (to express the OOCSMP model structure), Causal Block Diagrams (CBDs), and Statecharts (to specify the methods of the OOCSMP classes). A graph grammar is able to generate OOCSMP code, and then a compiler for this language (C-OOL) generates Java applets for the simulation execution.     

Sub-pixel mapping and sub-pixel sharpening using neural network predicted wavelet coefficients

Sub-pixel mapping and sub-pixel sharpening are techniques for increasing the spatial resolution of sub-pixel image classifications. The proposed method makes use of wavelets and artificial neural networks. Wavelet multiresolution analysis facilitates the link between different resolution levels. In this work a higher resolution image is constructed after estimation of the detail wavelet coefficients with neural networks. Detail wavelet coefficients are used to synthesize the high-resolution approximation. The applied technique allows for both sub-pixel sharpening and sub-pixel mapping. An algorithm was developed on artificial imagery and tested on artificial as well as real synthetic imagery. The proposed method resulted in images with higher spatial resolution showing more spatial detail than the source imagery. Evaluation of the algorithm was performed both visually and quantitatively using established classification accuracy indices.     

Porous,Sintered Glass‐Ceramics from Inorganic Polymers Based on Fayalite Slag

The present paper deals with the synthesis of porous, sintered glass‐ceramics obtained at temperatures below 1150°C, originating from inorganic polymers based on fayalite slag. Firing led to the evaporation of water, dehydroxylation, and oxidation of Fe²⁺ above 345°C. For heating >700°C, the Si–O stretching band shifted from the 1160 and 750 cm^?1 to the 1255 and 830 cm^?1 region, due to a structural reorganization of the amorphous phase, whereas Fe–O bands appeared at 550 cm^?1. The final microstructure consisted predominantly of an amorphous phase, hematite, and franklinite. The open porosity and compressive strength decreased and increased, respectively, as the firing temperature increased. The final values suggest properties comparable to that of structural lightweight concrete, still, the materials synthesized herein, are lighter, and made primarily from secondary resources.     

Resistance of Listeria monocytogenes, Escherichia coli O157:H7 and Campylobacter jejuni after exposure to repetitive cycles of mild bactericidal treatments

While maintaining nutritional and sensorial attributes of fresh foods mild processing technologies generally deliver microbiologically perishable food products. Currently little information exists on possible increase in the resistance of pathogens after repetitive exposure to mild (sub-lethal) treatments. Multiple strain-cocktails of Listeria monocytogenes, Escherichia coli O157:H7 and Campylobacter jejuni were exposed to 20 consecutive cycles of sub-lethal inactivation by three different techniques. Used techniques comprised inactivation with lactic acid (LA), chlorine dioxide (ClO₂) and intense light pulses (ILP). Results showed that the selection of resistant cells was both species and technique dependent. While repetitive cycles of ClO₂ treatment did not result in increased resistance, repetitive inactivation with LA yielded L. monocytogenes culture of higher resistance in comparison to the parental culture. The increased resistance, expressed as decreased level of reduction in bacterial counts in subsequent inactivation cycles, was also observed with ILP for both L. monocytogenes and E. coli O157:H7 strains. Visual trend observations were confirmed through statistical linear regression analysis. No such effects were noted for C. jejuni which became undetectable after first 2–5 cycles. Current findings indicate the ability of foodborne pathogens to adapt to mild bactericidal treatments creating new challenges in risk assessment and more specifically in hazard analysis.