Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)

Multi-temporal change detection is commonly used in the detection of changes to ecosystems. Differencing single band indices derived from multispectral pre- and post-fire images is one of the most frequently used change detection algorithms. In this paper we examine a commonly used index used in mapping fire effects due to wildland fire. Subtracting a post-fire from a pre-fire image derived index produces a measure of absolute change which then can be used to estimate total carbon release, biomass loss, smoke production, etc. Measuring absolute change however, may be inappropriate when assessing ecological impacts. In a pixel with a sparse tree canopy for example, differencing a vegetation index will measure a small change due stand-replacing fire. Similarly, differencing will produce a large change value in a pixel experiencing stand-replacing fire that had a dense pre-fire tree canopy. If all stand-replacing fire is defined as severe fire, then thresholding an absolute change image derived through image differencing to produce a categorical classification of burn severity can result in misclassification of low vegetated pixels. Misclassification of low vegetated pixels also happens when classifying severity in different vegetation types within the same fire perimeter with one set of thresholds. Comparisons of classifications derived from thresholds of dNBR and relative dNBR data for individual fires may result in similar classification accuracies. However, classifications of relative dNBR data can produce higher accuracies on average for the high burn severity category than dNBR classifications derived from a universal set of thresholds applied across multiple fires. This is important when mapping historic fires where precise field based severity data may not be available to aid in classification. Implementation of a relative index will also allow a more direct comparison of severity between fires across space and time which is important for landscape level analysis. In this paper we present a relative version of dNBR based upon field data from 14 fires in the Sierra Nevada mountain range of California, USA. The methods presented may have application to other types of disturbance events.     

Techniques for Computing Fitness of Use (FoU) for Time Series Datasets with Applications in the Geospatial Domain

Time series data are widely used in many applications including critical decision support systems. The goodness of the dataset, called the Fitness of Use (FoU), used in the analysis has direct bearing on the quality of the information and knowledge generated and hence on the quality of the decisions based on them. Unlike traditional quality of data which is independent of the application in which it is used, FoU is a function of the application. As the use of geospatial time series datasets increase in many critical applications, it is important to develop formal methodologies to compute their FoU and propagate it to the derived information, knowledge and decisions. In this paper we propose a formal framework to compute the FoU of time series datasets. We present three different techniques using the Dempster–Shafer belief theory framework as the foundation. These three approaches investigate the FoU by focusing on three aspects of data: data attributes, data stability, and impact of gap periods, respectively. The effectiveness of each approach is shown using an application in hydrological datasets that measure streamflow. While we use hydrological information analysis as our application domain in this research, the techniques can be used in many other domains as well.

Spectral feature analysis for assessment of water status and health level in coast live oak (Quercus agrifolia) leaves

Reflectance and relative water content (RWC %) were measured from a total of 306 coast live oak (Quercus agrifolia) leaf samples. The maximum (or minimum) first derivative (1D) and its corresponding wavelength position (WP) were extracted from 10 spectral slopes along each spectral reflectance curve. A correlation analysis was conducted between these spectral features (1Ds and WPs) and the corresponding RWC of oak leaves. An analysis of the variance of spectral features and RWC was also carried out between two health levels of oak leaves, healthy and infected. The results indicate that high correlations exist between some derivative spectral features (1Ds and WPs) and the RWC of oak leaves. With all 306 leaf spectra covering a wide range of RWC of oak leaves (including healthy, infected and newly dead), maximum (or minimum) derivative values at both sides of the absorption valleys near 1200, 1400 and 1940?nm and the WP of the right side of the 1200?nm valley and of both sides of the 1400?nm and 1940?nm valleys were found to have high correlations with RWC; and with a selection of 260 samples of only green and green–yellowish leaves (including only healthy and infected levels), the WPs at the right side of the 1400?nm valley, at the left side of the 1940?nm valley and at the red well each have a stable relationship with leave RWC. The result of an ANOVA of 20 spectral features suggests that the difference of some spectral features corresponding to two health levels of oak leaves is significant at a 0.95 confidence level, especially for the above-mentioned wavelength position features.     

A Hybrid Method for Quality Evaluation in the Context of Use for Mobile (3D) Television

Controlled psychoperceptual quality evaluation experiments are used to assess the excellence of produced audiovisual quality from fundamental signal processing algorithms to consumer services. When compromising produced quality for consumer services, used in dynamic and heterogeneous mobile contexts, the ecological validity of conventional quality evaluation methods can be questioned. The goal of this paper is to develop a method for evaluating the experienced multimedia quality in the context of use. We conducted three studies where the quality of mobile 2D and 3D television was assessed in three different field contexts, one simulated context and one controlled laboratory situation when audio-video compression and transmission parameters were varied. We propose a hybrid method for the design, data-collection and analysis of the experiments in the contexts of use. Its novelty is to complement conventional quantitative quality evaluation with concrete tools to identify factors that surround the assessment in the context. The methodological framework is part of our long-term aim to measure and understand the user-centered quality of experience.     

Combined in silico approaches for the identification of novel inhibitors of human islet amyloid polypeptide (hIAPP) fibrillation

Human islet amyloid polypeptide (hIAPP) is a natively unfolded polypeptide hormone of glucose metabolism, which is co-secreted with insulin by the β-cells of the pancreas. In patients with type 2 diabetes, IAPP forms amyloid fibrils because of diabetes-associated β-cells dysfunction and increasing fibrillation, in turn, lead to failure of secretory function of β-cells. This provides a target for the discovery of small organic molecules against protein aggregation diseases. However, the binding mechanism of these molecules with monomers, oligomers and fibrils to inhibit fibrillation is still an open question. In this work, ligand and structure-based in silico approaches were used to identify novel fibrillation inhibitors and/or fibril binding compounds. The best pharmacophore model was used as a 3D search query for virtual screening of a compound database to identify novel molecules having the potential to be therapeutic agents against protein aggregation diseases. Docking and molecular dynamics simulation studies were used to explore the interaction pattern and mechanism of the identified novel small molecules with predicted hIAPP structure, its aggregation prone conformation and fibril forming segments. We show that catechins with galloyl group and molecules having two to three planar apolar rings bind to hIAPP structures and fibril forming segments with greater affinity. The differences in binding affinities of different compounds against several fibril forming segments of the peptide suggest that a mixture of active compounds may be required for treatment of aggregation diseases.     

Novel e-nose for the discrimination of volatile organic biomarkers with an array of carbon nanotubes (CNT) conductive polymer nanocomposites (CPC) sensors

We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters.     

Application of an engineering algorithm with software code (C4.5) for specific ion detection in the chemical industries

The development of an on-line computer-based classification system for the automatic detection of different ions, existing in different solutions, is addressed using a machine learning algorithm. Different parameters (current, mass and resistance) were collected simultaneously. Then these laboratory measurements are used by an algorithm software as a logged data file, resulting in to inducing a decision tree. Later, a systematic software is designed based on the rules derived from this decision tree, to recognise the type of unknown solution used in the experiment. This is a new approach to data acquisition in chemical industries involving conducting polymers.     

The estimation of surface temperature over an agricultural area in the state of Haryana and Panjab,India, and its relationship with the Normalized Difference Vegetation Index (NDVI), using NOAA-AVHRR data

In this study, we attempted to determine surface temperature with a split window algorithm accounting for differential absorption effects of the Earth's atmosphere. We studied the dynamic response of surface temperature, over an extensive wheat-growing tract of India during different phenological stages of the crop, in relation to the normalized difference vegetation index (NDVI). Good agreement was obtained between the exponentially fitted surface temperatures recorded at the meteorological observatories, and the satellite-retrieved temperatures. We also observed a strong negative dynamic correlation between the NDVI and the retrieved surface temperature. We analysed the results on the basis of the phenology of the wheat crop, the land area under agriculture, and vegetation. Our study has indicated the utility of NDVI as a modulating parameter for the estimation of surface temperature.     

The narrative construction of our (social) world: steps towards an interactive learning environment for children with autism

Children with autism exhibit a deficit in narrative comprehension which adversely impacts upon their social world. The authors’ research agenda is to develop an interactive software system which promotes an understanding of narrative structure (and thus the social world) while addressing the needs of individual children. This paper reports the results from a longitudinal study, focussing on ‘primitive’ elements of narrative, presented as proto-narratives, in an interactive software game which adapts to the abilities of individual children. A correlation has been found with a real-world narrative comprehension task, and for most children a clear distinction in their understanding of narrative components.     

Generic platform for registration and online offering of assistance-on-demand (AoD) services in an inclusive infrastructure

Universal Access in the Information Society - An increasing percentage of the population needs assistance services for a wide range of activities related to their independent living, which can be...     

Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0-14.0 μm)

Field emissivity measurements were made of leaves collected from nine deciduous tree and agricultural plant species. The data show, for the first time, that it is possible to discriminate subtle spectral emissivity features of leaves from the natural background emission. Under conditions of controlled measurement geometry (leaves arranged to cover a flat surface), the field emissivity spectra agreed fairly well with emissivity values calculated from laboratory directional hemispherical reflectance measurements. Spectral features associated with a variety of leaf chemical constituents, including cellulose, cutin, xylan, silica, and oleanolic acid could be identified in the field emissivity data. Structural aspects of leaf surfaces also influenced spectral behavior, notably the abundance of trichomes, as well as wax thickness and texture.Field spectral measurements made at increasing distances from natural plant canopies showed progressive attenuation of the spectral emissivity features. This attenuation is ascribed to increased multiple scattering that superimposes an opposite-in-sign reflected component on the emittance, and to the increasing number of canopy voids within the instrument field of view. Errors associated with the removal of atmospheric features and with the non-isotropic thermal characteristics of canopies also contribute to the loss of spectral information at greater measurement distances.In contrast to visible and short-wave infrared data, thermal infrared spectra of broad leaf plants show considerable spectral diversity, suggesting that such data eventually could be utilized to map vegetation composition. However, remotely measuring the subtle emissivity features of leaves still presents major challenges. To be successful, sensors operating in the 8-14 μm atmospheric window must have high signal-to-noise and a small enough instantaneous field of view to allow measurements of only a few leaf surfaces. Methods for atmospheric compensation, temperature-emissivity separation, and spectral feature analysis also will need to be refined to allow the recognition, and perhaps, exploitation of leaf thermal infrared spectral properties.     

A conceptual model for the implementation of an Inter-Knowledge Objects Exchange System (IKOES) in automotive industry

The level of efficiency achieved in the diffusion of knowledge within an organisation is acknowledged to be a competitive advantage. As a result, various means have emerged to help share this knowledge. Among the various existing solutions, the use of parameterised files consistently encapsulating data of a refined level of granularity (e.g. figures, words, etc.) is a well-known practice. However, these files – which we will call Parameterised Knowledge Objects (PKOs) – often exhibit redundancy. This has led to a need for mapping, a fastidious work with no added value, which slows down the product redesign process. The goal of this article is to propose a conceptual model for the implementation of an automated tool to manage exchanges between these PKOs. The implementable nature of the model was validated by the development of a demonstrator, tested on an application provided by our industrial partner—the Renault Powertrain Technology Design Department.     

Comparison of data from the Scanning Multifrequency Microwave Radiometer (SMMR) with data from the Advanced Very High Resolution Radiometer (AVHRR) for terrestrial environmental monitoring: an overview

Abstract

Comparison between the microwave polarized difference temperature (MPDT) derived from 37 GHz band data and the normalized difference vegetation index (NDVI) derived from near-infrared and red bands, from several empirical investigations are summarized. These indicate the complementary character of the two measures in environmental monitoring. Overall the NDVI is more sensitive to green leaf activity, whereas the MPDT appears also to be related to other elements of the above-ground biomass. Monitoring of hydrological phenomena is carried out much more effectively by the MPDT. Further work is needed to explain spectral and temporal variation in MPDT both through modelling and field experiments.     

Sign changing solutions and multiple solutions of an elliptic eigenvalue problem with constraint in H1(RN)

In this paper, we prove the existence of sign changing solutions and multiple solutions of a semilinear elliptic eigenvalue problem. One of the key points here is to construct nonempty invariant sets of the gradient flow which contain the positive and the negative solution of the problem.     

A technique for monitoring SO2 in combustion exhausts: Use of a non-Nernstian sensing element in combination with an upstream catalytic filter

Detection of sulfur dioxide (SO₂) at high temperature (600–750 °C) in the presence of some interferents found in combustion exhausts (NO₂, NO, CO₂, CO, and hydrocarbon (C₃H₆)) is described. The detection scheme involves use of a catalytic filter in front of a non-Nernstian (mixed-potential) sensing element. The catalytic filter was a Ni:Cr powder bed operating at 850 °C, and the sensing elements were pairs of platinum (Pt) and oxide (Ba-promoted copper chromite ((Ba,Cu)_xCr_yO_z) or Sr-modified lanthanum ferrite (LSF)) electrodes on yttria-stabilized zirconia. The Ni:Cr powder bed was capable of reducing the sensing element response to NO₂, NO, CO, and C₃H₆, but the presence of NO₂ or NO (“NO_x”, at 100 ppm by volume) still interfered with the SO₂ response of the Pt–(Ba,Cu)_xCr_yO_z sensing element at 600 °C, causing approximately a 7 mV (20%) reduction in the response to 120 ppm SO₂ and a response equivalent to about 20 ppm SO₂ in the absence of SO₂. The Pt–LSF sensing element, operated at 750 °C, did not suffer from this NO_x interference but at the cost of a reduced SO₂ response magnitude (120 ppm SO₂ yielded 10 mV, in contrast to 30 mV for the Pt-(Ba,Cu)_xCr_yO_z sensing element). The powder bed and Pt–LSF sensing element were operated continuously over approximately 350 h, and the response to SO₂ drifted downward by about 7%, with most of this change occurring during the initial 100 h of operation.     

Assessing the efficiency of multispectral satellite and airborne hyperspectral images for land cover mapping in an aquatic environment with emphasis on the water caltrop (Trapa natans)

A number of clear issues are pertinent when considering whether, or not, to use a remotely sensed dataset. We evaluate these issues here by comparing an aerial hyperspectral image at 1.5 m geometric resolution that comprises 128 narrow bands within a spectral range between 400 nm and 1,000 nm as well as a nine-band Landsat 8 image at 30.0 m geometric resolution. We therefore applied Random Forest (RF) and Support Vector Machine (SVM) classifiers utilizing different input data sets to determine the best thematic accuracy for both types of images by involving all possible bands and then minimized them using variable selection and dimension reduction via Minimum Noise Fraction (MNF). We then compared Landsat images to an aerial hyperspectral one. The results of this analysis revealed that band selections based on variable importance and MNF-transformation improved thematic accuracy assessed as Overall Accuracy (OA). Results reveal a 1.00% improvement in OA via variable selection as 59 bands instead of 128 bands and a 1.50% via MNF-transformation of the hyperspectral image. This improvement was 4.52% in the Landsat image when using a MNF-transformation compared to the best performances without transformation or variable selection. Data also showed that application of Landsat spectral range on hyperspectral bands resulted in different outcomes; specifically, SVM resulted in a 91.50% OA while RF resulted in 95.50% OA. Landscape ecology results show that use of the Landsat image provided fewer land cover patches and that differences encompassed 6.30% of the whole area. We therefore conclude that Landsat data can be used with a number of limitations for accurate ecological mapping.     

Surface plasmon resonance imaging (SPRi) as an alternative technique for rapid and quantitative screening of small molecules, useful in drug discovery

Surface plasmon resonance imaging (SPRi) is a label free technology for biomolecular interaction, which gives access to binding kinetic parameters from real time acquisition. It offers the possibility to test in a single run a large number of interactions, allowing rapid identification of the most suitable compounds toward a given biological entity. Until now, this technique has proven to be relevant for interaction between relatively large molecules (protein, antibodies, DNA) but has not been challenged yet for the screening of small molecules that can be of interested in the field of drug discovery. As a proof a principle, we have used SPRi to screen for interaction of several small molecules, referred to as G4-ligands on G-quadruplex DNA. This technology allowed to easy discrimination of the binding properties of four G4-ligands on quadruplex DNA models.     

Searching for information in an online public access catalogue (OPAC): the impacts of information search expertise on the use of Boolean operators

Abstract Boolean systems still constitute most of the installed base of online public access catalogues (OPACs) in the French universities even if many studies have shown that Boolean operators are not frequently used by ‘non‐librarian’ users (by contrast with professional librarians). The first study examined the use of Boolean operators by French university students; In the second study, elaborated to evaluate the impact of information search expertise on this use, Boolean operators are explicitly presented and participants were explicitly invited to use them. We assumed that university students would not frequently use the operators in searching, and that even if they were explicitly invited to make use of them. Results obtained with the first study based on transaction logs analyses confirmed that French university students did not frequently use Boolean operators. The impact of information search expertise, analysed in the second study, compared three levels of expertise: Novice (university students), intermediate (future professional librarians), and expert (professional librarians). Results showed that, even if the three groups were invited to use Boolean operators, this use increased significantly with the level of information search expertise. University students, if they manage procedural functions of connectives in natural language, do not always manage the whole set of procedural functions carried by such connectives when used in the documentary language. So, the relevance of presenting explicit Boolean operators in the OPACs when users are ‘non‐librarians’ is questioned.