UV dosimeter based on dichloroindophenol and tin(IV) oxide

A UVB specific dosimeter is described comprising: a redox dye (2,6-dichloroindophenol, DCIP), a semiconductor ( tin(IV) oxide, SnO2) and a sacrificial electron donor ( glycerol) dispersed in a polymer ( hydroxy ethyl cellulose, HEC) film. The dosimeter is blue in the absence of UVB light but rapidly loses colour on exposure to UVB light. The spectral characteristics of a typical UVB dosimeter film and the mechanism by which the colour change occurs are detailed. DCIP UVB dosimeter films exhibit a response that is related to the irradiance level and duration of UVB exposure, the level of SnO2 present and to a lesser extent the level of glycerol present. The response of the dosimeter appears to be independent of dye concentration and film thickness. Furthermore, DCIP UVB dosimeter films respond to solar simulated light, exhibiting a colour loss that can be simply related to the Minimal Erythemal Dose (MED) exposure for skin type II. As a consequence, such indicators have potential for measuring solar radiation exposure and providing an early warning of erythema for most Caucasian skin (i.e. skin type II).

Nanocrystalline SnO2-based, UVB-activated, colourimetric oxygen indicator

Nanocrystalline SnO2, ncSnO(2), is used as a photosensitiser in a colourimetric O-2 indicator that comprises a sacrificial electron donor, glycerol, a redox dye, methylene blue (MB), and an encapsulating polymer, hydroxyethyl cellulose (HEC). Upon exposure to a burst of UVB light the indicator is activated (photo-bleached) as the MB is photoreduced by the ncSnO(2) particles. In the absence of oxygen, the film stays bleached, but recovers its original colour upon exposure to oxygen. Unlike its TiO2-based predecessor, the HEC/glycerol/MB/ncSnO(2) O-2 indicator is not activated by UVA light from white fluorescent lamps, but is by UVB light. This feature provides much greater control in the activation of the indicator. Other work shows the rate of activation depends upon I-0.75, where I is the UVB irradiance, indicating a partial dependence upon the electron-hole recombination process. The half-life of the recovery of the original colour of a UV-activated film, t(50), is directly proportional to the ambient level of oxygen. The advantages of using this indicator in modified atmosphere packaging as a possible quality assurance indicator are discussed briefly. (c) 2008 Elsevier B.V. All rights reserved.

UV dosimeters based on neotetrazolium chloride

A novel UV dosimeter is described comprising a tetrazolium dye, neotetrazolium chloride (NTC), dissolved in a film of polymer, polyvinyl alcohol (PVA). The dosimeter is pale yellow/colourless in the absence of UV light, and turns red upon exposure to UV light. The spectral characteristics of a typical UV dosimeter film and the mechanism through which the colour change occurs are detailed. The NTC UV dosimeter films exhibit a response to UV light that is related to the intensity and duration of UV exposure, the level of dye present in the films and the thickness of the films themselves. The response of the dosimeter is temperature independent over the range 20-40 degrees C and, like most UV dosimeters, exhibits a cosine-like response dependence upon irradiance angle. The introduction of a layer of a UV-screening compound which slows the rate at which the dosimeter responds to UVR enables the dosimeter response to be tailored to different UV doses. The possible use of these novel dosimeters to measure solar UV exposure dose is discussed. (c) 2008 Elsevier B.V. All rights reserved.

A solvent-based intelligence ink for oxygen

A solvent-based, irreversible oxygen indicator ink is described, comprising semiconductor photocatalyst nanoparticles, a solvent-soluble redox dye, mild reducing agent and polymer. Based on such an ink, a film - made of titanium dioxide, a blue, solvent-soluble, coloured ion-paired methylene blue dye, glycerol and the polymer zein - loses its colour rapidly (

A viologen-based UV indicator and dosimeter

A UV indicator/dosimeter based on benzyl viologen (BV2+) encapsulated in polyvinyl alcohol (PVA) is described. Upon exposure to UV light, the BV2+/PVA film turns a striking purple colour due to the formation of the cation radical, BV center dot+. The usual oxygen sensitivity of BV center dot+ is significantly reduced due to the very low oxygen permeability of the encapsulating polymer, PVA. Exposure of a typical BV2+/PVA film, for a set amount of time, to UVB light with different UV indices produces different levels of BV center dot+, as measured by the absorbance of the film at 550 nm. A plot of the change in absorbance at this wavelength, Delta Abs(550), as a function of UV index, UVI, produces a linear calibration curve which allows the film to be used as a UVB indicator, and a similar procedure could be employed to allow it to be used as a solar UVI indicator. A typical BV2+/PVA film generates a significant, semi-permanent (stable for > 24 h) saturated purple colour (absorbance similar to 0.8-0.9) upon exposure to sunlight equivalent to a minimal erythemal dose associated with Caucasian skin, i.e. skin type II. The current drawbacks of the film and the possible future use of the BV2+/PVA film as a personal solar UV dosimeter for all skin types are briefly discussed.

The comparative solvatochromism of arylazo and heteroarylazo compounds based on N,N-diethyl-m-acetylaminoaniline and N,N-diethyl-m-toluidine

Azobenzene dyes derived from various anilines and aminothiaheterocycles ate-coupled with commercially important N,N-diethyl-m-toluidine (T series) and iv,N-diethyl-m-acetylaminoaniline (A series) are positively solvatochromic. The visible spectra of 16 pairs of derivatives have been measured in up to 22 solvents, and the transition energies related to Kamlet-Taft solvent polarity parameters. In general, A-series dyes are more bathochromic than their T-series counterparts in nonpolar solvents, consistent with colour chemistry tradition, However, in more dipolar solvents the more bathochromic T-series representatives unexpectedly become more bathochromic than their A-series partners. The relative solvatochromic shifts of the A and T series are related to their respective dipole moments, These in turn are distinguished by the effect of the anilide carbonyl group dipole moment, which is antiparallel to, and thus reduces, the dipole moment of the chromogen.

Human figure segmentation using independent component analysis

In this paper, we present a Statistical Shape Model for Human Figure Segmentation in gait sequences. Point Distribution Models (PDM) generally use Principal Component analysis (PCA) to describe the main directions of variation in the training set. However, PCA assumes a number of restrictions on the data that do not always hold. In this work, we explore the potential of Independent Component Analysis (ICA) as an alternative shape decomposition to the PDM-based Human Figure Segmentation. The shape model obtained enables accurate estimation of human figures despite segmentation errors in the input silhouettes and has really good convergence qualities.

Equidiscrimination contours around an achromatic colour are convex but not balanced

A model based on the postreceptor channels followed by a Minkowski norm (Minkowski model) is widely used to fit experimental data on colour discrimination. This model predicts that contours of equal discrimination in colour space are convex and balanced (symmetrical). We have tested these predictions in an experiment. Two new statistical tests have been developed to analyse convexity and balancedness of experimental curves. Using these tests we have found that while they are in line with the convexity prediction, our experimental contours strongly testify against balancedness. It follows that the Minkowski model is, generally, inappropriate to model colour discrimination data. © 2002 Elsevier Science (USA).

IPPro: FPGA based Image Processing Processor

The paper presents IPPro which is a high performance, scalable soft-core processor targeted for image processing applications. It has been based on the Xilinx DSP48E1 architecture using the ZYNQ Field Programmable Gate Array and is a scalar 16-bit RISC processor that operates at 526MHz, giving 526MIPS of performance. Each IPPro core uses 1 DSP48, 1 Block RAM and 330 Kintex-7 slice-registers, thus making the processor as compact as possible whilst maintaining flexibility and programmability. A key aspect of the approach is in reducing the application design time and implementation effort by using multiple IPPro processors in a SIMD mode. For different applications, this allows us to exploit different levels of parallelism and mapping for the specified processing architecture with the supported instruction set. In this context, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the colour and morphology operations accelerated using multiple IPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 to 33 times for colour filtering and morphology operations respectively, with a reduced design effort and time.

Automatically Annotating Structured Web Data Using a SVM-Based Multiclass Classifier

In this paper, we propose a new learning approach to Web data annotation, where a support vector machine-based multiclass classifier is trained to assign labels to data items. For data record extraction, a data section re-segmentation algorithm based on visual and content features is introduced to improve the performance of Web data record extraction. We have implemented the proposed approach and tested it with a large set of Web query result pages in different domains. Our experimental results show that our proposed approach is highly effective and efficient.

A new look towards BAC-based array CGH through a comprehensive comparison with oligo-based array CGH

BACKGROUND: Currently, two main technologies are used for screening of DNA copy number; the BAC (Bacterial Artificial Chromosome) and the recently developed oligonucleotide-based CGH (Chromosomal Comparative Genomic Hybridization) arrays which are capable of detecting small genomic regions with amplification or deletion. The correlation as well as the discriminative power of these platforms has never been compared statistically on a significant set of human patient samples.

RESULTS: In this paper, we present an exhaustive comparison between the two CGH platforms, undertaken at two independent sites using the same batch of DNA from 19 advanced prostate cancers. The comparison was performed directly on the raw data and a significant correlation was found between the two platforms. The correlation was greatly improved when the data were averaged over large chromosomic regions using a segmentation algorithm. In addition, this analysis has enabled the development of a statistical model to discriminate BAC outliers that might indicate microevents. These microevents were validated by the oligo platform results.

CONCLUSION: This article presents a genome-wide statistical validation of the oligo array platform on a large set of patient samples and demonstrates statistically its superiority over the BAC platform for the Identification of chromosomic events. Taking advantage of a large set of human samples treated by the two technologies, a statistical model has been developed to show that the BAC platform could also detect microevents.

Two-part Segmentation of Text Documents

We consider the problem of segmenting text documents that have a
two-part structure such as a problem part and a solution part. Documents
of this genre include incident reports that typically involve
description of events relating to a problem followed by those pertaining
to the solution that was tried. Segmenting such documents
into the component two parts would render them usable in knowledge
reuse frameworks such as Case-Based Reasoning. This segmentation
problem presents a hard case for traditional text segmentation
due to the lexical inter-relatedness of the segments. We develop
a two-part segmentation technique that can harness a corpus
of similar documents to model the behavior of the two segments
and their inter-relatedness using language models and translation
models respectively. In particular, we use separate language models
for the problem and solution segment types, whereas the interrelatedness
between segment types is modeled using an IBM Model
1 translation model. We model documents as being generated starting
from the problem part that comprises of words sampled from
the problem language model, followed by the solution part whose
words are sampled either from the solution language model or from
a translation model conditioned on the words already chosen in the
problem part. We show, through an extensive set of experiments on
real-world data, that our approach outperforms the state-of-the-art
text segmentation algorithms in the accuracy of segmentation, and
that such improved accuracy translates well to improved usability
in Case-based Reasoning systems. We also analyze the robustness
of our technique to varying amounts and types of noise and empirically
illustrate that our technique is quite noise tolerant, and
degrades gracefully with increasing amounts of noise

A frontal view gait recognition based on 3D imaging using a time of flight camera

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
Project Source Code