Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Evaluation of different methods for Plasmodia detection, in well defined population groups in an endemic area of Brazil

In Brazil, more than 500,000 new cases of malaria were notified in 1992. Plasmodium falciparum and P.vivax are the responsible species for 99.3% of the cases. For adequate treatment, precoce diagnosis is necessary. In this work, we present the results of the traditional Plasmodia detection method, thick blood film (TBF), and the results of alternative methods: Immunofluorescence assay (IFA) with polyclonal antibody and Quantitative Buffy Coat method (QBC)® in a well defined population groups. The analysis were done in relation to the presence or absence of malaria clinical symptoms. Also different classes of immunoglobulins anti-P.falciparum were quantified for the global analysis of the results, mainly in the discrepant results. We concluded that alternative methods are more sensitive than TBF and that the association of epidemiological, clinical and laboratory findings is necessary to define the presence of malaria.

Estrutura a partir do Movimento em Sistemas Autónomos

Mestrado em Engenharia Electrotécnica e de Computadores - Ramo de Sistemas Autónomos

Surveillance of arbovirus infections in the atlantic forest region, State of São Paulo, Brazil: I. detection of hemagglutination-inhibition antibodies in wild birds between 1978 and 1990

We report data related to arbovirus antibodies detected in wild birds periodically captured from January 1978 to December 1990 in the counties of Salesópolis (Casa Grande Station), Itapetininga and Ribeira Valley, considering the different capture environments. Plasmas were examined using hemagglutination-inhibition (HI) tests. Only monotypic reactions were considered, except for two heterotypic reactions in which a significant difference in titer was observed for a determined virus of the same antigenic group. Among a total of 39,911 birds, 269 birds (0.7%) belonging to 66 species and 22 families were found to have a monotypic reaction for Eastern equine encephalitis (EEE), Venezuelan equine encephalitis (VEE), Western equine encephalitis (WEE), Ilheus (ILH), Rocio (ROC), St. Louis encephalitis (SLE), SP An 71686, or Caraparu (CAR) viruses. Analysis of the data provided information of epidemiologic interest with respect to these agents. Birds with positive serology were distributed among different habitats, with a predominance of unforested habitats. The greatest diversity of positive reactions was observed among species which concentrate in culture fields.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

A toolbox for hyperspectral image analysis

This paper introduces a new toolbox for hyperspectral imagery, developed under the MATLAB environment. This toolbox provides easy access to different supervised and unsupervised classification methods. This new application is also versatile and fully dynamic since the user can embody their own methods, that can be reused and shared. This toolbox, while extends the potentiality of MATLAB environment, it also provides a user-friendly platform to assess the results of different methodologies. In this paper it is also presented, under the new application, a study of several different supervised and unsupervised classification methods on real hyperspectral data.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Usefulness of the detection of Toxoplasma gondii antigens in AIDS patients

Toxoplasmic encephalitis (TE) is a mayor cause of central nervous system infection in patients with acquired immunodeficiency syndrome (AIDS). Toxoplasma antibodies were detected in 56 of 79 patients with AIDS (71%), in the present study. Fourteen out of 57 seropositive patients developed TF (25%) and had Toxoplasma gondii antigen detected in their urine. For this, most of them received an effective therapy, with the subsequent disappearance of the symptoms and discontinuity of excretion of the T. gondii antigens. Our results suggest that the monitoring of T. gondii antigen in the urine of AIDS patients may be useful to decide on the proper time for therapy, as well as to avoid the beginning of neurologic signs in these patients.

Dot-enzyme-linked immunosorbent assay (Dot-ELISA) for detection of pneumococcal polysaccharide antigens in pleural fluid effusion samples.: Comparison with bacterial culture, counterimmunoelectrophoresis and latex agglutination

A dot-enzyme-linked immunosorbent assay (Dot-ELISA) for pneumococcal antigen detection was standardized in view of the need for a rapid and accurate immunodiagnosis of acute pneumococcal pneumonia. A total of 442 pleural fluid effusion samples (PFES) from children with clinical and laboratory diagnoses of acute bacterial pneumonia, plus 38 control PFES from tuberculosis patients and 20 negative control serum samples from healthy children were evaluated by Dot-ELISA. The samples were previously treated with 0.1 M EDTA pH 7.5 at 90°C for 10 min and dotted on nitrocellulose membrane. Pneumococcal omniserum diluted at 1:200 was employed in this assay for antigen detection. When compared with standard bacterial culture, counterimmunoelectrophoresis and latex agglutination techniques, the Dot-ELISA results showed relative indices of 0.940 to sensitivity, 0.830 to specificity and 0.760 to agreement. Pneumococcal omniserum proved to be an optimal polyvalent antiserum for the detection of pneumococcal antigen by Dot-ELISA. Dot-ELISA proved to be a practical alternative technique for the diagnosis of pneumococcal pneumonia.

Entamoeba histolytica: detection of coproantigens by purified antibody in the capture sandwich ELISA

A sensitive and specific Capture Sandwich ELISA (CSE) was developed using polyclonal purified rabbit antibodies against three different axenic strains of Entamoeba histolytica: CSP from Brazil and HM1 - IMSS from Mexico, for the detection of coproantigens in fecal samples. Immunoglobulin G (IgG) againstis E. histolytica was isolated from rabbits immunized with throphozoites whole extract in two stages: affinity chromatography in a column containing E. histolytica antigens bound to Sepharose 4B was followed by another chromatography in Sepharose antibodies 4B-Protein A. A Capture Sandwich ELISA using purified antibodies was able to detect 70ng of amebae protein, showing a sensitivity of 93% and specificity of 94%. The combination of microscopic examination and CSE gave a concordance and discordance of 93.25% and 6.75%, respectively. It was concluded that CSE is highly specific for the detection of coproantigens of E. histolytica in feces of infected patients, is quicker to perform, easier and more sensitive than microscopic examination.

Pattern of mycobacterial antigen detection in leprosy

Immunohistochemistry reaction (Peroxidase anti-peroxidase - PAP) was carried out on fifty-two skin biopsies from leprosy patients with the purpose to identify the antigenic pattern in mycobacteria and to study the sensitivity of this method. Five different patterns were found: bacillar, granular, vesicular, cytoplasmatic and deposits, classified according to the antigenic material characteristics. Deposits (thinely particulate material) appeared more frequently, confirming the immunohistochemistry sensitivity to detect small amounts of antigens even when this material is not detected by histochemical stainings.

Dot-ELISA for the detection of IgM and IgG antibodies to Schistosoma mansoni worm and egg antigens, associated with egg excretion by patients

Human schistosomiasis, caused by Schistosoma mansoni, is highly prevalent in Brazil and usually diagnosed by time consuming stool analysis. Serological tests are of limited use in this disease, mainly for epidemiological studies, showing no discrimination between previous contact with the parasite and active infections. In the present study, we standardized and compared a Dot-ELISA for IgM and IgG antibodies against S. mansoni antigens from eggs and worms with a routine IgG and IgM immunofluorescence assay using similar antigens, in the study of sera from 27 patients who had quantified egg stool excretion. The positivity obtained for IgG Dot-ELISA was 96.3% and 88.9% for IgM Dot-ELISA with worm antigen and 92.6% and 90.9% with egg antigen. The IFI presented similar positivities using worm antigen, 92.6% (IgG) and 96.3% (IgM),and lower results with egg antigen, 77.8% (IgG and IgM). The patients studied were divided into two groups according to their egg excretion, with greater positivity of serological tests in higher egg excreters. When comparing the quantitative egg excretion and the serological titers of the patients, we detected a correlation only with IgM Dot-ELISA, with r=0.552 (p=0.0127). These data show that Dot-ELISA can be used for the detection of specific antibodies against S. mansoni in sera from suspected patients or in epidemiological studies and, with further purification of egg antigen and larger samples, IgM Dot-ELISA could be a possible tool for rough estimates of parasite burden in epidemiological studies.

Central nervous system virion detection in acute measles: histopathological, ultrastructural and pathogenetic aspects

Histopathological and ultrastructural studies of 23 patients who died with clinical diagnosis of measles were carried out. In 12 cases viral nucleocapsids were searched by electron microscopy and detected in 100% of the cases in the lungs and in 50% of the cases in the central nervous system. They were mostly intranuclear. Histopathological changes associated to neurological alterations and the detection of virion are discussed in relation to acute and delayed clinical manifestations.

Bacterial antigen detection in cerebrospinal fluid by the latex agglutination test

Eighty purulent cerebrospinal fluid (CSF) samples from patients with clinical evidence of meningitis were studied using the Directigen latex agglutination (LA) kit to determine the presence of bacterial antigen in CSF. The results showed a better diagnostic performance of the LA test than bacterioscopy by Gram stain, culture and counterimmunoelectrophoresis (CIE), as far as Neisseria meningitidis groups B and C, and Haemophilus influenzae type b are concerned, and a better performance than bacterioscopy and culture considering Streptococcus pneumoniae. Comparison of the results with those of culture showed that the LA test had the highest sensitivity for the Neisseria meningitidis group C. Comparing the results with those of CIE, the highest levels of sensitivity were detected for N. meningitidis groups B and C. Regarding specificity, fair values were obtained for all organisms tested. The degree of K agreement when the LA test was compared with CIE exhibited better K indices of agreement for N. meningitidis groups B and C.

Detection of Cryptococcus neoformans capsular polysaccharide antigen in asymptomatic HIV-infected patients

Serum samples from 242 HIV-positive persons were studied for the detection of capsular polysaccha-ride antigen of Cryptococcus neoformans; 193 of these patients presented less than 300 CD4+ cells/µl of blood and 49 patients had more than 300 CD4+ cells/µl. None of them had symptoms or signs characteristic of cryptococcosis. The capsular antigen of C. neofarmans was detected by latex agglutination technique with pronase pre-treatment (IMMY, Crypto-Latex Antigen Detection System, Immunomycologics Inc., OK, USA); in 61% of the samples, ELISA technique was also used (Premier, Cryptococcal Antigen, Meridian Diagnostic Inc., Cincinatti, Oh, USA). The comparative study of both methods showed that the results obtained were similar in 96.9% of the cases. The capsular antigen was detected in 13 out of 193 (6.7%) patients with less than 300 CD4+ cells/µl. Cryptococcosis was confirmed mycologically in 3 of these 13 cases (23%) by the isolation of C. neoformans in CSF or blood cultures. Three patients, who had presented negative results of both tests for capsular antigen, suffered disseminated cryptococcosis 4 to 8 months later. The predictive diagnostic value of capsular antigen detection of C. neoformans seems tobe low and we believe that it should not be done routinely in asymptomatic HIV-positive persons.