927 resultados para Linear discriminant analysis
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The aim of this study is to investigate the influence of unusual writing positions on a person's signature, in comparison to a standard writing position. Ten writers were asked to sign their signature six times, in each of four different writing positions, including the standard one. In order to take into consideration the effect of the day-to-day variation, this same process was repeated over 12 sessions, giving a total of 288 signatures per subject. The signatures were collected simultaneously in an off-line and on-line acquisition mode, using an interactive tablet and a ballpoint pen. Unidimensional variables (height to width ratio; time with or without in air displacement) and time-dependent variables (pressure; X and Y coordinates; altitude and azimuth angles) were extracted from each signature. For the unidimensional variables, the position effect was assessed through ANOVA and Dunnett contrast tests. Concerning the time-dependent variables, the signatures were compared by using dynamic time warping, and the position effect was evaluated through classification by linear discriminant analysis. Both of these variables provided similar results: no general tendency regarding the position factor could be highlighted. The influence of the position factor varies according to the subject as well as the variable studied. The impact of the session factor was shown to cover the impact that could be ascribed to the writing position factor. Indeed, the day-to-day variation has a greater effect than the position factor on the studied signature variables. The results of this study suggest guidelines for best practice in the area of signature comparisons and demonstrate the importance of a signature collection procedure covering an adequate number of sampling sessions, with a sufficient number of samples per session.
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OBJECTIVE: Mild neurocognitive disorders (MND) affect a subset of HIV+ patients under effective combination antiretroviral therapy (cART). In this study, we used an innovative multi-contrast magnetic resonance imaging (MRI) approach at high-field to assess the presence of micro-structural brain alterations in MND+ patients. METHODS: We enrolled 17 MND+ and 19 MND- patients with undetectable HIV-1 RNA and 19 healthy controls (HC). MRI acquisitions at 3T included: MP2RAGE for T1 relaxation times, Magnetization Transfer (MT), T2* and Susceptibility Weighted Imaging (SWI) to probe micro-structural integrity and iron deposition in the brain. Statistical analysis used permutation-based tests and correction for family-wise error rate. Multiple regression analysis was performed between MRI data and (i) neuropsychological results (ii) HIV infection characteristics. A linear discriminant analysis (LDA) based on MRI data was performed between MND+ and MND- patients and cross-validated with a leave-one-out test. RESULTS: Our data revealed loss of structural integrity and micro-oedema in MND+ compared to HC in the global white and cortical gray matter, as well as in the thalamus and basal ganglia. Multiple regression analysis showed a significant influence of sub-cortical nuclei alterations on the executive index of MND+ patients (p = 0.04 he and R(2) = 95.2). The LDA distinguished MND+ and MND- patients with a classification quality of 73% after cross-validation. CONCLUSION: Our study shows micro-structural brain tissue alterations in MND+ patients under effective therapy and suggests that multi-contrast MRI at high field is a powerful approach to discriminate between HIV+ patients on cART with and without mild neurocognitive deficits.
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Members of the Chlamydiales order all share a biphasic lifecycle alternating between small infectious particles, the elementary bodies (EBs) and larger intracellular forms able to replicate, the reticulate bodies. Whereas the classical Chlamydia usually harbours round-shaped EBs, some members of the Chlamydia-related families display crescent and star-shaped morphologies by electron microscopy. To determine the impact of fixative methods on the shape of the bacterial cells, different buffer and fixative combinations were tested on purified EBs of Criblamydia sequanensis, Estrella lausannensis, Parachlamydia acanthamoebae, and Waddlia chondrophila. A linear discriminant analysis was performed on particle metrics extracted from electron microscopy images to recognize crescent, round, star and intermediary forms. Depending on the buffer and fixatives used, a mixture of alternative shapes were observed in varying proportions with stars and crescents being more frequent in C. sequanensis and P. acanthamoebae, respectively. No tested buffer and chemical fixative preserved ideally the round shape of a majority of bacteria and other methods such as deep-freezing and cryofixation should be applied. Although crescent and star shapes could represent a fixation artifact, they certainly point towards a diverse composition and organization of membrane proteins or intracellular structures rather than being a distinct developmental stage.
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Assuming selective vulnerability of short association U-fibers in early Alzheimer's disease (AD), we quantified demyelination of the surface white matter (dSWM) with magnetization transfer ratio (MTR) in 15 patients (Clinical Dementia Rating Scale [CDR] 0.5-1; Functional Assessment Staging [FAST]: 3-4) compared with 15 controls. MTRs were computed for 39 areas in each hemisphere. We found a bilateral MTR decrease in the temporal, cingulate, parietal, and prefrontal areas. With linear discriminant analysis, we successfully classified all the participants with 3 variates including the cuneus, parahippocampal, and superior temporal regions of the left hemisphere. The pattern of dSWM changed with the age of AD onset. In early onset patients, we found bilateral posterior demyelination spreading to the temporal areas in the left hemisphere. The late onset patients showed a distributed bilateral pattern with the temporal and cingulate areas strongly affected. A correlation with Mini Mental State Examination (MMSE), Lexis, and memory tests revealed the dSWM impact on cognition. A specific landscape of dSWM in early AD shows the potential of MTR imaging as an in vivo biomarker superior to currently used techniques.
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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.
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In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.
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Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.
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The concentration of 15 polycyclic aromatic hydrocarbons (PAHs) in 57 samples of distillates (cachaça, rum, whiskey, and alcohol fuel) has been determined by HPLC-Fluorescence detection. The quantitative analytical profile of PAHs treated by Partial Least Square - Discriminant Analysis (PLS-DA) provided a good classification of the studied spirits based on their PAHs content. Additionally, the classification of the sugar cane derivatives according to the harvest practice was obtained treating the analytical data by Linear Discriminant Analysis (LDA), using naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, benz[b]fluoranthene, and benz[g,h,i]perylene, as a chemical descriptors.
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AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.
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Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.
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Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.
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In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1,MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.
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L'interface cerveau-ordinateur (ICO) décode les signaux électriques du cerveau requise par l’électroencéphalographie et transforme ces signaux en commande pour contrôler un appareil ou un logiciel. Un nombre limité de tâches mentales ont été détectés et classifier par différents groupes de recherche. D’autres types de contrôle, par exemple l’exécution d'un mouvement du pied, réel ou imaginaire, peut modifier les ondes cérébrales du cortex moteur. Nous avons utilisé un ICO pour déterminer si nous pouvions faire une classification entre la navigation de type marche avant et arrière, en temps réel et en temps différé, en utilisant différentes méthodes. Dix personnes en bonne santé ont participé à l’expérience sur les ICO dans un tunnel virtuel. L’expérience fut a était divisé en deux séances (48 min chaque). Chaque séance comprenait 320 essais. On a demandé au sujets d’imaginer un déplacement avant ou arrière dans le tunnel virtuel de façon aléatoire d’après une commande écrite sur l'écran. Les essais ont été menés avec feedback. Trois électrodes ont été montées sur le scalp, vis-à-vis du cortex moteur. Durant la 1re séance, la classification des deux taches (navigation avant et arrière) a été réalisée par les méthodes de puissance de bande, de représentation temporel-fréquence, des modèles autorégressifs et des rapports d’asymétrie du rythme β avec classificateurs d’analyse discriminante linéaire et SVM. Les seuils ont été calculés en temps différé pour former des signaux de contrôle qui ont été utilisés en temps réel durant la 2e séance afin d’initier, par les ondes cérébrales de l'utilisateur, le déplacement du tunnel virtuel dans le sens demandé. Après 96 min d'entrainement, la méthode « online biofeedback » de la puissance de bande a atteint une précision de classification moyenne de 76 %, et la classification en temps différé avec les rapports d’asymétrie et puissance de bande, a atteint une précision de classification d’environ 80 %.
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La présente thèse regroupe deux articles qui examinent le rôle de l’anxiété sociale sur les comportements délinquants à l’adolescence. Pour le premier article, l’apport de l’anxiété sociale sur l’émergence de comportements de délinquance générale et relationnelle parmi 191 adolescents a été évalué. Les adolescents provenaient d’écoles secondaires de la province de Québec qui participaient à l’évaluation d’une stratégie d’intervention Agir Autrement (SIAA), une stratégie de prévention du décrochage scolaire en milieu défavorisé. L’échantillon obtenu a permis d’identifier deux groupes d’adolescents présentant des caractéristiques de délinquance générale ou relationnelle pour tester le rôle prédictif de l’anxiété sociale, de l’estime de soi, de l’isolement social et de la dépression sur leur profil de délinquance. Les résultats d’une analyse linéaire discriminante ont révélé qu’au-delà des facteurs individuels et sociaux testés, l’anxiété sociale prédit les trajectoires de délinquance deux ans plus tard. Pour le deuxième article, des analyses de trajectoires à partir d’analyses par équations structurelles ont été effectuées pour expliquer les associations prospectives entre l’anxiété sociale, la dépression et l’isolement social au début de l’adolescence sur les comportements de délinquance générale et relationnelle. Les résultats ont montré que l’anxiété sociale et l’isolement social sont des prédicteurs importants dans le développement de la délinquance relationnelle, toutefois la dépression ne s’est pas avérée prédictive. Ces études contribuent à la recherche dans le domaine de l’anxiété en expliquant l’importance de poursuivre les travaux pour mieux cerner le rôle de l’anxiété sociale et de l’isolement social chez les adolescents qui commettent des actes de délinquance relationnelle.
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Kurzfassung: Der Markt für ökologische Lebensmittel wächst stark. Verbraucher kaufen Produkte aus ökologischem Landbau aus einer Vielzahl von Gründen. Ein Teil dieser Gründe lässt sich nicht auf die Produktqualität zurückführen, sondern beruht auf der Annahme, dass sich der Produktionsprozess des Ökologischen Landbaus hinsichtlich der Schonung von Umweltressourcen, der Nachhaltigkeit der Produktion und sozialen Komponenten vom konventionellen Anbau unterscheidet. Daneben spielt der Wunsch nach einer gesunden Ernährung eine Rolle. Ökologische Lebensmittel können als Vertrauensgüter verstanden werden. Lebensmittelskandale machten in den vergangenen Jahren auch vor ökologischen Lebens¬mitteln nicht Halt. Folgerichtig erschütterte dies das Vertrauen der Verbraucher in ökologische Produkte. Mit steigender Produktion könnte die Gefahr, das weitere solche Ereignisse auftreten, steigen. Daher besteht Bedarf für Methoden, die die ökologische Produktqualität im Sinne einer Authentizitätsprüfung prüfen. Eine solche Prüfung könnte sich auf die Analyse sekundärer Pflanzenstoffe stützen. Diese Gruppe von Pflanzeninhaltsstoffen spielt bei der Diskussion um die besondere Qualität ökologischer Pflanzenprodukte eine große Rolle. Postuliert wird, dass ökologisch angebaute Pflanzen mangels mineralischer Düngung und mangels Schädlingsbekämpfung mit synthetischen Pestiziden einem erhöhten Stress ausgesetzt sind. Dies soll sich in einem höheren Niveau der mit den Selbstverteidigungsmechanismen der Pflanze eng verbundenen sekundären Pflanzenstoffe ausdrücken. Wichtige Untergruppen der sekundären Pflanzenstoffe sind Carotinoide und Polyphenole. An Weizen (Triticum aestivum L. und Triticum durum L.) und Möhre (Daucus carota L.) als für den ökologischen Landbau wichtigen Produkten wurden Messungen der Carotinoid- und Polyphenolkonzentration mit dem Ziel durchgeführt, die potentielle Eignung dieser Pflanzenstoffe als Biomarker zur Authentizitätsprüfung ökologischer Produkte zu evaluieren. Dazu wurden Proben aus ökologischem und konventionellem Anbau (Paarvergleich) untersucht. Diese stammten aus Langzeit-Feldversuchen (Weizen aus dem DOK- und dem MASCOT-Versuch), Feldversuchen und von Betriebspaaren untersucht. Ein generell höheres Niveau sekundärer Pflanzenstoffe in Möhren bzw. Weizen aus ökologischem Anbau gegenüber Proben aus konventionellem Anbau wurde nicht gefunden. Die Carotinoide waren weder bei der Möhre noch beim Weizen zur Authentizitätsprüfung geeignet. Die Konzentration der Carotinoide wurde stark durch die nicht dem Anbau¬verfahren zuzuordnenden Faktoren Klima, Sorte und Standort beeinflusst. Die Luteinkonzentration war das einzige durch das Anbauverfahren systematisch beeinflusste Carotenoid bei Weizen und Möhre. Die Unterschiede der Luteinkonzentration waren aber im Paarvergleich von Proben (ökologischer versus konventioneller Anbau) nicht durchgängig signifikant. Die Eignung von Polyphenolen als potentielles Authentizitätskriterium wurde nur an Möhren geprüft. Im Paarvergleich unterschieden sich die Konzentrationen einzelner Polyphenole signifikant und konsistent über Probenjahre und Standorte, nicht jedoch über Sorten hinweg. Wie bei den Carotinoiden konnte auch hier ein starker Einfluss von Probenjahr, Standort und Sorte gezeigt werden. Trotz der Variation durch diese nicht dem Anbau zuzuordnenden Faktoren war eine korrekte Klassifizierung der Proben nach Anbauverfahren möglich. Dies wurde mittels Diskriminanzanalyse getestet. Die Polyphenole sind daher potentiell als Authentizitätskriterium geeignet.