947 resultados para swd: Support-Vektor-Maschine
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Thesis written in co-mentorship with Robert Michaud.
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La tribune de l'éditeur / Editor's Soapbox
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Les glycosides sont reconnus pour leur potentiel pharmaceutique tels que les antibiotiques, les agents anticancéreux et antiviraux. Ils sont impliqués dans plusieurs processus biologiques entre autres la reconnaissance cellulaire, l’inflammation, la réponse immunitaire, la croissance, le transport cellulaire, l’adhésion cellulaire et les groupes sanguin. Notre groupe excelle dans la glycosidation stéréocontrôlée avec un minimum de protection suivant le concept d’activation à distance d’aglycones hétérocycliques anomériques. La présence d’une quantité sous stoechiométrique d’acide de Lewis, les (2-pyridyl)-β-D-glycosides déprotégés sont d’excellents donneurs permettant de haute sélectivité pour l’anomère- α-D de glycosides simples et complexes. Inversement, (2-pyridyl)-α-D-glycosides donnent les β-D-glycosides avec de bonne sélectivité. Des exemples de formation stéréocontrôlée de glycosides sont présentés dans cette thèse avec des accepteurs tels que les phénols, les stéroïdes, les terpènes et les acides hydroxyaminés. Cette méthodologie de glycosidation a été appliquée sur support solide.
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This paper presents a reform initiative, the Supporting Montreal Schools Program (SMSP), created by the government of Quebec to assist 184 low socio-economic-status schools in Montreal implement seven reform strategies prescribed by the government. On a regular basis, the professional team of the SMSP engages in reflection and research with universities concerning one or more of the strategies they are charged with helping schools implement or the functioning of the SMSP more generally. The present research programme is part of the team’s ongoing reflection on a component of Strategy 4: professional development of school administrators and the school team. In this paper, we detail results from this initial and subsequent studies on the work of principals in low-performing schools. We also describe our collaborative relationship with the SMSP team, discuss the effectiveness of the SMSP in promoting the implementation of the seven governmentmandated strategies and critique the utility of our partnership with the SMSP and our use of that programme as a vehicle for linking research to practice.
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Essai doctoral présenté à la Faculté des études supérieures en vue de l’obtention du grade de Docteur en psychologie (D.Psy.), option clinique
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Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.
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Glucoamylase was immobilized on acid activated montmorillonite clay via two different procedures namely adsorption and covalent binding. The immobilized enzymes were characterized by XRD, NMR and N2 adsorption measurements and the activity of immobilized glucoamylase for starch hydrolysis was determined in a batch reactor. XRD shows intercalation of enzyme into the clay matrix during both immobilization procedures. Intercalation occurs via the side chains of the amino acid residues, the entire polypeptide backbone being situated at the periphery of the clay matrix. 27Al NMR studies revealed the different nature of interaction of enzyme with the support for both immobilization techniques. N2 adsorption measurements indicated a sharp drop in surface area and pore volume for the covalently bound glucoamylase that suggested severe pore blockage. Activity studies were performed in a batch reactor. The adsorbed and covalently bound glucoamylase retained 49% and 66% activity of the free enzyme respectively. They showed enhanced pH and thermal stabilities. The immobilized enzymes also followed Michaelis–Menten kinetics. Km was greater than the free enzyme that was attributed to an effect of immobilization. The immobilized preparations demonstrated increased reusability as well as storage stability.
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Three enzymes, α-amylase, glucoamylase and invertase, were immobilized on acid activated montmorillonite K 10 via two independent techniques, adsorption and covalent binding. The immobilized enzymes were characterized by XRD, N2 adsorption measurements and 27Al MAS-NMR spectroscopy. The XRD patterns showed that all enzymes were intercalated into the clay inter-layer space. The entire protein backbone was situated at the periphery of the clay matrix. Intercalation occurred through the side chains of the amino acid residues. A decrease in surface area and pore volume upon immobilization supported this observation. The extent of intercalation was greater for the covalently bound systems. NMR data showed that tetrahedral Al species were involved during enzyme adsorption whereas octahedral Al was involved during covalent binding. The immobilized enzymes demonstrated enhanced storage stability. While the free enzymes lost all activity within a period of 10 days, the immobilized forms retained appreciable activity even after 30 days of storage. Reusability also improved upon immobilization. Here again, covalently bound enzymes exhibited better characteristics than their adsorbed counterparts. The immobilized enzymes could be successfully used continuously in the packed bed reactor for about 96 hours without much loss in activity. Immobilized glucoamylase demonstrated the best results.
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This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective
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In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576
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Process parameters influencing e-glutaminase production by marine Vibrio costicola in solid state fermentation (SSF) using polystyrene as an inert support were optimised. Maximal enzyme yield (157 U/g dry substrate) was obtained at 2% (w/w) t:glutamine, 35°C and pH 7.0 after 24 h. Maltose and potassium dihydrogen phosphate at 1% (w/w) concentration enhanced enzyme yield by 23 and 18%, respectively, while nitrogen sources had an inhibitory effect. Leachate with high specific activity for glutaminase (4.2 U/mg protein) and low viscosity (0-966 Ns/m 2) was recovered from the polystyrene SSF system
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Vorgestellt wird eine weltweit neue Methode, Schnittstellen zwischen Menschen und Maschinen für individuelle Bediener anzupassen. Durch Anwenden von Abstraktionen evolutionärer Mechanismen wie Selektion, Rekombination und Mutation in der EOGUI-Methodik (Evolutionary Optimization of Graphical User Interfaces) kann eine rechnergestützte Umsetzung der Methode für Graphische Bedienoberflächen, insbesondere für industrielle Prozesse, bereitgestellt werden. In die Evolutionäre Optimierung fließen sowohl die objektiven, d.h. messbaren Größen wie Auswahlhäufigkeiten und -zeiten, mit ein, als auch das anhand von Online-Fragebögen erfasste subjektive Empfinden der Bediener. Auf diese Weise wird die Visualisierung von Systemen den Bedürfnissen und Präferenzen einzelner Bedienern angepasst. Im Rahmen dieser Arbeit kann der Bediener aus vier Bedienoberflächen unterschiedlicher Abstraktionsgrade für den Beispielprozess MIPS ( MIschungsProzess-Simulation) die Objekte auswählen, die ihn bei der Prozessführung am besten unterstützen. Über den EOGUI-Algorithmus werden diese Objekte ausgewählt, ggf. verändert und in einer neuen, dem Bediener angepassten graphischen Bedienoberfläche zusammengefasst. Unter Verwendung des MIPS-Prozesses wurden Experimente mit der EOGUI-Methodik durchgeführt, um die Anwendbarkeit, Akzeptanz und Wirksamkeit der Methode für die Führung industrieller Prozesse zu überprüfen. Anhand der Untersuchungen kann zu großen Teilen gezeigt werden, dass die entwickelte Methodik zur Evolutionären Optimierung von Mensch-Maschine-Schnittstellen industrielle Prozessvisualisierungen tatsächlich an den einzelnen Bediener anpaßt und die Prozessführung verbessert.
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Abstract: The paper describes an auditory interface using directional sound as a possible support for pilots during approach in an instrument landing scenario. Several ways of producing directional sounds are illustrated. One using speaker pairs and controlling power distribution between speakers is evaluated experimentally. Results show, that power alone is insufficient for positioning single isolated sound events, although discrimination in the horizontal plane performs better than in the vertical. Additional sound parameters to compensate for this are proposed.