Bioinformatics techniques to protein secondary structure prediction mostly depend on the information available in amino acid sequence. Support vector machines (SVM) have shown strong generalization ability in a number of application areas, including protein structure prediction. In this study, a new sliding window scheme is introduced with multiple windows to form the protein data for training and testing SVM. Orthogonal encoding scheme coupled with BLOSUM62 matrix is used to make the prediction. First the prediction of binary classifiers using multiple windows is compared with single window scheme, the results shows single window not to be good in all cases. Two new classifiers are introduced for effective tertiary classification. This new classifiers use neural networks and genetic algorithms to optimize the accuracy of the tertiary classifier. The accuracy level of the new architectures are determined and compared with other studies. The tertiary architecture is better than most available techniques.

<p>Simultaneous Localisation And Mapping SLAM-problemet är ett robotikproblem som består av att låta en robot kartlägga ett tidigare okänt område, och samtidigt lokalisera sig i den skapade kartan. Det här exjobbet presenterar ett försök till en lösning på SLAM-problemet som fungerar i konstant tid i en urban miljö. En sådan lösning måste hantera en datamängd som ständigt ökar, utan att beräkningskomplexiteten ökar signifikant.</p><p>Ett informationsfilter på fördröjd tillståndsform används för estimering av robotens trajektoria, och kamera och laseravståndssensorer används för att samla spatial information om omgivningarna längs färdvägen. Två olika metoder för att detektera loopslutningar föreslås. Den första är bildbaserad och använder Tree of Words för jämförelse av bilder. Den andra metoden är laserbaserad och använder en tränad klassificerare för att jämföra laserscans. När två posar, position och riktning, kopplats samman i en loopslutning beräknas den relativa posen med laserscansinriktning med hjälp av en kombination av Conditional Random Field-Match och Iterative Closest Point.</p><p>Experiment visar att både bild- och laserscansbaserad loopslutningsdetektion fungerar bra i stadsmiljö, och resulterar i good estimering av kartan såväl som robotens trajektoria.</p> / <p>In robotics, the Simultaneous Localisation And Mapping SLAM problem consists of letting a robot map a previously unknown environment, while simultaneously localising the robot in the same map. In this thesis, an attempt to solve the SLAM problem in constant time in a complex environment, such as a suburban area, is made. Such a solution must handle increasing amounts of data without significant increase in computation time.</p><p>A delayed state information filter is used to estimate the robot's trajectory, and camera and laser range sensors are used to acquire spatial information about the environment along the trajectory. Two approaches to loop closure detection are proposed. The first is image based using Tree of Words for image comparison. The second is laser based using a trained classifier for laser scan comparison. The relative pose, the difference in position and heading, of two poses matched in loop closure is calculated with laser scan alignment using a combination of Conditional Random Field-Match and Iterative Closest Point.</p><p>Experiments show that both image and laser based loop closure detection works well in a suburban area, and results in good estimation of the map as well as the robot's trajectory.</p>

Simultaneous Localisation And Mapping SLAM-problemet är ett robotikproblem som består av att låta en robot kartlägga ett tidigare okänt område, och samtidigt lokalisera sig i den skapade kartan. Det här exjobbet presenterar ett försök till en lösning på SLAM-problemet som fungerar i konstant tid i en urban miljö. En sådan lösning måste hantera en datamängd som ständigt ökar, utan att beräkningskomplexiteten ökar signifikant. Ett informationsfilter på fördröjd tillståndsform används för estimering av robotens trajektoria, och kamera och laseravståndssensorer används för att samla spatial information om omgivningarna längs färdvägen. Två olika metoder för att detektera loopslutningar föreslås. Den första är bildbaserad och använder Tree of Words för jämförelse av bilder. Den andra metoden är laserbaserad och använder en tränad klassificerare för att jämföra laserscans. När två posar, position och riktning, kopplats samman i en loopslutning beräknas den relativa posen med laserscansinriktning med hjälp av en kombination av Conditional Random Field-Match och Iterative Closest Point. Experiment visar att både bild- och laserscansbaserad loopslutningsdetektion fungerar bra i stadsmiljö, och resulterar i good estimering av kartan såväl som robotens trajektoria. / In robotics, the Simultaneous Localisation And Mapping SLAM problem consists of letting a robot map a previously unknown environment, while simultaneously localising the robot in the same map. In this thesis, an attempt to solve the SLAM problem in constant time in a complex environment, such as a suburban area, is made. Such a solution must handle increasing amounts of data without significant increase in computation time. A delayed state information filter is used to estimate the robot's trajectory, and camera and laser range sensors are used to acquire spatial information about the environment along the trajectory. Two approaches to loop closure detection are proposed. The first is image based using Tree of Words for image comparison. The second is laser based using a trained classifier for laser scan comparison. The relative pose, the difference in position and heading, of two poses matched in loop closure is calculated with laser scan alignment using a combination of Conditional Random Field-Match and Iterative Closest Point. Experiments show that both image and laser based loop closure detection works well in a suburban area, and results in good estimation of the map as well as the robot's trajectory.

Fluid inclusion and mineralogical features indicative of boiling have been characterized in 855 samples from epithermal precious metals deposits along the Veta Madre at Guanajuato, Mexico. Features associated with boiling that have been identified at Guanajuato include colloform texture silica, plumose texture silica, moss texture silica, ghost-sphere texture silica, lattice-bladed calcite, lattice-bladed calcite replaced by quartz and pseudo-acicular quartz after calcite and coexisting liquid-rich and vapor-rich fluid inclusions. Most samples were assayed for Au, Ag, Cu, Pb, Zn, As and Sb, and were divided into high-grade and low-grade samples based on the gold and silver concentrations. For silver, the cutoff for high grade was 100 ppm Ag, and for gold the cutoff was 1 ppm Au. The feature that is most closely associated with high grades of both gold and silver is colloform texture silica, and this feature also shows the largest difference in grade between the presence or absence of that feature (178.8 ppm Ag versus 17.2 ppm Ag, and 1.1 ppm Au versus 0.2 ppm Au). For both Ag and Au, there is no significant difference in average grade as a function of whether or not coexisting liquid-rich and vapor-rich fluid inclusions are present. The textural and fluid inclusion data obtained in this study were analyzed using the binary classifier within SPSS Clementine. The models that correctly predicted high versus low grade samples most consistently (~70-75% of the tests) for both Ag and Au were the neural network, the C5 decision tree and Quest decision tree models. For both Au and Ag, the presence of colloform silica texture was the variable with the greatest importance, i.e., the variable that has the greatest predictive power. Boiling features are absent or rare in samples collected along a traverse perpendicular to the Veta Madre. This suggests that if an explorationist observes these features in samples collected during exploration that an environment favorable to precious metal mineralization is nearby. Similarly, good evidence for boiling is observed in the deepest levels of the Veta Madre that have been sampled in the mines and drill cores, suggesting that additional precious metal reserves are likely beneath the deepest levels sampled. / Master of Science