Archives parlementaires de 1787 à 1860 ; 34-51. Assemblée nationale législative. Série 1 / Tome 35 / impr. par ordre du Sénat et de la Chambre des députés ; sous la dir. de M. J. Mavidal,... et de M. E. Laurent,... ; avec la collab. de MM. E. Tonnier et C. Pionnier

Collection : Les archives de la Révolution française ; 3.1

Cahier contenant des notes, en turc, en persan, en arabe, dont les plus importantes sont (folio 6 verso) des fetvas relatifs aux biens de main-morte de Sainte-Sophie, et le commencement d'un traité d'Insha (folio 35 verso).

Ravius (Christiani Ravij Berlinatis) ; Thévenot.

Recueil de poésies, par « HENRY BAULDE » (fol. 30, 32, 35, 36, 37, 39, 40, 43, 44, 46, 47, 56, 59, 60, 61, 65, 68, 69, 70, 73, 74), « ALAIN CHARRETIER » (fol. 15), « JEHAN DAUTON » (fol. 9), « JEHAN MAROT » (fol. 29, 30), « JEHAN MOLINET » (fol. 77, 85, 90, 93, 94, 95) et « JEHAN ROBERTET » (fol. 1, 75).

Commençant par : « Estant couché soubz ung myrthe plaisant, Et maintz chasteaulx en Espaigne faisant... » et finissant par : « Sans parage ou riens n'est nect, Moulu d'un groz Moulinet. Fin de la complaincte de Grece, composée par le dict Molinet » .

Musée littéraire : choix de littérature contemporaine française et étrangère. Série 35

Collection : Le siècle ; 1-46

Observatorio de la seguridad en Bogotá : balance enero - septiembre de 2008. Delitos de mayor impacto y contravenciones penales. No. 35 noviembre de 2008

Gestión del conocimiento

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.

HG 188.30-188.35

Very fine grained. Organic matter present. Lineations can also be seen throughout, mainly in one orientation suggesting a masepic fabric.

HG 198.20-198.35 Thin Section

Coarse grained brown sediment with angular-sub-angular grains. Contains mainly medium sized clasts with a few smaller aggregates. A dark organic rich domain can be seen within this sample. Grain crushing (edge-to-edge and into one another) can be seen alongside with grain stacks, and silt caps.

HG 216.35-216.45

Brown, coarse grained sample. Clasts range from small to medium in size and sub-angular to angular. Patched of clay rich domains can be seen throughout the sample. Rotation with and without a central grain can be seen throughout the sample. Edge-to-edge grain crushing and grain stacking can be seen throughout the sample.

HG 261.25-261.35 Thin Section

Brown sediment with small clasts, and an occasional medium sized clast. Clasts appear to be sub-rounded in shape. The sample contains many lineations, the majority oriented in the same direction. There are also darker areas present in the sample, they may contain organics.

HG 458.25-458.35

Dark brown sediment, with clasts ranging from small to large. The sample mainly contained smaller clasts. The clast shape ranges from sub-angular to sub-rounded. Lineations were common throughout the sample. It also contained areas with dark organic material, and a few faint water escape structures.