Land cover classification with multi-sensor fusion of partly missing data

We describe a system that uses decision tree-based tools for seamless acquisition of knowledge for classification of remotely sensed imagery. We concentrate on three important problems in this process: information fusion, model understandability, and handling of missing data. Importance of multi-sensor information fusion and the use of decision tree classifiers for such problems have been well-studied in the literature. However, these studies have been limited to the cases where all data sources have a full coverage for the scene under consideration. Our contribution in this paper is to show how decision tree classifiers can be learned with alternative (surrogate) decision nodes and result in models that are capable of dealing with missing data during both training and classification to handle cases where one or more measurements do not exist for some locations. We present detailed performance evaluation regarding the effectiveness of these classifiers for information fusion and feature selection, and study three different methods for handling missing data in comparative experiments. The results show that surrogate decisions incorporated into decision tree classifiers provide powerful models for fusing information from different data layers while being robust to missing data. © 2009 American Society for Photogrammetry and Remote Sensing

Interactive training of advanced classifiers for mining remote sensing image archives

Advances in satellite technology and availability of down-loaded images constantly increase the sizes of remote sensing image archives. Automatic content extraction, classification and content-based retrieval have become highly desired goals for the development of intelligent remote sensing databases. The common approach for mining these databases uses rules created by analysts. However, incorporating GIS information and human expert knowledge with digital image processing improves remote sensing image analysis. We developed a system that uses decision tree classifiers for interactive learning of land cover models and mining of image archives. Decision trees provide a promising solution for this problem because they can operate on both numerical (continuous) and categorical (discrete) data sources, and they do not require any assumptions about neither the distributions nor the independence of attribute values. This is especially important for the fusion of measurements from different sources like spectral data, DEM data and other ancillary GIS data. Furthermore, using surrogate splits provides the capability of dealing with missing data during both training and classification, and enables handling instrument malfunctions or the cases where one or more measurements do not exist for some locations. Quantitative and qualitative performance evaluation showed that decision trees provide powerful tools for modeling both pixel and region contents of images and mining of remote sensing image archives

Templated self-assembly of the bacterial flagellar motor torque ring in vitro

The Bacterial Flagellar Motor is an ion-driven rotary motor employed by many bacteria for motility and surface sensing, and a model system for the self-assembly and regulation of large protein complexes. Early in motor biogenesis a ring of the integral membrane protein FliF templates the cytoplasmic assembly of FliG, which subsequently templates transient incorporation of FliM1:FliN3 subunits. FliG, FliM and FliN collectively comprise the C-ring: site of torque generation and directional switching. Switching is regulated by binding of CheY-P to FliM1:FliN3, propagating a co-operative conformational change throughout the entire C-ring. The molecular details of C-ring structure, assembly and dynamics are unclear. Averaged cryo-EM structures of purified motors feature a curious symmetry mismatch between the FliF ring (~26-fold) and C-ring (~34-fold), while in vivo fluorescence shows a variation in FliM1:FliN3 population with rotation direction that is not resolved in the EM structures. The stoichiometries of FliG/M/N are all disputed, and cannot yet be measured accurately in vivo. More powerful techniques are available in vitro, but it is unclear whether dynamic structural features of the motor survive purification. Therefore, we aspire to assemble a C-ring in vitro as a platform for in vitro study. Furthermore, by substituting the difficult-to-reconstitute FliF template with a controllable DNA-origami mimic, we envisage studying self-assembly from the bottom up through template remodelling: a novel concept in the study of protein self-assembly. This thesis describes the development of linear DNA templates mimicking short fragments of the FliF ring. FliG arrangement on these templates is specified by DNA sequence design, and can be quantified with single-molecule fluorescence and native gel electrophoresis. The methods developed here will allow testing of the FliG domain-swap polymerization model as a mechanistic explanation for the symmetry mismatch, and lay the foundations for in vitro construction of a complete C-ring.</p

Subunit exchange in protein complexes

Over the past 50 years, protein complexes have been studied with techniques such as X-ray crystallography and electron microscopy, generating images which although detailed are static and homogeneous. More recently, limited application of in vivo fluorescence and other techniques has revealed that many complexes previously thought stable and compositionally uniform are dynamically variable, continually exchanging components with a freely circulating pool of “spares.” Here, we consider the purpose and prevalence of protein exchange, first reviewing the ongoing story of exchange in the bacterial flagella motor, before surveying reports of exchange in complexes across all domains of life, together highlighting great diversity in timescales and functions. Finally, we put this in the context of high-throughput proteomic studies which hint that exchange might be the norm, rather than an exception

DNA scaffolds support stable and uniform peptide nanopores

The assembly of peptides into membrane-spanning nanopores might be promoted by scaffolds to pre-organize the structures. Such scaffolds could enable the construction of uniform pores of various sizes and pores with controlled permutations around a central axis. Here, we show that DNA nanostructures can serve as scaffolds to arrange peptides derived from the octameric polysaccharide transporter Wza to form uniform nanopores in planar lipid bilayers. Our ring-shaped DNA scaffold is assembled from short synthetic oligonucleotides that are connected to Wza peptides through flexible linkers. When scaffolded, the Wza peptides form conducting nanopores of which only octamers are stable and of uniform conductance. Removal of the DNA scaffold by cleavage of the linkers leads to a rapid loss of the nanopores from the lipid bilayer, which shows that the scaffold is essential for their stability. The DNA scaffold also adds functionality to the nanopores by enabling reversible and permanent binding of complementary tagged oligonucleotides near the nanopore entrance

Transportation submarine type Kobben of Naval Shipyard into the Polish Naval Academy and selected aspects of safety

W artykule zaprezentowano charakterystykę operacji transportowych okrętu podwodnego typu Kobben z Portu Wojennego Gdynia do Akademii Marynarki Wojennej oraz wybranych aspektów bezpieczeństwa. Operacja transportu okrętu rozpoczęła się w Stoczni Marynarki Wojennej od zadokowania okrętu na specjalny ponton. Kolejnym etapem transportu było wyciągniecie okrętu podwodnego na ląd. Przesuwanie okrętu podwodnego typu Kobben tj. ciężkiego obiektu dla bezpieczeństwa możliwe było dzięki specjalistycznemu systemowi samopoziomujących się hydraulicznych wózków ślizgowych HWS-280 ELPO. Operacja ta, stanowiła rzadkość nawet na skalę światową, była zwieńczeniem wielu lat starań jakie podjęły władze Akademii Marynarki Wojennej (AMW) w Gdyni w celu pozyskania, przemieszczenia i posadowienia jednostki na terenie uczelni.The article presents the issues of transport security submarine type Kobben of Port Naval Gdynia into the Polish Naval Academy. Operation transport ship began Naval Shipyard from the docking of the ship on a special pontoon. The next step was to draw the transport purse underwater ashore. Moving the submarine type Kobben. Heavy object was made possible by specialist-tangential system self-leveling hydraulic cylinders. This operation, was a rarity even on a global scale, was the culmination of many years of effort it had taken the authorities of the Polish Naval Academy (PNA) in Gdynia to acquire, move and foundation units on campus

DNA scaffolds support stable and uniform peptide nanopores

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Interactive models for semantic labeling of satellite images

We describe a system for interactive training of models for semantic labeling of land cover. The models are build based on three levels of features: 1) pixel level, 2) region level, and 3) scene level features. We developed a Bayesian algorithm and a decision tree algorithm for interactive training. The Bayesian algorithm enables training based on pixel features. The scene level summaries of pixel features are used for fast retrieval of scenes with high/low content of features and scenes with low confidence of classification. The decision tree algorithm is based on region level features that are extracted based on 1) spectral and textural characteristics of the image, 2) shape descriptors of regions that are created through segmentation process, and 3) auxiliary information such as elevation data. The initial model can be created based on a database of ground truth and than be refined based on the feedback supplied by a data analyst who interactively trains the model using the system output and/or additional scenes. The combination of supervised and unsupervised methods provides a more complete exploration of model space. A user may detect the inadequacy of the model space and add additional features to the model. The graphical tools for the exploration of decision trees allow insight into the interaction of features used in the construction of models. The preliminary experiments show that accurate models can be build in a short time for a variety of land covers. The scalable classification techniques allow for fast searches for a specific label over a large area