Extraction of buildings from high-resolution satellite data and airborne Lidar

Automatic building extraction is a difficult object recognition problem due to a high complexity of the scene content and the object representation. There is a dilemma to select appropriate building models to be reconstructed; the models have to be generic in order to represent a variety of building shape, whereas they also have to be specific to differentiate buildings from other objects in the scene. Therefore, a scientific challenge of building extraction lies in constructing a framework for modelling building objects with appropriate balance between generic and specific models. This thesis investigates a synergy of IKONOS satellite imagery and airborne LIDAR data, which have recently emerged as powerful remote sensing tools, and aims to develop an automatic system, which delineates building outlines with more complex shape, but by less use of geometric constraints. The method described in this thesis is a two step procedure: building detection and building description. A method of automatic building detection that can separate individual buildings from surrounding features is presented. The process is realized in a hierarchical strategy, where terrain, trees, and building objects are sequentially detected. Major research efforts are made on the development of a LIDAR filtering technique, which automatically detects terrain surfaces from a cloud of 3D laser points. The thesis also proposes a method of building description to automatically reconstruct building boundaries. A building object is generally represented as a mosaic of convex polygons. The first stage is to generate polygonal cues by a recursive intersection of both datadriven and model-driven linear features extracted from IKONOS imagery and LIDAR data. The second stage is to collect relevant polygons comprising the building object and to merge them for reconstructing the building outlines. The developed LIDAR filter was tested in a range of different landforms, and showed good results to meet most of the requirements of DTM generation and building detection. Also, the implemented building extraction system was able to successfully reconstruct the building outlines, and the accuracy of the building extraction is good enough for mapping purposes

Significance of low energy impact damage on modal parameters of composite beams by design of experiments

This paper presents an experimental study on the effects of multi-site damage on the vibration response of composite beams damaged by low energy impacts around the barely visible impact damage limit (BVID). The variation of the modal parameters with different levels of impact energy and density of damage is studied. Vibration tests have been carried out with both burst random and classical sine dwell excitations in order to compare that which of the methods among Polymax and Half Bandwidth Method is more suitable for damping estimation in the presence of damage. Design of experiments (DOE) performed on the experimental data show that natural frequency is a more sensitive parameter for damage detection than the damping ratio. It also highlighted energy of impact as the factor having a more significant effect on the modal parameters. Half Bandwidth Method is found to be unsuitable for damping estimation in the presence of damage

Giant Shapiro Resonances in a Flux Driven Josephson Junction Necklace

We present a detailed study of the dynamic response of a ring of $N$ equally spaced Josephson junctions to a time-periodic external flux, including screening current effects. The dynamics are described by the resistively shunted Josephson junction model, appropriate for proximity effect junctions, and we include Faraday's law for the flux. We find that the time-averaged $I-V$ characteristics show novel {\em subharmonic giant Shapiro voltage resonances}, which strongly depend on having phase slips or not, on $N$, on the inductance and on the external drive frequency. We include an estimate of the possible experimental parameters needed to observe these quantized voltage spikes.Comment: 8 pages RevTeX, 3 figures available upon reques

Ballistic dynamics of a convex smooth-wall billiard with finite escape rate along the boundary

We focus on the problem of an impurity-free billiard with a random position-dependent boundary coupling to the environment. The response functions of such an open system can be obtained non-perturbatively from a supersymmetric generating functional. The derivation of this functional is based on averaging over the escape rates and results in a non-linear ballistic $\sigma$-model, characterized by system-specific parameters. Particular emphasis is placed on the {}``whispering gallery modes'' as the origin of surface diffusion modes in the limit of large dimensionless conductance.Comment: 12 pages, no figure

Fermi Edge Singularities in the Mesoscopic Regime: I. Anderson Orthogonality Catastrophe

For generic mesoscopic systems like quantum dots or nanoparticles, we study the Anderson orthogonality catastrophe (AOC) and Fermi edge singularities in photoabsorption spectra in a series of two papers. In the present paper we focus on AOC for a finite number of particles in discrete energy levels where, in contrast to the bulk situation, AOC is not complete. Moreover, fluctuations characteristic for mesoscopic systems lead to a broad distribution of AOC ground state overlaps. The fluctuations originate dominantly in the levels around the Fermi energy, and we derive an analytic expression for the probability distribution of AOC overlaps in the limit of strong perturbations. We address the formation of a bound state and its importance for symmetries between the overlap distributions for attractive and repulsive potentials. Our results are based on a random matrix model for the chaotic conduction electrons that are subject to a rank one perturbation corresponding, e.g., to the localized core hole generated in the photoabsorption process.Comment: 10 pages, 8 figures, submitted to Phys. Rev.

The Velocity Dispersion Function of Very Massive Galaxy Clusters: Abell 2029 and Coma

Based on an extensive redshift survey for galaxy clusters Abell 2029 and Coma, we measure the luminosity functions (LFs) and stellar mass functions (SMFs) for the entire cluster member galaxies. Most importantly, we measure the velocity dispersion functions (VDFs) for quiescent members. The MMT/Hectospec redshift survey for galaxies in A2029 identifies 982 spectroscopic members; for 838 members, we derive the central velocity dispersion from the spectroscopy. Coma is the only other cluster surveyed as densely. The LFs, SMFs, and VDFs for A2029 and Coma are essentially identical. The SMFs of the clusters are consistent with simulations. The A2029 and Coma VDFs for quiescent galaxies have a significantly steeper slope than those of field galaxies for velocity dispersion ≲ 100 {km} {{{s}}}-1. The cluster VDFs also exceed the field at velocity dispersion ≳ 250 {km} {{{s}}}-1. The differences between cluster and field VDFs are potentially important tests of simulations and of the formation of structure in the universe

BIM-GIS ORIENTED INTELLIGENT KNOWLEDGE DISCOVERY

Urban and population growth results in increasing pressure on the public utilities like transport, energy, healthcare services, crime management and emergency services in the realm of smart city management. Smart management of these services increases the necessity of dealing with big data which is come from different sources with various types and formats like 3D city information, GPS, traffic, mobile, Building Information Model (BIM), environmental, social activities and IoT stream data. Therefore, an approach to mine/analysis/interpret these data and extract useful knowledge from this diverse big data sources emerges in order to extract the hidden pattern of data using computational algorithms from statistics, machine learning and information theory. However, inconsistency, duplication and repetition and misconducting with the different type of discrete and continuous data can cause erroneous decision-making. This paper focuses on providing a rules extraction and supervised-decision making methods for facilitating the fusion of BIM and 2D and 3D GIS-based information coupling with IoT stream data residing in a spatial database and 3D BIM data. The proposed methods can be used in those applications like Emergency Response, Evacuation Planning, Occupancy Mapping, and Urban Monitoring to Smart Multi-Buildings so that their input data mostly come from 2D and 3D GIS, BIM and IoT stream. This research focus on proposing the unified rules extraction and decision engine to help smart citizens and managers using BIM and GIS data to make smart decision rather than focus on applications in certain field of BIM and GIS

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions

The immediate upstream region of the 5 '-UTR from the AUG start codon has a pronounced effect on the translational efficiency in Arabidopsis thaliana

The nucleotide sequence around the translational initiation site is an important cis-acting element for post-transcriptional regulation. However, it has not been fully understood how the sequence context at the 5'-untranslated region (5'-UTR) affects the translational efficiency of individual mRNAs. In this study, we provide evidence that the 5'-UTRs of Arabidopsis genes showing a great difference in the nucleotide sequence vary greatly in translational efficiency with more than a 200-fold difference. Of the four types of nucleotides, the A residue was the most favourable nucleotide from positions -1 to -21 of the 5'-UTRs in Arabidopsis genes. In particular, the A residue in the 5'-UTR from positions -1 to -5 was required for a high-level translational efficiency. In contrast, the T residue in the 5'-UTR from positions -1 to -5 was the least favourable nucleotide in translational efficiency. Furthermore, the effect of the sequence context in the -1 to -21 region of the 5'-UTR was conserved in different plant species. Based on these observations, we propose that the sequence context immediately upstream of the AUG initiation codon plays a crucial role in determining the translational efficiency of plant genes.ope