Sonar image interpretation for sub-sea operations

Mine Counter-Measure (MCM) missions are conducted to neutralise underwater explosives. Automatic Target Recognition (ATR) assists operators by increasing the speed and accuracy of data review. ATR embedded on vehicles enables adaptive missions which increase the speed of data acquisition. This thesis addresses three challenges; the speed of data processing, robustness of ATR to environmental conditions and the large quantities of data required to train an algorithm. The main contribution of this thesis is a novel ATR algorithm. The algorithm uses features derived from the projection of 3D boxes to produce a set of 2D templates. The template responses are independent of grazing angle, range and target orientation. Integer skewed integral images, are derived to accelerate the calculation of the template responses. The algorithm is compared to the Haar cascade algorithm. For a single model of sonar and cylindrical targets the algorithm reduces the Probability of False Alarm (PFA) by 80% at a Probability of Detection (PD) of 85%. The algorithm is trained on target data from another model of sonar. The PD is only 6% lower even though no representative target data was used for training. The second major contribution is an adaptive ATR algorithm that uses local sea-floor characteristics to address the problem of ATR robustness with respect to the local environment. A dual-tree wavelet decomposition of the sea-floor and an Markov Random Field (MRF) based graph-cut algorithm is used to segment the terrain. A Neural Network (NN) is then trained to filter ATR results based on the local sea-floor context. It is shown, for the Haar Cascade algorithm, that the PFA can be reduced by 70% at a PD of 85%. Speed of data processing is addressed using novel pre-processing techniques. The standard three class MRF, for sonar image segmentation, is formulated using graph-cuts. Consequently, a 1.2 million pixel image is segmented in 1.2 seconds. Additionally, local estimation of class models is introduced to remove range dependent segmentation quality. Finally, an A* graph search is developed to remove the surface return, a line of saturated pixels often detected as false alarms by ATR. The A* search identifies the surface return in 199 of 220 images tested with a runtime of 2.1 seconds. The algorithm is robust to the presence of ripples and rocks

Galactic Winds

Galactic winds are the primary mechanism by which energy and metals are recycled in galaxies and are deposited into the intergalactic medium. New observations are revealing the ubiquity of this process, particularly at high redshift. We describe the physics behind these winds, discuss the observational evidence for them in nearby star-forming and active galaxies and in the high-redshift universe, and consider the implications of energetic winds for the formation and evolution of galaxies and the intergalactic medium. To inspire future research, we conclude with a set of observational and theoretical challenges.Comment: Paper to be published in 2005 Annual Review of Astronomy & Astrophysics; revision based on comments from readers and production editor. Figure 1 was replaced to show the proper density scale. A PDF file combining both text and figures is available at http://www.astro.umd.edu/~veilleux/pubs/araa.pd

Modeling and Simulation in Engineering

The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering

Analysis and processing of mechanically stimulated electrical signals for the identification of deformation in brittle materials

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The fracture of brittle materials is of utmost importance for civil engineering and seismology applications. A different approach towards the aim of early identification of fracture and the prediction of failure before it occurs is attempted in this work. Laboratory experiments were conducted in a variety of rock and cement based material specimens of various shapes and sizes. The applied loading schemes were cyclic or increasing and the specimens were tested to compression and bending type loading of various levels. The techniques of Pressure Stimulated Current and Bending Stimulated Current were used for the detection of electric signal emissions during the various deformation stages of the specimens. The detected signals were analysed macroscopically and microscopically so as to find suitable criteria for fracture prediction and correlation between the electrical and mechanical parameters. The macroscopic proportionality of the mechanically stimulated electric signal and the strain was experimentally verified, the macroscopic trends of the PSC and BSC electric signals were modelled and the effects of material memory to the electric signals were examined. The current of a time-varying RLC electric circuit was tested against experimental data with satisfactory results and it was proposed as an electrical equivalent model. Wavelet based analysis of the signal revealed the correlation between the frequency components of the electric signal and the deformation stages of the material samples. Especially the increase of the high frequency component of the electric signal seems to be a good precursor of macrocracking initiation point. The additional electric stimulus of a dc voltage application seems to boost the frequency content of the signal and reveals better the stages of cracking process. The microscopic analysis method is scale-free and thus it can confront with the problems of size effects and material properties effects. The AC conductivity time series of fractured and pristine specimens were also analysed by means of wavelet transform and the spectral analysis was used to differentiate between the specimens. A non-destructive technique may be based on these results. Analysis has shown that the electric signal perturbation is an indicator of the forthcoming fracture, as well as of the fracture that has already occurred in specimens.The National Foundation of Scholarships (IKY) Greec

Typical Internal Defects of Gas-Insulated Switchgear and Partial Discharge Characteristics

Gas-insulated switchgear (GIS) is a common electrical equipment, which uses sulfur hexafluoride (SF6) as insulating medium instead of traditional air. It has good reliability and flexibility. However, GIS may have internal defects and partial discharge (PD) is then induced. PD will cause great harm to GIS and power system. Therefore, it is of great importance to study the intrinsic characteristics and detection of PD for online monitoring. In this chapter, typical internal defects of GIS and the PD characteristics are discussed. Several detection methods are also presented in this chapter including electromagnetic method, chemical method, and optical method

Silicon Nanowires the Route from Synthesis towards Applications

This work provides an overview on the silicon nanowires synthesis scenario by introducing the most employed bottom-up and top-down strategies, exploiting their main advantages and drawbacks. The impressive structural, optical and electrical properties of these nanostructures promote their implementation in low power consumption nanodevices with improved performances. Some representative examples of Si NW applications in field-effect transistors, broadband photodetectors, low-cost solar cells with improved light absorption and for selective and ultrasensitive biological detectors are reported. The realization of Si NWs by metal assisted chemical etching (MACE) by the use of discontinuous Au layers and the relationship among structural features and growth conditions are here discussed in detail. Indeed, the NW length, diameter, crystalline structure and doping can be precisely defined by using this low cost and industrially compatible process. Si NWs with quantum confined size are realized by MACE leading to the observation of room temperature light emission from Si. According to quantum confinement theory, the emission wavelength can be red-shifted by tuning the NW diameter opening the routes towards low-cost, Si-based photonics. Moreover, the realization of innovative multiwavelength light sources operating at room temperature is investigated by embedding a carbon nanotube (CNT) dispersion inside Si nanowire arrays using a low cost and Si technology compatible technology. The NW/CNT hybrid system exhibits a tunable emission both in the visible and in the infrared which is strategic for telecommunication applications. The conditions leading to the prevalence of the visible or the IR signal have been identified and are herein discussed. The design of 2D random fractal arrays of Si nanowires is here described. Indeed, the structural arrangement of MACE synthesized Si NWs can be engineering by the deposition of a thin Au layer that superimposes its complimentary fractal arrangement onto the Si NW arrays. Si NW fractal arrays display strong self-similarities over a wide range of length scales and the correlation among the fractal parameters and the optical properties are demonstrated. In fact, the ability to control the scattering, absorption and emission properties is investigated as a function of fractal dimension and lacunarity for different designs. A strong light trapping behavior in the visible range due to the efficient in-plane multiple scattering occurring in the Si NW layer has a promising potential for both photovoltaics and photonics. Furthermore, the first experimental observation of a constructive interference effect in the backscattered Raman light from strongly diffusing Si nanowires is reported. Coherent backscattering of light (CBS) is observed when electromagnetic waves undergo multiple scattering within a disordered optical medium. CBS effect arising from the interference of inelastic scattered Raman radiation has been demonstrated in random Si NW arrays. The results are interpreted within the theoretical model of mixed Rayleigh-Raman random walks, exploiting the role of phase coherence in multiple scattering phenomena. In conclusion, the decoration of MACE-synthesized Si NWs by Ag nanoparticles (NPs) produced by pulsed laser deposition (PLD) is an appealing strategy in order to couple the huge aspect ratio of NWs to plasmonic effects leading to the realization of ultrasensitive surface enhanced Raman spectroscopy (SERS) sensors. PLD conditions have been optimized to guarantee the uniform decoration of NW sidewall along all their length without the need of any post-deposition annealing by using a low-cost and Si implementable technology. The Ag NP morphology can be precisely tuned as a function of the NW length or the number of laser pulses and the correlation among the structural and optical properties of Si NWs decorated is reported, demonstrating a great potentiality for SERS applications

Jet Substructure Studies with CMS Open Data

We use public data from the CMS experiment to study the 2-prong substructure of jets. The CMS Open Data is based on 31.8/pb of 7 TeV proton-proton collisions recorded at the Large Hadron Collider in 2010, yielding a sample of 768,687 events containing a high-quality central jet with transverse momentum larger than 85 GeV. Using CMS's particle flow reconstruction algorithm to obtain jet constituents, we extract the 2-prong substructure of the leading jet using soft drop declustering. We find good agreement between results obtained from the CMS Open Data and those obtained from parton shower generators, and we also compare to analytic jet substructure calculations performed to modified leading-logarithmic accuracy. Although the 2010 CMS Open Data does not include simulated data to help estimate systematic uncertainties, we use track-only observables to validate these substructure studies.Comment: 35 pages, 19 figures, 6 tables, source contains sample event and additional plots; v2: references updated and figure formatting improved; v3: approximate version to appear in PR