Defending Against Adversarial Attacks in Transmission- and Distribution-level PMU Data

Phasor measurement units (PMUs) provide high-fidelity data that improve situation awareness of electric power grid operations. PMU datastreams inform wide-area state estimation, monitor area control error, and facilitate event detection in real time. As PMU data become more available and increasingly reliable, these devices are found in new roles within control systems, such as remedial action schemes and early warning detection systems. As with other cyber physical systems, maintaining data integrity and security pose a significant challenge for power system operators. In this paper, we present a comprehensive analysis of multiple machine learning techniques to detect malicious data injection within PMU data streams. The two datasets used in this study come from two PMU networks: an inter-university, research-grade distribution network spanning three institutions in the U.S. Pacific Northwest, and a utility transmission network from the Bonneville Power Administration. We implement the detection algorithms with TensorFlow, an open-source software library for machine learning, and the results demonstrate potential for distributing the training workload and achieving higher performance, while maintaining effectiveness in the detection of spoofed data.Comment: 9 pages, 2 figure

Real-Time Computational Gigapixel Multi-Camera Systems

The standard cameras are designed to truthfully mimic the human eye and the visual system. In recent years, commercially available cameras are becoming more complex, and offer higher image resolutions than ever before. However, the quality of conventional imaging methods is limited by several parameters, such as the pixel size, lens system, the diffraction limit, etc. The rapid technological advancements, increase in the available computing power, and introduction of Graphics Processing Units (GPU) and Field-Programmable-Gate-Arrays (FPGA) open new possibilities in the computer vision and computer graphics communities. The researchers are now focusing on utilizing the immense computational power offered on the modern processing platforms, to create imaging systems with novel or significantly enhanced capabilities compared to the standard ones. One popular type of the computational imaging systems offering new possibilities is a multi-camera system. This thesis will focus on FPGA-based multi-camera systems that operate in real-time. The aim of themulti-camera systems presented in this thesis is to offer a wide field-of-view (FOV) video coverage at high frame rates. The wide FOV is achieved by constructing a panoramic image from the images acquired by the multi-camera system. Two new real-time computational imaging systems that provide new functionalities and better performance compared to conventional cameras are presented in this thesis. Each camera system design and implementation are analyzed in detail, built and tested in real-time conditions. Panoptic is a miniaturized low-cost multi-camera system that reconstructs a 360 degrees view in real-time. Since it is an easily portable system, it provides means to capture the complete surrounding light field in dynamic environment, such as when mounted on a vehicle or a flying drone. The second presented system, GigaEye II , is a modular high-resolution imaging system that introduces the concept of distributed image processing in the real-time camera systems. This thesis explains in detail howsuch concept can be efficiently used in real-time computational imaging systems. The purpose of computational imaging systems in the form of multi-camera systems does not end with real-time panoramas. The application scope of these cameras is vast. They can be used in 3D cinematography, for broadcasting live events, or for immersive telepresence experience. The final chapter of this thesis presents three potential applications of these systems: object detection and tracking, high dynamic range (HDR) imaging, and observation of multiple regions of interest. Object detection and tracking, and observation of multiple regions of interest are extremely useful and desired capabilities of surveillance systems, in security and defense industry, or in the fast-growing industry of autonomous vehicles. On the other hand, high dynamic range imaging is becoming a common option in the consumer market cameras, and the presented method allows instantaneous capture of HDR videos. Finally, this thesis concludes with the discussion of the real-time multi-camera systems, their advantages, their limitations, and the future predictions

Optimization of the holographic process for imaging and lithography

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 272-297).Since their invention in 1948 by Dennis Gabor, holograms have demonstrated to be important components of a variety of optical systems and their implementation in new fields and methods is expected to continue growing. Their ability to encode 3D optical fields on a 2D plane opened the possibility of novel applications for imaging and lithography. In the traditional form, holograms are produced by the interference of a reference and object waves recording the phase and amplitude of the complex field. The holographic process has been extended to include different recording materials and methods. The increasing demand for holographic-based systems is followed by a need for efficient optimization tools designed for maximizing the performance of the optical system. In this thesis, a variety of multi-domain optimization tools designed to improve the performance of holographic optical systems are proposed. These tools are designed to be robust, computationally efficient and sufficiently general to be applied when designing various holographic systems. All the major forms of holographic elements are studied: computer generated holograms, thin and thick conventional holograms, numerically simulated holograms and digital holograms. Novel holographic optical systems for imaging and lithography are proposed. In the case of lithography, a high-resolution system based on Fresnel domain computer generated holograms (CGHs) is presented. The holograms are numerically designed using a reduced complexity hybrid optimization algorithm (HOA) based on genetic algorithms (GAs) and the modified error reduction (MER) method. The algorithm is efficiently implemented on a graphic processing unit. Simulations as well as experimental results for CGHs fabricated using electron-beam lithography are presented. A method for extending the system's depth of focus is proposed. The HOA is extended for the design and optimization of multispectral CGHs applied for high efficiency solar concentration and spectral splitting. A second lithographic system based on optically recorded total internal reflection (TIR) holograms is studied. A comparative analysis between scalar and (cont.) vector diffraction theories for the modeling and simulation of the system is performed.A complete numerical model of the system is conducted including the photoresist response and first order models for shrinkage of the holographic emulsion. A novel block-stitching algorithm is introduced for the calculation of large diffraction patterns that allows overcoming current computational limitations of memory and processing time. The numerical model is implemented for optimizing the system's performance as well as redesigning the mask to account for potential fabrication errors. The simulation results are compared to experimentally measured data. In the case of imaging, a segmented aperture thin imager based on holographically corrected gradient index lenses (GRIN) is proposed. The compound system is constrained to a maximum thickness of 5mm and utilizes an optically recorded hologram for correcting high-order optical aberrations of the GRIN lens array. The imager is analyzed using system and information theories. A multi-domain optimization approach is implemented based on GAs for maximizing the system's channel capacity and hence improving the information extraction or encoding process. A decoding or reconstruction strategy is implemented using the superresolution algorithm. Experimental results for the optimization of the hologram's recording process and the tomographic measurement of the system's space-variant point spread function are presented. A second imaging system for the measurement of complex fluid flows by tracking micron sized particles using digital holography is studied. A stochastic theoretical model based on a stability metric similar to the channel capacity for a Gaussian channel is presented and used to optimize the system. The theoretical model is first derived for the extreme case of point source particles using Rayleigh scattering and scalar diffraction theory formulations. The model is then extended to account for particles of variable sizes using Mie theory for the scattering of homogeneous dielectric spherical particles. The influence and statistics of the particle density dependent cross-talk noise are studied. Simulation and experimental results for finding the optimum particle density based on the stability metric are presented. For all the studied systems, a sensitivity analysis is performed to predict and assist in the correction of potential fabrication or calibration errors.by José Antonio Domínguez-Caballero.Ph.D

Computer-assisted detection of lung cancer nudules in medical chest X-rays

Diagnostic medicine was revolutionized in 1895 with Rontgen's discovery of x-rays. X-ray photography has played a very prominent role in diagnostics of all kinds since then and continues to do so. It is true that more sophisticated and successful medical imaging systems are available. These include Magnetic Resonance Imaging (MRI), Computerized Tomography (CT) and Positron Emission Tomography (PET). However, the hardware instalment and operation costs of these systems remain considerably higher than x-ray systems. Conventional x-ray photography also has the advantage of producing an image in significantly less time than MRI, CT and PET. X-ray photography is still used extensively, especially in third world countries. The routine diagnostic tool for chest complaints is the x-ray. Lung cancer may be diagnosed by the identification of a lung cancer nodule in a chest x-ray. The cure of lung cancer depends upon detection and diagnosis at an early stage. Presently the five-year survival rate of lung cancer patients is approximately 10%. If lung cancer can be detected when the tumour is still small and localized, the five-year survival rate increases to about 40%. However, currently only 20% of lung cancer cases are diagnosed at this early stage. Giger et al wrote that "detection and diagnosis of cancerous lung nodules in chest radiographs are among the most important and difficult tasks performed by radiologists"

Experimental study of localised deformation in porous sandstones

This PhD thesis presents a laboratory study aiming at a better understanding of the stress-strain response of the Vosges sandstone (porous rock) tested at a range of confining pressures (i.e., 20-190 MPa) and different axial strain levels. Localised deformation was captured at different scales by a combination of full-field experimental methods, including Ultrasonic Tomography (2D), Acoustic Emissions (3D), X-ray Tomography (3D), and 3D volumetric Digital Image Correlation, plus thin section and Scanning Electron Microscope observations (2D). These experimental methods were performed before, during and after a number of triaxial compression tests. The combined use of the experimental techniques, which have different sensitivity and resolution, described the processes of shear band and shear-enhanced compaction band generation, which formed at low to intermediate and relatively high confining pressures, respectively. Pure compaction bands were not identified. The deformation bands were characterised as zones of localised shear and/or volumetric strain and were captured by the experimental methods as features of low ultrasonic velocities, places of inter- and intra-granular cracking and structures of higher density material. The two main grain-scale mechanisms: grain breakage (damage) and porosity reduction (compaction) were identified in both shear band and shear-enhanced compaction band formation, which presented differences in the proportions of the mechanism and their order of occurrence in time

FDTD modelling of electromagnetic transformation based devices

PhDDuring this PhD study, several finite-difference time-domain (FDTD) methods were developed to numerically investigate coordinate transformation based metamaterial devices. A novel radially-dependent dispersive FDTD algorithm was proposed and applied to simulate electromagnetic cloaking structures. The proposed method can ac- curately model both lossless and lossy cloaks with ideal or reduced parameters. It was demonstrated that perfect “invisibility” from electromagnetic cloaks is only available for lossless metamaterials and within an extremely narrow frequency band. With a few modifications the method is able to simulate general media, such as concentrators and rotation coatings, which are produced by means of coordinate transformations techniques. The limitations of all these devices were thoroughly studied and explo- red. Finally, more useful cloaking structures were proposed, which can operate over a broad frequency spectrum. Several ways to control and manipulate the loss in the electromagnetic cloak ba- sed on transformation electromagnetics were examined. It was found that, by utili- sing inherent electric and magnetic losses of metamaterials, as well as additional lossy materials, perfect wave absorption can be achieved. These new devices demonstrate super-absorptivity over a moderate wideband range, suitable both for microwave and optical applications. Furthermore, a parallel three-dimensional dispersive FDTD method was introdu- ced to model a plasmonic nanolens. The device has its potential in subwavelength imaging at optical frequencies. The finiteness of such a nano-device and its impact on the system dynamic behaviour was numerically exploited. Lastly, a parallel FDTD method was also used to model another interesting coordinate transformation based device, an optical black hole, which can be characterised as an omnidirectional broad- band absorber

Symmetric rearrangeable networks and algorithms

A class of symmetric rearrangeable nonblocking networks has been considered in this thesis. A particular focus of this thesis is on Benes networks built with 2 x 2 switching elements. Symmetric rearrangeable networks built with larger switching elements have also being considered. New applications of these networks are found in the areas of System on Chip (SoC) and Network on Chip (NoC). Deterministic routing algorithms used in NoC applications suffer low scalability and slow execution time. On the other hand, faster algorithms are blocking and thus limit throughput. This will be an acceptable trade-off for many applications where achieving ”wire speed” on the on-chip network would require extensive optimisation of the attached devices. In this thesis I designed an algorithm that has much lower blocking probabilities than other suboptimal algorithms but a much faster execution time than deterministic routing algorithms. The suboptimal method uses the looping algorithm in its outermost stages and then in the two distinct subnetworks deeper in the switch uses a fast but suboptimal path search method to find available paths. The worst case time complexity of this new routing method is O(NlogN) using a single processor, which matches the best known results reported in the literature. Disruption of the ongoing communications in this class of networks during rearrangements is an open issue. In this thesis I explored a modification of the topology of these networks which gives rise to what is termed as repackable networks. A repackable topology allows rearrangements of paths without intermittently losing connectivity by breaking the existing communication paths momentarily. The repackable network structure proposed in this thesis is efficient in its use of hardware when compared to other proposals in the literature. As most of the deterministic algorithms designed for Benes networks implement a permutation of all inputs to find the routing tags for the requested inputoutput pairs, I proposed a new algorithm that can work for partial permutations. If the network load is defined as ρ, the mean number of active inputs in a partial permutation is, m = ρN, where N is the network size. This new method is based on mapping the network stages into a set of sub-matrices and then determines the routing tags for each pair of requests by populating the cells of the sub-matrices without creating a blocking state. Overall the serial time complexity of this method is O(NlogN) and O(mlogN) where all N inputs are active and with m < N active inputs respectively. With minor modification to the serial algorithm this method can be made to work in the parallel domain. The time complexity of this routing algorithm in a parallel machine with N completely connected processors is O(log^2 N). With m active requests the time complexity goes down to (logmlogN), which is better than the O(log^2 m + logN), reported in the literature for 2^0.5((log^2 -4logN)^0.5-logN)<= ρ <= 1. I also designed multistage symmetric rearrangeable networks using larger switching elements and implement a new routing algorithm for these classes of networks. The network topology and routing algorithms presented in this thesis should allow large scale networks of modest cost, with low setup times and moderate blocking rates, to be constructed. Such switching networks will be required to meet the bandwidth requirements of future communication networks

EVALUATION OF MASS FILTERED, TIME DILATED, TIME-OF-FLIGHT MASS SPECTROMETRY

The Naval Research Laboratory's Trace Element Accelerator Mass Spectrometer (NRL-TEAMS) system offers a unique opportunity to develop a new type of time-of-flight (TOF) SIMS. This opportunity derives from use of a Pretzel magnet as a recombinator and mass filter in the injector to the accelerator. Mass filtering prior to time-of-flight analysis removes extraneous species, shortening the analysis time for a single beam pulse, thereby improving the duty cycle. Using this approach, it is possible to obtain an expanded portion of a narrow segment of the entire time-of-flight spectrum created by a single beam pulse. A longer flight path for greater momenta in the Pretzel magnet introduces time dilation. Potential benefits derived from time dilation and mass filtering include improved duty cycle, shorter analysis time, increased precision, and better resolution. While the NRL-TEAMS system is not designed for TOF work, it has been used as a test bed to prove the theoretical benefit of such a design. Theoretical treatments of the spectrometer have shown improved resolution is possible under certain conditions, when compared to a traditional TOF spectrometer. SIMION 8.0 computer simulations were used to model the system and provide insight to the theoretical capabilities of the Pretzel magnet. As expected, models have shown that as field decreases, and therefore path length increases, mass resolution improves. Generally, the model matched well to experimental results provided by the NRL TEAMS system. These experimental results have predicted fundamental parameters of the system accurately and consistently, and confirmed the validity of the model. This research improved the current system's performance through improved electronics and pulsing and further uses the model to predict the theoretical benefits of a system designed for use with a Pretzel magnet

The investigation of the characterisation of flotation froths and design of a machine vision system for monitoring the operation of a flotation cell ore concentration

Electrical and Electronic EngineeringThis dissertation investigates the application of digital image processing techniques in the development of a machine vision system that is capable of characterising the froth structures prevalent on the surface of industrial flotation cells. At present, there is no instrument available that has the ability to measure the size and shape of the bubbles that constitute the surface froth. For this reason, research into a vision based system for surface froth characterisation has been undertaken. Being able to measure bubble size and shape would have far reaching consequences, not only in enhancing the understanding of the flotation process but also in the control and optimization of flotation cells