EIT Reconstruction Algorithms: Pitfalls, Challenges and Recent Developments

We review developments, issues and challenges in Electrical Impedance Tomography (EIT), for the 4th Workshop on Biomedical Applications of EIT, Manchester 2003. We focus on the necessity for three dimensional data collection and reconstruction, efficient solution of the forward problem and present and future reconstruction algorithms. We also suggest common pitfalls or ``inverse crimes'' to avoid.Comment: A review paper for the 4th Workshop on Biomedical Applications of EIT, Manchester, UK, 200

Xampling: Signal Acquisition and Processing in Union of Subspaces

We introduce Xampling, a unified framework for signal acquisition and processing of signals in a union of subspaces. The main functions of this framework are two. Analog compression that narrows down the input bandwidth prior to sampling with commercial devices. A nonlinear algorithm then detects the input subspace prior to conventional signal processing. A representative union model of spectrally-sparse signals serves as a test-case to study these Xampling functions. We adopt three metrics for the choice of analog compression: robustness to model mismatch, required hardware accuracy and software complexities. We conduct a comprehensive comparison between two sub-Nyquist acquisition strategies for spectrally-sparse signals, the random demodulator and the modulated wideband converter (MWC), in terms of these metrics and draw operative conclusions regarding the choice of analog compression. We then address lowrate signal processing and develop an algorithm for that purpose that enables convenient signal processing at sub-Nyquist rates from samples obtained by the MWC. We conclude by showing that a variety of other sampling approaches for different union classes fit nicely into our framework.Comment: 16 pages, 9 figures, submitted to IEEE for possible publicatio

Thermal radiation analysis system TRASYS 2: User's manual

The Thermal Radiation Analyzer System (TRASYS) program put thermal radiation analysis on the same basis as thermal analysis using program systems such as MITAS and SINDA. The user is provided the powerful options of writing his own executive, or driver logic and choosing, among several available options, the most desirable solution technique(s) for the problem at hand. This User's Manual serves the twofold purpose of instructing the user in all applications and providing a convenient reference book that presents the features and capabilities in a concise, easy-to-find manner

Functional requirements for the man-vehicle systems research facility

The NASA Ames Research Center proposed a man-vehicle systems research facility to support flight simulation studies which are needed for identifying and correcting the sources of human error associated with current and future air carrier operations. The organization of research facility is reviewed and functional requirements and related priorities for the facility are recommended based on a review of potentially critical operational scenarios. Requirements are included for the experimenter's simulation control and data acquisition functions, as well as for the visual field, motion, sound, computation, crew station, and intercommunications subsystems. The related issues of functional fidelity and level of simulation are addressed, and specific criteria for quantitative assessment of various aspects of fidelity are offered. Recommendations for facility integration, checkout, and staffing are included

AN EXPERIMENTAL INVESTIGATION OF HIGH-SPEED AIR-BREATHING VEHICLE PERFORMANCE METRICS

High-speed air-breathing vehicles are one of the main hypersonic vehicles currently being developed. There is a current push by major world powers to develop these vehicles and one of the major limiting factors is engine design. The high-speed air-breathing vehicles necessitate an engine that can perform at higher speeds and higher temperatures, such as a scramjet. This engine is broken into three main parts: the inlet, isolator, and combustor. One of the primary concerns for these vehicles is engine unstart, which is when there is no longer supersonic flow through the engine and the engine can no longer perform. This is typically considered a worst-case scenario for these vehicles and is equated with vehicle loss. This study is broken into two main experiments looking at the inlet and isolator sections of the scramjet flow path. These experiments were done with computational counterparts as the need for complementary studies has been well documented in the literature. Specifically for scramjets, the flight Mach number, Reynolds number, and enthalpy are very difficult to match in ground testing. Thus, there is a distinct need for computational studies to support ground testing in vehicle development. The inlet study uses a crossing shock-wave/boundary-layer interaction as a canonical representation of an inlet, specifically at an off-design-condition with a large shock-wave/boundary layer created in the inlet flow. Then, vortex generators were employed to determine the effect of passive flow control on such an interaction. They were shown to delay separation but cause in increase in flow distortion. The isolator study used a dynamic cylinder model to create a shock train in the wind tunnel test section. This accurately modeled a shock train in an isolator section of a scramjet flow path. Unstart was then created by moving the shock train with the dynamic cylinder which changed the backpressure ratio. Additionally, the asymmetrical nature of the shock train was investigated in the experimental data after the asymmetry was noted in the computations. The experimental data conferred well with the computational data as a strong asymmetrical trend was shown

Applications of Artificial Intelligence to Cryptography

This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on how AI can be applied for encrypting data and undertaking cryptanalysis of such data and other data types in order to assess the cryptographic strength of an encryption algorithm, e.g. to detect patterns of intercepted data streams that are signatures of encrypted data. This includes some of the authors’ prior contributions to the field which is referenced throughout. Applications are presented which include the authentication of high-value documents such as bank notes with a smartphone. This involves using the antenna of a smartphone to read (in the near field) a flexible radio frequency tag that couples to an integrated circuit with a non-programmable coprocessor. The coprocessor retains ultra-strong encrypted information generated using EC that can be decrypted on-line, thereby validating the authenticity of the document through the Internet of Things with a smartphone. The application of optical authentication methods using a smartphone and optical ciphers is also briefly explored