One of the fastest developing areas in the entertainment industry is digital animation. Television programmes and movies frequently use 3D animations to enhance or replace actors and scenery. With the increase in computing power, research is also being done to apply these animations in an interactive manner. Two of the biggest obstacles to the success of these undertakings are control (manipulating the models) and realism. This text describes many of the ways to improve control and realism aspects, in such a way that interactive animation becomes possible. Specifically, lip-synchronisation (driven by human speech), and various modeling and rendering techniques are discussed. A prototype that shows that interactive animation is feasible, is also described. / Mr. A. Hardy Prof. S. von Solms

M. Tech. (Electrical & Electronic Engineering) / In this research we compare conventional data acquisition system (DAS) with the embedded data acquisition systems. The performance specifications of 4 different types of DAQ cards are drawn up with special emphasis made on the following parameters: Slew rate, settling time, relative accuracy and system noise. These parameters are taken from 2 conventional DAS and then compared to those taken from 2 embedded data acquisition systems under the same electrical conditions. The embedded DAQ system’s hardware was built using the PIC Microcontroller interfaced to the Digital to Analog Convertors (DAC). MPLAB C18 is used to create a program which communicates with the embedded DAQ system, to transmit generated signals. National Instrument's LabView is used to create a program which communicates with the conventional DAQ system, to acquire external generated signals and retransmit the signals. In most cases the performance of conventional and embedded are close, but one of the embedded DAS seem to be unstable at high frequencies.

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With the prevalence of smartphones, pedestrians and joggers today often walk or run while listening to music. Since they are deprived of auditory stimuli that could provide important cues to dangers, they are at a much greater risk of being hit by cars or other vehicles. We start this research into building a wearable system that uses multichannel audio sensors embedded in a headset to help detect and locate cars from their honks and engine and tire noises. Based on this detection, the system can warn pedestrians of the imminent danger of approaching cars. We demonstrate that using a segmented architecture and implementation consisting of headset-mounted audio sensors, front-end hardware that performs signal processing and feature extraction, and machine-learning-based classification on a smartphone, we are able to provide early danger detection in real time, from up to 80m distance, with greater than 80% precision and 90% recall, and alert the user on time (about 6s in advance for a car traveling at 30mph). The time delay between audio signals in a microphone array is the most important feature for sound-source localization. This work also presents a polarity-coincidence, adaptive time-delay estimation (PCC-ATDE) mixed-signal technique that uses 1-bit quantized signals and a negative-feedback architecture to directly determine the time delay between signals in the analog inputs and convert it to a digital number. This direct conversion, without a multibit ADC and further digital-signal processing, allows for ultra low power consumption. A prototype chip in 0:18μm CMOS with 4 analog inputs consumes 78nW with a 3-channel 8-bit digital time-delay output while sampling at 50kHz with a 20μs resolution and 6.06 ENOB. We present a theoretical analysis for the nonlinear, signal-dependent feedback loop of the PCC-ATDE. A delay-domain model of the system is developed to estimate the power bandwidth of the converter and predict its dynamic response. Results are validated with experiments using real-life stimuli, captured with a microphone array, that demonstrate the technique’s ability to localize a sound source. The chip is further integrated in an embedded platform and deployed as an audio-based vehicle-bearing IoT system. Finally, we investigate the signal’s envelope, an important feature for a host of applications enabled by machine-learning algorithms. Conventionally, the raw analog signal is digitized first, followed by feature extraction in the digital domain. This work presents an ultra-low-power envelope-to-digital converter (EDC) consisting of a passive switched-capacitor envelope detector and an inseparable successive approximation-register analog-to-digital converter (ADC). The two blocks integrate directly at different sampling rates without a buffer between them thanks to the ping-pong operation of their sampling capacitors. An EDC prototype was fabricated in 180nm CMOS. It provides 7.1 effective bits of ADC resolution and supports input signal bandwidth up to 5kHz and an envelope bandwidth up to 50Hz while consuming 9.6nW.

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Underwater networks are a field that has been gathering attention. Land-based methods of network construction from discovery to advanced routing are all well established. Due to the unique constraints of operating in an underwater environment, many of these tried-and-true approaches need modification if they function at all. Peer discovery and lowlevel networking have been dealt with by previous research. In this thesis we describe and evaluate eight possible routing schemes with different system-knowledge requirements. We show that with a minimal set of information it is possible to achieve near-optimal results with energy costs considerably lower than centralized optimal algorithms. We demonstrate this by constructing and evaluating a custom simulation environment in MATLAB. This is implemented in a mixed procedural and array-centric approach. Simulated networks are structured on a line topology. All nodes a spaced along the horizontal axis at a random depth. It is assumed that neighbor-discovery has been completed before the simulation starts, and all nodes have access to a global list of connected neighbors. We demonstrate the effectiveness of distributed algorithms in an ideal environment, leading to the conclusion that near-optimal results can be achieved with local information only.

The major objective of this report is to present information regarding the design, construction, and testing of the Digital Oscilloscope Peripheral which allows the IBM Personal Computer (IBM PC) to be used as both a digital oscilloscope and a spectrum analyzer. The design and development of both hardware and software are described briefly; however, the test results are analyzed and discussed in great detail. All documents including the circuit diagrams, program flowcharts and listings, and user manual are provided in the appendices for reference. Several different products are referred to in this report; the following lists each one and its respective company: IBM, XT, AT, and PS/2 are registered trademarks of International Business; Machines Corporation.; MS-DOS is a registered trademark of Microsoft Corporation.; and Turbo Basic is a registered trademark of Borland International, Inc.

Millimeter-wave imaging has gathered attention in recent years for its ability to penetrate clothing, thin layers of soils, and certain construction materials. However, image quality remains a challenge that needs to be addressed. One way of improving image quality is by increasing the dimensions of the collecting aperture. A sparse array can be used to synthesize a larger aperture with a limited set of relatively small detectors. In this research we design, build, and test a test-bed having an active source at 94 GHz and an array of coherent detectors, mounted on arms that extend radially on a rotary table. Using this test bed a circular area with a maximum diameter of 900 mm can be scanned. The signal is down-converted using heterodyne receivers with digital in-phase and quadrature detection. Signal correlation is performed using the digitized data, which is stored for post-processing, electronic focusing, and image reconstruction. Near-field imaging using interferometric reconstructions is achieved using electronic focusing. Imaging tests show the ability of the system to generate imagery of concealed and unconcealed objects at distances between 400 and 700 mm. A study of the effects of redundant and nonredundant configurations on image quality for 4 common detector configurations is presented. In this document we show that an active sparse-aperture imaging system using digital correlators is a viable way to generate millimeter-wave images.

While specialized hardware description languages allow for maximum capability and efficiency in a design automation system, the use of a general purpose language in the same role can make the system more available or more available or more practical for a larger set of users. This project demonstrates the use of ADA* for the description and simulation of small digital signal processing systems. Building on conventions and primitives proposed by Denyer and Renshaw, a simple subsystem was described in ADA and then tested with a small simulator also written in ADA. * ADA is a trademark of the United States Department of Defense - ADA Joint Program Office (AJPO).