Block Truncation Coding (BTC) techniques, to date, utilize a two-level image block code. This thesis presents and studies a new BTC method employing a three-level image coding technique. This new method is applied to actual image frames and compared with other well-known block truncation coding techniques. The method separates an image into disjoint, rectangular regions of fixed size and finds the highest and lowest pixel values of each. Using these values, the image block pixel value range is calculated and divided into three equal sections. The individual image block pixels are then quantized according to the region into which their pixel value falls; they are quantized to a 2 if they fall in the upper third , a 1 in the middle third, and a O if in the lower third range region. Thus, each pixel now requires only two bits for transmission. This is one bit per pixel more than the other well-known BTC techniques and thus it has a smaller compression ratio. When the BTC techniques were applied to actual images, the resulting 3LBTC reconstructed images had the smallest mean-squared-error of the techniques applied. It also produced favorable results in terms of the entropy of the reconstructions as compared to the entropy of the original images. The reconstructed images were also very good replicas of the originals and the 3LBTC process had the fastest processing speed. For applications where coding and reconstruction speed are crucial and bandwidth is not critical, the 3LBTC provides an image coding solution.

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Parametric modeling has many applications. These applications include data estimation and interpolation, modern spectral estimation, and data encoding. This research applies parametric modeling to radar cross section data in an attempt to encode it as well as preserve its spectrum. Traditionally, radar data has been processed through Fourier spectral estimation techniques. These methods not only require large amounts of data, for good spectral estimates, but assume the unobserved data values are zero which leads to spectral smearing. Modern spectral estimation methods alleviate these problems by basing the spectral estimate on a parametric model fit to the data set. The spectral estimate is then derived from the parameters of the model. For models which give a good fit to the data, a good spectral estimate can be made. The most common parametric models are the autoregressive moving-average (ARMA), the moving-average (MA) and the autoregressive (AR) model. These models represent filters, which when excited by a white Gaussian noise sequence give some output sequence. If the parameters of the models and the noise sequence are selected properly, a desired output data sequence can be modeled. The variance of the white noise is often small compared to the variance of the data sequence. This means that the model parameters plus the noise can be stored with fewer bits than the original data sequence while maintaining the same amount of accuracy in the data. The model parameters and noise sequence can be used to reproduce the original data sequence. Further, if only the spectrum of the data is of interest, only the noise variance plus the parameters need to be stored. This could lead to an even greater amount of data reduction. Most high resolution radar data applications require only that the spectrum of the data be preserved which makes modern spectral estimation appealing. This research project applies parametric modeling and modern spectral estimation to high resolution radar data as a means of encoding it. Several different parametric modeling techniques are evaluated to see which would be most useful in radar data encoding. The Burg AR parametric model was chosen due to its computational efficiency and its good spectral estimates. The Burg method applied to two radar range profile data sets gave a reduction in data storage by a factor of four. Further encoding was achieved by fitting the Burg AR parameters to a set of basis functions. This produced an additional data reduction by a factor of 36, for a total compression factor of 144. The latter led to some distortion of the high resolution range profiles, yet targets were still sufficiently characterized. / Master of Science

<p dir="ltr">We study the communication model with perfect feedback considered by Berlekamp (PhD Thesis, 1964), in which Alice wishes to communicate a binary message to Bob through a noisy adversarial channel, and has the ability to receive feedback from Bob via an additional noiseless channel. Berlekamp showed that in this model one can tolerate 1/3 fraction of errors (a.k.a., bit-flips or substitutions) with non-vanishing communication rate, which strictly improves upon the 1/4 error rate that is tolerable in the classical one-way communication setting without feedback. In the case when the channel is corrupted by erasures, it is easy to show that a fraction of erasures tending to 1 can be tolerated in the noiseless feedback setting, which also beats the 1/2 fraction that is maximally correctable in the no-feedback setting. In this thesis, we consider a more general perfect feedback channel that may introduce both errors and erasures. We show the following results:</p><p dir="ltr">1. If α, β ∈ [0, 1) are such that 3α + β < 1, then there exists a code that achieves a positive communication rate tolerating α fraction of errors and β fraction of erasures. Furthermore, no code can achieve a positive-rate in this channel when 3α + β ≥ 1.</p><p dir="ltr">2. For the case when 3α + β < 1, we compute the maximal asymptotic communication rate achievable in this setting.</p>

No description available.

With magnetic storage devices already achieving storage densities of up to 400 Gigabits per square inch (Gb/in2), the state of the art is rapidly approaching theoretical limits (dictated by thermal stability concerns). Hence, there is an eort in the industry to develop alternative magnetic storage technologies. Two-dimensional magnetic recording (TDMR) is one such candidate technology. In contrast to other technologies(e.g. heat-assisted magnetic recording [1], bit-patterned media [2]) which rely on signicant changes being made to the recording medium, TDMR relies on the use of traditional recording media, while relying on signal processing to make improvements in the recording density. Though advantageous due to the fact that no drastic re-engineering of media is required, there are signicant challenges that need to be addressed in order to make TDMR a viable candidate for next-generation recordingsystems.The main challenges involved in TDMR arise due to (i) the small bit-area, along with an aggressive write/read process, which leads to a large amount of noise, and (ii) the two-dimensional nature of the recording process { so far not encountered in today's systems. Thus, a gamut of 2D signal processing algorithms need be developed for the compensation of errors occurring due to the aggressive write/read processes. In this dissertation, we present some of the work done with regard to the signal processing tasks involved in TDMR. In particular, we describe our work on (i) channel modelling, (ii) detection strategies, and (iii) error-correction coding strategies targetted at TDMR.

Researchers have studied memory recall of crisis-oriented or emotional events in non-educational settings. However, within the health care field, there has been a limited study of the the concept of recall of crisis oriented or emotional events in& health care education. Crisis-oriented events such as natural disasters, acts of bioterroism, and industrial accidents, have been reported to impact memory. Patient safety is a primary focus in anesthesia education, appropriate crisis management is imperative to quality anesthesia care. Due to the critical nature of anesthesia delivery, there is a strong, constant need to develop methods that will enhance, support, and improve current anesthesia practices that impact patient safety. Educational methodologies used by both clinical and didactic instructors that will improve teaching effectiveness need to be investigated to ensure that patient safety content is being delivered to nurse anesthesia students in a manner consistent with the American Association of Nurse Anesthetists (AANAs) Council on Accreditation's COAs) standards of care. Utilizing a simulated anesthesia crisis situation, this study compared the differences in cognitive imprinting and application to practice between two content delivery methods, the written case study and patient safety vignettes, in nurse anesthesia students. The control group was given a written case study which is considered a traditional method of content delivery. The treatment groups studied vignettes, which are short, realistic, simulated audio-visual videos that demonstrate content to be relayed. The research hypothesis studied the use of anesthesia crisis oriented vignettes as an educational tool to impact memory recall, thus potentially improving application to clinical practice. Hypotheses for the study were: Hypothesis 1 (Hl): Student anesthetists exposed to audio-visual vignettes will exhibit superior clinical performance during simulated apparatus-related crisis events, evidenced by higher group mean demonstration scores, when compared to a matched group exposed to written case studies. Hypothesis 2 (H2): Student anesthetists exposed to audio-visual vignettes will exhibit superior recall of apparatus related material, evidenced by higher group mean post-test scores, when compared to a matched group exposed to written case studies. Using the paired samples t-test and analysis of variance procedure (ANOVA), statistical findings were evaluated for significance. The different teaching methodologies were represented in the abbreviation of the variables studied. Two different crisis oriented events were presented in vignette format, a malfunctioning unidirectional expiratory valve and a malfunctioning suctioning apparatus. Variables that were studied include: clinical performance during the anesthesia machine checkout process by recreating the stuck expiratory valve and malfunctioning suction apparatus scenarios. Statistically, mixed results were obtained. The impact that the stuck expiratory valve vignette had on student recall and clinical performance was found to be insignificant. The impact resulting from exposure to the non-functioning suction apparatus vignette was found to be significant for both student recall and clinical performance. Other recall and clinical performance measures related to the non- functioning suction apparatus were also found to be significant. Conclusions: In this research study, memory and clinical performance were impacted when the anesthesia provider incorporated the correct anesthesia apparatus checkout process and crisis management skills into their practice. This research demonstrated that under the conditions of this study, teaching methodology impacted some areas of clinical performance. Due to the small sample size and because the clinical performance measurements tools were newly designed for this particular study, findings from this study cannot be generalized to any other group or population. However, the findings from this study merit further investigation into the potential use of vignettes as an educational methodology to impact clinical practice and improve patient safety.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016 / The design and implementation of network coding into a location based ad- dressing algorithm for VANET has been investigated. Theoretical analysis of the network coding algorithm has been done by using a simplified topology called the ladder topology. The theoretical models were shown to describe the way that network coding and standard location based addressing works over the VANET network. All tests were performed over simulation. Network coding was shown to improve performance by a factor of 1.5 to 2 times in both simulation and theoretical models. The theoretical models demonstrate a fundamental limit to how much network coding can improve performance by, and these were confirmed by the simulations. Network coding does have a susceptibility to interference, but the other benefits of the techniques are substantial despite this. Network coding demonstrates strong possibilities for future development for VANET protocols. The ladder topology is an important tool for future analysis. / GS

A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering, 2016 / Reliable and e cient data transmission have been the subject of current research, most especially in realistic channels such as the Rayleigh fading channels. The focus of every new technique is to improve the transmission reliability and to increase the transmission capacity of the communication links for more information to be transmitted. Modulation schemes such as M-ary Quadrature Amplitude Modulation (M-QAM) and Orthogonal Frequency Division Multiplexing (OFDM) were developed to increase the transmission capacity of communication links without additional bandwidth expansion, and to reduce the design complexity of communication systems. On the contrary, due to the varying nature of communication channels, the message transmission reliability is subjected to a couple of factors. These factors include the channel estimation techniques and Forward Error Correction schemes (FEC) used in improving the message reliability. Innumerable channel estimation techniques have been proposed independently, and in combination with di erent FEC schemes in order to improve the message reliability. The emphasis have been to improve the channel estimation performance, bandwidth and power consumption, and the implementation time complexity of the estimation techniques. Of particular interest, FEC schemes such as Reed-Solomon (RS) codes, Turbo codes, Low Density Parity Check (LDPC) codes, Hamming codes, and Permutation codes, are proposed to improve the message transmission reliability of communication links. Turbo and LDPC codes have been used extensively to combat the varying nature of communication channels, most especially in joint iterative channel estimation and decoding receiver structures. In this thesis, attention is focused on using RS codes to improve the message reliability of a communication link because RS codes have good capability of correcting random and burst errors, and are useful in di erent wireless applications. This study concentrates on symbol level soft decision decoding of RS codes. In this regards, a novel symbol level iterative soft decision decoder for RS codes based on parity-check equations is developed. This Parity-check matrix Transformation Algorithm (PTA) is based on the soft reliability information derived from the channel output in order to perform syndrome checks in an iterative process. Performance analysis verify that this developed PTA outperforms the conventional RS hard decision decoding algorithms and the symbol level Koetter and Vardy (KV ) RS soft decision decoding algorithm. In addition, this thesis develops an improved Distance Metric (DM) method of deriving reliability information over Rayleigh fading channels for combined demodulation with symbol level RS soft decision decoding algorithms. The newly proposed DM method incorporates the channel state information in deriving the soft reliability information over Rayleigh fading channels. Analysis verify that this developed metric enhances the performance of symbol level RS soft decision decoders in comparison with the conventional method. Although, in this thesis, the performance of the developed DM method of deriving soft reliability information over Rayleigh fading channels is only veri ed for symbol level RS soft decision decoders, it is applicable to any symbol level soft decision decoding FEC scheme. Besides, the performance of the all FEC decoding schemes plummet as a result of the Rayleigh fading channels. This engender the development of joint iterative channel estimation and decoding receiver structures in order to improve the message reliability, most especially with Turbo and LDPC codes as the FEC schemes. As such, this thesis develops the rst joint iterative channel estimation and Reed- Solomon decoding receiver structure. Essentially, the joint iterative channel estimation and RS decoding receiver is developed based on the existing symbol level soft decision KV algorithm. Consequently, the joint iterative channel estimation and RS decoding receiver is extended to the developed RS parity-check matrix transformation algorithm. The PTA provides design ease and exibility, and lesser computational time complexity in an iterative receiver structure in comparison with the KV algorithm. Generally, the ndings of this thesis are relevant in improving the message transmission reliability of a communication link with RS codes. For instance, it is pertinent to numerous data transmission technologies such as Digital Audio Broadcasting (DAB), Digital Video Broadcasting (DVB), Digital Subscriber Line (DSL), WiMAX, and long distance satellite communications. Equally, the developed, less computationally intensive, and performance e cient symbol level decoding algorithm for RS codes can be use in consumer technologies like compact disc and digital versatile disc. / GS2016

A thesis submitted in ful lment of the requirements for the degree of Master of Science in the Centre of Excellence in Telecommunications and Software School of Electrical and Information Engineering, March 2016 / In order to compare low rate error correcting codes to MIMO schemes with transmit diversity, two systems with the same throughput are compared. A VBLAST MIMO system with (15; 5) Reed-Solomon coding is compared to an Alamouti MIMO system with (15; 10) Reed-Solomon coding. The latter is found to perform signi cantly better, indicating that transmit diversity is a more e ective technique for minimising errors than reducing the code rate. The Guruswami-Sudan/Koetter-Vardy soft decision decoding algorithm was implemented to allow decoding beyond the conventional error correcting bound of RS codes and VBLAST was adapted to provide reliability information. Analysis is also performed to nd the optimal code rate when using various MIMO systems. / MT2016