The graphic user interface of the AudioGraph Recorder (PC version) : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

With the popularity of the use of computers and the development of the Internet, many multimedia-authoring systems have been developed for computer-based teaching and learning. This is playing an increasingly important role in education. One authoring system is the AudioGraph project developed at Massey university of N.Z., which have been developed for recording audio-graphic presentation material for publication in an html reference environment, i.e. "on the web". One of the tools in the AudioGraph project is the AudioGraph Recorder, which is a Macintosh application for recording or authoring web-based multimedia presentations. Due to the success of the publication of the AudioGraph application and the need of PC users, an AudioGraph Recorder for the PCs is required. This project is about the porting of the AudioGraph Recorder from the Macintosh platform to the PC platform. First this project report explains the functionality of the AudioGraph Recoder (the Macintosh version), especially how the end users interact with the interface of the AudioGraph Recorder, and the corresponding state changes of the controls in the interface. Then the report compares the development tools used in both platforms. The Macintosh version of the AudioGraph Recorder has been developed with the PowerPlant framework in CodeWarrior environment, but the PC version uses MFC framework in Visual C++ 6.0. This report also describes in detail how the interface of the AudioGraph Recorder application was constructed with the MFC, and implementation of some functionality of the application. At the same time some internals of the MFC framework are discussed

An Opportunistic Error Correction Layer for OFDM Systems

In this paper, we propose a novel cross layer scheme to lower power\ud consumption of ADCs in OFDM systems, which is based on resolution\ud adaptive ADCs and Fountain codes. The key part in the new proposed\ud system is that the dynamic range of ADCs can be reduced by\ud discarding the packets which are transmitted over 'bad' sub\ud carriers. Correspondingly, the power consumption in ADCs can be\ud reduced. Also, the new system does not process all the packets but\ud only processes surviving packets. This new error correction layer\ud does not require perfect channel knowledge, so it can be used in a\ud realistic system where the channel is estimated. With this new\ud approach, more than 70% of the energy consumption in the ADC can be\ud saved compared with the conventional IEEE 802.11a WLAN system under\ud the same channel conditions and throughput. The ADC in a receiver\ud can consume up to 50% of the total baseband energy. Moreover, to\ud reduce the overhead of Fountain codes, we apply message passing and\ud Gaussian elimination in the decoder. In this way, the overhead is\ud 3% for a small block size (i.e. 500 packets). Using both methods\ud results in an efficient system with low delay

Opportunistic Error Correction for WLAN Applications

The current error correction layer of IEEE 802.11a WLAN is designed\ud for worst case scenarios, which often do not apply. In this paper,\ud we propose a new opportunistic error correction layer based on\ud Fountain codes and a resolution adaptive ADC. The key part in the\ud new proposed system is that only packets are processed by the\ud receiver chain which have encountered ``good'' channel conditions.\ud Others are discarded. With this new approach, around $\frac{2}{3}$\ud of the energy consumption can be saved compared with the\ud conventional IEEE 802.11a WLAN system under the same channel\ud conditions and throughput

Normal approximation for nonlinear statistics using a concentration inequality approach

Let $T$ be a general sampling statistic that can be written as a linear statistic plus an error term. Uniform and non-uniform Berry--Esseen type bounds for $T$ are obtained. The bounds are the best possible for many known statistics. Applications to U-statistics, multisample U-statistics, L-statistics, random sums and functions of nonlinear statistics are discussed.Comment: Published at http://dx.doi.org/10.3150/07-BEJ5164 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Multiple Timescale Energy Scheduling for Wireless Communication with Energy Harvesting Devices

The primary challenge in wireless communication with energy harvesting devices is to efficiently utilize the harvesting energy such that the data packet transmission could be supported. This challenge stems from not only QoS requirement imposed by the wireless communication application, but also the energy harvesting dynamics and the limited battery capacity. Traditional solar predictable energy harvesting models are perturbed by prediction errors, which could deteriorate the energy management algorithms based on this models. To cope with these issues, we first propose in this paper a non-homogenous Markov chain model based on experimental data, which can accurately describe the solar energy harvesting process in contrast to traditional predictable energy models. Due to different timescale between the energy harvesting process and the wireless data transmission process, we propose a general framework of multiple timescale Markov decision process (MMDP) model to formulate the joint energy scheduling and transmission control problem under different timescales. We then derive the optimal control policies via a joint dynamic programming and value iteration approach. Extensive simulations are carried out to study the performances of the proposed schemes

Moderate deviations in Poisson approximation: a first attempt

Poisson approximation using Stein's method has been extensively studied in the literature. The main focus has been on bounding the total variation distance. This paper is a first attempt on moderate deviations in Poisson approximation for right-tail probabilities of sums of dependent indicators. We obtain results under certain general conditions for local dependence as well as for size-bias coupling. These results are then applied to independent indicators, 2-runs, and the matching problem.Comment: 21 page