The nonredundant contourlet transform (NRCT): a multiresolution and multidirection image representation with perfect reconstruction property

Multiresolution and multidirection image representation has recently been an attractive research area, in which multiresolution corresponds to varying scale of structure in images, while multidirection deals with the oriented nature of image structure. Numerous new systems, such as the contourlet transform, have been developed. The contourlet transform has the benefit of efficiently capturing the oriented geometrical structures of images; however, it has the drawback of a 4/3 redundancy in its oversampling ratio. In order to eliminate the redundancy, this thesis proposes a progressive version of the contourlet transform which can be calculated with critical sampling. The new proposed image representation is called the nonredundant contourlet transform (NRCT), which is constructed with an efficient framework of filter banks. In addition to critical sampling, the proposed NRCT possesses many valuable properties including perfect reconstruction, sparse expression, multiresolution, and multidirection. Numerical experiments demonstrate that the novel NRCT has better peak signal-to-noise performance than the traditional contourlet transform. Moreover, for low ratios of retained coefficients, the NRCT outperforms the wavelet transform which is a standard method for the critically sampled representation of images. -- After examining the computational complexity of the nonredundant contourlet transform, this thesis applies the NRCT to fingerprint image compression, since fingerprint images are examples of images with oriented structures. Based on an appropriately designed filter bank structure, the NRCT is easily compatible with the wavelet transform. Hence a new transform is created called the semi-NRCT, which takes the advantages of the directional selectivity of the NRCT and the lower complexity of the wavelet transform. Finally, this thesis proposes a new fingerprint image compression scheme based on the semi-NRCT. The semi-NRCT-based fingerprint image compression is compared with other transform-based compressions, for example the wavelet-based and the contourlet-based algorithms, and is shown to perform favorably

Characterization of a Weak Allele of Zebrafish cloche Mutant

Hematopoiesis is a complicated and dynamic process about which the molecular mechanisms remain poorly understood. Danio rerio (zebrafish) is an excellent vertebrate system for studying hematopoiesis and developmental mechanisms. In the previous study, we isolated and identified a cloche172 (clo172) mutant, a novel allele compared to the original cloche (clo) mutant, through using complementation test and initial mapping. Here, according to whole mount in-situ hybridization, we report that the endothelial cells in clo172 mutant embryos, although initially developed, failed to form the functional vascular system eventually. In addition, further characterization indicates that the clo172 mutant exhibited weaker defects instead of completely lost in primitive erythroid cells and definitive hematopoietic cells compared with the clos5 mutant. In contrast, primitive myeloid cells were totally lost in clo172 mutant. Furthermore, these reappeared definitive myeloid cells were demonstrated to initiate from the remaining hematopoietic stem cells (HSCs) in clo172 mutant, confirmed by the dramatic decrease of lyc in clo172runx1w84x double mutant. Collectively, the clo172 mutant is a weak allele compared to the clos5 mutant, therefore providing a model for studying the early development of hematopoietic and vascular system, as well as an opportunity to further understand the function of the cloche gene

Essays on investigating non-linear economic relationships in China

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Statistical Models For Harvested Power From Human Motion

This paper investigates the statistical properties of human motion-based harvested power, and provides models for the distribution, auto-correlation and cross-correlation of harvested power at different body locations, namely left wrist, right wrist, left ankle and waist. The models are developed based on empirical acceleration measurements while the subjects perform unscripted daily tasks. The measured accelerations are converted to harvestable power by assuming a velocity-damped resonant harvesting generator. The provided models enable realistic analysis and simulation of wearable communication systems with motion-based energy harvesting

Modeling, analysis and design of energy harvesting communication systems

Thesis (Ph. D.)--University of Rochester. Dept. of Electrical and Computer Engineering, 2013.Wireless sensor networks (WSNs) are envisioned to have a significant impact for many applications such as health monitoring and area surveillance. Despite many advances in energy aware communication techniques for WSNs, the limitation of energy supply is still a critical issue. One of the most attractive approaches to extend the lifetime of WSNs is harvesting energy from the ambient sources, such as solar, wind and vibration. However, the inherent dynamic and randomness of these sources give rise to many new challenges to modeling and management of harvested energy as well as the analysis of energy harvesting systems. This dissertation involves modeling and analysis of energy harvesting sensors and networks: (i) A Markovian model is developed for energy harvesting sensors, which unifies the processes of energy harvesting, event arrivals, energy storage, and queueing unprocessed events. The probability of event loss and the average queueing delay are analyzed, which further guides a near-optimal design of sensor nodes, in terms of sizing the capacity of energy storage, harvesting device and event queue capacity; (ii) A mathematical model is developed for energy harvesting sensor networks with a multi-source and single-sink topology. The probability of event loss in the network is analyzed due to channel errors and lack of energy in sensors, which is utilized for the system design of sizing the storage and harvesting components of sensor nodes; (iii) Empirical humanmotion based harvesting power is measured for 20 subjects. The statistical properties of harvesting power are analyzed for probability density function, auto-correlation co- efficient and cross-correlation coefficient among four locations. A Markovian model of the human-motion harvestable power is developed. This dissertation makes unique contributions in the following aspects. The proposed models derive closed-form expressions for the probability of event loss and average queueing delay, which provide insight into the performance and the system design of energy harvesting sensor nodes and networks. Statistical and Markovian models are developed for the harvestable energy measured from human motion when subjects perform normal daily activities. These are the first of such models available and will provide the research community with a proper basis for analysis and design

An Analytical Approach To The Design Of Energy Harvesting Wireless Sensor Nodes

Energy harvesting is one of the promising solutions to the problem of limited battery capacity in many wireless devices. This paper addresses the problem of system design of energy harvesting capable wireless devices in terms of the required sizes for energy and data buffers, as well as the size of the harvester, for given delay and loss requirements. We analyze the performance of an energy harvesting node, considering a stochastic model that takes into account energy harvesting and event arrival processes. We derive closed-form expressions for the probability of event loss and the average queueing delay. Our event-driven continuous time simulations validate our analytical results. Employing these results, we provide a near-optimal approach to the design of the system in terms of sizing the energy harvesting device, the energy storage, and the event queue capacity. © 2013 IEEE

Linkages between Shanghai and Hong Kong stock indices

This article examines the dynamics of the linkages between Shanghai and Hong Kong stock indices. While the volatility linkage is analysed by a Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MVGARCH) framework, the dependence of returns is examined by a copula approach. Eight different copula functions are applied in this study including two time-varying ones which capture the dynamics of the linkage. The result shows significant tail dependence of the returns in the two markets

Solar and Wind Data

<p>The data of Solar and Wind collected in the University of Rochester campus.</p