Segmented compressed sampling for analog-to-information conversion: Method and performance analysis

A new segmented compressed sampling method for analog-to-information conversion (AIC) is proposed. An analog signal measured by a number of parallel branches of mixers and integrators (BMIs), each characterized by a specific random sampling waveform, is first segmented in time into $M$ segments. Then the sub-samples collected on different segments and different BMIs are reused so that a larger number of samples than the number of BMIs is collected. This technique is shown to be equivalent to extending the measurement matrix, which consists of the BMI sampling waveforms, by adding new rows without actually increasing the number of BMIs. We prove that the extended measurement matrix satisfies the restricted isometry property with overwhelming probability if the original measurement matrix of BMI sampling waveforms satisfies it. We also show that the signal recovery performance can be improved significantly if our segmented AIC is used for sampling instead of the conventional AIC. Simulation results verify the effectiveness of the proposed segmented compressed sampling method and the validity of our theoretical studies.Comment: 32 pages, 5 figures, submitted to the IEEE Transactions on Signal Processing in April 201

Metal-organic frameworks for selective gas separation : a thesis presented in partial fulfilment of the requirements of the degree of Doctor of Philosophy in Chemistry at Massey University, Manawatū, New Zealand

Listed in 2019 Dean's List of Exceptional ThesesWith an ever increasing need for a more energy-efficient and environmentally benign procedure for gas separation, adsorbents with tailored structures and tunable surface properties are in high demand. Metal–organic frameworks (MOFs), constructed from metalcontaining nodes connected by organic bridges, are such a new type of porous materials. They are promising candidates as adsorbents for gas separations due to their large surface areas, adjustable pore sizes and controllable properties, as well as acceptable thermal stability. However, the bottleneck in this context is that MOFs are expensive to be fabricated and majority of them are not stable in harsh environments, which are often required by industrial processes. In this thesis, we introduce three families of metal-organic frameworks with exceptional gas separation performance for a variety of different gas mixtures separation. Their unique separation performances are well supported by isotherm measurement, X-ray crystallography, DFT calculations, and breakthrough test. These MOFs are all readily synthesizable by inexpensive precursor and highly stable at extreme conditions

Vegetative growth and fruit set of olive (Olea europaea L. cv. ‘Zard’) in response to some soil and plant factors

This experiment was conducted to explore the reasons of difference between ‘Zard’ olive orchard with the poor vegetative growth rate and fruit set and orchard with suitable vegetative growth rate and fruit set in relation to some soil and plant factors during two seasons. Note that assumptions were based on the overall canopy greenness of the olive trees, so experimental orchards in which the planted trees showed optimum leaf greenness were considered good situations for optimum vegetative growth and productivity. Remote sensing technologies based on normalized difference vegetation index (NDVI) were employed on olive orchards, and two orchards meeting the criteria of highest amount of greenness and lowest amount of greenness were selected. Length of current-year shoot (LCYS) and fruit set were considered indicators of tree vegetative growth and productivity, respectively. Results clearly indicated a significant difference between the two selected orchards in terms of canopy volume (CV), leaf nitrogen content (N), leaf potassium content (K), silt, sand, Sodium adsorption rate (SAR), available phosphorous (Pavi), total neutralizing value (TNV), electrical conductivity (EC), chloride (Cl), and Fe variables. A stepwise regression method was used to evaluate the effects of soil and plant variables on fruit set and LCYS. According to the obtained results, the main reasons for differences between two orchards in fruit set and vegetative growth was N and K deficiencies, soil salinity, and a high percentage of silt in the soil

Numerical analysis of the deformational behavior of hydrocarbon reservoirs based on an improved elastoplastic constitutive model

The goal of the current research is to make more comprehensive the elastoplastic stresses effects and oil reservoirs behave in solid phase. These stresses are largely caused by the behavior of subsurface fluid in reservoirs. In reservoir formations, there are frequently significant spatial changes at various length scales. Additionally, a number of physical events influence the flow model in various hierarchies. To fully describe the flow and deformation concerning all of these sizes, more computing power is required. One of the principal problems in the oil field business has always been how to describe, optimize, and simulate the behavior of the solid portion of oil reservoirs. To model fluid flow in reservoirs, deformable media, and porous media, more effectively, several scales must be taken into account. This approach is difficult in different scales, and the results of the simulation's speed, accuracy, and precision indicates this. A hybrid multi-physical multi-scale model has recently been developed as a solution to this problem. The goal of the current work is to update this model to represent solid-phase deformations better. For this improvement, the model is changed into a geomechanical model with the capacity to simulate a plastic region using an integrated yield function as well as using an implicit technique to solve convergence equations concurrently. The simulation outcomes demonstrate that the improved multi-scale mixed physical model is an effective model for modelling oil reservoirs with elastoplastic deformation. This model's calculation speed and accuracy have been tested, and the results are satisfactory. In addition, this paper modeled land subsidence, which Sokolova et al. claim is impacted by a lack of reservoirs, and it fits quite well with other studies. Results have demonstrated that plastic stresses affect both the rate of oil production and the behavior of subsidence. It can be included as a safety feature for infrastructure and oil surface plants

SPARSE CHANNEL ESTIMATION WITH L P -NORM AND REWEIGHTED L 1 -NORM PENALIZED LEAST MEAN SQUARES

ABSTRACT The least mean squares (LMS) algorithm is one of the most popular recursive parameter estimation methods. In its standard form it does not take into account any special characteristics that the parameterized model may have. Assuming that such model is sparse in some domain (for example, it has sparse impulse or frequency response), we aim at developing such LMS algorithms that can adapt to the underlying sparsity and achieve better parameter estimates. Particularly, the example of channel estimation with sparse channel impulse response is considered. The proposed modifications of LMS are the l p -norm and reweighted l 1 -norm penalized LMS algorithms. Our simulation results confirm the superiority of the proposed algorithms over the standard LMS as well as other sparsity-aware modifications of LMS available in the literature