• Quantification of nanowire uptake by live cells

      Margineanu, Michael B. (2015-05)
      Nanostructures fabricated by different methods have become increasingly important for various applications at the cellular level. In order to understand how these nanostructures “behave” and for studying their internalization kinetics, several attempts have been made at tagging and investigating their interaction with living cells. In this study, magnetic iron nanowires with an iron oxide layer are coated with (3-Aminopropyl)triethoxysilane (APTES), and subsequently labeled with a fluorogenic pH-dependent dye pHrodo™ Red, covalently bound to the aminosilane surface. Time-lapse live imaging of human colon carcinoma HCT 116 cells interacting with the labeled iron nanowires is performed for 24 hours. As the pHrodo™ Red conjugated nanowires are non-fluorescent outside the cells but fluoresce brightly inside, internalized nanowires are distinguished from non-internalized ones and their behavior inside the cells can be tracked for the respective time length. A machine learning-based computational framework dedicated to automatic analysis of live cell imaging data, Cell Cognition, is adapted and used to classify cells with internalized and non-internalized nanowires and subsequently determine the uptake percentage by cells at different time points. An uptake of 85 % by HCT 116 cells is observed after 24 hours incubation at NW-to-cell ratios of 200. While the approach of using pHrodo™ Red for internalization studies is not novel in the literature, this study reports for the first time the utilization of a machine-learning based time-resolved automatic analysis pipeline for quantification of nanowire uptake by cells. This pipeline has also been used for comparison studies with nickel nanowires coated with APTES and labeled with pHrodo™ Red, and another cell line derived from the cervix carcinoma, HeLa. It has thus the potential to be used for studying the interaction of different types of nanostructures with potentially any live cell types.
    • Quantifying the Ionized Dopant Concentrations of InGaN-based Nanowires for Enhanced Photoelectrochemical Water Splitting Performance

      Zhang, Huafan (2018-11-04)
      III-nitride nanowires (NWs) have been recognized as efficient photoelectrochemical (PEC) devices due to their large surface-to-volume ratio, tunable bandgap, and chemical stability. Doping engineering can help to enhance the PEC performance further. Therefore, addressing the effects of Si and Mg doping on the III-nitride NW photoelectrodes is of great interest. In this study, doping levels of NWs were tuned by the dopant effusion cell temperature of the molecular beam epitaxy (MBE) growth. The successful doping of the III-nitride NWs was confirmed using photoluminescence (PL), Raman spectroscopy, and open circuit potential (OCP) measurements. The ionized dopant concentrations of Si-doped InGaN/GaN NWs were systematically quantified by electrochemical impedance studies (EIS). Due to the three dimensional surfaces of NWs, modified Mott-Schottky formulas were induced to improve the accuracy of ionized dopant concentrations. The highest dopant concentration of Si-doped InGaN NWs can reach 2.1x1018 cm-3 at Tsi = 1120 oC. Accordingly, the estimated band edge potentials of the tested NWs straddled the redox potential of water splitting. The PEC performance of these devices was investigated by linear scan voltammetry (LSV), chronoamperometry tests, and gas evolution measurements. The results were consistent with the quantified dopant concentrations. The current density of n-InGaN NWs doped at TSi = 1120 oC was nine times higher than the undoped NWs. Additionally, the doped NWs exhibited stoichiometric hydrogen and oxygen evolution. By doping Mg into InGaN and GaN segments separately, the p-InGaN/p-GaN NWs demonstrated improved PEC performance, compared with undoped-InGaN/p-GaN and n-InGaN/n-GaN NWs. The p-InGaN/p-GaN NWs exhibited a highly stable current density at ~-9.4 mA/cm2 for over ten hours with steady gas evolution rates (~107 μmol/cm2/hr for H2) at near a stoichiometric ratio (H2: O2~ 1.8:1). This study demonstrated that optimizing the doping level and appropriate band engineering of III-nitride NWs is crucial for enhancing their PEC water splitting performance.
    • Quantum-Classical correspondence in nonlinear multidimensional systems: enhanced di usion through soliton wave-particles

      Brambila, Danilo (2012-05)
      Quantum chaos has emerged in the half of the last century with the notorious problem of scattering of heavy nuclei. Since then, theoreticians have developed powerful techniques to approach disordered quantum systems. In the late 70's, Casati and Chirikov initiated a new field of research by studying the quantum counterpart of classical problems that are known to exhibit chaos. Among the several quantum-classical chaotic systems studied, the kicked rotor stimulated a lot of enthusiasm in the scientific community due to its equivalence to the Anderson tight binding model. This equivalence allows one to map the random Anderson model into a set of fully deterministic equations, making the theoretical analysis of Anderson localization considerably simpler. In the one-dimensional linear regime, it is known that Anderson localization always prevents the diffusion of the momentum. On the other hand, for higher dimensions it was demonstrated that for certain conditions of the disorder parameter, Anderson localized modes can be inhibited, allowing then a phase transition from localized (insulating) to delocalized (metallic) states. In this thesis we will numerically and theoretically investigate the properties of a multidimensional quantum kicked rotor in a nonlinear medium. The presence of nonlinearity is particularly interesting as it raises the possibility of having soliton waves as eigenfunctions of the systems. We keep the generality of our approach by using an adjustable diffusive nonlinearity, which can describe several physical phenomena. By means of Variational Calculus we develop a chaotic map which fully describes the soliton dynamics. The analysis of such a map shows a rich physical scenario that evidences the wave-particle behavior of a soliton. Through the nonlinearity, we trace a correspondence between quantum and classical mechanics, which has no equivalent in linearized systems. Matter waves experiments provide an ideal environment for studying Anderson localization, as the interactions in these systems can be easily controlled by Feshbach resonance techniques. In the end of this thesis, we propose an experimental realization of the kicked rotor in a dipolar Bose Einstein Condensate.
    • Quasi-Newton Exploration of Implicitly Constrained Manifolds

      Tang, Chengcheng (2011-08)
      A family of methods for the efficient update of second order approximations of a constraint manifold is proposed in this thesis. The concept of such a constraint manifold corresponds to an abstract space prescribed by implicit nonlinear constraints, which can be a set of objects satisfying certain desired properties. This concept has a variety of applications, and it has been successfully introduced to fabrication-aware architectural design as a shape space consisting of all the implementable designs. The local approximation of such a manifold can be first order, in the tangent space, or second order, in the osculating surface, with higher precision. For a nonlinearly constrained manifold with rather high dimension and codimension, the computation of second order approximants (osculants) is time consuming. In this thesis, a type of so-called quasi-Newton manifold exploration methods which approximate the new osculants by updating the ones of a neighbor point by 1st-order information is introduced. The procedures are discussed in detail and the examples implemented to visually verify the methods are illustrated.
    • Rainbow Particle Imaging Velocimetry

      Xiong, Jinhui (2017-04-27)
      Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. This work tackles this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a “rainbow”), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient to track 3D trajectories of particles by combining 2D spatial and 1D color information. For reconstruction, this thesis derives an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. The proposed method is evaluated by both simulations and an experimental prototype setup.
    • A Raman Flow Cytometer: An Innovative Microfluidic Approach for Continuous Label-Free Analysis of Cells via Raman Spectroscopy

      De Grazia, Antonio (2015-05-05)
      In this work a Raman flow cytometer is presented. It is a whole new microfluidic device that takes advantage of basic principles of Raman spectroscopy and fluorescent flow cytometry mixed together in a system of particularly shaped channels. These are indeed composed by specific shape and sizes – thanks to which cells can flow one-by-one – and a trap by means of which cells are trapped in order to perform Raman analysis on single ones in a constant and passive way. In this sense the microfluidic device promotes a fast method to look for single cells in a whole multicellular sample. It is a label-free analysis and this means that, on the contrary of what happens with fluorescent flow cytometry, the sample does not need to undergo any particular time-consuming pretreatment before being analyzed. Moreover it gives a complete information about the biochemical content of the sample thanks to the involvement of Raman spectroscopy as method of analysis. Many thought about a device like this, but eventually it is the first one being designed, fabricated and tested. The materials involved in the production of the Raman flow cytometer are chosen wisely. In particular the chip – the most important component of the device – is multilayered, being composed by a slide of calcium fluoride (which gives a negligible signal in Raman analyses), a photosensitive resist containing a pattern with channels and another slide of calcium fluoride in order for the channels to be sealed on both sides. The chip is, in turn, connected to gaskets and external frames. Several fabrication processes are followed to ultimately get the complete Raman flow cytometer and experiments on red blood cells demonstrate its validity in this field.
    • The Recombination Mechanism and True Green Amplified Spontaneous Emission in CH3NH3PbBr3 Perovskite

      Priante, Davide (2015-08)
      True-green wavelength emitters at 555 nm are currently dominated by III-V semiconductor-based inorganic materials. Nevertheless, due to high lattice- and thermal-mismatch, the overall power efficiency in this range tends to decline for high current density showing the so-called efficiency droop in the green region (“green gap”). In order to fill the research green gap, this thesis examines the low cost solution-processability of organometal halide perovskites, which presents a unique opportunity for light-emitting devices in the green-yellow region owing to their superior photophysic properties such as high photoluminescence quantum efficiency, small capture cross section of defect states as well as optical bandgap tunability across the visible light regime. Specifically, the mechanisms of radiative recombination in a CH3NH3PbBr3 hybrid perovskite material were investigated using low-temperature, power-dependent (77 K), temperature-dependent photoluminescence (PL) measurements. We noted three recombination peaks at 77K, one of which originated from bulk defect states, and other two from surface defect states. The latter were identified as bound-excitonic (BE) radiative transitions related to particle size inhomogeneity or grain size induced surface state in the sample. Both transitions led to PL spectra broadening as a result of concurrent blue- and red-shifts of these excitonic peaks. The blue-shift is most likely due to the Burstein-Moss (band filling) effect. Interestingly, the red-shift of the second excitonic peak becomes pronounced with increasing temperature leading to a true-green wavelength of 553 nm for CH3NH3PbBr3. On the other hand, red-shifted peak originates from the strong absorption in the second excitonic peak owed to the high density of surface states and carrier filling of these states due to the excitation from the first excitonic recombination. We also achieved amplified spontaneous emission around excitation threshold energy of 350 μJ/cm2 when optically pumped using 475 nm laser pulses, thus supporting the assignment of carrier absorption and re-excitation mentioned above. This dissertation work led to the following article: D. Priante, I. Dursun, M. S. Alias, D. Shi, V. A. Melnikov, T. K. Ng, O. F. Mohammed, O. M. Bakr, and B. S. Ooi, "The recombination mechanisms leading to amplified spontaneous emission at the true-green wavelength in CH3NH3PbBr3 perovskites", Applied Physics Letters, 106, 081902, 2015. DOI: 10.1063/1.4913463
    • Reconfigurable Electronics Platform: Concept, Mechanics, Materials and Process

      Damdam, Asrar N. (2018-08)
      Electronic platforms that are able to re-shape and assume different geometries are attractive for the advancing biomedical technologies, where the re-shaping feature increases the adaptability and compliance of the electronic platform to the human body. In this thesis, we present a serpentine-honeycomb reconfigurable electronic platform that has the ability to reconfigure into five different geometries: quatrefoil, ellipse, diamond, star and one irregular geometry. We show the fabrication processes of the serpentine-honeycomb reconfigurable platform in a micro-scale, using amorphous silicon, and in a macro-scale using polydimethylsiloxane (PDMS). The chosen materials are biocompatible, where the silicon was selected due to its superior electrical properties while the PDMS was selected due to its unique mechanical properties. We study the tensile strain for both fabricated-versions of the design and we demonstrate their reconfiguring capabilities. The resulting reconfiguring capabilities of the serpentine-honeycomb reconfigurable platform broaden the innovation opportunity for wearable electronics, implantable electronics and soft robotics.
    • Red Sea Acropora hemprichii Bacterial Population Dynamics under Adverse Anthropogenic Conditions

      Lizcano, Javier (2012-08)
      Reef-building corals are cornerstones of life in the oceans. Understanding their interactions with microorganisms and their surrounding physicochemical conditions is important to comprehend reef functioning and ultimately protect coral reef ecosystems. Corals associate with a complex and specific array of microorganisms that supposedly affect their physiology and therefore can significantly determine the condition of a coral ecosystem. As environmental conditions may shape bacterial diversity and ecology in the coral symbiosis, ecosystem changes might have unfavorable consequences for the holobiont, to date poorly understood. Here, we were studying microbial community changes in A. hemprichii as a consequence of simulated eutrophication and overfishing over a period of 16 weeks by using in situ caging and slow release fertilizer treatments in an undisturbed Red Sea reef (22.18ºN, 38.57ºW). We used 16S rDNA amplicon sequencing to evaluate the individual and combined effects of overnutrification and fishing pressure, two of the most common local threats to coral reefs. With our data we hope to better understand bacterial population dynamics under anthropogenic influences and its role in coral resilience. Projecting further, this data will be useful to better predict the consequences of human activity on reef ecosystems.
    • The regeneration of a liquid desiccant using direct contact membrane distillation to unlock the potential of coastal desert agriculture

      Cribbs, Kimberly (2018-04)
      In Gulf Cooperation Council (GCC) countries, a lack of freshwater, poor soil quality, and ambient temperatures unsuitable for cultivation for parts of the year hinders domestic agriculture. The result is a reliance on a fluctuating supply of imported fresh produce which may have high costs and compromised quality. There are agricultural technologies available such as hydroponics and controlled environment agriculture (CEA) that can allow GCC countries to overcome poor soil quality and ambient temperatures unsuitable for cultivation, respectively. Evaporative cooling is the most common form of cooling for CEA and requires a significant amount of water. In water-scarce regions, it is desirable for sea or brackish water to be used for evaporative cooling. Unfortunately, in many coastal desert regions, evaporative cooling does not provide enough cooling due to the high wet-bulb temperature of the ambient air during hot and humid months of the year. A liquid desiccant dehumidification system has been proven to lower the wet-bulb temperature of ambient air in the coastal city of Jeddah, Saudi Arabia to a level that allows for evaporative cooling to meet the needs of heat-sensitive crops. Much of the past research on the regeneration of the liquid desiccant solution has been on configurations that release water vapor back to the atmosphere. Studies have shown that the amount of water captured by the liquid desiccant when used to dehumidify a greenhouse can supply a significant amount of the water needed for irrigation. This thesis studied the regeneration of a magnesium chloride (MgCl2) liquid desiccant solution from approximately 20 to 31wt% by direct contact membrane distillation and explored the possibility of using the recovered water for irrigation. Two microporous hydrophobic PTFE membranes were experimentally tested and modeled when the bulk feed and coolant temperature difference was between 10 and 60°C. In eight experiments, the salt rejection was higher than 99.97% and produced permeate suitable for irrigation with a concentration of MgCl2 less than 94 ppm.
    • Regularization Techniques for Linear Least-Squares Problems

      Suliman, Mohamed Abdalla Elhag (2016-04)
      Linear estimation is a fundamental branch of signal processing that deals with estimating the values of parameters from a corrupted measured data. Throughout the years, several optimization criteria have been used to achieve this task. The most astonishing attempt among theses is the linear least-squares. Although this criterion enjoyed a wide popularity in many areas due to its attractive properties, it appeared to suffer from some shortcomings. Alternative optimization criteria, as a result, have been proposed. These new criteria allowed, in one way or another, the incorporation of further prior information to the desired problem. Among theses alternative criteria is the regularized least-squares (RLS). In this thesis, we propose two new algorithms to find the regularization parameter for linear least-squares problems. In the constrained perturbation regularization algorithm (COPRA) for random matrices and COPRA for linear discrete ill-posed problems, an artificial perturbation matrix with a bounded norm is forced into the model matrix. This perturbation is introduced to enhance the singular value structure of the matrix. As a result, the new modified model is expected to provide a better stabilize substantial solution when used to estimate the original signal through minimizing the worst-case residual error function. Unlike many other regularization algorithms that go in search of minimizing the estimated data error, the two new proposed algorithms are developed mainly to select the artifcial perturbation bound and the regularization parameter in a way that approximately minimizes the mean-squared error (MSE) between the original signal and its estimate under various conditions. The first proposed COPRA method is developed mainly to estimate the regularization parameter when the measurement matrix is complex Gaussian, with centered unit variance (standard), and independent and identically distributed (i.i.d.) entries. Furthermore, the second proposed COPRA method deals with discrete ill-posed problems when the singular values of the linear transformation matrix are decaying very fast to a significantly small value. For the both proposed algorithms, the regularization parameter is obtained as a solution of a non-linear characteristic equation. We provide a details study for the general properties of these functions and address the existence and uniqueness of the root. To demonstrate the performance of the derivations, the first proposed COPRA method is applied to estimate different signals with various characteristics, while the second proposed COPRA method is applied to a large set of different real-world discrete ill-posed problems. Simulation results demonstrate that the two proposed methods outperform a set of benchmark regularization algorithms in most cases. In addition, the algorithms are also shown to have the lowest run time.
    • Regularized Discriminant Analysis: A Large Dimensional Study

      Yang, Xiaoke (2018-04-28)
      In this thesis, we focus on studying the performance of general regularized discriminant analysis (RDA) classifiers. The data used for analysis is assumed to follow Gaussian mixture model with different means and covariances. RDA offers a rich class of regularization options, covering as special cases the regularized linear discriminant analysis (RLDA) and the regularized quadratic discriminant analysis (RQDA) classi ers. We analyze RDA under the double asymptotic regime where the data dimension and the training size both increase in a proportional way. This double asymptotic regime allows for application of fundamental results from random matrix theory. Under the double asymptotic regime and some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that only depends on the data statistical parameters and dimensions. This result not only implicates some mathematical relations between the misclassification error and the class statistics, but also can be leveraged to select the optimal parameters that minimize the classification error, thus yielding the optimal classifier. Validation results on the synthetic data show a good accuracy of our theoretical findings. We also construct a general consistent estimator to approximate the true classification error in consideration of the unknown previous statistics. We benchmark the performance of our proposed consistent estimator against classical estimator on synthetic data. The observations demonstrate that the general estimator outperforms others in terms of mean squared error (MSE).
    • A regularized stationary mean-field game

      Yang, Xianjin (2016-04-19)
      In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.
    • Relay Selection and Resource Allocation in One-Way and Two-Way Cognitive Relay Networks

      Alsharoa, Ahmad M. (2013-05-08)
      In this work, the problem of relay selection and resource power allocation in one- way and two-way cognitive relay networks using half duplex channels with different relaying protocols is investigated. Optimization problems for both single and multiple relay selection that maximize the sum rate of the secondary network without degrading the quality of service of the primary network by respecting a tolerated interference threshold were formulated. Single relay selection and optimal power allocation for two-way relaying cognitive radio networks using decode-and-forward and amplify-and-forward protocols were studied. Dual decomposition and subgradient methods were used to find the optimal power allocation. The transmission process to exchange two different messages between two transceivers for two-way relaying technique takes place in two time slots. In the first slot, the transceivers transmit their signals simultaneously to the relay. Then, during the second slot the relay broadcasts its signal to the terminals. Moreover, improvement of both spectral and energy efficiency can be achieved compared with the one-way relaying technique. As an extension, a multiple relay selection for both one-way and two-way relaying under cognitive radio scenario using amplify-and-forward were discussed. A strong optimization tool based on genetic and iterative algorithms was employed to solve the 
formulated optimization problems for both single and multiple relay selection, where discrete relay power levels were considered. Simulation results show that the practical and low-complexity heuristic approaches achieve almost the same performance of the optimal relay selection schemes either with discrete or continuous power distributions while providing a considerable saving in terms of computational complexity.
    • Removal and Degradation Pathways of Sulfamethoxazole Present in Synthetic Municipal Wastewater via an Anaerobic Membrane Bioreactor

      Sanchez Huerta, Claudia (2016-05)
      The current global water crisis in addition to continues contamination of natural water bodies with harmful organic micropollutants (OMPs) have driven the development of new water treatment technologies that allow the efficient removal of such compounds. Among a long list of OMPs, antibiotics are considered as top priority pollutants to be treated due to their great resistance to biological treatments and their potential to develop bacterial resistance. Different approaches, such as membrane-based and advance oxidation processes have been proposed to alleviate or minimize antibiotics discharge into aquatic environments. However most of these processes are costly and generate either matrices with high concentration of OMPs or intermediate products with potentially greater toxicity or persistence. Therefore, this thesis proposes the study of an anaerobic membrane bioreactor (AnMBR) for the treatment of synthetic municipal wastewater containing sulfamethoxazole (SMX), a world widely used antibiotic. Besides the general evaluation of AnMBR performance in the COD removal and biogas production, this research mainly focuses on the SMX removal and its degradation pathway. Thus 5 SMX quantification was performed through solid phase extraction-liquid chromatography/mass spectrometry and the identification of its transformation products (TPs) was assessed by gas chromatography/mass spectrometry technique. The results achieved showed that, working under optimal conditions (35°C, pH 7 and ORP around -380 to -420 mV) and after a biomass adaptation period (maintaining 0.85 VSS/TSS ratio), the AnMBR process provided over 95% COD removal and 95-98% SMX removal, while allowing stable biogas composition and methane production (≈130 mL CH4/g CODremoved). Kinetic analysis through a batch test showed that after 24 h of biological reaction, AnMBR process achieved around 94% SMX removal, indicating a first order kinetic reaction with K= 0.119, which highlights the high degradation capacity of the anaerobic bacteria. Along the AnMBR process, 7 TPs were identified and possible degradation pathways were proposed. At low influent SMX concentrations (<10ppb), the only TPs detected was (1) Benzene sulfonamide N-Butyl. However, as the influent SMX concentration increased, it was possible to identify (2) Sulfanilamide, (3) Sulfisomidine and (4) 4-Aminothiophenol. Further degradation of compounds 2, 3 and 4 were detected after 9 hours of biological reaction in a batch test, producing three new intermediate products: (5) Aniline, (6) 4-Pyrimidinamine, 2,6-dimethyl and (7) Acetamide, N-(4-mercaptophenyl). Most of the detected TPs present a less complex structure than SMX, which can be associates with a lower toxicity.
    • Removal Efficiency of Microbial Contaminants from Hospital Wastewaters

      Timraz, Kenda Hussain Hassan (2016-02)
      This study aims to evaluate the removal efficiency of microbial contaminants from two hospitals on-site Wastewater Treatment Plants (WWTPs) in Saudi Arabia. Hospital wastewaters often go untreated in Saudi Arabia as in many devolving countries, where no specific regulations are imposed regarding hospital wastewater treatment. The current guidelines are placed to ensure a safe treated wastewater quality, however, they do not regulate for pathogenic bacteria and emerging contaminants. Results from this study have detected pathogenic bacterial genera and antibiotic resistant bacteria in the sampled hospitals wastewater. And although the treatment process of one of the hospitals was able to meet current quality guidelines, the other hospital treatment process failed to meet these guidelines and disgorge of its wastewater might be cause for concern. In order to estimate the risk to the public health and the impact of discharging the treated effluent to the public sewage, a comprehensive investigation is needed that will facilitate and guide suggestions for more detailed guidelines and monitoring.
    • Removal of Organic Micropollutants by Aerobic Activated Sludge

      Wang, Nan (2013-06)
      The study examined the removal mechanism of non-acclimated and acclimated aerobic activated sludge for 29 target organic micropollutants (OMPs) at low concentration. The selection of the target OMPs represents a wide range of physical-chemical properties such as hydrophobicity, charge state as well as a diverse range of classes, including pharmaceuticals, personal care products and household chemicals. The removal mechanisms of OMPs include adsorption, biodegradation, hydrolysis, and vaporization. Adsorption and biodegradation were found to be the main routes for OMPs removal for all target OMPs. Target OMPs responded to the two dominant removal routes in different ways: (1) complete adsorption, (2) strong biodegradation and weak adsorption, (3) medium biodegradation and adsorption, and (4) weak sorption and weak biodegradatio. Kinetic study showed that adsorption of atenolol, mathylparaben and propylparaben well followed first-order model (R2: 0.939 to 0.999) with the rate constants ranging from 0.519-7.092 h-1. For biodegradation kinetics, it was found that benzafibrate, bisphenol A, diclofenac, gemfibrozil, ibuprofen, caffeine and DEET followed zero-order model (K0:1.15E-4 to 0.0142 μg/Lh-1, R2: 0.991 to 0.999), while TCEP, naproxen, dipehydramine, oxybenzone and sulfamethoxazole followed first-order model (K1:1.96E-4 to 0.101 h-1, R2: 0.912 to 0.996). 4 Inhibition by sodium azide (NaN3)and high temperature sterilization was compared, and it was found that high temperature sterilization will damage cells and change the sludge charge state. For the OMPs adaptation removal study, it was found that some of OMPs effluent concentration decreased, which may be due to the slow adaptation of the sludge or the increase of certain bacteria culture; some increased due to chromic toxicity of the chemicals; most of the OMPs had stable effluent concentration trend, it was explained that some of the OMPs were too difficutl to remove while other showed strong quick adaptation. A new module combined of sequencing batch reactor (SBR) and nanofiltration membrane filtration (NF-MBR) was developed to further study the OMPs removal and to exam the concept of compounds (CRT). The NF-MBR was proved to be a promising bioreactor, as OMPs were rejected by NF membrane which leaded to a low OMPs concentration in permeate water, the apparent removal rate was over 80% for most of the OMPs.
    • Repetition-based Interactive Facade Modeling

      AlHalawani, Sawsan (2012-07)
      Modeling and reconstruction of urban environments has gained researchers attention throughout the past few years. It spreads in a variety of directions across multiple disciplines such as image processing, computer graphics and computer vision as well as in architecture, geoscience and remote sensing. Having a virtual world of our real cities is very attractive in various directions such as entertainment, engineering, governments among many others. In this thesis, we address the problem of processing a single fa cade image to acquire useful information that can be utilized to manipulate the fa cade and generate variations of fa cade images which can be later used for buildings' texturing. Typical fa cade structures exhibit a rectilinear distribution where in windows and other elements are organized in a grid of horizontal and vertical repetitions of similar patterns. In the firt part of this thesis, we propose an efficient algorithm that exploits information obtained from a single image to identify the distribution grid of the dominant elements i.e. windows. This detection method is initially assisted with the user marking the dominant window followed by an automatic process for identifying its repeated instances which are used to define the structure grid. Given the distribution grid, we allow the user to interactively manipulate the fa cade by adding, deleting, resizing or repositioning the windows in order to generate new fa cade structures. Having the utility for the interactive fa cade is very valuable to create fa cade variations and generate new textures for building models. Ultimately, there is a wide range of interesting possibilities of interactions to be explored.
    • Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

      Aman, Beshir M. (2012-12)
      This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.
    • Resource Allocation for Cloud Radio Access Networks

      Dhifallah, Oussama Najeeb (2016-04)
      Cloud-radio access network (CRAN) is expected to be the core network architecture for next generation mobile radio system. In CRANs, joint signal processing is performed at multiple cloud computing centers (clouds) that are connected to several base stations (BSs) via high capacity backhaul links. As a result, large-scale interference management and network power consumption reduction can be effectively achieved. Unlike recent works on CRANs which consider a single cloud processing and treat inter-cloud interference as background noise, the first part of this thesis focuses on the more practical scenario of the downlink of a multi-cloud radio access network where BSs are connected to each cloud through wireline backhaul links. Assume that each cloud serves a set of pre-known single-antenna mobile users (MUs). This part focuses on minimizing the network total power consumption subject to practical constraints. The problems are solved using sophisticated techniques from optimization theory (e.g. Dual Decomposition-based algorithm and the alternating direction method of multipliers (ADMM)-based algorithm). One highlight of this part is that the proposed solutions can be implemented in a distributed fashion by allowing a reasonable information exchange between the coupled clouds. Additionally, feasible solutions of the considered optimization problems can be estimated locally at each iteration. Simulation results show that the proposed distributed algorithms converge to the centralized algorithms in a reasonable number of iterations. To further account of the backhaul congestion due to densification in CRANs, the second part of this thesis considers the downlink of a cache-enabled CRAN where each BS is equipped with a local-cache with limited size used to store the popular files without the need for backhauling. Further, each cache-enabled BS is connected to the cloud via limited capacity backhaul link and can serve a set of pre-known single antenna MUs. This part assumes that only imperfect channel state information (CSI) is available at the cloud. This part focuses on jointly minimizing the network total power consumption as well as backhaul cost. It then suggests solving this optimization problem using the majorization-minimization (MM) approach. Simulation results show that the proposed algorithm converges in a reasonable number of iterations.