Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.

A smart sensing platform for the discrimination of human movement

This thesis documents the design, implementation and testing of a smart sensing platform that is able to discriminate between differences or small changes in a persons walking. The distributive tactile sensing method is used to monitor the deflection of the platform surface using just a small number of sensors and, through the use of neural networks, infer the characteristics of the object in contact with the surface. The thesis first describes the development of a mathematical model which uses a novel method to track the position of a moving load as it passes over the smart sensing surface. Experimental methods are then described for using the platform to track the position of swinging pendulum in three dimensions. It is demonstrated that the method can be extended to that of real-time measurement of balance and sway of a person during quiet standing. Current classification methods are then investigated for use in the classification of different gait patterns, in particular to identify individuals by their unique gait pattern. Based on these observations, a novel algorithm is developed that is able to discriminate between abnormal and affected gait. This algorithm, using the distributive tactile sensing method, was found to have greater accuracy than other methods investigated and was designed to be able to cope with any type of gait variation. The system developed in this thesis has applications in the area of medical diagnostics, either as an initial screening tool for detecting walking disorders or to be able to automatically detect changes in gait over time. The system could also be used as a discrete biometric identification method, for example identifying office workers as they pass over the surface.

Productivity change using growth accounting and frontier-based approaches:evidence from a Monte Carlo analysis

This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivitygrowth estimates derived from growthaccounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.

Photo-sketch synthesis and recognition based on subspace learning

This paper aims to reducing difference between sketches and photos by synthesizing sketches from photos, and vice versa, and then performing sketch-sketch/photo-photo recognition with subspace learning based methods. Pseudo-sketch/pseudo-photo patches are synthesized with embedded hidden Markov model. Because these patches are assembled by averaging their overlapping area in most of the local strategy based methods, which leads to blurring effect to the resulted pseudo-sketch/pseudo-photo, we integrate the patches with image quilting. Experiments are carried out to demonstrate that the proposed method is effective to produce pseudo-sketch/pseudo-photo with high quality and achieve promising recognition results. © 2009.

Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

A study of methods used to analyze total oil and polycyclic aromatic hydrocarbons in produced water: steps towards the validation of molecularly imprinted polymers for use in marine environmetns

Produced water is a by-product of offshore oil and gas production, and is released in large volumes when platforms are actively processing crude oil. Some pollutants are not typically removed by conventional oil/water separation methods and are discharged with produced water. Oil and grease can be found dispersed in produced water in the form of tiny droplets, and polycyclic aromatic hydrocarbons (PAHs) are commonly found dissolved in produced water. Both can have acute and chronic toxic effects in marine environments even at low exposure levels. The analysis of the dissolved and dispersed phases are a priority, but effort is required to meet the necessary detection limits. There are several methods for the analysis of produced water for dispersed oil and dissolved PAHs, all of which have advantages and disadvantages. In this work, EPA Method 1664 and APHA Method 5520 C for the determination of oil and grease will be examined and compared. For the detection of PAHs, EPA Method 525 and PAH MIPs will be compared, and results evaluated. APHA Method 5520 C Partition-Infrared Method is a liquid-liquid extraction procedure with IR determination of oil and grease. For analysis on spiked samples of artificial seawater, extraction efficiency ranged from 85 – 97%. Linearity was achieved in the range of 5 – 500 mg/L. This is a single-wavelength method and is unsuitable for quantification of aromatics and other compounds that lack sp³-hybridized carbon atoms. EPA Method 1664 is the liquid-liquid extraction of oil and grease from water samples followed by gravimetric determination. When distilled water spiked with reference oil was extracted by this procedure, extraction efficiency ranged from 28.4 – 86.2%, and %RSD ranged from 7.68 – 38.0%. EPA Method 525 uses solid phase extraction with analysis by GC-MS, and was performed on distilled water and water from St. John’s Harbour, all spiked with naphthalene, fluorene, phenanthrene, and pyrene. The limits of detection in harbour water were 0.144, 3.82, 0.119, and 0.153 g/L respectively. Linearity was obtained in the range of 0.5-10 g/L, and %RSD ranged from 0.36% (fluorene) to 46% (pyrene). Molecularly imprinted polymers (MIPs) are sorbent materials made selective by polymerizing functional monomers and crosslinkers in the presence of a template molecule, usually the analytes of interest or related compounds. They can adsorb and concentrate PAHs from aqueous environments and are combined with methods of analysis including GC-MS, LC-UV-Vis, and desorption electrospray ionization (DESI)- MS. This work examines MIP-based methods as well as those methods previously mentioned which are currently used by the oil and gas industry and government environmental agencies. MIPs are shown to give results consistent with other methods, and are a low-cost alternative improving ease, throughput, and sensitivity. PAH MIPs were used to determine naphthalene spiked into ASTM artificial seawater, as well as produced water from an offshore oil and gas operation. Linearity was achieved in the range studied (0.5 – 5 mg/L) for both matrices, with R² = 0.936 for seawater and R² = 0.819 for produced water. The %RSD for seawater ranged from 6.58 – 50.5% and for produced water, from 8.19 – 79.6%.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Periodic nonlinear Fourier transform for fiber-optic communications, Part I:theory and numerical methods

In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.

PCR-Based Analysis of Mitochondrial DNA Copy Number, Mitochondrial DNA Damage, and Nuclear DNA Damage.

Because of the role that DNA damage and depletion play in human disease, it is important to develop and improve tools to assess these endpoints. This unit describes PCR-based methods to measure nuclear and mitochondrial DNA damage and copy number. Long amplicon quantitative polymerase chain reaction (LA-QPCR) is used to detect DNA damage by measuring the number of polymerase-inhibiting lesions present based on the amount of PCR amplification; real-time PCR (RT-PCR) is used to calculate genome content. In this unit, we provide step-by-step instructions to perform these assays in Homo sapiens, Mus musculus, Rattus norvegicus, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Oryzias latipes, Fundulus grandis, and Fundulus heteroclitus, and discuss the advantages and disadvantages of these assays.

Active Surface Deformation Technology for Management of Marine Biofouling

Biofouling, the accumulation of biomolecules, cells, organisms and their deposits on submerged and implanted surfaces, is a ubiquitous problem across various human endeavors including maritime operations, medicine, food industries and biotechnology. Since several decades, there have been substantial research efforts towards developing various types of antifouling and fouling release approaches to control bioaccumulation on man-made surfaces. In this work we hypothesized, investigated and developed dynamic change of the surface area and topology of elastomers as a general approach for biofouling management. Further, we combined dynamic surface deformation of elastomers with other existing antifouling and fouling-release approaches to develop multifunctional, pro-active biofouling control strategies.

This research work was focused on developing fundamental, new and environment-friendly approaches for biofouling management with emphasis on marine model systems and applications, but which also provided fundamental insights into the control of infectious biofilms on biomedical devices. We used different methods (mechanical stretching, electrical-actuation and pneumatic-actuation) to generate dynamic deformation of elastomer surfaces. Our initial studies showed that dynamic surface deformation methods are effective in detaching laboratory grown bacterial biofilms and barnacles. Further systematic studies revealed that a threshold critical surface strain is required to debond a biofilm from the surface, and this critical strain is dependent on the biofilm mechanical properties including adhesion energy, thickness and modulus. To test the dynamic surface deformation approach in natural environment, we conducted field studies (at Beaufort, NC) in natural seawater using pneumatic-actuation of silicone elastomer. The field studies also confirmed that a critical substrate strain is needed to detach natural biofilm accumulated in seawater. Additionally, the results from the field studies suggested that substrate modulus also affect the critical strain needed to debond biofilms. To sum up, both the laboratory and the field studies proved that dynamic surface deformation approach can effectively detach various biofilms and barnacles, and therefore offers a non-toxic and environmental friendly approach for biofouling management.

Deformable elastomer systems used in our studies are easy to fabricate and can be used as complementary approach for existing commercial strategies for biofouling control. To this end, we aimed towards developed proactive multifunctional surfaces and proposed two different approaches: (i) modification of elastomers with antifouling polymers to produce multifunctional, and (ii) incorporation of silicone-oil additives into the elastomer to enhance fouling-release performance.

In approach (i), we modified poly(vinylmethylsiloxane) elastomer surfaces with zwitterionic polymers using thiol-ene click chemistry and controlled free radical polymerization. These surfaces exhibited both fouling resistance and triggered fouling-release functionalities. The zwitterionic polymers exhibited fouling resistance over short-term (∼hours) exposure to bacteria and barnacle cyprids. The biofilms that eventually accumulated over prolonged-exposure (∼days) were easily detached by applying mechanical strain to the elastomer substrate. In approach (ii), we incorporated silicone-oil additives in deformable elastomer and studied synergistic effect of silicone-oils and surface strain on barnacle detachment. We hypothesized that incorporation of silicone-oil additive reduces the amount of surface strain needed to detach barnacles. Our experimental results supported the above hypothesis and suggested that surface-action of silicone-oils plays a major role in decreasing the strain needed to detach barnacles. Further, we also examined the effect of change in substrate modulus and showed that stiffer substrates require lower amount of strain to detach barnacles.

In summary, this study shows that (1) dynamic surface deformation can be used as an effective, environmental friendly approach for biofouling control (2) stretchable elastomer surfaces modified with anti-fouling polymers provides a pro-active, dual-mode approach for biofouling control, and (3) incorporation of silicone-oils additives into stretchable elastomers improves the fouling-release performance of dynamic surface deformation technology. Dynamic surface deformation by itself and as a supplementary approach can be utilized biofouling management in biomedical, industrial and marine applications.

Evaluating the spatial transferability and temporal repeatability of remote-sensing-based lake water quality retrieval algorithms at the European scale: a meta-analysis approach

Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.

Relative abundance of anaerobic methanotrophic archaea in bacterial mat Cascadia margin off Oregon

The microbially mediated anaerobic oxidation of methane (AOM) is the major biological sink of the greenhouse gas methane in marine sediments (doi:10.1007/978-94-009-0213-8_44) and serves as an important control for emission of methane into the hydrosphere. The AOM metabolic process is assumed to be a reversal of methanogenesis coupled to the reduction of sulfate to sulfide involving methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) as syntrophic partners which were describes amongst others in Boetius et al. (2000; doi:10.1038/35036572). In this study, 16S rRNA-based methods were used to investigate the distribution and biomass of archaea in samples from sediments above outcropping methane hydrate at Hydrate Ridge (Cascadia margin off Oregon) and (ii) massive microbial mats enclosing carbonate reefs (Crimea area, Black Sea). Sediment samples from Hydrate Ridge were obtained during R/V SONNE cruises SO143-2 in August 1999 and SO148-1 in August 2000 at the crest of southern Hydrate Ridge at the Cascadia convergent margin off the coast of Oregon. The second study area is located in the Black Sea and represents a field in which there is active seepage of free gas on the slope of the northwestern Crimea area. Here, a field of conspicuous microbial reefs forming chimney-like structures was discovered at a water depth of 230 m in anoxic waters. The microbial mats were sampled by using the manned submersible JAGO during the R/V Prof. LOGACHEV cruise in July 2001. At Hydrate Ridge the surface sediments were dominated by aggregates consisting of ANME-2 and members of the Desulfosarcina-Desulfococcus branch (DSS) (ANME-2/DSS aggregates), which accounted for >90% of the total cell biomass. The numbers of ANME-1 cells increased strongly with depth; these cells accounted 1% of all single cells at the surface and more than 30% of all single cells (5% of the total cells) in 7- to 10-cm sediment horizons that were directly above layers of gas hydrate. In the Black Sea microbial mats ANME-1 accounted for about 50% of all cells. ANME-2/DSS aggregates occurred in microenvironments within the mat but accounted for only 1% of the total cells. FISH probes for the ANME-2a and ANME-2c subclusters were designed based on a comparative 16S rRNA analysis. In Hydrate Ridge sediments ANME-2a/DSS and ANME-2c/DSS aggregates differed significantly in morphology and abundance. The relative abundance values for these subgroups were remarkably different at Beggiatoa sites (80% ANME-2a, 20% ANME-2c) and Calyptogena sites (20% ANME-2a, 80% ANME-2c), indicating that there was preferential selection of the groups in the two habitats.

Physical oceanography during Nathaniel B. Palmer cruises NBP06-01 and NBP06-08 to the Ross Sea

We calculate net community production (NCP) during summer 2005-2006 and spring 2006 in the Ross Sea using multiple approaches to determine the magnitude and consistency of rates. Water column carbon and nutrient inventories and surface ocean O2/Ar data are compared to satellite-derived primary productivity (PP) estimates and 14C uptake experiments. In spring, NCP was related to stratification proximal to upper ocean fronts. In summer, the most intense C drawdown was in shallow mixed layers affected by ice melt; depth-integrated C drawdown, however, increased with mixing depth. Delta O2/Ar-based methods, relying on gas exchange reconstructions, underestimate NCP due to seasonal variations in surface Delta O2/Ar and NCP rates. Mixed layer Delta O2/Ar requires approximately 60 days to reach steady state, starting from early spring. Additionally, cold temperatures prolong the sensitivity of gas exchange reconstructions to past NCP variability. Complex vertical structure, in addition to the seasonal cycle, affects interpretations of surface-based observations, including those made from satellites. During both spring and summer, substantial fractions of NCP were below the mixed layer. Satellite-derived estimates tended to overestimate PP relative to 14C-based estimates, most severely in locations of stronger upper water column stratification. Biases notwithstanding, NCP-PP comparisons indicated that community respiration was of similar magnitude to NCP. We observed that a substantial portion of NCP remained as suspended particulate matter in the upper water column, demonstrating a lag between production and export. Resolving the dynamic physical processes that structure variance in NCP and its fate will enhance the understanding of the carbon cycling in highly productive Antarctic environments.

Aerodynamic optimization using Adjoint methods and parametric CAD models

This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.