Efficient state estimation via inference on a probabilistic graphical model

This thesis presents a unique and efficient solver to the state estimation (SE) problem for the power grid, based on probabilistic graphical models (PGMs). SE is a method of estimating the varying state values of voltage magnitude and phase at every bus within a power grid based on meter measurements. However, existing SE solvers are notorious for their computational inefficiency to calculate the matrix inverse, and hence slow convergence to produce the final state estimates. The proposed PGM-based solver estimates the state values from a different perspective. Instead of calculating the matrix inverse directly, it models the power grid as a PGM, and then assigns potentials to nodes and edges of the PGM, based on the physical constraints of the power grid. This way, the original SE problem is transformed into an equivalent probabilistic inference problem on the PGM, for which two efficient algorithms are proposed based on Gaussian belief propagation (GBP). The equivalence between the proposed PGM-based solver and existing SE solvers is shown in terms of state estimates, and it is experimentally demonstrated that this new method converges much faster than existing solvers

Deuteron compton scattering below pion threshold

A series of experiments were performed at the Tagged Photon Facility at MAX-lab in Lund, Sweden to study photon scattering from the deuteron and extract the neutron polarizabilities. The deuteron Compton scattering cross section was measured at laboratory angles of $60^o$, $120^o$, and $150^o$ for photon energies from 70 - 112 MeV. The photons were scattered from the Lund liquid deuterium target and detected in three large (20'' x 20'') NaI photon spectrometers. These detectors have sufficient energy resolution ($\sim$2$\%$ at 100 MeV) to separate the elastically and inelastically scattered photons. The extracted scattering cross section for this experiment was found to have angular distributions that matched prior experiments but needed a scaling factor to bring the absolute cross section into agreement. This scaling factor was determined to have a value of 1.47 $\pm$ 0.10. Suggestions are made for future studies that could yield further knowledge of the scaling factor and potentially allow for this data to be re-normalized

Learning to Love the Loquacious Library

Libraries are underutilized resources available to high school teachers. Our team set out with the goal to bring more students into the library by designing a set of “units” for which teachers could bring classes into the library. Each unit addresses Common Core Standards while simultaneously teaching a valuable skill or specific lesson. We wanted these lessons to be applicable to students, include a form of genuine assessment, while also helping teachers transition to the Common Core standards. These units are designed to be taught by librarians, but to teach skills/lessons that teachers would in their own classroom

Insects of Western North America 7. Survey of selected arthropod taxa of Fort Sill, Comanche County, Oklahoma. 4. Hexapoda: selected Coleoptera and Diptera with cumulative list of arthropoda and additional taxa

August 22, 2011

A rigorous evaluation of crossover and mutation in genetic programming

The role of crossover and mutation in Genetic Programming (GP) has been the subject of much debate since the emergence of the field. In this paper, we contribute new empirical evidence to this argument using a rigorous and principled experimental method applied to six problems common in the GP literature. The approach tunes the algorithm parameters to enable a fair and objective comparison of two different GP algorithms, the first using a combination of crossover and reproduction, and secondly using a combination of mutation and reproduction. We find that crossover does not significantly outperform mutation on most of the problems examined. In addition, we demonstrate that the use of a straightforward Design of Experiments methodology is effective at tuning GP algorithm parameters

A Survey Overviewing Technological Aspects of Wastewater Treatment Facilities in the State of Tennessee

Wastewater is produced from several industrial and anthropogenic activities and includes the sources such as showers, sinks, washing machines, dishwasher, toilet, etc. It contains microbes, pathogens, and several other organic and inorganic substances that are harmful to the environment and that must be removed before the water can safely be returned to natural streams. This sewage is pumped to the cleaning facilities through the drainage system. The treatment facilities called wastewater treatment plants (WWTPs) are operated in the cities at different capacities suitable to handle the water volume. Although all these facilities display a basically similar treatment process, there exists a few variations depending upon the capacities, location, cost of operation, population it serves, and type of contaminants required to remove. In this research, a comprehensive report illustrating the different aspects of WWTPs in the State of Tennessee will be drafted. This will include evaluating and summarizing the similarities and variations among the different WWTPs: For example, some facilities implement chlorination methods in tertiary treatment unit; others, UV-based methods, and more advanced cases use UV photocatalysis, etc. The research will also include a general discussion about the pros and cons of these similarities and differences and recommend some potentially novel technologies. These may be susceptible of upscaling and adaptable to treat sewage more effectively and less costly. We believe that the outcome of this research will be useful information for potentially improving sewage treatment across the State of Tennessee of the current scenarios and provides a future direction

Cipta tular yang beri manfaat

There is a great need to be able to measure chemical environments at both the cellular and sub- cellular levels in real time because chemical irregularities in these environments are indicative of many disease states. In this project, a surface-enhanced Raman scattering (SERS) based optical fiber sensor is designed to monitor pH in real time. SERS spectra of reporter molecules adsorbed on the fiber are used to deliver information on the chemical composition of the environment