Stander Symposium abstract book - University of Dayton

9:00 AM to 10:30 AM
Isolation and Characterization of Wastewater Phage
Presenter(s): Yexun Wang
Advisor(s): Denise G Taylor
Civil-Environmental Engineering and Engineering Mechanics - Graduate Research
Biological transformation processes are widely used in wastewater treatment, where those processes are dependent on mixed microorganisms,
mainly bacteria. However, filamentous bacteria, a type of existing bacterial microorganisms in wastewater, need to be controlled to prevent excessive
overgrowth that interferes with wastewater treatment. Current research on this program is seeking a biocontrol of filamentous bacteria via
selective bacteriophages other than chemicals to protect other useful microbes. This project is to search for a number of phage groups that control
the growth of specific filamentous bacteria in sludge production processes without interfering with the other bacteria. Samples were enriched for
phage. Phages were isolated in one of two host bacteria and then selectivity tested against the other host. Sphaerotilus natans, a type of filamentous
bacteria that is known in the activated sludge process, was used as the host with inoculating phages, as well as E.coli which may be common
in wastewater treatment processes. Samples were obtained of supernatant from diverse treatment processes at various wastewater treatment
plants. All the samples were thought to be good candidates since no article pointed out which process was better than the others. Other than
the optimum control conditions regarding enrichment, maintenance and storage that is still being explored, the controls of growth, inoculation
methods and storage of hosts would be recommended individually and compared with previous protocols.
Accelerating Robotic Arm Calibration on GPGPUs
Presenter(s): Chong Chen
Advisor(s): Tarek M Taha
Electrical and Computer Engineering - Graduate Research
We examine the acceleration of a robotic arm calibration algorithm using a general purpose GPU (GPGPU). The algorithm utilized requires a radial
basis function neural network for calibration and takes approximately 9 days to run on a standard desktop computer. The most time consuming
component of this algorithm is a matrix inversion operation. This is carried out on an NVIDIA GPGPU using the Cholesky Factorization. On an NVIDIA
Tesla S1070 GPGPU, this same algorithm ran about 300 times faster than a standard desktop computer running an optimized version of the code.
Analysis of Motion Blur Using Double Discrete Wavelet Transform
Presenter(s): Yi Zhang
Advisor(s): Keigo Hirakawa
Electrical and Computer Engineering - Graduate Research
Object motion causes spatially varying blur. Estimating such a type of blur from a single image is an ill-posed problem that is difficult to solve. In
this paper, we introduce the notion of double discrete wavelet transform (DDWT) designed to sparsify the blurred image and blur kernel simultaneously.
Based on DDWT analysis, we are able to accurately estimate motion blur kernels and recover the latent sharp image. The blind image
deblurring solution proposed here handles spatially varying motion blurs effectively and efficiently.
Barium Strontium Titanate Varactor-Tuned Spiral Bandstop Filter for Microwave
Applications
Presenter(s): Hailing Yue
Advisor(s): Guru Subramanyam
Electrical and Computer Engineering - Graduate Research
A novel Barium-Strontium-Titanate(BST) varactor-tuned spiral bandstop filter (BSF) is presented. The BST varactor operation is based on the
nonlinear dielectric tunability of BST thin film sandwiched between two metal layers in a conductor-backed coplanar waveguide(CBCPW) transmission
line configuration. The varactor area is formed by the overlap area between the spiral shunt line in the bottom metal layer and the center
signal line in the top metal layer. The considered spiral-structured devices of spiral shunt line sizes were designed, simulated and fabricated. The
fabricated BSF is expected to achieve up to 40 dB rejection at microwave stop band with an optimized Q factor.
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