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Polar Geospatial Center

Abstract: 

Polar Geospatial Center

The Polar Geospatial Center (PGC) provides geospatial support, mapping, and GIS/remote sensing solutions to researchers and logistics groups in the polar science community. The Center collaborates with scientists to complete their research goals in a safe, timely, and efficient manner by providing expertise and access to geospatial data and derived products. While scientists have developed elevation models over most of the earth from varied sources, the Polar Regions lack even coarse resolution digital elevation models (DEMs). This dearth of data severely limits the potential for topographic analysis in hydrology, ecology, geology, and geomorphology, and greatly reduces the accuracy of satellite imagery. Using two algorithms developed by NASA Ames and the Byrd Polar Research Center at the Ohio State University, PGC is leveraging the high volume of stereoscopic imagery being acquired in polar areas to create high resolution DEMs for distribution to the polar science community. Preliminary tests and data distribution suggest that the science community both needs and is ready to utilize such DEMs for synoptic mapping and change detection .

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Group name: 
morinp

Dell Town Hall Meeting, September 4

posted on September 3, 2013 As part of the ongoing selection process for the next HPC system at MSI, MSI has invited top high performance computing vendors to present their high performance computing portfolios and roadmaps to users in a open discussion setting. Dell Computing will be at MSI on...

Big Data, Model Combining, and Predictive Modeling of High Dimensional Data

Abstract: 

Big Data, Model Combining, and Predictive Modeling of High Dimensional Data

Big Data and the predictive modeling of high-dimensional datasets are of great interest to practitioners in many fields, such as finance, biology, and economics. These researchers are taking a methodology, model combination, that is widely and efficiently used for low-dimensional datasets and adapting it for high-dimensional situations. The project will develop a general risk bound for the group's methodology for high-dimensional predictive modeling, especially classification problems. Further, an efficient computing algorithm for the combination schemes will be developed and wrapped into a publicly available R package.

Many Big-Data sets (real data) will be analyzed by multiple high-dimensional classification methods using cross-validation. It will take about 10 million non-linear numerical optimizations for process. Besides working with real data, the researchers will perform various numerical experiments in order to have a better understanding of their methods. For different scenarios, they will compare their methods with between five and ten other popular methods and run large number of replicates to reduce the bias from the samplings. This will take about 10 million calculations.

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Group name: 
yangyh

Fast RF Calculations for High Field MRI

Abstract: 

Fast RF Calculations for High Field MRI

Radio-frequency electromagnetic analysis of high field MRI coils is an indispensable task for the development of new coil designs, for optimization of existing coils through tuning and matching when they are loaded with human models, and to ensure safety through specific absorption rate (SAR) and temperature calculations. Finite difference time domain (FDTD)-based solvers have been the method of choice so far since they can easily handle the inhomogeneities in the human model and the utilization of low-cost GPU accelerators helped in reducing the simulation times. Nonetheless, these solvers still suffer long simulation times due to the resonant nature of MRI coils. Initial experiments and a recent publication show that frequency-domain hybrid methods, such as method of moments (MOM)-finite element method (FEM), are better suited to MRI experiments in terms of solution time. In addition, because they use surface-conformal tetrahedral meshes instead of cubical voxels, they are free from staircasing errors hence yield superior accuracy compared to FDTD. The cost of the FEM-MOM approach is that it needs more memory and high-performance computing clusters to handle high-resolution human models with low simulation times. MSI resources are therefore necessary for this work.

Group name: 
vaughanj

UofM Receives Funding From NSF for Dedicated Campus Research Network

The University of Minnesota today announced the National Science Foundation (NSF) has awarded it $500,000 to build a dedicated research and computing network enabling researchers on its Twin Cities campus to more easily collaborate and innovate with research institutions around the world in their...

Visitor Numbers to LMVL at an All-Time High

The LMVL hit a milestone in October by logging its 1,000th visitor for the year 2011. Over 100 of these visitors were from businesses and government agencies that are interested in the research being performed at the University and at MSI. We have also been visited by government officials, notably...

Computing Workshops Offered

The SC09 Education Program and the National Computational Science Institute are offering a number of workshops over the summer and fall. Workshops are available in a number of fields related to high-performance computing, including parallel and cluster computing, biology, chemistry, physics,...

Analysis of Performance Determinants in NYC Taxicab Industry

Abstract: 

Analysis of Performance Determinants in NYC Taxicab Industry

The project explores NYC Taxi and Limousine Commission data on yellow cab trips in 2013. The principal question is to what extent the locus of rent creation resides with individual drivers and/or taxi fleets and leasing agents. The study employs various regression techniques with multidimensional categorical variables to separate the effects via variance and higher moments decomposition. MSI resources are required to estimate the regressions with tens of thousands of dummy variables on the set of 170 million observations.

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Group name: 
wangr

High-Throughput Data Transfer for Astrophysics Simulations

MSI, with the support of the University of Minnesota’s NTS (Network and Telecommunication Services), has recently deployed a system to take advantage of the ten-gigabit network known as the Northern Lights GigaPoP network . With this system in place, MSI was able to help Peter J. Mendygral, a post-...

High-Throughput Microscale Assays for Vascular Contractility and Remodeling

Abstract: 

High-Throughput Microscale Assays for Vascular Contractility and Remodeling

Tissue engineered models of muscular contraction and remodeling are necessary to relate in vivo function to in vitro experimental platforms. These researchers are developing an assay that will improve upon previous muscular thin film (MTF) methods developed to measure contractility of cardiovascular smooth and striated muscle in vitro. This assay will be employed to determine the effects of growth factor stimulation on remodeling of tissues subjected to pressure pulses simulating blast traumatic brain injuries. The researchers employ soft lithography techniques, such as microcontact printing, to provide guidance cues for tissue organization in order to engineer realistic in vitro tissue mimics. Previously, MTFs have been used to characterize the effect of blast-like vascular injury in the initiation of cerebral vasospasm. The researchers are combining the current MTF assay with a traction force microscopy approach that will allow significant increases in experimental efficiency. New methods for microcontact printing will be developed and employed to construct arrays with multiple MTF-like tissue constructs whose mechanical function can be tested simultaneously using fluorescent beads and confocal microscopy. Imaris or a memory-intensive MATLAB digital image correlation code will be used to track bead positions, yielding datasets that can be used to determine the mechanical properties of the tissues. The researchers will create arrays of structurally identical tissues for high-throughput screening of growth factor-stimulated perturbation of vascular function. They expect to find a link between platelet-released growth factors and the progression from hypercontractility to large-scale remodeling typical of cerebral vasospasm onset. This assay will provide a platform for development of therapeutics for cerebral vasospasms caused by blast traumatic brain injury.

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Group name: 
alfordpw

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