Video data compression using artificial neural network differential vector quantization

An artificial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Differential Vector Quantization is used to preserve edge features, and a new adaptive algorithm, known as Frequency-Sensitive Competitive Learning, is used to develop the vector quantizer codebook. To develop real time performance, a custom Very Large Scale Integration Application Specific Integrated Circuit (VLSI ASIC) is being developed to realize the associative memory functions needed in the vector quantization algorithm. By using vector quantization, the need for Huffman coding can be eliminated, resulting in superior performance against channel bit errors than methods that use variable length codes

MatlabMPI

The true costs of high performance computing are currently dominated by software. Addressing these costs requires shifting to high productivity languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI point-to-point communications standard. The key technical innovation of MatlabMPI is that it implements the widely used MPI ``look and feel'' on top of standard Matlab file I/O, resulting in an extremely compact (~250 lines of code) and ``pure'' implementation which runs anywhere Matlab runs, and on any heterogeneous combination of computers. The performance has been tested on both shared and distributed memory parallel computers (e.g. Sun, SGI, HP, IBM, Linux and MacOSX). MatlabMPI can match the bandwidth of C based MPI at large message sizes. A test image filtering application using MatlabMPI achieved a speedup of ~300 using 304 CPUs and ~15% of the theoretical peak (450 Gigaflops) on an IBM SP2 at the Maui High Performance Computing Center. In addition, this entire parallel benchmark application was implemented in 70 software-lines-of-code, illustrating the high productivity of this approach. MatlabMPI is available for download on the web (www.ll.mit.edu/MatlabMPI).Comment: Download software from http://www.ll.mit.edu/MatlabMPI, 12 pages including 7 color figures; submitted to the Journal of Parallel and Distributed Computin

Nonlinear multiclass discriminant analysis

An alternative nonlinear multiclass discriminant algorithm is presented.This algorithm is based on the use of kernel functions and is designed to optimize a general linear discriminant analysis criterion based on scatter matrices.By reformulating these matrices in a specific form,a straightforward derivation a lows the kernel function to be introduced in a simple and direct way.Moreover,we propose a method to determine the value of the regularization parameter,based on this derivation.This work was supported in part by the HPCMO PET program and by the Spanish Ministry of Science and Technolog

Stress and Anxiety Among Correctional Health Care Professionals in a U.S. State Prison System During COVID-19

Since prisons were an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, the experience of correctional health care professionals (HCPs) may differ from HCPs in other settings. This cross-sectional descriptive study assessed stress, anxiety, and burnout levels in home and work environments among HCPs employed by one U.S. state prison system during the period of initial COVID-19 vaccine rollout. Participants (N = 444) were invited to voluntarily participate in an anonymous questionnaire distributed by prison administration from March 1 through May 17, 2021. Measures were adapted from a prior study of noncorrectional HCPs during the COVID-19 pandemic. Descriptive statistics (mean; standard deviation; 25th, 50th, and 75th percentiles), ranking measures that could alleviate anxiety and stress related to the pandemic, and qualitative responses were analyzed. Responses from 43% of HCPs (192) revealed that correctional HCPs experienced high levels of stress and anxiety at work and at home during the pandemic, with particularly high levels among females and registered nurses. Understanding and addressing these stressors will be of critical importance as prison systems work to avoid turnover of experienced HCPs in such specialized settings and also help inform human resource planning at state prison systems for future public health responses

Nonlinear multiclass discriminant analysis

An alternative nonlinear multiclass discriminant algorithm is presented.This algorithm is based on the use of kernel functions and is designed to optimize a general linear discriminant analysis criterion based on scatter matrices.By reformulating these matrices in a specific form,a straightforward derivation a lows the kernel function to be introduced in a simple and direct way.Moreover,we propose a method to determine the value of the regularization parameter,based on this derivation.This work was supported in part by the HPCMO PET program and by the Spanish Ministry of Science and Technolog

Campus Bridging: Campus Leadership Engagement in Building a Coherent Campus Cyberinfrastructure Workshop Report

This report presents the discussions at and recommendations made at “Campus Leadership Engagement in Building a Coherent Campus Cyberinfrastructure,” a workshop held in Anaheim, California from October 10-12, 2010. The main goals for this workshop focused on gathering the thoughts, ideas and perspectives of senior university administrators. The resulting report covers the topics of: - The current state of campus bridging from the perspectives of the CIO and VP for Research. - Challenges and opportunities at the campus leader level for enablement of campus bridging in the university community. - The senior campus leadership advocacy role for promoting campus bridging.This workshop and preparation of this report and related documents were supported by several sources, including: National Science Foundation through grant #OCI-1059812 (Patrick Dreher PI; Craig A. Stewart; James Pepin; Guy Almes; Michael Mundrane Co-PIs) (Co-Principal Investigator) RENCI (the Renaissance Computing Institute, http://www.renci.org/) supported this workshop and report by generously providing the time and effort of Patrick Dreher and through underwriting of this effort by RENCI Director Stanley Ahalt Indiana University Pervasive Technology Institute (http://pti.iu.edu/) for funding staff providing logistical support of the task force activities, writing and editorial staff, and layout and production of the final report document. Texas A&M University (http://www.tamu.edu) supported this workshop and report by generously providing the time and effort of Guy Almes. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation, the Indiana University Pervasive Technology Institute, or Indiana University