Buffer Management for Packets with Processing Times

2015 ◽  
pp. 47-58 ◽  
Author(s):  
Yossi Azar ◽  
Oren Gilon
Keyword(s):  
Buffer Management ◽  
Processing Times

A new tool for rapid development of electron microscopy negatives and micrographs: Initial impressions of the MOHR/PRO-8 processor

1992 ◽  
Vol 50 (2) ◽  
pp. 972-973
Author(s):  
James C. Long
Keyword(s):  
Electron Microscopy ◽  
Processing Time ◽  
Rapid Development ◽  
Processing Times ◽  
Initial Impressions ◽  
Transport Method

Over the years, many techniques and products have been developed to reduce the amount of time spent in a darkroom processing electron microscopy negatives and micrographs. One of the latest tools, effective in this effort, is the Mohr/Pro-8 film and rc paper processor.At the time of writing, a unit has been recently installed in the photographic facilities of the Electron Microscopy Center at Texas A&M University. It is being evaluated for use with TEM sheet film, SEM sheet film, 35mm roll film (B&W), and rc paper.Originally designed for use in the phototypesetting industry, this processor has only recently been introduced to the field of electron microscopy.The unit is a tabletop model, approximately 1.5 × 1.5 × 2.0 ft, and uses a roller transport method of processing. It has an adjustable processing time of 2 to 6.5 minutes, dry-to-dry. The installed unit has an extended processing switch, enabling processing times of 8 to 14 minutes to be selected.

Robust Scheduling for Flexible Job-Shop Problems with Uncertain Processing Times

2015 ◽  
Vol 135 (6) ◽  
pp. 713-720
Author(s):  
Wan-Ling Li ◽  
Tomohiro Murata ◽  
Muhammad Hafidz Fazli bin Md Fauadi
Keyword(s):  
Job Shop ◽  
Flexible Job Shop ◽  
Robust Scheduling ◽  
Processing Times

How Digital and Physical Care Team Interaction Affect Processing Times: A Case Study of Hospitalists

2017 ◽  
Author(s):  
Itai Gurvich ◽  
Lu Wang ◽  
Kevin O'Leary ◽  
Nicholas D Soulakis ◽  
Jan A. Van Mieghem
Keyword(s):  
Care Team ◽  
Team Interaction ◽  
Processing Times ◽  
Affect Processing ◽  
Physical Care

scholarly journals A gold mine, but still no Klondike: Nordic register data in health inequalities research

2019 ◽  
Vol 47 (6) ◽  
pp. 618-630 ◽  
Author(s):  
Kjetil A. Van Der Wel ◽  
Olof Östergren ◽  
Olle Lundberg ◽  
Kaarina Korhonen ◽  
Pekka Martikainen ◽  
...  
Keyword(s):  
National Level ◽  
Data Access ◽  
Register Data ◽  
Future Research ◽  
Gold Mine ◽  
Birth Cohorts ◽  
Policy And Practice ◽  
Research Papers ◽  
Processing Times ◽  
Acquisition Processes

Aims: Future research on health inequality relies on data that cover life-course exposure, different birth cohorts and variation in policy contexts. Nordic register data have long been celebrated as a ‘gold mine’ for research, and fulfil many of these criteria. However, access to and use of such data are hampered by a number of hurdles and bottlenecks. We present and discuss the experiences of an ongoing Nordic consortium from the process of acquiring register data on socio-economic conditions and health in Denmark, Finland, Norway and Sweden. Methods: We compare experiences of data-acquisition processes from a researcher’s perspective in the four countries and discuss the comparability of register data and the modes of collaboration available to researchers, given the prevailing ethical and legal restrictions. Results: The application processes we experienced were time-consuming, and decision structures were often fragmented. We found substantial variation between the countries in terms of processing times, costs and the administrative burden of the researcher. Concerned agencies differed in policy and practice which influenced both how and when data were delivered. These discrepancies present a challenge to comparative research. Conclusions: We conclude that there are few signs of harmonisation, as called for by previous policy documents and research papers. Ethical vetting needs to be centralised both within and between countries in order to improve data access. Institutional factors that seem to facilitate access to register data at the national level include single storage environments for health and social data, simplified ethical vetting and user guidance.

scholarly journals Automated Cytogenetic Biodosimetry at Population-Scale

Radiation ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 79-94
Author(s):  
Peter K. Rogan ◽  
Eliseos J. Mucaki ◽  
Ben C. Shirley ◽  
Yanxin Li ◽  
Ruth C. Wilkins ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Dicentric Chromosome ◽  
Automated Assignment ◽  
Simulated Population ◽  
Dose Estimation ◽  
Processing Times ◽  
Multiple Processors ◽  
Exposure Levels ◽  
Population Scale

The dicentric chromosome (DC) assay accurately quantifies exposure to radiation; however, manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates unattended DC detection and determines radiation exposures, fulfilling IAEA criteria for triage biodosimetry. This study evaluates the throughput of high-performance ADCI (ADCI-HT) to stratify exposures of populations in 15 simulated population scale radiation exposures. ADCI-HT streamlines dose estimation using a supercomputer by optimal hierarchical scheduling of DC detection for varying numbers of samples and metaphase cell images in parallel on multiple processors. We evaluated processing times and accuracy of estimated exposures across census-defined populations. Image processing of 1744 samples on 16,384 CPUs required 1 h 11 min 23 s and radiation dose estimation based on DC frequencies required 32 sec. Processing of 40,000 samples at 10 exposures from five laboratories required 25 h and met IAEA criteria (dose estimates were within 0.5 Gy; median = 0.07). Geostatistically interpolated radiation exposure contours of simulated nuclear incidents were defined by samples exposed to clinically relevant exposure levels (1 and 2 Gy). Analysis of all exposed individuals with ADCI-HT required 0.6–7.4 days, depending on the population density of the simulation.

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