Computer Engineering Commons^™

Learnings From A National Cyberattack Digital Disaster During The Sars-Cov-2 Pandemic In A Pediatric Emergency Medicine Department, Fiona Leonard, Hugh O'Reilly, Carol Blackburn, Laura Melody, Dani Hall, Eleanor Ryan, Kate Bruton, Pamela Doyle, Bridget Conway, Michael Barrett

Articles

Objective: The primary objective was to analyze the impact of the national cyberattack in May 2021 on patient flow and data quality in the Paediatric Emergency Department (ED), amid the SARS-CoV-2 (COVID-19) pandemic. Methods: A single site retrospective time series analysis was conducted of three 6-week periods: before, during, and after the cyberattack outage. Initial emergent workflows are described. Analysis includes diagnoses, demographic context, key performance indicators, and the gradual return of information technology capability on ED performance. Data quality was compared using 10 data quality dimensions. Results: Patient visits totaled 13 390. During the system outage, patient experience times …

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles …

Data Management System For A Semiautonomous Shuttle Car For Underground Room And Pillar Coal Mines, Vasilis Androulakis, Steven Schafrik, Joseph Sottile, Zacharias Agioutantis

Mining Engineering Faculty Publications

In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart …

A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan

Turkish Journal of Electrical Engineering and Computer Sciences

High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data …

Data Management Of Data Processing Framework In Green Data Center, Zhang Xiao, Gao Yuan, Xiaoliang Wang, Yiyong Ge, Haixiang Yang, Shupeng Wan

Journal of System Simulation

Abstract: Using renewable energy in data center is an environment-friendly way to solve the problem of high energy consumption of data center. Since renewable energy is variable, delaying the jobs which has no strict deadline i a widely used strategy to maximize the usage of renewable energy. Meanwhile, turning the idle servers off can further reduce energy consumption. If the data required by the jobs to be processed are unavailable, some servers in sleep state need to be reactivated to guarantee that the data required by the jobs are available. Such operation may lead to energy waste due to the …

Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham

Asian Management Insights

Improving predictions and allocations to determine the optimal matching of demand and supply in a dynamic, uncertain future.

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

Estimating The Selectivity Of Like Queries Using Pattern-Based Histograms, Mehmet Ayti̇mur, Ali̇ Çakmak

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate cost and time estimation of a query is one of the major success indicators for database management systems. SQL allows the expression of flexible queries on text-formatted data. The LIKE operator is used to search for a specified pattern (e.g., LIKE "luck %") in a string database. It is vital to estimate the selectivity of such flexible predicates for the query optimizer to choose an efficient execution plan. In this paper, we study the problem of estimating the selectivity of a LIKE query predicate over a bag of strings. We propose a new type of pattern-based histogram structure to …

Building A Data “Deep State” @Gvsu, Matt Schultz

Matt Schultz

A Centralized Management System For Raster Data, Felix Linde, Ralf Wieland, Karin Groth

International Congress on Environmental Modelling and Software

We present a concept for a system to manage and distribute geo-referenced raster data from multiple possible sources on the institute level. The core concept is to centralize all import routines for data from different sources and formats, store the information in a common data format and distribute the needed information for research purposes upon request. By using hdf5 files, it can be assured that geo-spatial data is always kept in close connection with the corresponding meta-data. Furthermore this approach builds a technical basis for enhancing data fusion methods by allowing the use of common analysis routines, regardless of the …

A Scientific Data Management Infrastructure For Environmental Monitoring And Modelling, Daniel Henzen, Matthias Mueller, Simon Jirka, Ivo Senner, Thomas Kaeseberg, Jin Zhang, Lars Bernard, Peter Krebs

International Congress on Environmental Modelling and Software

Environmental projects often require the collaboration of researchers from different disciplines or domains in an interoperable context. With regard to data handling, most of these projects have an analogous workflow: phenomena are monitored, observation data are captured, (pre-) processed, exchanged, published, and finally disseminated among other scientists, practitioners and stakeholders. In many cases, each of the project partners implements these workflows separately and the integration of the distributed data sets happen in later project stages. In this paper, we present building blocks for research data infrastructure which covers the complete project cycle and supports data integration right from the beginning. …

Practical Guidance For Integrating Data Management Into Long-Term Ecological Monitoring Projects, Robert D. Sutter, Susan Wainscott, John R. Boetsch, Craig Palmer, David J. Rugg

Library Faculty Publications

Long-term monitoring and research projects are essential to understand ecological change and the effectiveness of management activities. An inherent characteristic of long-term projects is the need for consistent data collection over time, requiring rigorous attention to data management and quality assurance. Recent papers have provided broad recommendations for data management; however, practitioners need more detailed guidance and examples. We present general yet detailed guidance for the development of comprehensive, concise, and effective data management for monitoring projects. The guidance is presented as a graded approach, matching the scale of data management to the needs of the organization and the complexity …

The Social Life Of Big Data - Pawsey Resources, Luke Edwards

The Social Life of Big Data Symposium

The presentation covers the supercomputing facilities and services available at the Pawsey Supercomputing Centre, Western Australia.
The Pawsey Supercomputing Centre is an unincorporated joint venture between CSIRO, Curtin University, Edith Cowan University, Murdoch University and the University of Western Australia and is supported by the Western Australian Government.

Presentation On Evaluating The Creation And Preservation Challenges Of Photogrammetry-Based 3d Models, Michael J. Bennett

UConn Library Presentations

No abstract provided.

Evaluating The Creation And Preservation Challenges Of Photogrammetry-Based 3d Models, Michael J. Bennett

Published Works

Though the roots of photogrammetry can be traced back to photography’s earliest days, only recent advances in both digital technology and software applications have put the possibilities of 3D modeling from 2D source images in the hands of the greater cultural heritage community. The possibilities of such 3D digital rendering are many. With these possibilities come unique digital preservation challenges. This study explores basic close-range photogrammetry as applied to sample archival objects. Additionally, the latest BagIt and ZIP-based bundling formats along with repository-based solutions are also surveyed as potential 3D data management and archiving aggregators for resulting 3D models.

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Wilson A Higashino

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Foss Big Data Storage Solution, Gary L. Jaffe

STAR Program Research Presentations

Utilizing the AERO Institute as an IT test bed or “sandbox”, a small-agile development team will design, build, and test a data management storage system to support post processing of archived and in-flight data collected with the Piccolo flight control system and Compact Fiber Optic Sensing System (C-FOSS). Both systems are integrated on the APV3 aircraft, a small remote-operated vehicle. Due to the amount of data collected from C-FOSS, a system will be designed to sort and organize large data sets. An open-source database will be explored as a viable solution to manage large data loads and provide multi-cluster system …

Automating Data Management And Sharing Within A Large-Scale, Heterogeneous Sensor Network, Jeffery S. Horsburgh, Amber Spackman Jones, Stephanie Reeder

International Congress on Environmental Modelling and Software

Hydrology researchers are collecting data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that require infrastructure for data storage, management, and sharing. Managing streaming sensor data is challenging, especially in large networks with large numbers of sites and sensors. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data product. It also depends on the ability of researchers to share and access the data in usable formats. In this paper …

Web Service And Plug-In Architecture For Flexibility And Openness Of Environmental Data Sharing Platforms, Stephen Knox, Philipp Meier, Julien Harou

International Congress on Environmental Modelling and Software

The sharing, comparison and maintenance of computer model input and result data for real-world projects is a challenge. In collaborative research projects, particularly when collaboration occurs between multiple institutions in different locations, the complications are greater still. The co-development of water resource network simulation and optimization models is one field that faces this challenge. There is a need for ways to allow multiple users to build and apply models collaboratively. This paper argues that a web service architecture is an appropriate approach for multi-institution maintenance of resource network models. We describe the design of a prototype system that allows developers …

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Katarina Grolinger

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Electrical and Computer Engineering Publications

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Vsfs: A Versatile Searchable File System For Hpc Analytics, Lei Xu, Ziling Huang, Hong Jiang, Lei Tian, David Swanson

CSE Technical Reports

Big-data/HPC analytics applications have urgent needs for file-search services to drastically reduce the scale of the input data to accelerate analytics. Unfortunately, the existing solutions either are poorly scalable for large-scale systems, or lack well-integrated interface to allow applications to easily use them. We propose a distributed searchable file system, VSFS, which provide a novel and flexible POSIX-compatible searchable file system namespace that can be seamlessly integrate with any legacy code without modification. Additionally, to provide real-time indexing and searching performance, VSFS uses DRAM-based distributed consistent hashing ring to manages all file-index. The results of our evaluation show that VSFS …

Sports Data Mining Technology Used In Basketball Outcome Prediction, Chenjie Cao

Dissertations

Driven by the increasing comprehensive data in sports datasets and data mining technique successfully used in different area, sports data mining technique emerges and enables us to find hidden knowledge to impact the sport industry. In many instances, predicting the outcomes of sporting events has always been a challenging and attractive work and is therefore drawing a wide concern to conduct research in this field. This project focuses on using machine learning algorithms to build a model for predicting the NBA game outcomes and the algorithms involve Simple Logistics Classifier, Artificial Neural Networks, SVM and Naïve Bayes. In order to …

Sheep Updates 2005 - Part 2, Peter Tozer, Janette Drew, K. E. Kemper, M. L. Hebart, F. D. Brien, K. S. Jaensch, R. J. Grimson, D. H. Smith, A. M. M. Ramsay, J. S. Richards, K. D. Atkins, T. Thompson, W. K. Murray, J. R. L. Hall, Chris Carter, Peter Tozer, Mark Hyder, John Young, B. A. Mcgregor, Patricia Harper

Sheep Updates

This session covers seven papers from different authors: CONCURRENT SESSIONS - STRATEGIC MANAGEMENT 1.Finishing Pastoral Lambs, Peter Tozer, Patricia Harper, Janette Drew, Department of Agriculture Western Australia 2. Coating Improves Wool Quality under Mixed Farming Conditions, KE Kemper, ML Hebart, FD Brien, KS Grimson, DH Smith AMM Ramsay, South Australian Research and Development Institute 3. J. S. Richards, K.D. Atkins, T. Thompson, W. K. Murray, Australian Sheep Industry Co-operative Research Centre and NSW Department of Primary Industries, Orange Agricultural Institute, Forest Rd. Orange 4. Strategic Risk Management in the Sheep Industry, J.R.L. Hall, ICON Agriculture (JRL Hall & Co) 5. …

Metadata And Buckets In The Smart Object, Dumb Archive (Soda) Model, Michael L. Nelson, Kurt Maly, Delwin R. Croom Jr., Steven W. Robbins

Computer Science Faculty Publications

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs), and discuss the role of metadata in SODA. The premise of the SODA model is to "push down" many of the functionalities generally associated with archives into the data objects themselves. Thus the data objects become "smarter", and the archives "dumber". In the SODA model, archives become primarily set managers, and the objects themselves negotiate and handle presentation, enforce terms and conditions, and perform data content management. Buckets are our implementation of smart objects, and da is our reference implementation for dumb archives. We also present our …

Message-Bundle Converting In Intenet Protocol Multicast-Based High Level Architecture Exercises, Tracy A. Bobo

Theses and Dissertations

The Department of Defense is pushing for more wide-spread and realistic interactive training simulations which increases the demand on network capacity and resources. While network bandwidth is a measurable resource, packet bandwidth, or the number of packets-per-second (Pk/s) a host can handle, is a shifting commodity. This research analyzes host performance characteristics under varying data loads. The hosts include SGI single and multi-processor systems and Intel Pentium platforms using both Windows 95 and Linux Operating Systems. The networking media covers Ethernet, ATM and FDDI. For the ATM network, both AAL5 and IP over ATM were analyzed. With the data from …