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Search Publications by: Alden A. Dima (Fed)

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Displaying 1 - 25 of 45

KPI Extraction from Maintenance Work Orders-A Comparison of Expert Labeling, Text Classification and AI-Assisted Tagging for Computing Failure Rates of Wind Turbines

December 6, 2023
Author(s)
Marc-Alexander Lutz, Bastian Schafermeier, Rachael Sexton, Michael Sharp, Alden A. Dima, Stefan Faulstich, Jagan Mohini Aluri
Maintenance work orders are commonly used to document information about wind turbine operation and maintenance. This includes details about proactive and reactive wind turbine downtimes, such as preventative and corrective maintenance. However, the

An Infrastructure for Curating, Querying, and Augmenting Document Data: COVID-19 Case Study

August 8, 2023
Author(s)
Eswaran Subrahmanian, Guillaume Sousa Amaral, Talapady N. Bhat, Mary C. Brady, Kevin G. Brady, Jacob Collard, Sarra Chouder, Philippe Dessauw, Alden A. Dima, John T. Elliott, Walid Keyrouz, Nicolas Lelouche, Benjamin Long, Rachael Sexton, Ram D. Sriram
With the advent of the COVID-19 pandemic, there was the hope that data science approaches could help discover means for understanding, mitigating, and treating the disease. This manifested itself in the creation of the COVID-19 Open Research Dataset (CORD

LabelVizier: Interactive Validation and Relabeling for Technical Text Annotations

March 30, 2023
Author(s)
Xiaoyu Zhang, Xiwei Xuan, Rachael Sexton, Alden A. Dima
With the rapid accumulation of text data brought forth by advances in data-driven techniques, the task of extracting "data annotations"—concise, high-quality data summaries from unstructured raw text—has become increasingly important. Researchers in the

Adapting natural language processing for technical text

June 29, 2021
Author(s)
Alden A. Dima, Sarah Lukens, Melinda Hodkiewicz, Thurston Sexton, Michael Brundage
Despite recent dramatic successes, Natural Language Processing (NLP) is not ready to address a variety of real-world problems. Its reliance on large standard corpora, a training and evaluation paradigm that favors the learning of shallow heuristics, and

A Visual Analytics Approach for the Diagnosis of Heterogeneous and Multidimensional Machine Maintenance Data

May 10, 2021
Author(s)
Xiaoyu Zhang, Takanori Fujiwara, Senthil K. Chandrasegaran, Michael Brundage, Thurston Sexton, Alden A. Dima, Kwan-Liu Ma
Analysis of large, high-dimensional, and heterogeneous datasets is challenging as no one technique is suitable for visualizing and clustering such data in order to make sense of the underlying information. For instance, heterogeneous logs detailing machine

A Controlled Vocabulary and Metadata Schema for Materials Science Data Discovery

April 29, 2021
Author(s)
Andrea M. Medina-Smith, Chandler Becker, Raymond L. Plante, Laura Bartolo, Alden A. Dima, James A. Warren, Robert Hanisch
The International Materials Resource Registries (IMRR) working group of the Research Data Alliance (RDA) was created to spur initial development of a federated registry system to allow for easier discovery and access to materials data. As part of this

Implementing a Registry Federation for Materials Science Data Discovery

April 13, 2021
Author(s)
Raymond L. Plante, Chandler Becker, Andrea M. Medina-Smith, Kevin G. Brady, Alden A. Dima, Benjamin J. Long, Laura M. Bartolo, Robert Hanisch
As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are available and

Requirements Analysis of Large Policy Corpora

January 5, 2021
Author(s)
Alden A. Dima, Aaron Massey
Regulators, policy makers, and consumers are interested in proactively identifying services with acceptable or compliant data use policies, privacy policies, and terms of service. Academic requirements engineering researchers and legal scholars have

Technical Language Processing: Unlocking Maintenance Knowledge

December 11, 2020
Author(s)
Michael P. Brundage, Thurston B. Sexton, Melinda Hodkiewicz, Alden A. Dima, Sarah Lukens
Out-of-the-box natural-language processing (NLP) pipelines need re-imagining to understand and meet the requirements of the engineering sector. Text-based documents account for a significant portion of data collected during the life cycle of asset

MSEC: A QUANTITATIVE RETROSPECTIVE

June 25, 2020
Author(s)
Rachael Sexton, Michael Brundage, Alden A. Dima, Michael Sharp
The Manufacturing Science and Engineering Conference (MSEC) in 2020 is the 15th annual conference put on by the Manufacturing Engineering Division (MED) of ASME. MED and ASME MSEC focuses on manufacturing sciences, technology, and applications, including

An Informatics Infrastructure for the Materials Genome Initiative

July 6, 2016
Author(s)
Alden A. Dima, Sunil K. Bhaskarla, Chandler A. Becker, Mary C. Brady, Carelyn E. Campbell, Philippe J. Dessauw, Robert J. Hanisch, Ursula R. Kattner, Kenneth G. Kroenlein, Adele P. Peskin, Raymond L. Plante, Guillaume Sousa Amaral, Zachary T. Trautt, James A. Warren, Sharief S. Youssef, Sheng Yen Li, Pierre Francois Rigodiat, Marcus W. Newrock
A materials data infrastructure that enables the sharing and transformation of a wide range of materials data is an essential part of achieving the goals of the Materials Genome Initiative. We describe two high-level requirements of such an infrastructure

Shape Descriptors Comparison for Cell Tracking

October 15, 2015
Author(s)
Michael P. Majurski, Christopher Zheng, Joe Chalfoun, Alden A. Dima, Mary C. Brady
New microscope technologies are enabling the acquisition of large volumes of live cell image data. Accurate temporal object tracking is required to facilitate the analysis of this data. One principle component of cell tracking is correspondence, matching

Evaluation of Low-Contrast Detectability of Iterative Reconstruction across Multiple Institutions, CT Scanner Manufacturers, and Radiation Exposure Levels

February 19, 2015
Author(s)
Adele P. Peskin, Ganesh Saiprasad, James J. Filliben, Alden A. Dima
Purpose: To evaluate the impact of Iterative Reconstruction (IR) compared with Filtered Back Projection (FBP) using low-contrast objects in phantom images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of the Gammex 464

Structural Materials Data Demonstration Project: Resource for Thermal Process Modeling

July 1, 2014
Author(s)
Carelyn E. Campbell, Ursula R. Kattner, Alden A. Dima, Scott Henry, Larry A. Berardinis, Tom Searles, Laura M. Bartolo
Integrated Computational Materials Engineering (ICME)requires the availability of supporting data for modeling across multiple length scales. It also requires robust data schema and input-output protocols. To address these needs, a team working under a

Segmenting Time-lapse Phase Contrast Images of Adjacent NIH 3T3 Cells

January 15, 2013
Author(s)
Joe Chalfoun, Alden A. Dima, Marcin Kociolek, Michael W. Halter, Antonio Cardone, Adele P. Peskin, Peter Bajcsy, Mary C. Brady
We present a new method for segmenting phase contrast images of NIH 3T3 fibroblast cells that is accurate even when cells are in contact. The problem of segmentation, when cells are in contact, poses a challenge to the accurate automation of cell counting

Big Data Issues in Quantitative Imaging

August 29, 2012
Author(s)
Mary C. Brady, Alden A. Dima, Charles D. Fenimore, James J. Filliben, John Lu, Adele Peskin, Mala Ramaiah, Ganesh Saiprasad, Ram D. Sriram