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Articles 1 - 12 of 12

Full-Text Articles in Engineering

A Framework For Assessing And Designing Human Annotation Practices In Human-Ai Teaming, Suzanne Ashley Stevens Jun 2021

A Framework For Assessing And Designing Human Annotation Practices In Human-Ai Teaming, Suzanne Ashley Stevens

Theses and Dissertations

This thesis work examines how people accomplish annotation tasks (i.e., labelling data based on content) while working with an artificial intelligence (AI) system. When people and AI systems work together to accomplish a task, this is referred to as human-AI teaming. This study reports on the results of an interview and observation study of 15 volunteers from the Washington DC area as the volunteers annotated Twitter messages (tweets) about the COVID-19 pandemic. During the interviews, researchers observed the volunteers as they annotated tweets, noting any needs, frustrations, or confusion that the volunteers expressed about the task itself or when ...


From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen Jan 2020

From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen

Faculty of Engineering and Information Sciences - Papers: Part B

The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative ...


Msg-Fast: Metagenomic Shotgun Data Fast Annotation Using Microbial Gene Catalogs, Stuart M. Brown, Hao Chen, Yuhan Hao, Bobby P. Laungani, Thahmina A. Ali, Changsu Dong, Carlos Lijeron, Baekdoo Kim, Claudia Wultsch, Zhiheng Pei, Konstantinos Krampis Jan 2019

Msg-Fast: Metagenomic Shotgun Data Fast Annotation Using Microbial Gene Catalogs, Stuart M. Brown, Hao Chen, Yuhan Hao, Bobby P. Laungani, Thahmina A. Ali, Changsu Dong, Carlos Lijeron, Baekdoo Kim, Claudia Wultsch, Zhiheng Pei, Konstantinos Krampis

Publications and Research

Background: Current methods used for annotating metagenomics shotgun sequencing (MGS) data rely on a computationally intensive and low-stringency approach of mapping each read to a generic database of proteins or reference microbial genomes.

Results: We developed MGS-Fast, an analysis approach for shotgun whole-genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads that is an alternative to using the integrated catalog of reference genes database of well-annotated genes compiled from human microbiome data. This method is rapid and provides high-stringency matches (>90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method ...


Creation Of An Annotated Library On Fda Approved Nanomedicines, Marley R. Hodson, Tanin Izadi, Nastassja Lewinski Ph.D, Bridget T. Mcinnes Ph.D Jan 2015

Creation Of An Annotated Library On Fda Approved Nanomedicines, Marley R. Hodson, Tanin Izadi, Nastassja Lewinski Ph.D, Bridget T. Mcinnes Ph.D

Undergraduate Research Posters

Nanomedicine is a type of nanotechnology used in the medical field to limit the dosage amount and target drug delivery to specific cells. Nanomedicines that are approved and used tend to be extremely successful; however despite over a decade of research, only a limited number of nanomedicines have advanced for clinical use. A possible reason for the numerous nanomedicine failures is lack of easily accessible information and research on previous nanomedicines. In this project, we have compiled nanomedicine labeling information from the Drugs@FDA website. We have extracted phrases/sentences from labels relating to keywords on nanomaterial properties and drug ...


Design And Application Of Methods For Curating Genetic Variation Databases, Sean Stephen Ephraim Jul 2014

Design And Application Of Methods For Curating Genetic Variation Databases, Sean Stephen Ephraim

Theses and Dissertations

Cordova (Curated Online Reference Database Of Variation Annotations) is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with population study information and pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research.


Computational Methods For Efficient Exome Sequencing-Based Genetic Testing, Adam Peter Deluca May 2013

Computational Methods For Efficient Exome Sequencing-Based Genetic Testing, Adam Peter Deluca

Theses and Dissertations

Exome sequencing, the process of sequencing the set of all known exons simultaneously using next-generation sequencing technology, has dramatically changed the landscape of genetic research and genetic testing. The incredible volume of data produced by these experiments creates challenges in: 1) annotating the affects of observed variants, 2) filtering to remove noise, 3) identifying plausible disease-causing variants, and 4) validating experimental results. Here we will present a series of bioinformatic tools and techniques intended to address these challenges with exome sequencing and associated validation experiments.

First, we will present the Automated Sequence Analysis Pipeline (ASAP), a tool for the efficient ...


A Database Server For Next-Generation Scientific Data Management, Mohamed Eltabakh, Walid G. Aref, Ahmed Elmagarmid Jan 2010

A Database Server For Next-Generation Scientific Data Management, Mohamed Eltabakh, Walid G. Aref, Ahmed Elmagarmid

Cyber Center Publications

The growth of scientific information and the increasing automation of data collection have made databases integral to many scientific disciplines including life sciences, physics, meteorology, earth and atmospheric sciences, and chemistry. These sciences pose new data management challenges to current database system technologies. This dissertation addresses the following three challenges: (1) Annotation Management: Annotations and provenance information are important metadata that go hand-in-hand with scientific data. Annotating scientific data represents a vital mechanism for scientists to share knowledge and build an interactive and collaborative environment. A major challenge is: How to manage large volumes of annotations, especially at various granularities ...


Emotional Speech Corpus Construction, Annotation And Distribution, Brian Vaughan, Charlie Cullen, Spyros Kousidis, John Mcauley May 2008

Emotional Speech Corpus Construction, Annotation And Distribution, Brian Vaughan, Charlie Cullen, Spyros Kousidis, John Mcauley

Conference papers

This paper details a process of creating an emotional speech corpus by collecting natural emotional speech assets, analysisng and tagging them (for certain acoustic and linguistic features) and annotating them within an on-line database. The definition of specific metadata for use with an emotional speech corpus is crucial, in that poorly (or inaccurately) annotated assets are of little use in analysis. This problem is compounded by the lack of standardisation for speech corpora, particularly in relation to emotion content. The ISLE Metadata Initiative (IMDI) is the only cohesive attempt at corpus metadata standardisation performed thus far. Although not a comprehensive ...


The Annotation Of Traditional Irish Dance Music Using Matt2 And Tansey, Bryan Duggan, Brendan O'Shea, Mikel Gainza, Padraig Cunningham Jan 2008

The Annotation Of Traditional Irish Dance Music Using Matt2 And Tansey, Bryan Duggan, Brendan O'Shea, Mikel Gainza, Padraig Cunningham

Conference papers

Current estimates put the canon of traditional Irish dance tunes at least 7,000 compositions. Given this diversity, a common problem faced by musicians and ethnomusicologists is identifying tunes from recordings. This is evident even in the number of commercial recordings whose title is gan aimn (without name). This work attempts to solve this problem by developing a Content Based Music Information Retrieval (CBMIR) System adapted to the characteristics of traditional Irish music. A system is presented called MATT2 (Machine Annotation of Traditional Tunes) whose primary goal is to annotate recordings of traditional Irish dance music with useful meta-data including ...


The Penn Discourse Treebank 2.0 Annotation Manual, Rashmi Prasad, Eleni Miltsakaki, Nikhil Dinesh, Alan Lee, Aravind Joshi, Livio Robaldo, Bonnie L. Webber Dec 2007

The Penn Discourse Treebank 2.0 Annotation Manual, Rashmi Prasad, Eleni Miltsakaki, Nikhil Dinesh, Alan Lee, Aravind Joshi, Livio Robaldo, Bonnie L. Webber

IRCS Technical Reports Series

This report contains the guidelines for the annotation of discourse relations in the Penn Discourse Treebank (http://www.seas.upenn.edu/~pdtb), PDTB. Discourse relations in the PDTB are annotated in a bottom up fashion, and capture both lexically realized relations as well as implicit relations. Guidelines in this report are provided for all aspects of the annotation, including annotation explicit discourse connectives, implicit relations, arguments of relations, senses of relations, and the attribution of relations and their arguments. The report also provides descriptions of the annotation format representation.


Automatic Annotation Of Database Images For Query-By-Concept, Nualsawat Hiransakolwong Jan 2004

Automatic Annotation Of Database Images For Query-By-Concept, Nualsawat Hiransakolwong

Electronic Theses and Dissertations, 2004-2019

As digital images become ubiquitous in many applications, the need for efficient and effective retrieval techniques is more demanding than ever. Query by Example (QBE) and Query by Concept (QBC) are among the most popular query models. The former model accepts example images as queries and searches for similar ones based on low-level features such as colors and textures. The latter model allows queries to be expressed in the form of high-level semantics or concept words, such as "boat" or "car," and finds images that match the specified concepts. Recent research has focused on the connections between these two models ...


An Image Database Semantically Structured Based On Automatic Image Annotation For Content-Based Image Retrieval, Xuejian Xiong, Kap Luk Chan, Lei Wang Jan 2002

An Image Database Semantically Structured Based On Automatic Image Annotation For Content-Based Image Retrieval, Xuejian Xiong, Kap Luk Chan, Lei Wang

Faculty of Engineering and Information Sciences - Papers: Part A

In this paper, we presented a semantically structured image database for content-based image retrieval. A class descriptor is proposed to represent each class using a multiprototype model, which can be obtained by using a learning scheme, such as the Unsupervised Optimal Fuzzy Clustering algorithm, on a group of sample images manually selected from the class. Based on the proposed Image-Class Matching Distance, a similarity measure at the semantic level between an image and classes, images can be annotated by tokens of classes. Hence, composite features of images, including low-level descriptors, class descriptors, and image annotation, are stored into a structured ...