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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=error">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=error]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for error]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/402/Estimating-Temporal-Boundaries-For-Events-Using-Social-Media-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/369/Machine-aided-human-translation-An-automated-system-for-transcribing-dictated-document-translations"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/349/Learning-by-Reading-Automatic-Knowledge-Extraction-Through-Semantic-Analysis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/341/Recovering-from-Internet-Routing-Failures-using-Declarative-Policies-and-Argumentation-Protocols"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/324/Security-Through-Policy-and-Trust-in-Mobile-Ad-Hoc-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/311/Understanding-RSM-Relief-Social-Media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/300/Virtual-Patients-as-Intelligent-Agents"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/267/An-Investigation-of-Linguistic-Information-for-Speech-Recognition"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/39/From-Need-to-Know-to-Need-to-Share-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/52/OWLCHecker"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1202/Towards-a-Dynamic-Data-Driven-AI-Regional-Weather-Forecast-Model"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1132/Knowledge-Graphs-and-Reinforcement-Learning-A-Hybrid-Approach-for-Cybersecurity-Problems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1018/Jointly-Identifying-and-Fixing-Inconsistent-Readings-from-Information-Extraction-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1005/The-Integration-of-Artificial-Intelligence-for-Improved-Operational-Air-Quality-Forecasting"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/952/Post-Quantum-Error-Correction-for-Quantum-Annealers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/280/Understanding-RSM-Relief-Social-Media"/>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration">
  <title><![CDATA[Phd proposal: A Semantic Resolution Framework for Manufacturing Capability Data Integration]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration</link>
  <description><![CDATA[Building flexible manufacturing supply chains requires interoperable and accurate manufacturing service capability (MSC) information of all supply chain participants. Today, MSC information, which is typically published either on the supplier’s web site or registered at an e-marketplace portal, has been shown to fall short of the interoperability and accuracy requirements. This issue can be addressed by annotating the MSC information using shared ontologies. However, ontology-based approach...]]></description>
  <dc:date>2013-05-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/402/Estimating-Temporal-Boundaries-For-Events-Using-Social-Media-Data">
  <title><![CDATA[Estimating Temporal Boundaries For Events Using Social Media Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/402/Estimating-Temporal-Boundaries-For-Events-Using-Social-Media-Data</link>
  <description><![CDATA[MS Thesis Defense


Social media websites like Twitter, Flickr and YouTube generate a high volume of user generated content as a major event occurs. Our goal is to automatically determine as accurately as possible when an event starts and when it ends by analyzing the content of social media data. Estimating these temporal boundaries segments the event-related data into three major phases: the buildup to the event, the event itself, and the post-event effects and repercussions.
We describ...]]></description>
  <dc:date>2011-06-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/369/Machine-aided-human-translation-An-automated-system-for-transcribing-dictated-document-translations">
  <title><![CDATA[Machine aided human translation - An automated system for transcribing dictated document translations]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/369/Machine-aided-human-translation-An-automated-system-for-transcribing-dictated-document-translations</link>
  <description><![CDATA[A model is presented for machine aided human translation (MAHT) that integrates source language text and target language acoustic information to produce the text translation of source language document. It is evaluated on a scenario where a human translator dictates a first draft target language translation of a source language document. Information obtained from the source language document, including translation probabilities derived from statistical machine translation (SMT) and named enti...]]></description>
  <dc:date>2010-10-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/349/Learning-by-Reading-Automatic-Knowledge-Extraction-Through-Semantic-Analysis">
  <title><![CDATA[Learning by Reading: Automatic Knowledge Extraction Through Semantic Analysis]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/349/Learning-by-Reading-Automatic-Knowledge-Extraction-Through-Semantic-Analysis</link>
  <description><![CDATA[Ph.D. Dissertation Defense

To support rich semantic analysis of text, traditional natural language processing tools require access to a cache of static knowledge with both broad coverage and deep meaning.  Acquiring this knowledge by hand is so expensive and error-prone, it has been dubbed the "knowledge acquisition bottleneck".  In this work, we present a method for reducing the impact of this bottleneck by automating the knowledge acquisition task using the novel approach of bootstrappin...]]></description>
  <dc:date>2010-07-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/341/Recovering-from-Internet-Routing-Failures-using-Declarative-Policies-and-Argumentation-Protocols">
  <title><![CDATA[Recovering from Internet Routing Failures using Declarative Policies and Argumentation Protocols]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/341/Recovering-from-Internet-Routing-Failures-using-Declarative-Policies-and-Argumentation-Protocols</link>
  <description><![CDATA[Many Internet failures are caused by misconﬁgurations of the BGP routers that manage routing of trafﬁc between domains. The problems are usually due to a combination of human errors and the lack of a high-level language for specifying routing policies that can be used to generate router conﬁgurations. We describe an implemented approach that uses a declarative language for specifying network-wide routing policies to automatically conﬁgure routers and show how it can also be used by so...]]></description>
  <dc:date>2010-04-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/324/Security-Through-Policy-and-Trust-in-Mobile-Ad-Hoc-Networks">
  <title><![CDATA[Security Through Policy and Trust in Mobile Ad Hoc Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/324/Security-Through-Policy-and-Trust-in-Mobile-Ad-Hoc-Networks</link>
  <description><![CDATA[Abstract:

Mobile ad hoc networks (MANETs) are susceptible to various node misbehaviors due to their unique features, such as highly dynamic network topology, rigorous power constraints and error-prone transmission media.Significant research efforts have been made to address the problem of misbehavior detection as well as trust management for MANETs. However,little research work has been done to distinguish truly malicious behaviors from the faulty behaviors. Both the malicious behaviors an...]]></description>
  <dc:date>2009-11-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/311/Understanding-RSM-Relief-Social-Media">
  <title><![CDATA[Understanding RSM: Relief Social Media]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/311/Understanding-RSM-Relief-Social-Media</link>
  <description><![CDATA[Anand Karandikar and Will Murnane will talk about a project they areworking on.  

This talk describes a new ONR-sponsored two-year research project
'Understanding RSM: Relief Social Media' that we are beginning in
conjunction with colleagues at the Lockheed Martin Advanced Technology
Laboratory.  The RSM project is aimed at helping to detect and monitor
information about crises and associated relief efforts from online
sources including both social media and main stream media.

Ther...]]></description>
  <dc:date>2009-09-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/300/Virtual-Patients-as-Intelligent-Agents">
  <title><![CDATA[Virtual Patients as Intelligent Agents]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/300/Virtual-Patients-as-Intelligent-Agents</link>
  <description><![CDATA[Virtual patient (VP) environments are becoming very popular as an educational, reference and assessment tool for the medical profession. Technologically, however, state-of-the-art VP environments devoted to training cognitive skills are still little more than decision trees whose nodes present static material and allow users a choice of which daughter node to visit next. The Maryland Virtual Patient (MVP) project seeks to simulate medical encounters at a higher level of verisimilitude. To thi...]]></description>
  <dc:date>2009-05-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment">
  <title><![CDATA[Feature Engineering for Sentiment]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment</link>
  <description><![CDATA[Sentiment analysis upon free text is a difficult domain since
 free text is often informally written, poorly structured, and
 rife with spelling and grammatical errors. These
 characteristics make them difficult to parse and process with
 standard language analysis tools. These factors have made
 machine learning techniques such as bag of words support vector
 machines very popular. We describe a better feature space to
 use with support vector machines that relies upon the uneven
 di...]]></description>
  <dc:date>2008-11-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/267/An-Investigation-of-Linguistic-Information-for-Speech-Recognition">
  <title><![CDATA[An Investigation of Linguistic Information for Speech Recognition]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/267/An-Investigation-of-Linguistic-Information-for-Speech-Recognition</link>
  <description><![CDATA[After several decades of effort, speech recognition technologies have made
significant progress and various speech based applications have been
developed.  However, current speech recognition systems still generate
erroneous output, which hinders the wide adoption of speech applications. 
Given that speech recognition systems' goal of error-free output can not
be realized in near future, mechanisms for automatically detecting and
even correcting speech recognition errors are called on t...]]></description>
  <dc:date>2008-10-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/39/From-Need-to-Know-to-Need-to-Share-">
  <title><![CDATA[From 'Need to Know’ to ‘Need to Share’:]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/39/From-Need-to-Know-to-Need-to-Share-</link>
  <description><![CDATA[From 'Need to Know’ to ‘Need to Share’: UMBC to Lead Six Campus-Team to Turn 9-11 Commission Intel-Sharing Reforms into Technology System

$7.5-million, Five-Year DoD Grant Partners UMBC With Purdue, Michigan, Illinois, Others

CONTACT: Chip Rose, UMBC News, 
410-455-5793, 
crose@umbc.edu


A six-campus team of computer scientists led by UMBC has been awarded a $7.5 million, five-year grant from the Department of Defense to turn the 9-11 Commission’s recommendations for bette...]]></description>
  <dc:date>2008-04-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web">
  <title><![CDATA[SemNews: news text to Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web</link>
  <description><![CDATA[SemNews Understands the News 

 Prototype UMBC system interprets online news stories  and  publishes text meaning on the Semantic Web

      SemNews is a prototype
application being developed by UMBC Ph.D. student Akshay Java that
uses a sophisticated text understanding system to interpret summaries
of news stories, publishes the results on the semantic web and
provides browsing and query services over them.  The project is the
result of a collaboration between the UMBC's Institute ...]]></description>
  <dc:date>2006-01-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/52/OWLCHecker">
  <title><![CDATA[OWLCHecker]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/52/OWLCHecker</link>
  <description><![CDATA[Develop a tool to help OWL ontology writers follow good style.  The
first step is to come up with a set of style conventions. these could
include conventions for documentation, importing ontologies,
organization, etc.  An author could apply the tool to an ontology and
get a HTML report on warnings and errors detected by the checker.

One model might be  Checkstyle
-- a development tool to help programmers write Java code that adheres
to a coding standard. It automates the process of c...]]></description>
  <dc:date>2004-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin">
  <title><![CDATA[Security Compliance for Smart Manufacturing using Knowledgegraph based Digital Twin]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin</link>
  <description><![CDATA[The combination of Information Technology (IT) and Operational Technology (OT) in smart manufacturing, driven by smart factory innovations and Internet of Things (IoT) devices, generates vast, diverse, and rapidly evolving Big Data, which in turn increases cybersecurity and compliance issues. Adherence to security standards, such as NIST SP 800-171, which requires rigorous access control and audit reporting, is currently obstructed by the resource-intensive and error-prone aspects of manual e...]]></description>
  <dc:date>2025-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1202/Towards-a-Dynamic-Data-Driven-AI-Regional-Weather-Forecast-Model">
  <title><![CDATA[Towards a Dynamic Data Driven AI Regional  Weather Forecast Model]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1202/Towards-a-Dynamic-Data-Driven-AI-Regional-Weather-Forecast-Model</link>
  <description><![CDATA[The advent of long-term reanalysis datasets such as ECMWF
ERA 4/5 has enabled the development of AI-driven machine learning
models for weather forecasting. The major benefit of AI as an approach
is its ability to reduce computational forecast time from tens of hours

to tens of seconds, thereby enabling a variety of new applications rang-
ing from extreme regional weather event forecasting to first responder

aid for wildfires, severe storms, floods, oil spills, tornadoes, and other
...]]></description>
  <dc:date>2024-11-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1132/Knowledge-Graphs-and-Reinforcement-Learning-A-Hybrid-Approach-for-Cybersecurity-Problems">
  <title><![CDATA[Knowledge Graphs and Reinforcement Learning: A Hybrid Approach for Cybersecurity Problems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1132/Knowledge-Graphs-and-Reinforcement-Learning-A-Hybrid-Approach-for-Cybersecurity-Problems</link>
  <description><![CDATA[With the explosion of available data and computational power, machine learning and deep learning techniques are being increasingly used to solve problems. The domain of cybersecurity is no exception, as we have seen multiple papers in the recent past using data-driven machine learning approaches for different tasks.

Rule-based and supervised machine learning-based approaches are often brittle in detecting attacks, can be defeated by adversaries that adapt, and cannot use the knowledge of e...]]></description>
  <dc:date>2023-07-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning">
  <title><![CDATA[A General Framework for Auditing Differentially Private Machine Learning]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning</link>
  <description><![CDATA[We present a framework to statistically audit the privacy guarantee conferred by a differentially private machine learner in practice. While previous works have taken steps toward evaluating privacy loss through poisoning attacks or membership inference, they have been tailored to specific models or have demonstrated low statistical power. Our work develops a general methodology to empirically evaluate the privacy of differentially private machine learning implementations, combining improved ...]]></description>
  <dc:date>2022-11-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1018/Jointly-Identifying-and-Fixing-Inconsistent-Readings-from-Information-Extraction-Systems">
  <title><![CDATA[Jointly Identifying and Fixing Inconsistent Readings from Information Extraction Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1018/Jointly-Identifying-and-Fixing-Inconsistent-Readings-from-Information-Extraction-Systems</link>
  <description><![CDATA[Information extraction systems analyze text to produce entities and beliefs, but their output often has errors. In this paper, we analyze the reading consistency of the extracted facts with respect to the text from which they were derived and show how to detect and correct errors. We consider both the scenario when the provenance text is automatically found by an information extraction system and when it is curated by humans. We contrast consistency with credibility; define and explore consis...]]></description>
  <dc:date>2022-05-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models">
  <title><![CDATA[Continuously Generalized Ordinal Regression for Linear and Deep Models]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1016/Continuously-Generalized-Ordinal-Regression-for-Linear-and-Deep-Models</link>
  <description><![CDATA[Ordinal regression is a classification task where classes have an order and prediction error increases the further the predicted class is from the true class. The standard approach for modeling ordinal data involves fitting parallel separating hyperplanes that optimize a certain loss function. This assumption offers sample efficient learning via inductive bias, but is often too restrictive in real-world datasets where features may have varying effects across different categories. Allowing cla...]]></description>
  <dc:date>2022-04-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1005/The-Integration-of-Artificial-Intelligence-for-Improved-Operational-Air-Quality-Forecasting">
  <title><![CDATA[The Integration of Artificial Intelligence for Improved Operational Air Quality Forecasting]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1005/The-Integration-of-Artificial-Intelligence-for-Improved-Operational-Air-Quality-Forecasting</link>
  <description><![CDATA[The National Oceanic and Atmospheric Administration (NOAA) is actively seeking to integrate the latest research in Artificial Intelligence (AI) techniques to solve a number of operational challenges. We describe two efforts underway that integrate deep learning techniques to improve operational air quality (AQ) forecasting.
The first effort is a collaboration between NOAA and the University of Maryland Baltimore County (UMBC) that uses deep learning to improve bias correction of model predic...]]></description>
  <dc:date>2021-12-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis">
  <title><![CDATA[Using Knowledge Graphs and Reinforcement Learning for Malware Analysis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis</link>
  <description><![CDATA[Machine learning algorithms used to detect attacks are limited by the fact that they cannot incorporate the background knowledge that an analyst has. This limits their suitability in detecting new attacks. Reinforcement learning is different from traditional machine learning algorithms used in the cybersecurity domain. Compared to traditional ML algorithms, reinforcement learning does not need a mapping of the input-output space or a specific user-defined metric to compare data points. This i...]]></description>
  <dc:date>2020-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/952/Post-Quantum-Error-Correction-for-Quantum-Annealers">
  <title><![CDATA[Post-Quantum Error-Correction for Quantum Annealers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/952/Post-Quantum-Error-Correction-for-Quantum-Annealers</link>
  <description><![CDATA[We present a general post-quantum error-correcting technique for quantum annealing, called multi-qubit correction (MQC), that views the evolution in an open-system as a Gibbs sampler and reduces a set of (first) excited states to a new synthetic state with lower energy value. After sampling from the ground state of a given (Ising) Hamiltonian, MQC compares pairs of excited states to recognize virtual tunnels—i.e., a group of qubits that changing their states simultaneously can result in a n...]]></description>
  <dc:date>2020-09-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers">
  <title><![CDATA[Leveraging Artificial Intelligence to Advance Problem-Solving with Quantum Annealers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/890/Leveraging-Artificial-Intelligence-to-Advance-Problem-Solving-with-Quantum-Annealers</link>
  <description><![CDATA[We show how to advance quantum information processing, specifically problem-solving with quantum annealers, in the realm of artificial intelligence.  We introduce SAT++, as a novel quantum programming paradigm, that can compile classical algorithms (implemented in classical programming languages) and execute them on quantum annealers.   Moreover, we introduce a post-quantum error correction method that can find samples with significantly lower energy values, compared to the state-of-the-art t...]]></description>
  <dc:date>2020-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/280/Understanding-RSM-Relief-Social-Media">
  <title><![CDATA[Understanding RSM: Relief Social Media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/280/Understanding-RSM-Relief-Social-Media</link>
  <description><![CDATA[This presentation describes a new ONR-sponsored two-year research project
'Understanding RSM: Relief Social Media' that we are beginning in
conjunction with colleagues at the Lockheed Martin Advanced Technology
Laboratory.  The RSM project is aimed at helping to detect and monitor
information about crises and associated relief efforts from online
sources including both social media and main stream media.

There has been a dramatic rise in the use of online social media
systems like Tw...]]></description>
  <dc:date>2009-09-15</dc:date>
 </item>
</rdf:RDF>
