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<!--
	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=mac">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=mac]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for mac]]></description>
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    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/486/Modeling-and-Extracting-information-about-Cybersecurity-Events-from-Text"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/483/From-Strings-to-Things"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/464/Tutorials-by-Center-for-Hybrid-Multicore-Productivity-Research-students"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/454/The-Semantic-Web-there-and-back-again"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/447/Generating-Linked-Data-from-Tables-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/40/Platys-From-Position-to-Place-in-Next-Generation-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/28/McNamee-receives-best-paper-award"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/46/AgentRX"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/105/ALDA-Automated-Legal-Document-Analytics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/8/DAML-ITTalks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/42/flipix"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/45/My-iCal-Agent"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/92/Platys-From-Position-to-Place-in-Next-Generation-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/63/Trauma-Pod"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/80/XPod"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance"/>
      <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/1180/Semantically-Rich-Approach-to-Automating-Regulations-of-Medical-Devices"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1136/Knowledge-Infusion-in-Privacy-Preserving-Data-Generation"/>
      <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/1052/Targeted-Knowledge-Infusion-To-Make-Conversational-AI-Explainable-and-Safe"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1050/Drug-Abuse-Ontology-to-Harness-Web-Based-Data-for-Substance-Use-Epidemiology-Research-Ontology-Development-Study"/>
      <rdf:li resource="http://ebiquity.umbc.edu/research/area/id/32/Machine-learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/389/After-75-Years-of-AI-Can-Machines-Think-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/394/After-75-years-of-AI-Can-Machines-Think-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/395/After-75-Years-of-AI-Can-Machines-Think-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/75/An-Intelligent-Broker-for-Pervasive-Context-Aware-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/67/Authorization-and-Privacy-for-Semantic-Web-Services"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/298/Coarse-and-Fine-Grained-Sentiment-Analysis-of-Online-Text"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/183/Finding-knowledge-data-and-answers-on-the-Semantic-Web"/>
    </rdf:Seq>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/486/Modeling-and-Extracting-information-about-Cybersecurity-Events-from-Text">
  <title><![CDATA[Modeling and Extracting information about Cybersecurity Events from Text]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/486/Modeling-and-Extracting-information-about-Cybersecurity-Events-from-Text</link>
  <description><![CDATA[People rely on the Internet to carry out much of the their daily activities such as banking, ordering food and socializing with their family and friends. The technology facilitates our lives, but also comes with many problems, including cybercrimes, stolen data and identity theft. With the large and increasing number of transaction done every day, the frequency of cybercrime events is also increasing. Since the number of security-related events is too high for manual review and monitoring, we...]]></description>
  <dc:date>2017-05-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction">
  <title><![CDATA[Generative Adversarial Networks, An Introduction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction</link>
  <description><![CDATA[While deep learning has made historic improvements in speech recognition and object recognition in recent years, almost all of these gains have been in supervised learning of now fairly well understood discriminative models. In the larger context of machine learning, less is understood about both unsupervised and generative models, but Generative Adversarial Networks have emerged as a promising approach to making progress in that direction. 

We are going to introduce Generative Adversarial...]]></description>
  <dc:date>2017-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/483/From-Strings-to-Things">
  <title><![CDATA[From Strings to Things]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/483/From-Strings-to-Things</link>
  <description><![CDATA[The Web is the greatest source of general knowledge available today. Its current form, however, suffers from two limitations.  The first is that text and multimedia objects on the Web are easy for people to understand but difficult for machines to interpret and use.  The second is that the Web's access paradigm remains dominated by information retrieval, where keyword queries produce a ranked list of documents that must be read to find the desired information.  I'll discuss research in natura...]]></description>
  <dc:date>2016-07-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data">
  <title><![CDATA[PhD defense: Lushan Han, Schema Free Querying of Semantic Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data</link>
  <description><![CDATA[Schema Free Querying of Semantic Data

Lushan Han

Developing interfaces to enable casual, non-expert users to query complex structured data has been the subject of much research over the past forty years. We refer to them as as schema-free query interfaces, since they allow users to freely query data without understanding its schema, knowing how to refer to objects, or mastering the appropriate formal query language. Schema-free query interfaces address fundamental problems in natural la...]]></description>
  <dc:date>2014-05-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/464/Tutorials-by-Center-for-Hybrid-Multicore-Productivity-Research-students">
  <title><![CDATA[Tutorials by Center for Hybrid Multicore Productivity Research students]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/464/Tutorials-by-Center-for-Hybrid-Multicore-Productivity-Research-students</link>
  <description><![CDATA[UMBC's Center for Hybrid Multicore Productivity Research, an NSF Industry & University Cooperative Research Center is holding its Industry Advisory Board meeting at UMBC 12-14 June. Students from UMBC and UCSD will present tutorials on a number of the technologies underlying ongoing CHMPR projects in a session from 1:00-5:00 on Wednesday June 12 in ITE 456. The tutorial session is free and open to the public.


	3-D Printing – Timothy Blattner (UMBC)
	Semantic Table Information – Va...]]></description>
  <dc:date>2013-06-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage">
  <title><![CDATA[Nimbus: Scalable, Distributed, In-Memory Data Storage]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/463/Nimbus-Scalable-Distributed-In-Memory-Data-Storage</link>
  <description><![CDATA[MS Defense

The Apache Hadoop project provides a framework for reliable, scalable, distributed computing. The storage layer of Hadoop, called the Hadoop Distributed File System (HDFS), is an append-only distributed file system designed for commodity hardware. The append-only nature of the file system limits the ability for applications to have random reads and writes of data. This was addressed by Apache HBase and Apache Accumulo, which both allow for quick random access to a highly scalabl...]]></description>
  <dc:date>2013-06-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/454/The-Semantic-Web-there-and-back-again">
  <title><![CDATA[The Semantic Web: there and back again]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/454/The-Semantic-Web-there-and-back-again</link>
  <description><![CDATA[The Web has made us all smarter by providing ubiquitous and easy access to virtually all human knowledge. Most of the knowledge is encoded as text, images or videos -- representations that people can easily process, understand and use but which still are difficult for machines. Making this knowledge more accessible to machines will unleash new and more intelligent computer applications and systems. Enabling computers to fully understand text, images and videos is a long term goal that will re...]]></description>
  <dc:date>2013-04-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/447/Generating-Linked-Data-from-Tables-">
  <title><![CDATA[Generating Linked Data from Tables.]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/447/Generating-Linked-Data-from-Tables-</link>
  <description><![CDATA[Large amounts of information is stored in tables, spreadsheets, CSV files and databases for a number of domains, including the Web, healthcare, e-science and public policy. The tables' structure facilitates human understanding, yet this very structure makes it difficult for machine understanding. This talk will focus on describing our work on making the intended meaning of tabular data explicit by representing it as RDF linked data, potentially making large amounts of scientific and medical d...]]></description>
  <dc:date>2013-03-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning">
  <title><![CDATA[Predicting Chronic Diseases with Machine Learning]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning</link>
  <description><![CDATA[In recent years we saw an explosion of cheap genetic tests, which lead to the emergence of personalized medicine.  Personalized medicine is defined as practice of medicine that is tailored to specifics of individual patient.  My work addresses the problem of attempting to predict individual’s predisposition towards certain chronic diseases based on the individual’s genetic makeup.  The benefits of such work allow for more selective administration of invasive tests such as biopsies, which ...]]></description>
  <dc:date>2013-03-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability">
  <title><![CDATA[An architecture for enterprise information interoperability]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability</link>
  <description><![CDATA[The World Wide Web differed from other early hypertext systems in the removal of "back links" (the ability of a hyperlinked object to link back to a referring resource). The removal of back links allowed the scalability inherent in the Web's design, but sacrificed the knowledge necessary to update links when content moved. Persistent URLs (PURLs) have been used on the Web since 1995 to provide an inexpensive and partial solution to link updates via HTTP redirection: PURLs do not change thei...]]></description>
  <dc:date>2012-11-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/40/Platys-From-Position-to-Place-in-Next-Generation-Networks">
  <title><![CDATA[Platys: From Position to Place in Next Generation Networks]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/40/Platys-From-Position-to-Place-in-Next-Generation-Networks</link>
  <description><![CDATA[A UMBC research team led by Anupam Joshi and Tim Finin received an award from
NSF for four-year project that will explore how advances
in mobile technology and networking can support systems that
understand and adapt their behavior to their user's context,
activities and preferences.

Platys is a collaborative research project between
UMBC and groups at North Carolina State (led by Munindar
Singh and Injong
Rhee) and Duke (led by Romit Roy Choudhury)
Universities.  The group will sh...]]></description>
  <dc:date>2009-08-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released">
  <title><![CDATA[Swoogle 2006 released]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released</link>
  <description><![CDATA[Swoogle 2006 is a a major
new version of Swoogle, a search engine for the Semantic Web.
Swoogle helps knowledge engineers and software agents find
knowledge on the web encoded in the semantic web languages RDF
and OWL.  It crawls the Web looking for documents that consists
of RDF or have embedded RDF within them.  USing Swoogle, people
and agents can discover Semantic Web ontologies, terms and data.

 Swoogle 2005 is a nearly complete rewrite of Swoogle Classic, which
now answers to ...]]></description>
  <dc:date>2006-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere">
  <title><![CDATA[Welcome to the Splogosphere]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere</link>
  <description><![CDATA[Welcome to the Splogosphere!

UMBC study estimates that 75% of posts to English language weblogs are spam


Baltimore, December 16, 2005

 A weblog monitoring system developed by UMBC Ph.D. student Pranam
Kolari shows that a new form of spam -- spam blogs or splogs --
has quickly become a serious problem. 

 Splogs are "fake"
weblog sites that have been set up to carry paid advertisements,
promote affiliated web sites by increasing their PageRank, and to get
new sites noti...]]></description>
  <dc:date>2005-12-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/28/McNamee-receives-best-paper-award">
  <title><![CDATA[McNamee receives best paper award]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/28/McNamee-receives-best-paper-award</link>
  <description><![CDATA[PhD student Paul
McNamee received a best paper award at the 2005 SIGIR Doctoral
Consortium for his paper 

Advancing Corpus-Based Bilingual
Retrieval,
28th Annual International ACM SIGIR Conferenc, 
Doctoral Consortium, Salvador, Brazil, 15 August 2005.

In addiiton to being a PhD student in the Computer Science program at UMBC, Paul is a Senior Computer Scientist in the Research and
Technology Development Center of the Johns Hopkins University Applied
Physics Laboratory.]]></description>
  <dc:date>2005-08-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/46/AgentRX">
  <title><![CDATA[AgentRX]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/46/AgentRX</link>
  <description><![CDATA[During the past two attempts to demonstrate our highly distributed
majordemo system we experienced many low level problems that prevented
the demo from going smoothly.  These ranged from machines being off
the network, to agents not being in the right state, to speakers being
unplugged.  It is well known that keeping a complex distributed system
up and running is a difficult task, made even all the more difficult
if many of the components are partially or completely autonomous.
This pr...]]></description>
  <dc:date>2003-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/105/ALDA-Automated-Legal-Document-Analytics">
  <title><![CDATA[ALDA: Automated Legal Document Analytics]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/105/ALDA-Automated-Legal-Document-Analytics</link>
  <description><![CDATA[There has been an exponential growth in use of digitized legal documents in recent years. Majority of services on the Internet have associated legal documents such as Terms of Services, Privacy Policies and Service Level agreements. A large corpus of court cases, judgments and compliance/regulations are now digitally available for e-discovery. Moreover, businesses are maintaining large data sets of legal contracts that they have signed with their employees, customers and contractors. Furtherm...]]></description>
  <dc:date>2014-06-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/8/DAML-ITTalks">
  <title><![CDATA[DAML / ITTalks]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/8/DAML-ITTalks</link>
  <description><![CDATA[DAML Tools for supporting Intelligent Information Annotation, Sharing and RetrievalWith the vast quantity of information now available on the Internet, there is a need to manage this information by marking it with a semantic language, such as DARPA Agent Markup Language (DAML), and using intelligent search engines and other tools, in conjunction with ontology-based matching, to provide better search results and data manipulation capabilities. The aim of the semantic web is to make the current...]]></description>
  <dc:date>2000-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/42/flipix">
  <title><![CDATA[flipix]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/42/flipix</link>
  <description><![CDATA[Create a program that  can automatically rotate an image from a digital camera so that it is oriented correctly.   A machine learning approach will be used to develop a model that can predict the proper orientation from low level image features.  If interested, contact Tim Finin.]]></description>
  <dc:date>2003-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance">
  <title><![CDATA[Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Healthcare providers are deploying a large number of AI-driven Medical devices to help monitor and medicate patients. For patients with chronic ailments, like diabetes or gastric diseases, usage of these devices becomes part of their daily lifestyle. These medical devices often capture personally identifiable information (PII) and hence are strictly regulated by the Food and Drug Administration (FDA) to ensure the safety and efficacy of the medical device. Medical device regulations are curre...]]></description>
  <dc:date>2023-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/45/My-iCal-Agent">
  <title><![CDATA[My iCal Agent]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/45/My-iCal-Agent</link>
  <description><![CDATA[The goal is to create an autonomous agent to maintain a personalized calendar for its user by using the iCal framework


iCal is a standard for publishing and sharing personal calendars. Using iCal-based applications (e.g., iCal and Mozilla Calendar), users can publish their personal calendars on a public calendar server (e.g., .Mac or iCalX) and subscribe to public calendars that are published by other users.
 

The design of My iCal Agent will take advantage of this publish/subscribe ...]]></description>
  <dc:date>2003-11-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/92/Platys-From-Position-to-Place-in-Next-Generation-Networks">
  <title><![CDATA[Platys: From Position to Place in Next Generation Networks]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/92/Platys-From-Position-to-Place-in-Next-Generation-Networks</link>
  <description><![CDATA[Platys is a collaborative research project between
UMBC and groups at North Carolina State (led by Munindar
Singh and Injong
Rhee) and Duke (led by Romit Roy Choudhury)
Universities.  The group will share $1.8M in research funding
from NSF's Network
Science and Engineering program.

Platys will develop a high-level notion of 'context' that
exploits the capabilities of next generation networks to enable
applications that deliver better user experiences. In particular,
it exploits mo...]]></description>
  <dc:date>2009-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/63/Trauma-Pod">
  <title><![CDATA[Trauma Pod]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/63/Trauma-Pod</link>
  <description><![CDATA[DARPA's Defense Sciences Office has funded a team led by SRI
to develop a prototype toward the development of a future
generation of battlefield-based unmanned medical treatment
systems.  These "Trauma Pods" will stabilize injured
soldiers within minutes after a battlefield trauma and
administer life-saving medical and surgical care prior to
evacuation and during transport.

The first phase of the program is an effort to develop
robotic technology to perform a totally unmanned surg...]]></description>
  <dc:date>2005-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/80/XPod">
  <title><![CDATA[XPod]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/80/XPod</link>
  <description><![CDATA[The XPod system aims
to integrate awareness of human activity and musical
preferences to produce an adaptive system
that plays the contextually correct music. The
XPod project introduces a “smart” music player
that learns its user’s preferences and activity, and
tailors its music selections accordingly. We are using
a BodyMedia device that has been shown to accurately
measure a user’s physiological state. The
device is able to monitor a number of variables to
determine its u...]]></description>
  <dc:date>2004-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance">
  <title><![CDATA[LLM based Knowledge Graph Approach to Automating Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Advanced medical devices increasingly rely on AI driven frameworks to automate compliance processes, ensuring safety and efficacy while reducing regulatory burdens. In the US, software-based medical devices, including those utilizing AI/ML models, are regulated by the FDA’s Center for Devices and Radiological Health (CDRH) under the Code of Federal Regulations (CFR) Title 21. These regulations are extensive, cross-referenced documents that require significant human effort to parse, leading ...]]></description>
  <dc:date>2025-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting">
  <title><![CDATA[DUNE: A Machine Learning Deep UNET++ based ensemble Approach to Monthly, Seasonal and Annual Climate Forecasting]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting</link>
  <description><![CDATA[Capitalizing on the recent availability of ERA5 monthly averaged, long-term data records of mean atmospheric and climate fields derived from the high-resolution reanalysis, deep learning architectures provide an alternative to physics-based daily numerical weather predictions for subseasonal to seasonal (S2S) and annual forecasts. A novel deep U-Net++-based ensemble (DUNE) neural architecture is introduced, incorporating encoder–decoder structures with residual blocks. When initialized with...]]></description>
  <dc:date>2025-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance">
  <title><![CDATA[MedReg-KG: KnowledgeGraph for Streamlining Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Healthcare providers are deploying a large number
of AI-driven Medical devices to help monitor and medicate
patients. For patients with chronic ailments, like diabetes or
gastric diseases, usage of these devices becomes part of their
daily lifestyle. These medical devices often capture personally
identifiable information (PII) and hence are strictly regulated by
the Food and Drug Administration (FDA) to ensure the safety
and efficacy of the medical device. Medical device regulations
a...]]></description>
  <dc:date>2024-12-15</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/1180/Semantically-Rich-Approach-to-Automating-Regulations-of-Medical-Devices">
  <title><![CDATA[Semantically Rich Approach to Automating Regulations of Medical Devices]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1180/Semantically-Rich-Approach-to-Automating-Regulations-of-Medical-Devices</link>
  <description><![CDATA[Advanced medical devices increasingly use sophisticated AI/ML models to enable real-time analytics for monitoring patients. In the US, these AI models, which often form the underlying device software, are regulated by the Center for Devices & Radiological Health (CDRH) at the Food & Drug Administration (FDA) to ensure the safety & efficacy of the medical device. These regulations for medical devices are currently available as large textual documents, called Code of Federal Regulations (CFR) T...]]></description>
  <dc:date>2024-07-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach">
  <title><![CDATA[Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach</link>
  <description><![CDATA[Background:

Artificial intelligence (AI) and machine learning (ML) technology design and development continues to be rapid, despite major limitations in its current form as a practice and discipline to address all socio-humanitarian issues and complexities. From these limitations emerges an imperative to strengthen AI/ML literacy in underserved communities and build a more diverse AI/ML design and development workforce engaged in health research.

Objective:

AI/ML has the potential to...]]></description>
  <dc:date>2023-09-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1136/Knowledge-Infusion-in-Privacy-Preserving-Data-Generation">
  <title><![CDATA[Knowledge Infusion in Privacy Preserving Data Generation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1136/Knowledge-Infusion-in-Privacy-Preserving-Data-Generation</link>
  <description><![CDATA[Security monitoring is crucial for maintaining a strong IT infrastructure by protecting against emerging threats, identifying vulnerabilities, and detecting potential points of failure. It involves deploying advanced tools to continuously monitor networks, systems, and configurations. However, organizations face challenges in adapting modern techniques like Machine Learning (ML) due to privacy and security risks associated with sharing internal data.  Compliance with regulations like GDPR fur...]]></description>
  <dc:date>2023-08-06</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/1052/Targeted-Knowledge-Infusion-To-Make-Conversational-AI-Explainable-and-Safe">
  <title><![CDATA[Targeted Knowledge Infusion To Make Conversational AI Explainable and Safe]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1052/Targeted-Knowledge-Infusion-To-Make-Conversational-AI-Explainable-and-Safe</link>
  <description><![CDATA[Conversational Systems (CSys) represent practical and tangible outcomes of advances in NLP and AI. CSys see continuous improvements through unsupervised training of large language models (LLMs) on a humongous amount of generic training data. However, when these CSys are suggested for use in domains like Mental Health, they fail to match the acceptable standards of clinical care, such as the clinical process in Patient Health Questionnaire (PHQ-9). The talk will present Knowledge-infused Learn...]]></description>
  <dc:date>2023-02-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1050/Drug-Abuse-Ontology-to-Harness-Web-Based-Data-for-Substance-Use-Epidemiology-Research-Ontology-Development-Study">
  <title><![CDATA[Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1050/Drug-Abuse-Ontology-to-Harness-Web-Based-Data-for-Substance-Use-Epidemiology-Research-Ontology-Development-Study</link>
  <description><![CDATA[Background: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends.

Methods: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontol...]]></description>
  <dc:date>2022-12-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/research/area/id/32/Machine-learning">
  <title><![CDATA[Machine learning]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/32/Machine-learning</link>
  <description><![CDATA[Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases.]]></description>
  <dc:date>2026-05-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/389/After-75-Years-of-AI-Can-Machines-Think-">
  <title><![CDATA[After 75 Years of AI, Can Machines Think?]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/389/After-75-Years-of-AI-Can-Machines-Think-</link>
  <description><![CDATA[Mathematician Alan Turing proposed a simple test to answer the question 'Can machines think?' nearly 75 years ago. Today, the surprising abilities of generative AI systems like ChatGPT make many wonder if we can finally respond positively. Dr. Finin will briefly cover AI's history leading up to the recent development of systems using neural networks and large language models like ChatGPT and what to expect in the next few years. He'll touch on what current systems can and cannot do, the ways ...]]></description>
  <dc:date>2024-04-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/394/After-75-years-of-AI-Can-Machines-Think-">
  <title><![CDATA[After 75 years of AI, Can Machines Think?]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/394/After-75-years-of-AI-Can-Machines-Think-</link>
  <description><![CDATA[Mathematician Alan Turing proposed a simple test to answer the question 'Can machines think?' nearly 75 years ago. Today, the surprising abilities of the latest generative AI systems make many wonder if we can finally respond positively. The talk briefly covers AI's history leading up to the recent development of systems using neural networks and large language models like ChatGPT and what to expect in the next few years.

A presentation given at the Charlestown Retirement Community on Apri...]]></description>
  <dc:date>2025-04-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/395/After-75-Years-of-AI-Can-Machines-Think-">
  <title><![CDATA[After 75 Years of AI, Can Machines Think?]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/395/After-75-Years-of-AI-Can-Machines-Think-</link>
  <description><![CDATA[Mathematician Alan Turing proposed a simple test to answer the question 'Can machines think?' nearly 75 years ago. Today, the surprising abilities of the latest generative AI systems make many wonder if we can finally respond positively. The talk briefly covers AI's history leading up to the recent development of systems using neural networks and large language models like ChatGPT and what to expect in the next few years.

A presentation given at the Charlestown Retirement Community on Apri...]]></description>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/75/An-Intelligent-Broker-for-Pervasive-Context-Aware-Systems">
  <title><![CDATA[An Intelligent Broker for Pervasive Context-Aware Systems]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/75/An-Intelligent-Broker-for-Pervasive-Context-Aware-Systems</link>
  <description><![CDATA[Presentation slides used in Harry Chen's PhD dissertation defense.

Context-aware systems exploit the use of situational information, or context, to provide relevant information and services to users. A great challenge remains in defining an architecture that supports context-aware systems. Critical research issues include modeling and reasoning (how to represent contextual information for machine processing and reasoning), knowledge sharing (how to enable agents to acquire consistent knowl...]]></description>
  <dc:date>2004-12-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/67/Authorization-and-Privacy-for-Semantic-Web-Services">
  <title><![CDATA[Authorization and Privacy for Semantic Web Services]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/67/Authorization-and-Privacy-for-Semantic-Web-Services</link>
  <description><![CDATA[Providing guarantees for security and privacy is paramount to the success of Semantic Web Services. In this article, the authors describe OWL-S policy annotations and extend the OWL-S Matchmaker and OWL-S Virtual Machine to support the processing of those policies.]]></description>
  <dc:date>2004-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/298/Coarse-and-Fine-Grained-Sentiment-Analysis-of-Online-Text">
  <title><![CDATA[Coarse and Fine Grained Sentiment Analysis of Online Text]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/298/Coarse-and-Fine-Grained-Sentiment-Analysis-of-Online-Text</link>
  <description><![CDATA[Sentiment analysis - the automated extraction of expressions of positive and negative attitudes from text - has received a great amount of attention over the last ten years. Over the same period, via the widespread growth in the use of what we have come to call social media, there has been an explosion in the amount of publically available user generated text on the Web. This text has the potential of providing a source of real time, time tagged sentiments from people all over the globe.

T...]]></description>
  <dc:date>2010-05-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift">
  <title><![CDATA[Detecting Domain Shift]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift</link>
  <description><![CDATA[Machine learning systems are typically trained in the lab and then deployed in the wild. But what happens when the data to which they are exposed in the wild change in a way that hurts accuracy? For example, a system may be trained to classify movie reviews as either positive or negative (i.e., sentiment classification), but over time book reviews get mixed into the data stream. The problem of responding to such changes when they are known to have occurred has been studied extensively. In thi...]]></description>
  <dc:date>2010-09-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach">
  <title><![CDATA[Detecting Spam Blogs: A Machine Learning Approach]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach</link>
  <description><![CDATA[Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by posts from splogs – false blogs with machine generated or hijacked content whose sole purpose is to host ads or raise the PageRank of target sites. We discuss how SVM models based on local and link-based features can be used t...]]></description>
  <dc:date>2006-07-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web">
  <title><![CDATA[Finding Data, Knowledge, and Answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form. As the volume of Semantic Web data grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perfo...]]></description>
  <dc:date>2007-05-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/183/Finding-knowledge-data-and-answers-on-the-Semantic-Web">
  <title><![CDATA[Finding knowledge, data and answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/183/Finding-knowledge-data-and-answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.

As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to per...]]></description>
  <dc:date>2006-07-17</dc:date>
 </item>
</rdf:RDF>
