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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=learning">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
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  <description><![CDATA[UMBC ebiquity RSS Tag Search for learning]]></description>
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      <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/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/96/Tables-to-Linked-Data"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/80/XPod"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1223/WIP-The-Impact-of-Financial-Aid-and-Academic-Pathways-on-Graduation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1205/Impostors-Among-Us-An-Agentic-Approach-to-Identifying-and-Resolving-Conflicts-in-Collaborative-Network-Environments"/>
      <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/1189/Enhancing-Trustworthiness-in-LLM-Generated-Code-A-Reinforcement-Learning-and-Domain-Knowledge-Constrained-Approach"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities"/>
      <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"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/333/Automatically-Generating-Linked-Data-from-Tables"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/195/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/140/Recognizing-Activities-using-RFID"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/141/Recognizing-Activities-using-RFID"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/11/Resource-Guide-for-Trust-on-the-Semantic-Web"/>
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 <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/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue">
  <title><![CDATA[Is your personal data at risk? App analytics to the rescue]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue</link>
  <description><![CDATA[According to Virustotal, a prominent virus and malware tool, the Google Play Store has a few thousand apps from major malware families. Given such a revelation, access control systems for mobile data management, have reached a state of critical importance. We propose the development of a system which would help us detect the pathways using which user's data is being stolen from their mobile devices. We use a multi layered approach which includes app meta data analysis, understanding code patt...]]></description>
  <dc:date>2015-09-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation">
  <title><![CDATA[Many Facets of Energy Disaggregation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation</link>
  <description><![CDATA[In this week's Ebiquity meeting, PhD student Nilavra Phatak from the UMBC Information Systems Department will discuss his work on "Many Facets of Energy Disaggregation".

The objective of energy disaggregation is to get the appliance-wise energy consumption from the whole home energy signal. The disaggregated energy consumption provides a better insight into the electrical usage and helps the consumers to modify usage in order to save money and energy. The application of energy disaggregati...]]></description>
  <dc:date>2014-10-29</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/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/451/Information-Extraction-of-Security-related-entities-and-concepts-from-unstructured-text">
  <title><![CDATA[Information Extraction of Security related entities and concepts from unstructured text]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/451/Information-Extraction-of-Security-related-entities-and-concepts-from-unstructured-text</link>
  <description><![CDATA[Cyber Security has been a big concern especially in past one decade where it is witnessed that targets ranging from large number of internet users to government agencies are being attacked because of vulnerabilities present in the system. Even though these vulnerabilities are identified and published publicly but response has always been slow in covering up these vulnerabilities because there is no automatic mechanism to understand and process this unstructured text that is published on inter...]]></description>
  <dc:date>2013-04-01</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/443/Virtual-Collaboration-and-Training-in-Medicine-through-Multimedia-e-Learning-system">
  <title><![CDATA[Virtual Collaboration and Training in Medicine through Multimedia e-Learning system]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/443/Virtual-Collaboration-and-Training-in-Medicine-through-Multimedia-e-Learning-system</link>
  <description><![CDATA[Virtual Collaboration and Training in Medicine through Multimedia e-Learning system

Web-based virtual collaboration is increasingly gaining popularity in almost every area in our society due to the fact that it can bridge the gap imposed by time and geographical constraints. However, in the medical field, such collaboration has been less popular. Some of the reasons were timeliness, security, and preciseness of the information they are dealing with. We propose a web-based distributed medic...]]></description>
  <dc:date>2013-02-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse">
  <title><![CDATA[Analytics for Detecting Web and Social Media Abuse]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse</link>
  <description><![CDATA[The Web and online social media provide invaluable communication services to a global Internet user base. The tremendous success of these services, however, has also created valuable opportunities for criminals and other miscreants to abuse them for their own gain. As a result, it is both an important yet challenging problem to detect, monitor, and curtail this abuse. However, the large scale and diversity of these services, combined with the tactics used by attackers, make it difficult to di...]]></description>
  <dc:date>2012-03-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/38/Looking-back-at-the-ebiquity-research-group-s-2006">
  <title><![CDATA[Looking back at the ebiquity research group's 2006]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/38/Looking-back-at-the-ebiquity-research-group-s-2006</link>
  <description><![CDATA[Maybe it's a bit of a cliché, but this is the traditional time to look back on the past year and reflect on how things are going.  It has been an active productive year.  Here's a rundown of our past year by the numbers.

205,000 is the number of visits to the Ebiquity web site.  Our monthly page visits increased five fold over the year and we currently receive about 25,000 visits a month.


   



743 people have
registered as users of the Swoogle
semantic web search system.  By ...]]></description>
  <dc:date>2007-01-01</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/project/html/id/109/Accelerated-Cybersecurity">
  <title><![CDATA[Accelerated Cybersecurity]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/109/Accelerated-Cybersecurity</link>
  <description><![CDATA[We conduct cutting edge research to address the national and global challenges in Cybersecurity by leveraging Cognitive Computing approaches Accelerated to work in soft real time. We aim to create a platform for Academia, Industry and Government to collaborate seamlessly and to advance UMBCâ€™s position as a leading research university in cybersecurity-related disciplines. We are a member of IBMâ€™s AI Horizonâ€™s Network.]]></description>
  <dc:date>2016-09-01</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/71/ArRf-Activity-Recognition-with-RF">
  <title><![CDATA[ArRf - Activity Recognition with RF]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/71/ArRf-Activity-Recognition-with-RF</link>
  <description><![CDATA[As the population ages tools for aiding in the care of elderly become increasingly valuable.  There is a need for a suite of tools that monitor senior citizens, help them through their day, and alert others if they need help.  Several good techniques for creating systems that assist senior citizens have emerged.  What all such computer systems lack is a good way to determine what a person is actually doing.  Entering every task that a person does into a computer is time consuming and not prac...]]></description>
  <dc:date>2005-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/79/Context-Aware-Surgical-Training">
  <title><![CDATA[Context-Aware Surgical Training]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/79/Context-Aware-Surgical-Training</link>
  <description><![CDATA[We propose to design and implement a prototype context aware surgical training environment (CAST) as part of the University of Maryland Surgical Simulation Training Center (SIMCenter).  This system will be used to explore the role that an intelligent pervasive computing environment can play to enhance the training of surgery students, residents and specialists.  The research will build on prior work on context aware “smart spaces” done at UMBC, leverage our experience in working with RFID...]]></description>
  <dc:date>2006-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/75/Feeds-that-matter">
  <title><![CDATA[Feeds that matter]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/75/Feeds-that-matter</link>
  <description><![CDATA[Finding good feeds is getting harder as the Blogosphere grows. We analyze the Bloglines public feed subscriptions and describe techniques to induce an intuitive set of feed topics. The FTM! prototype service uses a ranked list of the "feeds that matter" for each topic to allow users to browse the catalog and subscribe to interesting feeds.]]></description>
  <dc:date>2006-05-01</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/68/memeta">
  <title><![CDATA[memeta]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/68/memeta</link>
  <description><![CDATA[Weblogs, or blogs, have become an important new way to publish information, engage in discussions and form communities. The memeta project is developing a framework for representing and studying the structure and content of communities of blogs. We are particularly interested in how metadata about blogs can be extracted, discovered and computed and how that metadata can be used in the analysis of blogs and to provide new blog related services.  Examples of concrete problems we hope to be able...]]></description>
  <dc:date>2005-03-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/96/Tables-to-Linked-Data">
  <title><![CDATA[Tables to Linked Data]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/96/Tables-to-Linked-Data</link>
  <description><![CDATA[Vast amounts of information is encoded in tables found in documents, on the Web, and in spreadsheets or databases. Integrating or searching over this information benefits from understanding its intended meaning and making it explicit in a semantic representation language like RDF. Most current approaches to generating Semantic Web representations from tables requires human input to create schemas and often results in graphs that do not follow best practices for linked data. Evidence for a tab...]]></description>
  <dc:date>2010-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/57/Text-Mining-Approach-to-Ontology-Enrichment">
  <title><![CDATA[Text Mining Approach to Ontology Enrichment]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/57/Text-Mining-Approach-to-Ontology-Enrichment</link>
  <description><![CDATA[Ontologies have been widely accepted as the most advanced knowledge representation model. They are among the most important building blocks of semantic web, hence, very crucial for the success of semantic web. Huge effort is needed from the domain expert in order to construct ontologies manually. There is a need for semi-automatic approach in ontology building which will help the domain expert in constructing extensive domain ontologies efficiently. We propose the use of text mining technique...]]></description>
  <dc:date>2003-10-01</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/1223/WIP-The-Impact-of-Financial-Aid-and-Academic-Pathways-on-Graduation">
  <title><![CDATA[WIP: The Impact of Financial Aid and Academic Pathways on Graduation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1223/WIP-The-Impact-of-Financial-Aid-and-Academic-Pathways-on-Graduation</link>
  <description><![CDATA[Our work seeks to find out whether we can predict a student's graduation in STEM majors using AI, specifically in Engineering and Computing, based on both academic factors known at admission time and financial factors that the institution can control. We create an integrated predictive modeling system that uses financial assistance in conjunction with academic preparation and enrollment methods to determine student success as measured by graduation. The dataset contains anonymized records of ...]]></description>
  <dc:date>2026-03-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1205/Impostors-Among-Us-An-Agentic-Approach-to-Identifying-and-Resolving-Conflicts-in-Collaborative-Network-Environments">
  <title><![CDATA[Impostors Among Us: An Agentic Approach to Identifying and Resolving Conflicts in Collaborative Network Environments]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1205/Impostors-Among-Us-An-Agentic-Approach-to-Identifying-and-Resolving-Conflicts-in-Collaborative-Network-Environments</link>
  <description><![CDATA[Today’s networked cyber-physical environments contain a wide range of agents, including fixed sensors, unmanned aerial vehicles (UAVs), and unmanned ground vehicles (UGVs), which help accomplish the objective(s) of a given mission. These collaborating agents support informed decision making for humans to accomplish mission objectives such as surveillance or search and rescue. However, these agents and their sensors are subject to various failures, including power, communication, hardware, a...]]></description>
  <dc:date>2025-10-10</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/1189/Enhancing-Trustworthiness-in-LLM-Generated-Code-A-Reinforcement-Learning-and-Domain-Knowledge-Constrained-Approach">
  <title><![CDATA[Enhancing Trustworthiness in LLM Generated Code: A Reinforcement Learning and Domain-Knowledge Constrained Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1189/Enhancing-Trustworthiness-in-LLM-Generated-Code-A-Reinforcement-Learning-and-Domain-Knowledge-Constrained-Approach</link>
  <description><![CDATA[Imagine analyzing a piece of code that uses the function ConnectToServer() with an encrypted string as its argument. A large language model (LLM), trained on extensive programming data, might flag the use of encryption as suspicious and generate an explanation suggesting that the function likely connects to a malicious server. While this explanation might seem plausible, it can often be unfaithful—it overgeneralizes from statistical patterns in its training data without truly understanding ...]]></description>
  <dc:date>2025-02-25</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/1079/A-Study-of-the-Landscape-of-Privacy-Policies-of-Smart-Devices">
  <title><![CDATA[A Study of the Landscape of Privacy Policies of Smart Devices]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1079/A-Study-of-the-Landscape-of-Privacy-Policies-of-Smart-Devices</link>
  <description><![CDATA[As the adoption of smart devices continues to permeate all aspects of our lives, concerns surrounding user privacy have become more pertinent than ever before. While privacy policies define the data management practices of their manufacturers, previous work has shown that they are rarely read and understood by users. Hence, automatic analysis of privacy policies has been shown to help provide users with appropriate insights. Previous research has extensively analyzed privacy policies of websi...]]></description>
  <dc:date>2023-12-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis">
  <title><![CDATA[Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis</link>
  <description><![CDATA[Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The use of Big Data in farming requires the collection and analysis of data from various sources such as sensors, satellites, and farmer surveys. While Big Data can provide the farming community with valuable insights and improve efficiency, there is significant concern regarding the security of this data as well as th...]]></description>
  <dc:date>2023-12-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities">
  <title><![CDATA[Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities</link>
  <description><![CDATA[Our study is motivated by robotics, where when dealing with robots or other physical systems, we often need to balance competing concerns of relying on complex, multimodal data coming from a variety of sensors with a general lack of large representative datasets.  Despite the complexity of modern robotic platforms and the need for multimodal interaction, there has been little research on integrating more than two modalities in a low data regime with the real-world constraint that sensors fail...]]></description>
  <dc:date>2023-10-01</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/research/area/id/14/Data-Mining">
  <title><![CDATA[Data Mining]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/14/Data-Mining</link>
  <dc:date>2026-07-20</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>2026-07-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/research/area/id/36/Question-and-Answering-QnA-System">
  <title><![CDATA[Question and Answering (QnA) System]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/36/Question-and-Answering-QnA-System</link>
  <description><![CDATA[Our research focuses on developing new techniques and approaches to developing Question and Answer (QnA) systems. We focus on developing semantically rich , policy based applications that cater to a variety of domains like cybersecurity and Legal/Compliance.]]></description>
  <dc:date>2026-07-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/333/Automatically-Generating-Linked-Data-from-Tables">
  <title><![CDATA[Automatically Generating Linked Data from Tables]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/333/Automatically-Generating-Linked-Data-from-Tables</link>
  <description><![CDATA[Evidence for a table’s meaning can be found in its metadata but currently requires human interpretation. We describe techniques grounded in graphical models and probabilistic reasoning to infer meaning associated with a table. Using background knowledge from the Linked Open Data cloud, we automatically infer the semantics of column headers, table cell values (e.g., strings and numbers) and relations between columns and represent the inferred meaning as graph of RDF triples.]]></description>
  <dc:date>2011-11-15</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/181/Context-Aware-Surgical-Training-Environment">
  <title><![CDATA[Context Aware Surgical Training Environment]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/181/Context-Aware-Surgical-Training-Environment</link>
  <description><![CDATA[As part of the University of Maryland Medical School’s Operating Room of the Future Project we are developing a prototype context aware surgical training environment (CAST).  This facility will become part of the University of Maryland Surgical Simula-tion Training Center (SIMCenter) being built in Baltimore.  The CAST system will be used to explore the role that an intelligent pervasive computing environment can play to enhance the training of surgery students, residents and specialists.  ...]]></description>
  <dc:date>2006-06-19</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/397/GenAI-in-Formative-Assessment-of-Student-Learning">
  <title><![CDATA[GenAI in Formative Assessment of Student Learning]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/397/GenAI-in-Formative-Assessment-of-Student-Learning</link>
  <description><![CDATA[If students were persuaded that AI could fairly and accurately assess their ungraded (formative) practice, might faculty be willing and able to provide more opportunities for them to do so? If so, would it make a difference in more high-stakes (summative) assessments like midterm and final exams or assignments? If so, how might faculty best nudge and support students to take advantage of AI-assisted practice?

In this panel presentation, three faculty from three colleges show and tell how a...]]></description>
  <dc:date>2025-05-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/195/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web">
  <title><![CDATA[Learning the Semantic Meaning of a Concept from the Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/195/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web</link>
  <description><![CDATA[Many researchers have applied text classification techniques to the ontology mapping problem. The mapping results in these researches heavily depend on the availability of highly relevant text exemplars associated with individual concepts. However, manual preparation of exemplars is costly. In this work, we propose to automatically collect text exemplars by downloading and processing web pages listed in the search results obtained by querying a search engine. Search queries are formed for eac...]]></description>
  <dc:date>2006-08-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/140/Recognizing-Activities-using-RFID">
  <title><![CDATA[Recognizing Activities using RFID]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/140/Recognizing-Activities-using-RFID</link>
  <description><![CDATA[Discovering the activites of daily life through a wearable RFID tag reader.]]></description>
  <dc:date>2005-09-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/141/Recognizing-Activities-using-RFID">
  <title><![CDATA[Recognizing Activities using RFID]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/141/Recognizing-Activities-using-RFID</link>
  <dc:date>2005-09-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/11/Resource-Guide-for-Trust-on-the-Semantic-Web">
  <title><![CDATA[Resource Guide for Trust on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/11/Resource-Guide-for-Trust-on-the-Semantic-Web</link>
  <description><![CDATA[This page is a collection of information and resources about trust research on the semantic web. Our interests includes but not limited in trust representation, trust inference and trust based application.  Trust representation includes trust ontology development. Trust inference includes trust learning (how to generate trust knowledge from our daily experience), trust network inference (how to derive trust knowledge from learned trust knowledge), and trust based inference (how to use trust k...]]></description>
  <dc:date>2003-11-04</dc:date>
 </item>
</rdf:RDF>
