Now showing items 426-445 of 911

    • Kapton Polyimide-Based EEG Microelectrode Array and Interfaces for Mice Brainwave Recordings and Analysis 

      Gupta, D.; Islam, M.; Nam, H.; Lobo, M. K.; Choa, F. S. (SPIE, 2018)
      There is a rise in the study of functional connectivity among various cortical regions and investigations to uncover causal links between a stimulus and the corresponding neural dynamics through electrophysiological imaging ...
    • KELVIN: a tool for automated knowledge base construction 

      McNamee, Paul; Mayfield, James; Finin, Tim; Oates, Tim; Lawrie, Dawn; Xu, Tan; Oard, Doug (2013-06-03)
      We present KELVIN, an automated system for processing a large text corpus and distilling a knowledge base about persons, organizations, and locations. We have tested the KELVIN system on several corpora, including: (a) the ...
    • KELVIN: Extracting Knowledge from Large Text Collections 

      Mayfield, James; McNamee, Paul; Harmon, Craig; Finin, Tim; Lawrie, Dawn (AAAI Press, 2014-11-13)
      We describe the KELVIN system for extracting entities and relations from large text collections and its use in the TAC Knowledge Base Population Cold Start task run by the U.S. National Institute of Standards and Technology. ...
    • Key Establishment in Large Dynamic Groups Using One-Way Function Trees 

      Sherman, Alan T.; McGrew, David A. (IEEE, 2003-05-21)
      We present, implement, and analyze a new scalable centralized algorithm, called OFT, for establishing shared cryptographic keys in large, dynamically changing groups. Our algorithm is based on a novel application of one-way ...
    • KGCleaner : Identifying and Correcting Errors Produced by Information Extraction Systems 

      Padia, Ankur; Ferraro, Frank; Finin, Tim
      KG Cleaner is a framework to identify and correct errors in data produced and delivered by an information extraction system. These tasks have been understudied and KG Cleaner is the first to address both. We introduce a ...
    • KiloGrams: Very Large N-Grams for Malware Classification 

      Raff, Edward; Fleming, William; Zak, Richard; Anderson, Hyrum; Finlayson, Bill; Nicholas, Charles; McLean, Mark (2019-08-01)
      N-grams have been a common tool for information retrieval and machine learning applications for decades. In nearly all previous works, only a few values of n are tested, with n>6 being exceedingly rare. Larger values of n ...
    • Knowledge Base Evaluation for Semantic Knowledge Discovery 

      Mayfield, James; Dorr, Bonnie J.; Finin, Tim; Oard, Doug; Piatko, Christine (2008-11-14)
      Semantic knowledge discovery has traditionally been evaluated at the text level. For example, evaluations such as MUC and ACE evaluate the information extraction of particular types of semantic roles and relations primarily ...
    • Knowledge Begets Knowledge: Steps towards Assisted Knowledge Acquisition in Cyc 

      Witbrock, Michael; Matuszek, Cynthia; Brusseau, Antoine; Kahlert, Robert; Fraser, C. Bruce; Lenat, Douglas (AAAI, 2005)
      The Cyc project is predicated on the idea that, in order to be effective and flexible, computer software must have an understanding of the context in which its tasks are performed. We believe this context is what is known ...
    • Knowledge Enrichment by Fusing Representations for Malware Threat Intelligence and Behavior 

      Piplai, Aritran; Mittal, Sudip; Abdelsalam, Mahmoud; Gupta, Maanak; Joshi, Anupam; Finin, Tim
      Security engineers and researchers use their disparate knowledge and discretion to identify malware present in a system. Sometimes, they may also use previously extracted knowledge and available Cyber Threat Intelligence ...
    • Knowledge graph fact prediction via knowledge-enriched tensor factorization 

      Padia, Ankur; Kalpakis, Konstantinos; Ferraro, Francis; Finin, Tim (Elsevier, 2019-02-15)
      We present a family of novel methods for embedding knowledge graphs into real-valued tensors. These tensor-based embeddings capture the ordered relations that are typical in the knowledge graphs represented by semantic web ...
    • A Knowledge-Based Approach To Intrusion Detection Modeling 

      More, Sumit; Mathews, M. Lisa; Joshi, Anupam; Finin, Tim (IEEE, 2012-05-24)
      Current state of the art intrusion detection and prevention systems (IDPS) are signature-based systems that detect threats and vulnerabilities by cross-referencing the threat or vulnerability signatures in their databases. ...
    • A Knowledge-Based Approach to Network Security: Applying Cyc in the Domain of Network Risk Assessment 

      Shepard, Blake; Matuszek, Cynthia; Fraser, C. Bruce; Wechtenhiser, William; Crabbe, David; Güngördü, Zelal; Jantos, John; Hughes, Todd; Lefkowitz, Larry; Witbrock, Michael; Lenat, Doug; Larson, Erik (Association for the Advancement of Articifical Intelligence (AAAI), 2005-07)
      CycSecureTM is a network risk assessment and network monitoring application that relies on knowledge-based artificial intelligence technologies to improve on traditional network vulnerability assessment. CycSecure integrates ...
    • KQML - A Language and Protocol for Knowledge and Information Exchange 

      Finin, Tim; Fritzson, Rich; McKay, Don; McEntire, Robin
      This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language( KQML), a new language and protocol for exchanging information and knowledge. This work is part a larger effort, ...
    • KQML as an agent communication language 

      Finin, Tim; Fritzson, Richard; McKay, Don; McEntire, Robin (ACM, 1994-10-29)
      This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge. This work is part of a larger effort, ...
    • Large enhancement of interface second-harmonic generation near the zero- ¯ n gap of a negative-index Bragg grating 

      D’Aguanno, Giuseppe; Mattiucci, Nadia; Bloemer, Mark J.; Scalora, Michael (American Physical Society (APS), 2006-03-06)
      We predict a large enhancement of interface second-harmonic generation near the zero- ¯n gap of a Bragg grating made of alternating layers of negative- and positive-index materials. Field localization and coherent ...
    • Large Scale Taxonomy Classification using BiLSTM with Self-Attention 

      Gao, Hang; Oates, Tim (ACM, 2018-07)
      In this paper we present a deep learning model for the task of large scale taxonomy classification, where the model is expected to predict the corresponding category ID path given a product title. The proposed approach ...
    • Large Third-Order Nonlinearities in Atomic Layer Deposition Grown Nitrogen-Enriched TiO₂ Nanoscale Films 

      Kuis, Robinson; Gougousi, Theodosia; Basaldua, Isaac; Burkins, Paul; Kropp, Jaron A.; Johnson, Anthony M. (IEEE, 2020-08)
      Nonlinear refractive index, n₂, values as high as 1±.1x10⁻⁹ cm² /W were measured in atomic layer deposition (ALD) grown TiO₂ nanoscale films, using femtosecond thermally managed Z-scan. The several order of magnitude ...
    • LASCA: Learning Assisted Side Channel Delay Analysis for Hardware Trojan Detection 

      Vakil, Ashkan; Behnia, Farnaz; Mirzaeian, Ali; Homayoun, Houman; Karimi, Naghmeh; Sasan, Avesta (2020-01-17)
      In this paper, we introduce a Learning Assisted Side Channel delay Analysis (LASCA) methodology for Hardware Trojan detection. Our proposed solution, unlike the prior art, does not require a Golden IC. Instead, it trains ...
    • A Layered Approach to Semantic Similarity Analysis of XML Schemas 

      Kim, Jaewook; Peng, Yun; Kulvatunyou, Serm; Ivezic, Nenad; Jones, Albert (IEEE, 2008-08-05)
      One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema mapping, which is known to be costly and error-prone. Past research on schema mapping has not fully ...
    • Learning Aligned Cross-Modal Representations from Weakly Aligned Data 

      Castrejón, Lluís; Aytar, Yusuf; Vondrick, Carl; Pirsiavash, Hamed; Torralba, Antonio (IEEE, 2016-06-30)
      People can recognize scenes across many different modalities beyond natural images. In this paper, we investigate how to learn cross-modal scene representations that transfer across modalities. To study this problem, we ...