Showing papers by "Mitre Corporation published in 2014"
01 Jan 2014
TL;DR: The results from three trials showed that framing had no significant effect on the likelihood that a participant would click a subsequent spear phishing email and that many participants either clicked all links or none regardless of whether they received training.
Abstract: To explore the effectiveness of embedded training, researchers conducted a large-scale experiment that tracked workers' reactions to a series of carefully crafted spear phishing emails and a variety of immediate training and awareness activities. Based on behavioral science findings, the experiment included four different training conditions, each of which used a different type of message framing. The results from three trials showed that framing had no significant effect on the likelihood that a participant would click a subsequent spear phishing email and that many participants either clicked all links or none regardless of whether they received training. The study was unable to determine whether the embedded training materials created framing changes on susceptibility to spear phishing attacks because employees failed to read the training materials.
202 citations
TL;DR: If adaptational lag has occurred over just a few decades in banked seeds of an annual species, it may be an important consideration for managing longer-lived species, as well as for attempts to conserve threatened populations through ex situ preservation.
Abstract: If climate change outpaces the rate of adaptive evolution within a site, populations previously well adapted to local conditions may decline or disappear, and banked seeds from those populations will be unsuitable for restoring them. However, if such adaptational lag has occurred, immigrants from historically warmer climates will outperform natives and may provide genetic potential for evolutionary rescue. We tested for lagging adaptation to warming climate using banked seeds of the annual weed Arabidopsis thaliana in common garden experiments in four sites across the species’ native European range: Valencia, Spain; Norwich, United Kingdom; Halle, Germany; and Oulu, Finland. Genotypes originating from geographic regions near the planting site had high relative fitness in each site, direct evidence for broad-scale geographic adaptation in this model species. However, genotypes originating in sites historically warmer than the planting site had higher average relative fitness than local genotypes in every site, especially at the northern range limit in Finland. This result suggests that local adaptive optima have shifted rapidly with recent warming across the species’ native range. Climatic optima also differed among seasonal germination cohorts within the Norwich site, suggesting that populations occurring where summer germination is common may have greater evolutionary potential to persist under future warming. If adaptational lag has occurred over just a few decades in banked seeds of an annual species, it may be an important consideration for managing longer-lived species, as well as for attempts to conserve threatened populations through ex situ preservation.
149 citations
TL;DR: This work proposes that an optimizable solution does not equal a generalizable solution, and introduces a new machine learning-based Polarity Module for detecting negation in clinical text, and extensively compare its performance across domains.
Abstract: A review of published work in clinical natural language processing (NLP) may suggest that the negation detection task has been “solved.” This work proposes that an optimizable solution does not equal a generalizable solution. We introduce a new machine learning-based Polarity Module for detecting negation in clinical text, and extensively compare its performance across domains. Using four manually annotated corpora of clinical text, we show that negation detection performance suffers when there is no in-domain development (for manual methods) or training data (for machine learning-based methods). Various factors (e.g., annotation guidelines, named entity characteristics, the amount of data, and lexical and syntactic context) play a role in making generalizability difficult, but none completely explains the phenomenon. Furthermore, generalizability remains challenging because it is unclear whether to use a single source for accurate data, combine all sources into a single model, or apply domain adaptation methods. The most reliable means to improve negation detection is to manually annotate in-domain training data (or, perhaps, manually modify rules); this is a strategy for optimizing performance, rather than generalizing it. These results suggest a direction for future work in domain-adaptive and task-adaptive methods for clinical NLP.
100 citations
06 Oct 2014
TL;DR: An overview of the resources of the NCR is provided which may be especially helpful for DoD PMs to find the best approach for testing the cyberspace resiliency of their systems under development.
Abstract: The National Cyber Range (NCR) is an innovative Department of Defense (DoD) resource originally established by the Defense Advanced Research Projects Agency (DARPA) and now under the purview of the Test Resource Management Center (TRMC). It provides a unique environment for cyber security testing throughout the program development life cycle using unique methods to assess resiliency to advanced cyberspace security threats. This paper describes what a cyber security range is, how it might be employed, and the advantages a program manager (PM) can gain in applying the results of range events. Creating realism in a test environment isolated from the operational environment is a special challenge in cyberspace. Representing the scale and diversity of the complex DoD communications networks at a fidelity detailed enough to realistically portray current and anticipated attack strategies (e.g., Malware, distributed denial of service attacks, cross-site scripting) is complex. The NCR addresses this challenge by representing an Internet-like environment by employing a multitude of virtual machines and physical hardware augmented with traffic emulation, port/protocol/service vulnerability scanning, and data capture tools. Coupled with a structured test methodology, the PM can efficiently and effectively engage with the Range to gain cyberspace resiliency insights. The NCR capability, when applied, allows the DoD to incorporate cyber security early to avoid high cost integration at the end of the development life cycle. This paper provides an overview of the resources of the NCR which may be especially helpful for DoD PMs to find the best approach for testing the cyberspace resiliency of their systems under development.
92 citations
TL;DR: The Visible Infrared Imager Radiometer Suite (VIIRS) Cloud Mask (VCM) as discussed by the authors is an intermediate product between the production of VIIRS sensor data records and 22 downstream Environmental Data Records that each depends upon the VCM output.
Abstract: The Visible Infrared Imager Radiometer Suite (VIIRS) Cloud Mask (VCM) determines, on a pixel-by-pixel basis, whether or not a given location contains cloud. The VCM serves as an intermediate product (IP) between the production of VIIRS sensor data records and 22 downstream Environmental Data Records that each depends upon the VCM output. As such, the validation of the VCM IP is critical to the success of the Suomi National Polar-orbiting Partnership (S-NPP) product suite. The methods used to validate the VCM and the current results are presented in this paper. Detailed analyses of golden granules along with tools providing deep insights into granule performance, and specific cloud detection tests reveal the details behind a given granule's performance. Matchup results with CALIPSO, in turn, indicate the large-scale performance of the VCM and whether or not it is meeting its specifications. Comparisons with other cloud masks indicate comparable performance for the determination of clear pixels. As of September 2013 the VCM is either meeting or within 2% of all of its documented requirements.
83 citations
TL;DR: The design, construction, and demonstration of a nanoelectronic finite-state machine, fabricated using a design-oriented approach enabled by a deterministic, bottom–up assembly process that does not require individual nanowire registration, which suggests that proposed general-purpose nanocomputers can be realized in the near future.
Abstract: Implementation of complex computer circuits assembled from the bottom up and integrated on the nanometer scale has long been a goal of electronics research. It requires a design and fabrication strategy that can address individual nanometer-scale electronic devices, while enabling large-scale assembly of those devices into highly organized, integrated computational circuits. We describe how such a strategy has led to the design, construction, and demonstration of a nanoelectronic finite-state machine. The system was fabricated using a design-oriented approach enabled by a deterministic, bottom-up assembly process that does not require individual nanowire registration. This methodology allowed construction of the nanoelectronic finite-state machine through modular design using a multitile architecture. Each tile/module consists of two interconnected crossbar nanowire arrays, with each cross-point consisting of a programmable nanowire transistor node. The nanoelectronic finite-state machine integrates 180 programmable nanowire transistor nodes in three tiles or six total crossbar arrays, and incorporates both sequential and arithmetic logic, with extensive intertile and intratile communication that exhibits rigorous input/output matching. Our system realizes the complete 2-bit logic flow and clocked control over state registration that are required for a finite-state machine or computer. The programmable multitile circuit was also reprogrammed to a functionally distinct 2-bit full adder with 32-set matched and complete logic output. These steps forward and the ability of our unique design-oriented deterministic methodology to yield more extensive multitile systems suggest that proposed general-purpose nanocomputers can be realized in the near future.
77 citations
08 Apr 2014
TL;DR: A suite of metrics for measuring network-wide cyber security risk based on a model of multi-step attack vulnerability (attack graphs) is described, with family-level metrics combined into an overall metric for network vulnerability risk.
Abstract: We describe a suite of metrics for measuring network-wide cyber security risk based on a model of multi-step attack vulnerability (attack graphs). Our metrics are grouped into families, with family-level metrics combined into an overall metric for network vulnerability risk. The Victimization family measures risk in terms of key attributes of risk across all known network vulnerabilities. The Size family is an indication of the relative size of the attack graph. The Containment family measures risk in terms of minimizing vulnerability exposure across protection boundaries. The Topology family measures risk through graph theoretic properties (connectivity, cycles, and depth) of the attack graph. We display these metrics (at the individual, family, and overall levels) in interactive visualizations, showing multiple metrics trends over time.
64 citations
TL;DR: In this paper, the effects of network topologies in the propagation of evasive behavior have been investigated and it was shown that tax evaders are more likely to declare all their income in networks with higher levels of centrality across the agents, especially when faced with large penalties proportional to their incomes.
58 citations
TL;DR: Two general practices in choosing a standards approach are suggested: vertical decomposition of interoperability issues, in order to define a narrow, formal, tractable problem, and option-exclusion rules, as they are much simpler than stating optimal-choice rules.
Abstract: Data standards are a powerful, real-world tool for enterprise interoperability, yet there exists no well-grounded methodology for selecting among alternative standards approaches. We focus on a specific sub-problem within a community's data sharing challenge and identify four major standards-based approaches to that task. We present characteristics of a data sharing community that one should consider in selecting a standards approach--such as relative power, motivation level, and technical sophistication of different participants--and illustrate with real-world examples. These characteristics and other factors are then analyzed to develop decision rules for selecting among the four approaches. Independent of the data exchange problem, we suggest two general practices in choosing a standards approach: (1) vertical decomposition of interoperability issues, in order to define a narrow, formal, tractable problem, and (2) option-exclusion rules, as they are much simpler than stating optimal-choice rules.
52 citations
TL;DR: This DATABASE virtual issue captures the major results from the Fourth bioCreative Challenge Evaluation Workshop, and is the sixth special issue devoted to BioCreative.
Abstract: BioCreative: Critical Assessment of Information Extraction in Biology is an international community-wide effort for evaluating text mining (TM) and information extraction systems applied to the biological domain (http://www.biocreative.org/).The Challenge Evaluations and the accompanying BioCreative Workshops bring together the TM and biology communities to drive the development of practically relevant TM systems. One of the main goals of this initiative is that the resulting systems facilitate a more efficient literature information access to biologists in general, but also provide tools that can be directly integrated into the biocuration workflow and the knowledge discovery process carried out by databases. Beyond addressing the current barriers faced by TM technologies applied to biological literature, BioCreative has further been conducting user requirement analyses, user-based evaluations and fostering standards development for TM tool reuse and integration. This DATABASE virtual issue captures the major results from the Fourth BioCreative Challenge Evaluation Workshop, and is the sixth special issue devoted to BioCreative. Built on the success of the previous Challenge Evaluations and Workshops (BioCreative I, II, II.5, III, 2012) (1–5), the BioCreative IV Workshop was held in Bethesda, MD, on October 7–9, 2013.
52 citations
TL;DR: Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic.
Abstract: The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.
TL;DR: Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites, and informed future directions regarding interoperability and data access for ONC's Data Access Framework initiative.
Proceedings Article•
22 Mar 2014TL;DR: Commonalities as well as dissimilarities in factors between the two domains are found, suggesting the possibility of creating a core model of trust that could be modified for individual domains.
Abstract: Our research goals are to understand and model the factors that affect trust in automation across a variety of application domains. For the initial surveys described in this paper, we selected two domains: automotive and medical. Specifically, we focused on driverless cars (e.g., Google Cars) and automated medical diagnoses (e.g., IBM’s Watson). There were two dimensions for each survey: the safety criticality of the situation in which the system was being used and name-brand recognizability. We designed the surveys and administered them electronically, using Survey Monkey and Amazon’s Mechanical Turk. We then performed statistical analyses of the survey results to discover common factors across the domains, domain-specific factors, and implications of safety criticality and brand recognizability on trust factors. We found commonalities as well as dissimilarities in factors between the two domains, suggesting the possibility of creating a core model of trust that could be modified for individual domains. The results of our research will allow for the creation of design guidelines for autonomous systems that will be better accepted and used by target populations.
01 Jul 2014
TL;DR: The results of the survey and follow‐up interaction with SoSWG members, identified seven areas of challenge or SoS Pain Points and the pain points along with the questions they pose for the systems engineering community.
Abstract: The INCOSE SoS Working Group (SoSWG) identified the need to understand the SoS issues of importance to the systems engineering community as an initial SoSWG activity at their meeting in January 2012 in Jacksonville, Florida. The results of the survey and follow-up interaction with SoSWG members, identified seven areas of challenge or SoS Pain Points. This paper summarizes the survey and working group feedback and describes the pain points along with the questions they pose for the systems engineering community. The work described in this paper is the product of the INCOSE Systems of Systems Working Group, and acknowledges the contributions of working group members, including Alan Harding, Scott Workinger, Kelly Griendling, Eric Honour, Claire Ingram, Michael Henshaw, Bryan Herdlick, and others who responded to the survey and participated in the formulation and discussions of these SoS pain points.
02 Apr 2014
TL;DR: This paper provides conditions that permit the multivariate PCM to precisely predict the mean of the original system output, and explores additional capabilities of the multi-variable PCM, in terms of cross-statistics prediction, relation to the minimum mean-square estimator, and computational feasibility for large dimensional data.
Abstract: Modern large-scale infrastructure systems have typical complicated structure and dynamics, and extensive simulations are required to evaluate their performance. The probabilistic collocation method (PCM) has been developed to effectively simulate a system's performance under parametric uncertainty. In particular, it allows reduced-order representation of the mapping between uncertain parameters and system performance measures/outputs, using only a limited number of simulations; the resultant representation of the original system is provably accurate over the likely range of parameter values. In this paper, we extend the formal analysis of single-variable PCM to the multivariate case, where multiple uncertain parameters may or may not be independent. Specifically, we provide conditions that permit multivariate PCM to precisely predict the mean of original system output. We also explore additional capabilities of the multivariate PCM, in terms of cross-statistics prediction, relation to the minimum mean-square estimator, computational feasibility for large dimensional parameter sets, and sample-based approximation of the solution. At the end of the paper, we demonstrate the application of multivariate PCM in evaluating air traffic system performance under weather uncertainties.
Mitre Corporation1, University of Toronto2, Northeastern University3, Google4, Wright State University5, University of California, Santa Barbara6, Otto-von-Guericke University Magdeburg7, University of Bonn8, Hong Kong Polytechnic University9, University of Manchester10, University of North Carolina at Chapel Hill11, Arizona State University12, National Scientific and Technical Research Council13, Durham University14
TL;DR: This research presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually cataloging and cataloging individual components of an integrated system.
Abstract: Leo Obrst a,∗, Michael Gruninger b, Ken Baclawski c, Mike Bennett d, Dan Brickley e, Gary Berg-Cross f, Pascal Hitzler g, Krzysztof Janowicz h, Christine Kapp i, Oliver Kutz j, Christoph Lange k, Anatoly Levenchuk l, Francesca Quattri m, Alan Rector n, Todd Schneider o, Simon Spero p, Anne Thessen q, Marcela Vegetti r, Amanda Vizedom s, Andrea Westerinen t, Matthew West u and Peter Yim v a The MITRE Corporation, McLean, VA, USA b University of Toronto, Toronto, Canada c Northeastern University, Boston, MA, USA d Hypercube Ltd., London, UK e Google, London, UK f Knowledge Strategies, Washington, DC, USA g Wright State University, Dayton, OH, USA h University of California, Santa Barbara, Santa Barbara, CA, USA i JustIntegration, Inc., Kissimmee, FL, USA j Otto von Guericke University Magdeburg, Magdeburg, Germany k University of Bonn, Bonn, Germany; Fraunhofer IAIS, Sankt Augustin, Germany l TechInvestLab.ru, Moscow, Russia m The Hong Kong Polytechnic University, Hong Kong n University of Manchester, Manchester, UK o PDS, Inc., Arvada, CO, USA p University of North Carolina, Chapel Hill, NC, USA q Arizona State University, Phoenix, AZ, USA r INGAR (CONICET/UTN), Santa Fe, Argentina s Criticollab, LLC, Durham, NC, USA t Nine Points Solutions, LLC, Potomac, MD, USA u Information Junction, Fareham, UK v CIM Engineering, Inc., San Mateo, CA, USA
University of Oxford1, Jacobs University Bremen2, Ghent University3, Marine Biological Laboratory4, European Bioinformatics Institute5, Michigan State University6, University of California, Berkeley7, University of Chicago8, Argonne National Laboratory9, Mitre Corporation10, DSM11, Howard Hughes Medical Institute12, Joint Genome Institute13, National Institutes of Health14, University of Manchester15, University of California, San Diego16, University of New Mexico17, University of Maryland, Baltimore18, Oak Ridge National Laboratory19, Northern Arizona University20
TL;DR: The recently enacted policy for proposing new activities that are intended to be taken on by the GSC, along with the template for proposing such new activities, are described.
Abstract: The Genomic Standards Consortium (GSC) is an open-membership community that was founded in 2005 to work towards the development, implementation and harmonization of standards in the field of genomics. Starting with the defined task of establishing a minimal set of descriptions the GSC has evolved into an active standards-setting body that currently has 18 ongoing projects, with additional projects regularly proposed from within and outside the GSC. Here we describe our recently enacted policy for proposing new activities that are intended to be taken on by the GSC, along with the template for proposing such new activities.
01 Jan 2014
TL;DR: This work represents the first investigation of cyber attack graph analysis based on graph databases - an important class of NoSQL database that includes Neo4j, a Not Only SQL (NoSQL) database optimized for graphs.
Abstract: We introduce a new modeling framework for mapping vulnerability paths through networks and associating them with observed attacker activities. We merge a complex blend of network relationships and events, such as topology, firewall policies, host configurations, vulnerabilities, attack patterns, intrusion alerts, and logs. Our persistence layer includes Neo4j, a Not Only SQL (NoSQL) database optimized for graphs. We explore how the Neo4j property-graph data model supports analysis and queries within our problem domain. For interoperability with other tools, we employ standardized cyber- security data exchange language. We show that our approach supports the same kinds of graph analytics as an existing attack graph tool, through the application of the Neo4j Cypher query language. We then extend those analytics through a much richer model of the network environment and attacker/defender activities. Our work represents the first investigation of cyber attack graph analysis based on graph databases - an important class of NoSQL database.
11 Jun 2014
TL;DR: The current state of technologies will be given on human odor analysis, detection, and classification, along with a discussion of each technology with a specific focus on recent developments.
Abstract: Human odor detection technologies have drawn attention due to the wide possibility of potential applications they open up in areas such as biometrics, criminal investigation and forensics, search for survivors under rubble, and security checkpoint screening. Gas chromatography/mass spectrometry (GC/MS) has been the most successful and powerful analytical approach developed to date for human odor analysis, and hundreds of human odorants have been identified using this tool. GC/MS has already enabled a good understanding to be obtained regarding human odor composition. Over the past two decades, research and development of E-nose technologies has accelerated at a fast pace, and in time may provide a complementary technology to those based on GC/MS. During the past several years, proof of concept has been demonstrated on the application of E-noses for real-time human odor detection and classification. In this review, the current state of technologies will be given on human odor analysis, detection, and classification, along with a discussion of each technology with a specific focus on recent developments. Technologies covered in this article include: various E-nose technologies; as well as gas chromatography integrated with mass spectrometry, ion mobility spectrometry, or other gas detectors. Other technologies will also be described such as optical sensors that have recently emerged for human odor detection, and the possibilities of exploiting absorbance spectroscopy and hyperspectral imaging.
22 Jun 2014
TL;DR: A real application example is presented, requirements for "big metadata" drawn from that example as well as other U.S. government analytic applications are discussed, and an effort to adapt an existing open source metadata manager to support the needs of big data ecosystems is described.
Abstract: Current big data ecosystems lack a principled approach to metadata management. This impedes large organizations' ability to share data and data preparation and analysis code, to integrate data, and to ensure that analytic code makes compatible assumptions with the data it uses. This use-case paper describes the challenges and an in-progress effort to address them. We present a real application example, discuss requirements for "big metadata" drawn from that example as well as other U.S. government analytic applications, and briefly describe an effort to adapt an existing open source metadata manager to support the needs of big data ecosystems.
01 Sep 2014
TL;DR: In this article, the authors highlight several human systems integrations issues surrounding Remotely Piloted Aircraft Systems (RPAS) and will engage the audiabearers in a discussion about human factors of UAVs.
Abstract: For over a decade the human factors of Remotely Piloted Aircraft Systems (RPAS, but also known as Unmanned Aerial Systems-UAS or Unmanned Aerial Vehicles –UAV) has been the continued focus of a community of scientists and engineers. Their efforts have been highlighted in various workshops, conferences and books and range from the design of effective ground control stations to crew coordination, spatial disorientation, supervisory control of multiple vehicles, soda straw views of camera feed, and training and selection. Much progress has been made. But new problems are surfacing of a different, more complex nature. Current pressing issues such as the integration of UAS in the national airspace, training and certification of civilian pilots, or exploitation of sensor data from these platforms and concomitant privacy concerns fall within the scope of the discipline of Human Systems Integration (HSI). This panel will highlight several human systems integrations issues surrounding RPAS and will engage the audi...
Proceedings Article•
22 Mar 2014TL;DR: This paper will examine questions and propose a framework for discussing autonomy assurance and trust in transportation applications, and explore the notion of a self-driving taxi-cab; and the evolution of a two-pilot flight deck, to single-p pilot operations.
Abstract: Automation in transportation (rail, air, road, etc.) is becoming increasingly complex and interconnected. Ensuring that these sophisticated non-deterministic software systems can be trusted and remain resilient is a community concern. As technology evolves, systems are moving increasingly towards autonomy where the “machine” is intelligent: perceiving, deciding, learning, etc. often without human engagement. Our current mechanisms and policies for oversight and certification of these systems to ensure they operate robustly in safety-critical situations are not keeping pace with technology advancements. How is an autonomous system different than an advanced automatic system? How is trust different for an autonomous system? What are different perspectives on trust? Is it appropriate to apply the techniques used to establish trust in a today’s transportation systems to establishing trust in an autonomous system? This paper will examine these questions and propose a framework for discussing autonomy assurance and trust in transportation applications. We will explore further with two examples: 1) the notion of a self-driving taxi-cab; and 2) the evolution of a two-pilot flight deck, to single-pilot operations.
TL;DR: A new quantitative approach that combines the use of a text analysis program with a mathematical algorithm to derive trends in levels of emotions expressed in social media and, more importantly, detect breakpoints when those trends changed abruptly.
Abstract: Although an extensive research literature on influence exists in fields like social psychology and communications, the advent of social media opens up new questions regarding how to define and measure influence online. In this paper, we present a new definition of influence that is tailored uniquely for online contexts and an associated methodology for gauging influence. According to our definition, influence entails the capacity to shift the patterns of emotion levels expressed by social media users. The source of influence may be the content of a user’s message or the context of the relationship between exchanging users. Regardless of the source, measuring influence requires first identifying shifts in the patterns of emotion levels expressed by users and then studying the extent that these shifts can be associated with a user. This paper presents a new quantitative approach that combines the use of a text analysis program with a mathematical algorithm to derive trends in levels of emotions expressed in social media and, more importantly, detect breakpoints when those trends changed abruptly. First steps have also been taken to predict future trends in expressions (as well as quantify their accuracy). These methods constitute a new approach to quantifying influence in social media that focuses on detecting the impact of influence (e.g., shifts in levels of emotions expressed) as opposed to focusing on the dynamics of simple social media counts, e.g., retweets, followers, or likes.
TL;DR: Findings illustrate that, in environments consisting of a variety of clinical documentation, de-identification models trained on writing complexity measures are better than models training on random groups and, in many instances, document types.
TL;DR: A system that extracts and displays temporal and geospatial entities in text and focuses on extracting major events from Wikipedia articles, although the ideas and tools can be easily used with articles from other sources such as news articles.
Abstract: This paper discusses a system that extracts and displays temporal and geospatial entities in text. The first task involves identification of all events in a document followed by identification of important events using a classifier. The second task involves identifying named entities associated with the document. In particular, we extract geospatial named entities. We disambiguate the set of geospatial named entities and geocode them to determine the correct coordinates for each place name, often called grounding. We resolve ambiguity based on sentence and article context. Finally, we present a user with the key events and their associated people, places and organizations within a document in terms of a timeline and a map. For purposes of testing, we use Wikipedia articles about historical events, such as those describing wars, battles and invasions. We focus on extracting major events from the articles, although our ideas and tools can be easily used with articles from other sources such as news articles. We use several existing tools such as Evita, Google Maps, publicly available implementationsofSupportVectorMachines,HiddenMarkovModelandConditionalRandomField, and the MIT SIMILE Timeline.
18 Sep 2014
TL;DR: In this article, the Cyber Resiliency Engineering Framework is extended to apply to resilience in general, with a focus on resilience of space systems, and opportunities and challenges are identified for resilience as an emergent property in an acknowledged system-of-systems.
Abstract: This paper describes how resiliency techniques apply to an acknowledged system-of-systems. The Cyber Resiliency Engineering Framework is extended to apply to resilience in general, with a focus on resilience of space systems. Resiliency techniques can improve system-of-systems operations. Both opportunities and challenges are identified for resilience as an emergent property in an acknowledged system-of-systems.
Posted Content•
TL;DR: This article used human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, and found evidence of a deep imprint of human sociality in language, observing that the words of natural human language possess a universal positivity bias, and the estimated emotional content of words is consistent between languages under translation.
Abstract: Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage. Alongside these general regularities, we describe inter-language variations in the emotional spectrum of languages which allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts.
TL;DR: Modelling interdependent systems by integrating two methods: functional dependency network analysis (FDNA) and the inoperability input-output model (IIM) enables hierarchical modelling of perturbations to systems at the physical or operational network levels.
Abstract: Interdependency is an important consideration in managing systems and systems of systems. Included in this consideration is identifying, representing, and measuring the ripple effects of dependencies between systems and consumers who rely on their products and services. Anticipating these effects enables planners to minimise dependency risks that, if realised, can have cascading impacts on the ability of systems to deliver services. This paper presents advances in modelling interdependent systems by integrating two methods: functional dependency network analysis (FDNA) and the inoperability input-output model (IIM). Their integration enables hierarchical modelling of perturbations to systems at the physical or operational network levels. To highlight the insights gained by integrating FDNA and IIM, a simulated electric power system that feeds a large metropolitan area is presented. This simulated case demonstrates that other consequence measures, such as the inoperability metric presented herein, must be used in conjunction with monetary objectives to generate holistic prioritisation strategies.
TL;DR: The study found that relative advantage, process support infrastructure, relative cost, technology accessibility, and relevant knowledge were significantly correlated to broadband internet use, which supports the case for further research to integrate and improve this model.
Abstract: Since 1980, corporations have spent nearly 50% of their revenue on technology, yet 50% of these new systems fail. The field of technology acceptance modeling posits that user acceptance is a root cause of these failures. Technology acceptance studies endeavor to determine the factors that lead users to adopt or reject a technology, but existing models have multiple weaknesses that impact their effectiveness and applicability. This study used enterprise system engineering principles to analyze and improve existing technology acceptance models, and proposed a new model that could be applied to disadvantaged user populations. The study analyzed information technology survey results from 338 firms across India and used the revised technology acceptance model to identify factors that were correlated to broadband internet use. The study found that relative advantage, process support infrastructure, relative cost, technology accessibility, and relevant knowledge were significantly correlated to broadband interne...
11 Dec 2014
Abstract: Closely spaced parallel runways (CSPRs), i.e.: runways spaced less than 2500 feet and as close as 700 feet, can be used for simultaneous arrivals when visual approaches can be conducted to both of the runways. Under current procedures, when the ceiling drops below a specified level in visual meteorological conditions (VMC), instrument approaches to both runways are not permitted, essentially reducing arrival capacity by half. The paired approach (PA) procedure is designed to enable continued use of both runways, even in instrument meteorological conditions (IMC), mitigating the loss of capacity. The Federal Aviation Administration is developing this capability as part of its NextGen initiative for deployment in the mid-term time frame. In the PA procedure, Air Traffic Control (ATC) pairs eligible aircraft and places them on a final approach course with required altitude separation and within a required longitudinal tolerance. The PA application on the trailing airplane computes and displays speed commands to achieve and maintain a desired spacing goal behind the lead, protecting against potential blunder by lead, or encounter with lead wake. The system also provides alerts if the safe zone is violated. The PA application requires Automatic Dependent Surveillance-Broadcast (ADS-B) position and velocity data from the leading aircraft and knowledge of ownship and lead planned final approach speeds (PFAS) in order to compute the interval required. This paper reports results of two real time simulations designed to assess the initial feasibility of flight crews and controllers, respectively, to conduct the tasks required by the paired approach procedure. Details of the speed guidance algorithms, displays, ATC capabilities, and ATC and flight crew procedures are provided. In both simulations, the flight environment of approaches to San Francisco International Airport was simulated to reflect the operations desired by the procedure. In the first simulation, 10 subject pilots with experience in operations at San Francisco International Airport participated in the study. In the second simulation, five controllers and supervisors from the Northern California TRACON (NCT) participated. All were experienced in the closely spaced parallel runway operations commonly used at the San Francisco International Airport (KSFO). Two controllers were current and qualified in the airspace and the rest were supervisory controllers with extensive experience in NCT operations for arrivals into KSFO. The simulation results indicated both the pilots and the controllers were able to perform the tasks expected of them for the conduct of the procedure well within acceptable workload limits. Subjective results for workload and objective results for achieved spacing and capacity are reported. The results suggest a steady state capacity of over 45 aircraft per hour should be possible with this procedure down to Category I minima. Recommendations for next steps are provided.