1,720,979 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Multi-frame convolutional neural networks for object detection in temporal data
Full text linkGiven the problem of detecting objects in video, existing neural-network solutions rely on a post-processing step to combine information across frames and strengthen conclusions. This technique has been successful for videos with simple, dominant objects but it cannot detect objects if a single frame does not contain enough information to distinguish the object from its background. This problem is especially relevant in the maritime environment, where a whitecap and a human survivor may look identical except for their movement through the scene. In order to evaluate a neural network's ability to combine information across multiple frames of information, we developed two versions of a convolutional neural network: one version was given multiple frames as input while the other version was only provided a single frame. We measured the performance of both versions on the benchmark 3DPeS Dataset and observed a significant increase in both recall and precision when the network was given 10 frames instead of just one.We also developed our own noisy dataset consisting of small birds flying across the Monterey Bay. This dataset contained many instances where, in a single frame, the objects to be detected were indistinguishable from the surrounding waves and debris. For this dataset, multiple frames were essential for reliable detections. We also observed a greater improvement in the false negative rate compared to the false positive rate in this noisier dataset, suggesting that the additional frames were especially useful for improving the detection of hard-to-detect objects.Approved for public release; distribution is unlimited.Outstanding ThesisLieutenant, United States Navyhttp://archive.org/details/multiframeconvol109455297
A dynamic three-dimensional network visualization program for integration into cyberciege and other network visualization scenarios
Full text linkDetailed information and intellectual understanding of a network's topology and vulnerabilities is invaluable to better securing computer networks. Network protocol analyzers and intrusion detection systems can provide this additional information. In particular, game-based trainers, such as CyberCIEGE, have been shown to improve the level of training and understanding of network security professionals. This thesis' objective is to enhance these applications by developing NTAV3D, or, Network Topology and Attack Visualizer (Three Dimensional). NTAV3D is a tool that displays network topology, vulnerabilities, and attacks in an interactive, three dimensional environment. This augments the design and gameplay of CyberCIEGE by increasing gameplayer interaction and data display. Additionally, NTAV3D can be expanded to provide this capability to network analysis and intrusion detection tools. Furthermore, NTAV3D expands on ideas and results from related work of the best ways to visualize network topology, vulnerabilities, and attacks. NTAV3D was created using open-source software technologies including Xj3D, X3D, Java, and XML. It is also one of the first applications to be built with only the Xj3D toolkit. Therefore, the development process allowed evaluation of these technologies, resulting in recommendations for future improvements.Approved for public release; distribution is unlimited.US Navy (USN) authors.http://archive.org/details/adynamicthreedim10945338
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Deep learning for media analysis in defense scenarios--an evaluation of an open-source framework for object detection in intelligence-related image sets
Full text linkThe Department of Defense struggles to develop and maintain cutting-edge software through the Defense Acquisition System. The pace of improvements in machine learning algorithms and software suggests the organization will fail to rapidly develop systems incorporating the latest innovations to meet its intelligence-related media analysis needs. In contrast, the trend of industry and academia releasing algorithms and software under permissive licenses bestows defense organizations with an opportunity. These groups can potentially overcome resource shortfalls and long acquisition timelines by implementing machine learning solutions with open-source software.We test this hypothesis by employing an open-source software library to evaluate publicly available deep learning algorithms on three prior defense-related datasets. We then compare performance of deep convolutional neural networks to past methods for detecting AK-47s, ships, and screenshots in images. Applying proven algorithms through the software framework, we test three object detectors that exceed or match classification performance for all three experiments in a third of the development time available to designers of the previous algorithms. We relate these tests to defense scenarios in order to provide a logical argument and empirical measure of the utility of open-source machine learning frameworks to meet the Department of Defense's intelligence-related media analysis needs.Approved for public release; distribution is unlimited.Outstanding ThesisCaptain, United States Marine Corpshttp://archive.org/details/deeplearningform109455551
Natural language processing of online propaganda as a means of passively monitoring an adversarial ideology
Full text linkReissued 30 May 2017 with Second Reader’s non-NPS affiliation added to title page.Online propaganda embodies a potent new form of warfare; one that extends the strategic reach of our adversaries and overwhelms analysts. Foreign organizations have effectively leveraged an online presence to influence elections and distance-recruit. The Islamic State has also shown proficiency in outsourcing violence, proving that propaganda can enable an organization to wage physical war at very little cost and without the resources traditionally required. To augment new counter foreign propaganda initiatives, this thesis presents a pipeline for defining, detecting and monitoring ideology in text. A corpus of 3,049 modern online texts was assembled and two classifiers were created: one for detecting authorship and another for detecting ideology. The classifiers demonstrated 92.70% recall and 95.84% precision in detecting authorship, and detected ideological content with 76.53% recall and 95.61% precision. Both classifiers were combined to simulate how an ideology can be detected and how its composition could be passively monitored across time. Implementation of such a system could conserve manpower in the intelligence community and add a new dimension to analysis. Although this pipeline makes presumptions about the quality and integrity of input, it is a novel contribution to the fields of Natural Language Processing and Information Warfare.Approved for public release; distribution is unlimited.Lieutenant, United States Coast Guardhttp://archive.org/details/naturallanguagep109455299
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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