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UNT Scholarly Works
Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks
Date: March 25, 2002
Creator: Amin, Kaizar A. & Mikler, Armin R.
Description: This article discusses agent-based distance vector routing. Abstract: In spite of the ever-increasing availability of computation and communication resources in modern networks, the overhead associated with network management protocols, such as traffic control and routing, continues to be an important aspect in the design of new methodologies. Resource efficiency of such protocols has become even more prominent with the recent developments of wireless and ad-hoc networks, which are marked by much more severe resource constraints in terms of bandwidth, memory, and computational capabilities. This paper presents an Agent-Based approach to Distance Vector Routing that addresses these resources constraints. Agent-Based Distance Vector Routing (ADVR) is a resource efficient implementation of Distance Vector Routing that is fault tolerant and scales well for large networks. ADVR draws upon some basic biologically inspired principles to facilitate coordination among the mobile agents that implement the routing task. Specifically, simulated pheromones are used to control the movement of agents within the network and to dynamically adjust the number of agents in the population. The behavior of ADVR is analyzed and compared to that of traditional Distance Vector Routing.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc111275/
An Algorithm for Open Text Semantic Parsing
Date: August 2004
Creator: Shi, Lei & Mihalcea, Rada
Description: Abstract: This paper describes an algorithm for open text shallow semantic parsing. The algorithm relies on a frame dataset (FrameNet) and a semantic network (WordNet), to identify semantic relations between words in open text, as well as shallow semantic features associated with concepts in the text. Parsing semantic structures allows semantic units and constituents to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30953/
Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation
Date: June 2010
Creator: Akkaya, Cem; Conrad, Alexander; Wiebe, Janyce & Mihalcea, Rada
Description: This paper discusses word sense disambiguation. Abstract: Amazon Mechanical Turk (MTurk) is a marketplace for so-called "human intelligence tasks" (HITs), or tasks that are easy for humans but currently difficult for automated processes. Providers upload tasks to MTurk which workers then complete. Natural language annotation is one such human intelligence task. In this paper, the authors investigate using MTurk to collect annotations for Subjectivity Word Sense Disambiguation (SWSD), a course-grained word sense disambiguation task. The authors investigate whether they can use MTurk to acquire good annotations with respect to gold-standard data, whether they can filter out low-quality workers (spammers), and whether there is a learning effect associated with repeatedly completing the same kind of task. While our results with respect to spammers are inconclusive, the authors are able to obtain high-quality annotations for the SWSD task. These results suggest a greater role for MTurk with respect to constructing a large scale SWSD system in the future, promising substantial improvement in subjectivity and sentiment analysis.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31023/
Anchor Nodes Placement for Effective Passive Localization
Date: 2011
Creator: Akl, Robert G.; Pasupathy, Karthik & Haidar, Mohamad
Description: This paper discusses anchor nodes placement for effective passive localization. Abstract: In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to locate sensor nodes' positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. The authors do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. The authors show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes ...
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc77116/
Annotating and Identifying Emotions in Text
Date: 2010
Creator: Strapparava, Carlo & Mihalcea, Rada
Description: This book chapter discusses annotating and identifying emotions in text. Abstract: This paper focuses on the classification of emotions and polarity in news headlines and it is meant as an exploration of the connection between emotions and lexical semantics. The authors first describe the construction of the data set used in evaluation exercise "Affective Text" task at SemEval 2007, annotated for six basic emotions: Anger, Disgust, Fear, Joy, Sadness, and Surprise, and for Positive and Negative polarity. The authors also briefly describe the participating systems and their results. Second, exploiting the same data set, the authors propose and evaluate several knowledge-based and corpus-based methods for the automatic identification of emotions in text.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31010/
Answering complex, list and context questions with LCC's Question-Answering Server
Date: November 2001
Creator: Harabagiu, Sanda; Moldovan, Dan; Paşca, Marius; Surdeanu, Mihai; Mihalcea, Rada; Gîrju, Roxana et al
Description: Abstract: This paper presents the architecture of the Question-Answering server (QAS) developed at the Language Computer Corporation (LCC) and used in the TREC-10 evaluations. LCC's QAS™ extracts answers for (a) factual questions of variable degree of difficulty; (b) questions that expect lists of answers; and (c) questions posed in the context of previous questions and answers. One of the major novelties is the implementation of bridging inference mechanisms that guide the search for answers to complex questions. Additionally, LCC's QAS™ encodes an efficient way of modeling context via reference resolution. In TREC-10, this system generated an RAR of 0.58 on the main task and 0.78 on the context task.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc83297/
Approximating User Distributions in WCDMA Networks Using 2-D Gaussian
Date: July 2005
Creator: Nguyen, Son & Akl, Robert G.
Description: This paper discusses approximating user distributions in WCDMA networks using 2-D Gaussian. Abstract: In this paper, we present an analytical model for approximating the user distributions in multi-cell third generation WCDMA networks using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distributions for every cell. This allows us to calculate the inter-cell interference and the reverse-link capacity of the network. The authors compare their model with simulation results and show that it is fast and accurate enough to be used efficiently in the planning process of large WCDMA networks.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30820/
Architecture Support for 3D Obfuscation
Date: May 2006
Creator: Gomathisankaran, Mahadevan & Tyagi, Akhilesh
Description: This article discusses architecture support for 3D obfuscation. Abstract: Software obfuscation is defined as a transformation of a program P into T(P) such that the whitebox and blackbox behaviors of T(P) are computationally indistinguishable. However, robust obfuscation is impossible to achieve with the existing software only solutions. This results from the power of the adversary model in DRM which is significantly more than in the traditional security scenarios. The adversary has complete control of the computing node - supervisory privileges along with the full physical as well as architectural object observational capabilities. In essence, this makes the operating system (or any other layer around the architecture) untrustworthy. Thus the trust has to be provided by the underlying architecture. In this paper, the authors develop an architecture to support 3-D obfuscation through the use of well known cryptographic methods. The three dimensional obfuscation hides the address sequencing, the contents associated with an address, and the temporal reuse of address sequences such as in loops (or the second order address sequencing). The software is kept as an obfuscated file system image statically. Moreover, its execution traces are also dynamically obfuscated along all the three dimensions of address sequencing, contents and second order ...
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc132973/
Attracting and Retaining Women in Computer Science and Engineering: Evaluating the Results
Date: June 2007
Creator: Keathly, David & Akl, Robert G.
Description: This paper discusses efforts to attract and retain students in computer science and engineering fields. Abstract: Computer science and engineering communities have been exploring a variety of activities and techniques to attract and retain more students, especially women and minorities, to computer science and computer engineering degree programs. This paper briefly describes the efforts and results of a plan for actively recruiting young women into undergraduate computer engineering and computer science programs hosted by the University of North Texas (UNT). It also describes a series of activities aimed at improving the retention rate of students already in our programs, particularly during the freshman year. Such recruitment and retention efforts are critical to the country's efforts to increase the number of engineering professionals, and are a priority for the Computer Science and Engineering (CSE) Department at UNT.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30834/
Automatic generation of a coarse grained WordNet
Date: June 2001
Creator: Mihalcea, Rada & Moldovan, Dan
Description: This paper discusses automatic generation of a coarse grained WordNet. Abstract: Several principles for the automatic transformation of WordNet into a coarser grained dictionary are proposed. A new version of WordNet is derived, leading to a reduction of 26% in the average polysemy of words, while introducing a small error rate of 2.1%, as measured on a sense tagged corpus.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc83310/