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The Effect of Item Distance on Organization in the Free Recall of Words

Description: The purpose of the present study was to investigate the effect of item distance, which is defined as the absolute number of words separating a single item from the other items of the category, upon clustering of the removed items. By studying clustering, psychologists hope to gain knowledge of the effect of organization on memory.
Date: August 1970
Creator: Clay, James H., (James Hamilton)
Partner: UNT Libraries

Final Report - From Measurements to Models: Cross-Comparison of Measured and Simulated Behavioral States of the Atmosphere

Description: The ARM sites and the ARM Mobile Facility (AMF) were constructed to make measurements of the atmosphere and radiation system in order to quantify deficiencies in the simulation of clouds within models and to make improvements in those models. While the measurement infrastructure of ARM is well-developed and a model parameterization testbed capability has been established, additional effort is needed to develop statistical techniques which permit the comparison of simulation output from atmospheric models with actual measurements. Our project establishes a new methodology for objectively comparing ARM measurements to the outputs of leading global climate models and reanalysis data. The quantitative basis for this comparison is provided by a statistical procedure which establishes an exhaustive set of mutually-exclusive, recurring states of the atmosphere from sets of multivariate atmospheric and cloud conditions, and then classifies multivariate measurements or simulation outputs into those states. Whether measurements and models classify the atmosphere into the same states at specific locations through time provides an unequivocal comparison result. Times and locations in both geographic and state space of model-measurement agreement and disagreement will suggest directions for the collection of additional measurements at existing sites, provide insight into the global representativeness of the current ARM sites (suggesting locations and times for use of the AMF), and provide a basis for improvement of models. Two different analyses were conducted: One, using the Parallel Climate Model, focused on an IPCC climate change scenario and clusters that characterize long-term changes in the hydrologic cycle. The other, using the GISS Model E GCM and the ARM Active Remotely Sensed Cloud Layers product, explored current climate cloud regimes in the Tropical West Pacific.
Date: October 22, 2007
Creator: Del Genio, Anthony D; Hoffman, Forrest M & Hargrove, Jr, William W
Partner: UNT Libraries Government Documents Department

Improving the Gameplay Experience and Guiding Bottom Players in an Interactive Mapping Game

Description: In game based learning, motivating the players to learn by providing them a desirable gameplay experience is extremely important. However, it's not an easy task considering the quality of today's commercial non-educational games. Throughout the gameplay, the player should neither get overwhelmed nor under-challenged. The best way to do so is to monitor the player's actions in the game because these actions can tell the reason behind the player's performance. They can also tell about the player's lacking competencies or knowledge. Based on this information, in-game educational interventions in the form of hints can be provided to the player. The success of such games depends on their interactivity, motivational outlook and thus player retention. UNTANGLED is an online mapping game based on crowd-sourcing, developed by Reconfigurable Computing Lab, UNT for the mapping problem of CGRAs. It is also an educational game for teaching the concepts of reconfigurable computing. This thesis performs qualitative comparative analysis on gameplays of low performing players of UNTANGLED. And the implications of this analysis are used to provide recommendations for improving the gameplay experience for these players by guiding them. The recommendations include strategies to reach a high score and a compact solution, hints in the form of preset patterns and a clustering based approach.
Access: This item is restricted to UNT Community Members. Login required if off-campus.
Date: May 2017
Creator: Ambekar, Kiran
Partner: UNT Libraries

Markov Model of Segmentation and Clustering: Applications in Deciphering Genomes and Metagenomes

Description: Rapidly accumulating genomic data as a result of high-throughput sequencing has necessitated development of efficient computational methods to decode the biological information underlying these data. DNA composition varies across structurally or functionally different regions of a genome as well as those of distinct evolutionary origins. We adapted an integrative framework that combines a top-down, recursive segmentation algorithm with a bottom-up, agglomerative clustering algorithm to decipher compositionally distinct regions in genomes. The recursive segmentation procedure entails fragmenting a genome into compositionally distinct segments within a statistical hypothesis testing framework. This is followed by an agglomerative clustering procedure to group compositionally similar segments within the same framework. One of our main objectives was to decipher distinctive evolutionary patterns in sex chromosomes via unraveling the underlying compositional heterogeneity. Application of this approach to the human X-chromosome provided novel insights into the stratification of the X chromosome as a consequence of punctuated recombination suppressions between the X and Y from the distal long arm to the distal short arm. Novel "evolutionary strata" were identified particularly in the X conserved region (XCR) that is not amenable to the X-Y comparative analysis due to massive loss of the Y gametologs following recombination cessation. Our compositional based approach could circumvent the limitations of the current methods that depend on X-Y (or Z-W for ZW sex determination system) comparisons by deciphering the stratification even if only the sequence of sex chromosome in the homogametic sex (i.e. X or Z chromosome) is available. These studies were extended to the plant sex chromosomes which are known to have a number of evolutionary strata that formed at the initial stage of their evolution, presenting an opportunity to examine the onset of stratum formation on the sex chromosomes. Further applications included detection of horizontally acquired DNAs in extremophilic eukaryote, Galdieria sulphuraria, which ...
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Date: August 2017
Creator: Pandey, Ravi Shanker
Partner: UNT Libraries

The Role of Knowledge and Attitude in Residential Irrigation Efficiency

Description: Residential irrigation efficiency is a long-term concern for any community that faces water supply stress. When ability to raise water prices is constrained, public education and conservation programs can produce reduced water usage. Understanding the factors behind residential irrigation efficiency allows the design of more effective conservation campaigns. Combining site-specific water budgets with usage data for four hundred homes in North Texas enables quantifying efficient irrigation behavior. A survey of homeowners tests for the presence of conservation-positive attitudes and the knowledge required to implement those attitudes. The influence of neighbors’ watering habits is investigated using spatial clustering tools. Findings are analyzed in the context of an attitude, knowledge, and habit model of conservation behavior. The presence of automatic irrigation systems, small irrigated areas, and having knowledge of the amount that one waters one’s lawn are found to contribute to more intensive irrigation. Mixed evidence for small-scale clustering in irrigation intensity is presented.
Date: August 2012
Creator: Nickerson, Joel
Partner: UNT Libraries

Chemical Profiling of the Plant Cell Wall through Raman Microspectroscopy

Description: This paper presents a computational framework for chemical pro.ling of the plant cell wall through the Raman spectroscopy. The system enables query of known spectral signatures and clustering of spectral data based on intrinsic properties. As a result, presence and relative concentration of speci.c chemical bonds can be quanti.ed. The primary contribution of this paper is in representation of raman pro.le in terms of .uorescence background and multiscale peak detection at each grid point (voxel). Such a representation allows ef.cient spatial segmentation based on the coupling between high-level salient properties and low-level symbolic representation at each voxel. The high-level salient properties refer to preferred peaks and their attributes for the entire image. The low-level symbolic representations are based on .uorescence background, spectral peak locations, and their attributes. We present results on a corn stover tissue section that is imaged through Raman microscopy, and the results are consistent with the literature. In addition, automatic clustering indicates several distinct layers of the cell walls with different spectral signatures.
Date: March 2, 2010
Creator: Han, Ju; Singh, Seema; Sun, Lan; Simmons, Blake; Auer, Manfred & Parvin, Bahram
Partner: UNT Libraries Government Documents Department

Two Rounds of Whole Genome Duplication in the Ancestral Vertebrate

Description: The hypothesis that the relatively large and complex vertebrate genome was created by two ancient, whole genome duplications has been hotly debated, but remains unresolved. We reconstructed the evolutionary relationships of all gene families from the complete gene sets of a tunicate, fish, mouse, and human, then determined when each gene duplicated relative to the evolutionary tree of the organisms. We confirmed the results of earlier studies that there remains little signal of these events in numbers of duplicated genes, gene tree topology, or the number of genes per multigene family. However, when we plotted the genomic map positions of only the subset of paralogous genes that were duplicated prior to the fish-tetrapod split, their global physical organization provides unmistakable evidence of two distinct genome duplication events early in vertebrate evolution indicated by clear patterns of 4-way paralogous regions covering a large part of the human genome. Our results highlight the potential for these large-scale genomic events to have driven the evolutionary success of the vertebrate lineage.
Date: April 12, 2005
Creator: Dehal, Paramvir & Boore, Jeffrey L.
Partner: UNT Libraries Government Documents Department

Information Structures in Notated Music: Statistical Explorations of Composers' Performance Marks in Solo Piano Scores

Description: Written notation has a long history in many musical traditions and has been particularly important in the composition and performance of Western art music. This study adopted the conceptual view that a musical score consists of two coordinated but separate communication channels: the musical text and a collection of composer-selected performance marks that serve as an interpretive gloss on that text. Structurally, these channels are defined by largely disjoint vocabularies of symbols and words. While the sound structures represented by musical texts are well studied in music theory and analysis, the stylistic patterns of performance marks and how they acquire contextual meaning in performance is an area with fewer theoretical foundations. This quantitative research explored the possibility that composers exhibit recurring patterns in their use of performance marks. Seventeen solo piano sonatas written between 1798 and 1913 by five major composers were analyzed from modern editions by tokenizing and tabulating the types and usage frequencies of their individual performance marks without regard to the associated musical texts. Using analytic methods common in information science, the results demonstrated persistent statistical similarities among the works of each composer and differences among the work groups of different composers. Although based on a small sample, the results still offered statistical support for the existence of recurring stylistic patterns in composers' use of performance marks across their works.
Date: May 2016
Creator: Buchanan, J. Paul
Partner: UNT Libraries

Clustering Algorithms for Time Series Gene Expression in Microarray Data

Description: Clustering techniques are important for gene expression data analysis. However, efficient computational algorithms for clustering time-series data are still lacking. This work documents two improvements on an existing profile-based greedy algorithm for short time-series data; the first one is implementation of a scaling method on the pre-processing of the raw data to handle some extreme cases; the second improvement is modifying the strategy to generate better clusters. Simulation data and real microarray data were used to evaluate these improvements; this approach could efficiently generate more accurate clusters. A new feature-based algorithm was also developed in which steady state value; overshoot, rise time, settling time and peak time are generated by the 2nd order control system for the clustering purpose. This feature-based approach is much faster and more accurate than the existing profile-based algorithm for long time-series data.
Date: August 2012
Creator: Zhang, Guilin
Partner: UNT Libraries

Amorphization and De-vitrification in Immiscible Copper-Niobium Alloy Thin Films

Description: While amorphous phases have been reported in immiscible alloy systems, there is still some controversy regarding the reason for the stabilization of these unusual amorphous phases. Direct evidence of nanoscale phase separation within the amorphous phase forming in immiscible Cu-Nb alloy thin films using 3D atom probe tomography has been presented. This evidence clearly indicates that the nanoscale phase separation is responsible for the stabilization of the amorphous phase in such immiscible systems since it substantially reduces the free energy of the undercooled liquid (or amorphous) phase, below that of the competing supersaturated crystalline phases. The devitrification of the immiscible Cu-Nb thin film of composition Cu-45% Nb has been studied in detail with the discussion on the mechanism of phase transformation. The initial phase separation in the amorphous condition seems to play a vital role in the crystallization of the thin film. Detailed analysis has been done using X-ray diffraction, transmission electron microscopy and 3D atom probe tomography.
Date: May 2007
Creator: Puthucode Balakrishnan, Anantharamakrishnan
Partner: UNT Libraries

Effects of Non-homogeneous Population Distribution on Smoothed Maps Produced Using Kernel Density Estimation Methods

Description: Understanding spatial perspectives on the spread and incidence of a disease is invaluable for public health planning and intervention. Choropleth maps are commonly used to provide an abstraction of disease risk across geographic space. These maps are derived from aggregated population counts that are known to be affected by the small numbers problem. Kernel density estimation methods account for this problem by producing risk estimates that are based on aggregations of approximately equal population sizes. However, the process of aggregation often combines data from areas with non-uniform spatial and population characteristics. This thesis presents a new method to aggregate space in ways that are sensitive to their underlying risk factors. Such maps will enable better public health practice and intervention by enhancing our ability to understand the spatial processes that result in disparate health outcomes.
Date: December 2014
Creator: Jones, Jesse Jack
Partner: UNT Libraries

Patterns of Change in Semantic Clustering in Schizophrenia Spectrum Disorders: What Can it Tell Us about the Nature of Clustering Deficits

Description: Semantic clustering has been used as a measure of learning strategies in a number of clinical populations and has been found to be deficient in individuals with Schizophrenia, but less attention has been paid to the dynamic use of this strategy over the course of fixed-order learning trials. In the current study, we examined this pattern of clustering use over trials in a sample of individuals with Schizophrenia, and explored whether the addition of this dynamic information would help us to better predict specific executive deficits. Results suggested that a decrease in semantic clustering across trials was associated with some executive deficits in the predicted manner. Nonetheless, the overall semantic clustering index generally proved more effective for the purposes, suggesting that in this population, the addition of dynamic information in strategy use is not likely to add considerably to clinical prediction and understanding.
Date: August 2001
Creator: Edwards, Kimberly
Partner: UNT Libraries

Algorithmic Techniques for Massive Data Sets

Description: This report describes the progress made during the Early Career Principal Investigator (ECPI) project on Algorithmic Techniques for Large Data Sets. Research was carried out in the areas of dimension reduction, clustering and finding structure in data, aggregating information from different sources and designing efficient methods for similarity search for high dimensional data. A total of nine different research results were obtained and published in leading conferences and journals.
Date: April 3, 2006
Creator: Charikar, Moses
Partner: UNT Libraries Government Documents Department

A normalized-cut algorithm for hierarchical vector field data segmentation

Description: In the context of vector field data visualization, it is often desirable to construct a hierarchical data representation. One possibility to construct a hierarchy is based on clustering vectors using certain similarity criteria. We combine two fundamental approaches to cluster vectors and construct hierarchical vector field representations. For clustering, a locally constructed linear least-squares approximation is incorporated into a similarity measure that considers both Euclidean distance between point pairs (for which dependent vector data are given) and difference in vector values. A modified normalized cut (NC) method is used to obtain a near-optimal clustering of a given discrete vector field data set. To obtain a hierarchical representation, the NC method is applied to simple, analytically defined vector fields as well as discrete vector field data generated by turbulent flow simulation. Our test results indicate that our proposed adaptation of the original NC method is a promising method as it leads to segmentation results that capture the qualitative and topological nature of the vector field data.
Date: January 13, 2003
Creator: Chen, Jiann-Liang; Bai, Zhaojun; Hamann, Bernd & Ligocki, Terry J.
Partner: UNT Libraries Government Documents Department

Detection of Ulcerative Colitis Severity and Enhancement of Informative Frame Filtering Using Texture Analysis in Colonoscopy Videos

Description: There are several types of disorders that affect our colon’s ability to function properly such as colorectal cancer, ulcerative colitis, diverticulitis, irritable bowel syndrome and colonic polyps. Automatic detection of these diseases would inform the endoscopist of possible sub-optimal inspection during the colonoscopy procedure as well as save time during post-procedure evaluation. But existing systems only detects few of those disorders like colonic polyps. In this dissertation, we address the automatic detection of another important disorder called ulcerative colitis. We propose a novel texture feature extraction technique to detect the severity of ulcerative colitis in block, image, and video levels. We also enhance the current informative frame filtering methods by detecting water and bubble frames using our proposed technique. Our feature extraction algorithm based on accumulation of pixel value difference provides better accuracy at faster speed than the existing methods making it highly suitable for real-time systems. We also propose a hybrid approach in which our feature method is combined with existing feature method(s) to provide even better accuracy. We extend the block and image level detection method to video level severity score calculation and shot segmentation. Also, the proposed novel feature extraction method can detect water and bubble frames in colonoscopy videos with very high accuracy in significantly less processing time even when clustering is used to reduce the training size by 10 times.
Date: December 2015
Creator: Dahal, Ashok
Partner: UNT Libraries

Towards Resilient Critical Infrastructures: Application of Type-2 Fuzzy Logic in Embedded Network Security Cyber Sensor

Description: Resiliency and cyber security of modern critical infrastructures is becoming increasingly important with the growing number of threats in the cyber-environment. This paper proposes an extension to a previously developed fuzzy logic based anomaly detection network security cyber sensor via incorporating Type-2 Fuzzy Logic (T2 FL). In general, fuzzy logic provides a framework for system modeling in linguistic form capable of coping with imprecise and vague meanings of words. T2 FL is an extension of Type-1 FL which proved to be successful in modeling and minimizing the effects of various kinds of dynamic uncertainties. In this paper, T2 FL provides a basis for robust anomaly detection and cyber security state awareness. In addition, the proposed algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental cyber-security test-bed.
Date: August 1, 2011
Creator: Linda, Ondrej; Vollmer, Todd; Alves-Foss, Jim & Manic, Milos
Partner: UNT Libraries Government Documents Department

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

Description: Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.
Date: April 1, 2011
Creator: Linda, Ondrej; Vollmer, Todd; Wright, Jason & Manic, Milos
Partner: UNT Libraries Government Documents Department

Improving Attack Graph Visualization through Data Reduction and Attack Grouping

Description: Various tools exist to analyze enterprise network systems and to produce attack graphs detailing how attackers might penetrate into the system. These attack graphs, however, are often complex and difficult to comprehend fully, and a human user may find it problematic to reach appropriate configuration decisions. This paper presents methodologies that can 1) automatically identify portions of an attack graph that do not help a user to understand the core security problems and so can be trimmed, and 2) automatically group similar attack steps as virtual nodes in a model of the network topology, to immediately increase the understandability of the data. We believe both methods are important steps toward improving visualization of attack graphs to make them more useful in configuration management for large enterprise networks. We implemented our methods using one of the existing attack-graph toolkits. Initial experimentation shows that the proposed approaches can 1) significantly reduce the complexity of attack graphs by trimming a large portion of the graph that is not needed for a user to understand the security problem, and 2) significantly increase the accessibility and understandability of the data presented in the attack graph by clearly showing, within a generated visualization of the network topology, the number and type of potential attacks to which each host is exposed.
Date: September 1, 2008
Creator: Homer, John; Varikuti, Ashok; Ou, Xinming & McQueen, Miles A.
Partner: UNT Libraries Government Documents Department