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Articles 1801 - 1830 of 2151
Full-Text Articles in Computer Sciences
User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang
User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang
Computer Science Faculty Publications
As detailed in Chap. 1, system implementations for dynamic taxonomies and faceted search allow a wide range of query possibilities on the data. Only when these are made accessible by appropriate user interfaces, the resulting applications can support a variety of search, browsing and analysis tasks. User interface design in this area is confronted with specific challenges. This chapter presents an overview of both established and novel principles and solutions.
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Computer Science Faculty Publications
Hierarchies are ubiquitous on the web for structuring online catalogs and indexing multidimensional attributed data sets. They are a natural metaphor for information seeking if their levelwise structure mirrors the user's conception of the underlying domain. In other cases, they can be frustrating, especially if multiple drill‐downs are necessary to arrive at information of interest. To support a broad range of users, site designers often expose multiple faceted classifications or provide within‐page pruning mechanisms. We present a new technique, called out-of-turn interaction, that increases the richness of user interaction at hierarchical sites, without enumerating all possible completion paths in the …
Corporate Voting, Paul H. Edelman, Robert B. Thompson
Corporate Voting, Paul H. Edelman, Robert B. Thompson
Vanderbilt Law School Faculty Publications
Discussion of shareholder voting frequently begins against a background of the democratic expectations and justifications present in decision-making in the public sphere. Directors are assumed to be agents of the shareholders in much the same way that public officers are representatives of citizens. Recent debates about majority voting and shareholder nomination of directors illustrate this pattern. Yet the corporate process differs in significant ways, partly because the market for shares permits a form of intensity voting and lets markets mediate the outcome in a way that would be foreign to the public setting and partly because the shareholders' role is …
Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.)
Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.)
Electrical & Computer Engineering Faculty Publications
Clinical MRI images are generally corrupted by random noise during acquisition with blurred subtle structure features. Many denoising methods have been proposed to remove noise from corrupted images at the expense of distorted structure features. Therefore, there is always compromise between removing noise and preserving structure information for denoising methods. For a specific denoising method, it is crucial to tune it so that the best tradeoff can be obtained. In this paper, we define several cost functions to assess the quality of noise removal and that of structure information preserved in the denoised image. Strength Pareto Evolutionary Algorithm 2 (SPEA2) …
A Symbolic Sonification Of L-Systems, Adam James Wilson
A Symbolic Sonification Of L-Systems, Adam James Wilson
Publications and Research
This paper describes a simple technique for the sonification of branching structures in plants. The example is intended to illustrate a qualitative definition of best practices for sonification aimed at the production of musical material. Visually manifest results of tree growth are modelled and subsequently mapped to pitch, time, and amplitude. Sample results are provided in symbolic music notation.
Untitled, Darren Poon
Untitled, Darren Poon
Architecture Master Theses
"My objective is to explore the potential of generative design processes driven by user-derived parameters established through computational protocols, algorithms, and simulations resulting in a process embodying ecologies of feedback and performances. Inherent in the designed process is the establishment of feedback, through each cycle of simulation, evaluation, and modification of the geometry.
This thesis project demonstrates a version of these processes specifically examining the performance driven building typology of the massive server farm. Specifically, its implicit correlations with fluid dynamic simulation and its biases toward an optimization of heat dissipation and plan layout. This project is situated between a …
Biomarker Identification For Prostate Cancer Using An Efficient Feature Selection Algorithm, Vamsi Krishnam Raju Mantena
Biomarker Identification For Prostate Cancer Using An Efficient Feature Selection Algorithm, Vamsi Krishnam Raju Mantena
Electrical & Computer Engineering Theses & Dissertations
In recent years, there has been an increased interest in using protein mass spectrometry to identify biomarkers that discriminate diseased from healthy individuals. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathological processes, or pharmacological responses to a therapeutic intervention. Identifying biomarkers will be an important step towards disease characterization and patient management. One challenge of biomarker identification is how to handle the high dimensional mass spectral data. In this thesis, we applied an efficient feature selection algorithm to mass spectrometry data obtained from prostate tissue samples to identify prostate …
Accelerating Near-Duplicate Video Matching By Combining Visual Similarity And Alignment Distortion, Hung-Khoon Tan, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Accelerating Near-Duplicate Video Matching By Combining Visual Similarity And Alignment Distortion, Hung-Khoon Tan, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Research Collection School Of Computing and Information Systems
In this paper, we investigate a novel approach to accelerate the matching of two video clips by exploiting the temporal coherence property inherent in the keyframe sequence of a video. Motivated by the fact that keyframe correspondences between near-duplicate videos typically follow certain spatial arrangements, such property could be employed to guide the alignment of two keyframe sequences. We set the alignment problem as an integer quadratic programming problem, where the cost function takes into account both the visual similarity of the corresponding keyframes as well as the alignment distortion among the set of correspondences. The set of keyframe-pairs found …
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu
Research Collection School Of Computing and Information Systems
In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …
The Development Of Genetic Algorithm For The Prediction Of Ship Motion From Wave Radar Data, Sumanth Tirumala Vangipuram
The Development Of Genetic Algorithm For The Prediction Of Ship Motion From Wave Radar Data, Sumanth Tirumala Vangipuram
Electrical & Computer Engineering Theses & Dissertations
Genetic Algorithms represent a model of natural process based on the Darwinian principle of evolution. Genetic algorithms are used to solve optimization problems by generating a set of possible solutions and determining which of these solutions most closely match the desired result. The Genetic Algorithm (GA) initially generates a random set of possible solutions, or populations, determines which members of the population are most desirable, and calculates better solutions by implementing genetic operations such as reproduction, cloning, and mutation. Problems where the evaluation of a solution is computationally simple enable the GA to search a vast search space. One of …
Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Theses and Dissertations
A design process is demonstrated for a coexistent scenario containing Spectrally Modulated, Spectrally Encoded (SMSE) and Direct Sequence Spread Spectrum (DSSS) signals. Coexistent SMSE-DSSS designs are addressed under both perfect and imperfect DSSS code tracking conditions using a non-coherent delay-lock loop (DLL). Under both conditions, the number of SMSE subcarriers and subcarrier spacing are the optimization variables of interest. For perfect DLL code tracking conditions, the GA and RSM optimization processes are considered independently with the objective function being end-to-end DSSS bit error rate. A hybrid GA-RSM optimization process is used under more realistic imperfect DLL code tracking conditions. In …
Service Oriented Transitive Closure Solution, Jonathan Baran
Service Oriented Transitive Closure Solution, Jonathan Baran
Computer Science and Computer Engineering Undergraduate Honors Theses
The goal of this project is a service based solution that utilizes parallel and distributed processing algorithms to solve the transitive closure problem for a large dataset. A dataset may be view conceptually as a table in a database, with a physical structure representing a file containing a sequence of records and fields. Two records are said to be transitively related if and only if they are directly related due to sharing of one or more specific fields, or a sequence may be made from one record to the other under the condition that all intermediate entries are related the …
Medical Image Modeling And Processing, Ramu Pedada
Medical Image Modeling And Processing, Ramu Pedada
Electrical & Computer Engineering Theses & Dissertations
During the last few decades of the twentieth century, medical imaging has been playing a prominent role in many fields of biomedical research and clinical practice. Image modalities such as x-rays, computed tomography (CT), and magnetic resonance images (MRI) have all been valuable additions to the radiologist's arsenal of imaging tools. Medical images assure quality diagnosis and patient safety by gathering valuable information without invading the human body. Apart from clinical diagnosis, medical images are used as tools for education where they are used for training individuals before operating on a patient. Many medical educators tum to simulation based training …
Image Pre-Processing Techniques For Hazard Detection In Poor Visibility Conditions, Girish Singh Rajput
Image Pre-Processing Techniques For Hazard Detection In Poor Visibility Conditions, Girish Singh Rajput
Electrical & Computer Engineering Theses & Dissertations
Runway incursion is a persistent problem that has resulted in some of the most devastating accidents in aviation history. With ever increasing air traffic and more passengers, runway safety is of utmost priority to the Federal Aviation Administration (FAA) and other agencies concerned with aviation. As the issue of aviation safety becomes increasingly important, developing a consistent application that detects runway incursions in various visibility conditions is crucial for the aviation industry. This thesis presents a novel method for detecting runway hazards in poor visibility conditions using image processing techniques. The first step is to obtain images of a runway …
Robust Edge-Detection Algorithm For Runway Edge Detection, Swathi Tandra
Robust Edge-Detection Algorithm For Runway Edge Detection, Swathi Tandra
Electrical & Computer Engineering Theses & Dissertations
Fog and other such weather conditions hamper the visibility of runway surfaces and any obstacles present on the runway, creating a situation where a pilot may not be able to safely land the aircraft. Assisting the pilot to land the aircraft safely in such conditions is an active area of research. A new method is being investigated that combines non-linear image enhancement with classification of runway edges to detect objects on the runway. The image is segmented into runway and non-runway regions, and objects that are found in the runway regions are deemed to constitute potential hazards. For runway edge …
Extending The Network Life Time In Wsn Using Energy Efficient Algorithm, Venkata Sesha Sai Koundinya Goparaju
Extending The Network Life Time In Wsn Using Energy Efficient Algorithm, Venkata Sesha Sai Koundinya Goparaju
Electrical & Computer Engineering Theses & Dissertations
Wireless Sensor networks have many potential applications. These wireless sensor networks necessitate specific design requirements of which energy efficiency is vital. The sensor networks consist of sensor nodes that operate on battery power, and replacement of these batteries is very often a strenuous task, since networks are deployed in areas where the act of replacing the batteries proves impractical.
With the limited available energy of sensor nodes, most of the energy is drained during communication. An energy efficient routing algorithm can prolong the lifetime of the network by gradually depleting the nodes in the network. Many of the routing protocols …
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Object Detection In Poor Visibility Conditions Using Image Segmentation, Triveni Vuppalapati
Object Detection In Poor Visibility Conditions Using Image Segmentation, Triveni Vuppalapati
Electrical & Computer Engineering Theses & Dissertations
It can be dangerous for a pilot to attempt to land an aircraft safely in poor visibility conditions such as rain, fog, haze, snow and low light, but external imagery of a runway can be enhanced to provide increased situational awareness. Objects that are detected in a scene may or may not be a hazard, so interpretation is left to the pilot. In order to detect whether an object is a hazard to safe landing, it is necessary to determine whether the object is on the runway. For this purpose, two image segmentation algorithms: histogram based d-peak algorithm and local …
Visualization Of An Approach To Data Clustering, Marisabel Guevara
Visualization Of An Approach To Data Clustering, Marisabel Guevara
Computer Science and Computer Engineering Undergraduate Honors Theses
Using visualization and clustering goals as guidelines, this thesis explores a graphic implementation of a data clustering technique that repositions vertices by applying physical laws of charges and springs to the components of the graph. The resulting visualizations are evidence of the success of the approach as well as of the data sets that lend themselves to a clustering routine. Due to the visual product of the implementation, the algorithm is most useful as an aid in understanding the grouping pattern of a data set. Either for a rapid analysis or to assist in presentation, the visual result of the …
Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov
Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Several models of user churn, resilience, and link lifetime have recently appeared in the literature [12], [13], [34], [35]; however, these results do not directly apply to classical Distributed Hash Tables (DHTs) in which neighbor replacement occurs not only when current users die, but also when new user arrive into the system, and where replacement choices are often restricted to the successor of the failed zone in the DHT space. To understand neighbor churn in such networks, this paper proposes a simple, yet accurate, model for capturing link dynamics in structured P2P systems and obtains the distribution of link lifetimes …
Prostate Segmentation On Pelvic Ct Images Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell
Prostate Segmentation On Pelvic Ct Images Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell
Computer Science Faculty Publications and Presentations
A genetic algorithm (GA) for automating the segmentation of the prostate on pelvic computed tomography (CT) images is presented here. The images consist of slices from three-dimensional CT scans. Segmentation is typically performed manually on these images for treatment planning by an expert physician, who uses the “learned” knowledge of organ shapes, textures and locations to draw a contour around the prostate. Using a GA brings the flexibility to incorporate new “learned” information into the segmentation process without modifying the fitness function that is used to train the GA. Currently the GA uses prior knowledge in the form of texture …
Symbolic Links In The Open Directory Project, Saverio Perugini
Symbolic Links In The Open Directory Project, Saverio Perugini
Computer Science Faculty Publications
We present a study to develop an improved understanding of symbolic links in web directories. A symbolic link is a hyperlink that makes a directed connection from a web page along one path through a directory to a page along another path. While symbolic links are ubiquitous in web directories such as Yahoo!, they are under-studied, and as a result, their uses are poorly understood. A cursory analysis of symbolic links reveals multiple uses: to provide navigational shortcuts deeper into a directory, backlinks to more general categories, and multiclassification. We investigated these uses in the Open Directory Project (ODP), the …
Enabling Synergy Between Psychology And Natural Language Processing For E-Government: Crime Reporting And Investigative Interview System, Alicia Iriberri '06, Chih Hao Ku '12, Gondy Leroy
Enabling Synergy Between Psychology And Natural Language Processing For E-Government: Crime Reporting And Investigative Interview System, Alicia Iriberri '06, Chih Hao Ku '12, Gondy Leroy
CGU Faculty Publications and Research
We are developing an automated crime reporting and investigative interview system. The system incorporates cognitive interview techniques to maximize witness memory recall, and information extraction technology to extract and annotate crime entities from witness narratives and interview responses. Evaluations of the IE components of the system show that it captures 70 to 77% of information from witness narratives with 93 to 100% precision. Our development goal is for the system to approximate progressively the performance effectiveness of a human investigative interviewer and to generate graphical visualizations of crime report information.
Natural Language Processing And E-Government: Crime Information Extraction From Heterogeneous Data Sources, Chih Hao Ku '12, Alicia Iriberri '06, Gondy Leroy
Natural Language Processing And E-Government: Crime Information Extraction From Heterogeneous Data Sources, Chih Hao Ku '12, Alicia Iriberri '06, Gondy Leroy
CGU Faculty Publications and Research
Much information that could help solve and prevent crimes is never gathered because the reporting methods available to citizens and law enforcement personnel are not optimal. Detectives do not have sufficient time to interview crime victims and witnesses. Moreover, many victims and witnesses are too scared or embarrassed to report incidents. We are developing an interviewing system that will help collect such information. We report here on one component, the crime information extraction module, which uses natural language processing to extract crime information from police reports, newspaper articles, and victims’ and witnesses’ crime narratives. We tested our approach with two …
A Multiprocessor Parallel Approach To Bit-Parallel Approximate String Matching, Elias Anwar Chibli
A Multiprocessor Parallel Approach To Bit-Parallel Approximate String Matching, Elias Anwar Chibli
Theses Digitization Project
The purpose of this project is to present with empirical results that a parallel design with the use of multiple processors can be successfully applied along with bit-parallel approximate string matching algorithms to solve practical bioinformatics problems. It will demonstrate that nearly optimal speedup can be achieved with a cluster of between two and eight workstations using MPI (Message Passing Interface), directly decreasing the total latency required to perform a string matching problem.
Traffic Analysis Of Udp-Based Flows In Ourmon, Jim Binkley, Divya Parekh
Traffic Analysis Of Udp-Based Flows In Ourmon, Jim Binkley, Divya Parekh
Computer Science Faculty Publications and Presentations
We present a custom UDP flow tuple with an IP address key and a set of simple related statistical attributes. Attributes are used to calculate a per host metric called the UDP work weight which roughly measures the amount of network noise caused by a host. The work weight is used to produce a near real-time sorted top N report for UDP host tuples. We also present a derived attribute based on an algorithm called the UDP guesstimator. The UDP guesstimator roughly classifies port report hosts into various traffic categories including security threats (DOS/scanning) or P2P hosts based on high …
Graphics Processor Based Implementation Of Bioinformatics Codes, Andrew Bellenir, Christian Trefftz, Greg Wolffe
Graphics Processor Based Implementation Of Bioinformatics Codes, Andrew Bellenir, Christian Trefftz, Greg Wolffe
Student Summer Scholars Manuscripts
We created a powerful computing platform based on video cards with the goal of accelerating the performance of bioinformatics codes. To satisfy the demands of the video gaming industry, modern graphics processing units (GPUs) have become very advanced computational devices, using a large set of stream processors to render multiple pixels in parallel. Recently, computer scientists have taken interest in a GPU's ability to execute a single instruction on multiple data (SIMD computation) for general applications, as opposed to graphics processing only. This is known as general purpose computation on a graphics processing unit, or GPGPU.
Our project was comprised …
Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Electrical & Computer Engineering Faculty Publications
Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …