Theory and Algorithms Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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

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 …

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 …

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 …

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 …

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.

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

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 …

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.

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

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

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

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

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

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

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

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 …

Object Detection And Classification With Applications To Skin Cancer Screening, Jonathan Blackledge, Dmitryi Dubovitskiy

Articles

This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

The principal issues associated with object recognition are presented which includes two novel fast segmentation algorithms for which C++ code is provided. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and …

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 …

Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti

Computer Science Faculty Publications

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. …

Morphology Independent Dynamic Locomotion Control For Virtual Characters, Adrian Boeing

Research outputs pre 2011

Physically based animation of virtual characters is an attractive technology for computer games. It enables characters to dynamically react to interactions with the environment. Existing dynamic simulation controllers are often complex to understand and manipulate, and so are of limited use for animators. This paper presents an extended spline-based control strategy similar to splines used in standard keyframe animation techniques. Unlike existing dynamic control strategies, this allows animators to modify the control system parameters in a manner similar to traditional kinematic animation techniques. A genetic algorithm is employed to produce the initial control parameters for the desired gait, and extend …

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 …

Web Search Algorithms And Pagerank, Laleh Samarbakhsh

Theses and Dissertations (Comprehensive)

The mathematical theory underlying the Google search engine is the PageRank algorithm, first introduced by Sergey Brin and Lawrence Page, the founders of Google. A ranking of web pages is made considering many criteria. PageRank exploits the graph structure of the web. The web’s hyperlink structure forms a massive directed graph, where the web pages are presented as nodes and hyperlinks as edges. The PageRank equation finds a score by solving a recursive equation which calculates the PageRank vector. The PageRank vector is the stationary distribution of an ergodic Markov chain. The Perron-Frobenius theorem ensures that the primitive matrix produced …