Computer Sciences Commons^™

Topic Detection And Tracking Using Hidden Markov Models, Aditya S. Tatavarty

UNLV Theses, Dissertations, Professional Papers, and Capstones

There is a continuous progress in automatic recording of broadcast speech using speech recognition. With the increasing use of this technology, a new source of data is added to the pool of information available over web. This has increased the need to categorize the resulting text, based on their topic for the purpose of information retrieval.

In this thesis we present an approach to automatically assign a topic or track a change of topic in a stream of input data. Our approach is based on the use of Hidden Markov Models and language processing techniques. We consider input text as …

Shop Problems In Scheduling, James Andro-Vasko

UNLV Theses, Dissertations, Professional Papers, and Capstones

The shop problems in scheduling will be discussed in this thesis. The ones I'll be discussing will be the flow shop, open shop, and job shop. The general idea of shop problems is that you're given a set of jobs and a set of machines. Each job is predeterminely broken into parts and there are rules to how each part is executed on a machine. In this thesis, several shop problems and their algorithms will be introduced that I have researched. There are several examples and counter examples that I have constructed. Also I will discuss how an arbitrary problem …

Using Smoothing Techniques To Improve The Performance Of Hidden Markov’S Model, Sweatha Boodidhi

UNLV Theses, Dissertations, Professional Papers, and Capstones

The result of training a HMM using supervised training is estimated probabilities for emissions and transitions. There are two difficulties with this approach Firstly, sparse training data causes poor probability estimates. Secondly, unseen probabilities have emission probability of zero. In this thesis, we report on different smoothing techniques and their implementations. We further report on our experimental results using standard precision and recall for various smoothing techniques.

Implementation Of Hidden Semi-Markov Models, Nagendra Abhinav Dasu

UNLV Theses, Dissertations, Professional Papers, and Capstones

One of the most frequently used concepts applied to a variety of engineering and scientific studies over the recent years is that of a Hidden Markov Model (HMM). The Hidden semi-Markov model (HsMM) is contrived in such a way that it does not make any premise of constant or geometric distributions of a state duration. In other words, it allows the stochastic process to be a semi-Markov chain. Each state can have a collection of observations and the duration of each state is a variable. This allows the HsMM to be used extensively over a range of applications. Some of …

Novel Application Of Neutrosophic Logic In Classifiers Evaluated Under Region-Based Image Categorization System, Wen Ju

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Neutrosophic logic is a relatively new logic that is a generalization of fuzzy logic. In this dissertation, for the first time, neutrosophic logic is applied to the field of classifiers where a support vector machine (SVM) is adopted as the example to validate the feasibility and effectiveness of neutrosophic logic. The proposed neutrosophic set is integrated into a reformulated SVM, and the performance of the achieved classifier N-SVM is evaluated under an image categorization system. Image categorization is an important yet challenging research topic in computer vision. In this dissertation, images are first segmented by a hierarchical two-stage self organizing …

Understanding Teacher Users Of A Digital Library Service: A Clustering Approach, Beijie Xu

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This research examined teachers' online behaviors while using a digital library service—the Instructional Architect (IA)—through three consecutive studies. In the first two studies, a statistical model called latent class analysis (LCA) was applied to cluster different groups of IA teachers according to their diverse online behaviors. The third study further examined relationships between teachers' demographic characteristics and their usage patterns. Several user clusters emerged from the LCA results of Study I. These clusters were named isolated islanders, lukewarm teachers, goal-oriented brokers, window shoppers, key brokers, beneficiaries, classroom practitioners, and dedicated sticky users. …

A Fully Automatic Segmentation Method For Breast Ultrasound Images, Juan Shan

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Breast cancer is the second leading cause of death of women worldwide. Accurate lesion boundary detection is important for breast cancer diagnosis. Since many crucial features for discriminating benign and malignant lesions are based on the contour, shape, and texture of the lesion, an accurate segmentation method is essential for a successful diagnosis. Ultrasound is an effective screening tool and primarily useful for differentiating benign and malignant lesions. However, due to inherent speckle noise and low contrast of breast ultrasound imaging, automatic lesion segmentation is still a challenging task.

This research focuses on developing a novel, effective, and fully automatic …

Prototyping Video Games With Animation, Richard C. Davis

Research Collection School Of Computing and Information Systems

This paper outlines a proposed design for StorySketch, a new video game storyboarding system. StorySketch borrows ideas from the K-Sketch animation sketching system, which allows short animations to be created in minutes or seconds. We build on K-Sketch in four ways. key frame animation capabilities, a branching timeline view, microphone and web-cam support, and hooks to connect to online game design documents.

Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato

Research Collection School Of Computing and Information Systems

In today's world, organizations are faced with increasingly large and complex problems that require decision-making under uncertainty. Current methods for optimizing such decisions fall short of handling the problem scale and time constraints. We argue that this is due to existing methods not exploiting the inherent structure of the organizations which solve these problems. We propose a new model called the OrgPOMDP (Organizational POMDP), which is based on the partially observable Markov decision process (POMDP). This new model combines two powerful representations for modeling large scale problems: hierarchical modeling and factored representations. In this paper we make three key contributions: …

Message-Passing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDPs provide a rigorous framework for multi-agent decision-theoretic planning. However, their high complexity has limited scalability. In this work, we present a promising new class of algorithms based on probabilistic inference for infinite-horizon ND-POMDPs---a restricted Dec-POMDP model. We first transform the policy optimization problem to that of likelihood maximization in a mixture of dynamic Bayes nets (DBNs). We then develop the Expectation-Maximization (EM) algorithm for maximizing the likelihood in this representation. The EM algorithm for ND-POMDPs lends itself naturally to a simple message-passing paradigm guided by the agent interaction graph. It is thus highly scalable w.r.t. the number of …

Design And Performance Analysis Of Mac Schemes For Wireless Sensor Networks Powered By Ambient Energy Harvesting, Zhi Ang Eu, Hwee-Pink Tan, Winston K. G. Seah

Research Collection School Of Computing and Information Systems

Energy consumption is a perennial issue in the design of wireless sensor networks (WSNs) which typically rely on portable sources like batteries for power. Recent advances in ambient energy harvesting technology have made it a potential and promising alternative source of energy for powering WSNs. By using energy harvesters with supercapacitors, WSNs are able to operate perpetually until hardware failure and in places where batteries are hard or impossible to replace. In this paper, we study the performance of different medium access control (MAC) schemes based on CSMA and polling techniques for WSNs which are solely powered by ambient energy …

Fragile Online Relationship: A First Look At Unfollow Dynamics In Twitter, Haewoon Kwak, Hyunwoo Chun, Sue. Moon

Research Collection School Of Computing and Information Systems

We analyze the dynamics of the behavior known as 'unfollow' in Twitter. We collected daily snapshots of the online relationships of 1.2 million Korean-speaking users for 51 days as well as all of their tweets. We found that Twitter users frequently unfollow. We then discover the major factors, including the reciprocity of the relationships, the duration of a relationship, the followees' informativeness, and the overlap of the relationships, which affect the decision to unfollow. We conduct interview with 22 Korean respondents to supplement the quantitative results.They unfollowed those who left many tweets within a short time, created tweets about uninteresting …

Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri

Research Collection School Of Computing and Information Systems

The use of distributed POMDPs for cooperative teams has been severely limited by the incredibly large joint policy- space that results from combining the policy-spaces of the individual agents. However, much of the computational cost of exploring the entire joint policy space can be avoided by observing that in many domains important interactions between agents occur in a relatively small set of scenarios, previously defined as coordination locales (CLs) [11]. Moreover, even when numerous interactions might occur, given a set of individual policies there are relatively few actual interactions. Exploiting this observation and building on an existing model shaping algorithm, …

Beespace Navigator: Exploratory Analysis Of Gene Function Using Semantic Indexing Of Biological Literature, Moushumi Sen Sarma, David Arcoleo, Radhika S. Khetani, Brant Chee, Xu Ling, Xin He, Jing Jiang, Qiaozhu Mei, Chengxiang Zhai, Bruce Schatz

Research Collection School Of Computing and Information Systems

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments …

Improving Data Freshness To Enhance The Quality Of Observations In Wireless Sensor Networks, Ramya Bala Ammu

Boise State University Theses and Dissertations

Wireless Sensor Networks (WSNs) are used to achieve either continuous monitoring or event-detection in the area of interest. In continuous monitoring applications, each sensor node transmits its sensed data to the sink node (base station) periodically; while in event-detection driven applications, nodes report to the sink node once an event occurs. Continuous monitoring applications require periodic refreshed data at the sink node. Data reaching the sink node after a certain threshold is not useful for processing or analysis because it is stale. Data freshness along with reliable data delivery is critical in such applications. Current protocols in this area measure …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 4: Predictive Analysis - Regression Modeling, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Processing And Classification Of Physiological Signals Using Wavelet Transform And Machine Learning Algorithms, Abed Al-Raoof Bsoul

Theses and Dissertations

Over the last century, physiological signals have been broadly analyzed and processed not only to assess the function of the human physiology, but also to better diagnose illnesses or injuries and provide treatment options for patients. In particular, Electrocardiogram (ECG), blood pressure (BP) and impedance are among the most important biomedical signals processed and analyzed. The majority of studies that utilize these signals attempt to diagnose important irregularities such as arrhythmia or blood loss by processing one of these signals. However, the relationship between them is not yet fully studied using computational methods. Therefore, a system that extract and combine …

A Speculative Approach To Parallelization In Particle Swarm Optimization, Matthew J. Gardner

Theses and Dissertations

Particle swarm optimization (PSO) has previously been parallelized primarily by distributing the computation corresponding to particles across multiple processors. In this thesis we present a speculative approach to the parallelization of PSO that we refer to as SEPSO. In our approach, we refactor PSO such that the computation needed for iteration t+1 can be done concurrently with the computation needed for iteration t. Thus we can perform two iterations of PSO at once. Even with some amount of wasted computation, we show that this approach to parallelization in PSO often outperforms the standard parallelization of simply adding particles to the …

Understanding User Generated Content Characteristics : A Hot-Event Perspective, Miao Wang, Guodong Li, Jie Feng, Lisong Xu, Byrav Ramamurthy, Wei Li, Xiaohong Guan

School of Computing: Conference and Workshop Papers

Nowadays, millions of Internet users watch and upload a large number of videos on User Generated Content (UGC) sites (e.g., Youtube) everyday. Moreover, online videos about hot events, such as breaking news and Olympic games, attract lots of users. In this paper, we study the characteristics of hot-event videos by collecting video traces of the largest UGC site in China for 28 days. We first empirically study statistical properties of such videos and find that hot-event videos contribute a large number of views, even though the total number of hotevent videos is relatively small. In addition, there exist extremely active …

Outdoor Scenes For Data Visualization, Benjamin A. Hillery

Theses and Dissertations

Recent cognitive research indicates that the human brain possesses special abilities for processing information relating to outdoor scenes. Simulated outdoor scenes are presented as an effective method of displaying higher dimensional data in an efficient and comprehensible manner. We demonstrate novel methods of using outdoor objects and scenes to display multidimensional content in a way that that is intuitive for humans to understand, and to exploit various cues commonly found in scenes from the natural world to communicate the values of multiple variables.

Real-Time Fundamental Frequency Estimation Algorithm For Disconnected Speech, Thomas Skjei

Theses and Dissertations

A new algorithm is presented for real-time fundamental frequency estimation of speech signals. This method extends and alters the YIN algorithm, which uses the autocorrelation-based difference function, by adding features to reduce latency, correct predictable errors, and make it structurally appropriate for real-time processing scenarios. The algorithm is shown to reduce the error rate of its predecessor while demonstrating latencies sufficient for real-time processing. The results indicate that the algorithm can be realized as a real-time estimator of spoken pitch and pitch variation, which has applications including diagnosis and biofeedback-based therapy of many speech disorders.

Applying The Diversity Map, A Visualization Technique, To The Protein Data Bank, Onyekwere Maduka Ogba

Computer Science Honors Theses

In this research, the Diversity Map, a visualization technique created in the Metoyer research lab in Oregon State, is used to visualize the diversity of all the molecules deposited in the Protein Data Bank. Data was split into a period of three years from 1990 to 2010 and analyzed individually by Dr. Laura Hunsicker-Wang in the department of chemistry with a research focus in protein, and ten student participants with varying level of knowledge in chemistry. Results show that the Diversity Map is a powerful tool in understanding data from the Protein Data Bank and furthermore, has strong potential in …

Circle The Cat: Developing Intelligent Strategies For A Simple Two-Player Game, Kirk Baly, Micheal Lay, Owen Prough

Symposium on Research and Creative Expression (SORCE)

Circle the Cat is an adaptation of the classic mathematical puzzle Qudraphage in which a cat attempts to escape a hexagonal board, but after each move one hexagon is blocked. We have coded a simulation of this classic puzzle. The result of our development allows for the implementation of varying strategies to computationally examine their effectiveness. The code itself, though extensive, is open enough for additions/extensions to be added fairly easily. Analysis of simpler strategies has allowed for improvement of both Cat and Player AI systems. We are currently looking at implementing more advanced systems, perhaps turning to machine learning.

Lazy Golfing, Didar Ashkerbekov, Max Hougas

Symposium on Research and Creative Expression (SORCE)

Walking golfers are expected to leave their golf bags just outside the edge of the green while they are putting the ball. We construct a simple model of this situation, in which the green is assumed to be a circle with the hole at the center and the golfer one-putts the ball. (He or she is a great golfer!) We construct a function to determine the distance that the golfer walks from his or her approach shot on the green and then to the next tee box. Given this model, we determine the optimal location for leaving the golf bag …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 3: Attitudinal Analysis - Artist Housing And Space Survey, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

A Cost-Benefit Analysis Of A Campus Computing Grid, Preston M. Smith

Purdue Polytechnic Masters Theses

Any major research institution has a substantial number of computer systems on its campus, often in the scale of tens of thousands. Given that a large amount of scientific computing is appropriate for execution in an opportunistic environment, a campus grid is an inexpensive way to build a powerful computational resource. What is missing, though, is a model for making an informed decision on the cost-effectives of a campus grid. In this thesis, the author describes a model for measuring the costs and benefits of building a campus computing resource based on the institution’s existing investment in computing hardware.

For …

A Bottom-Up Design And Implementation For Ambiguity-Compatible Natural Language Sentence Parsing, Elise Thrasher

Computer Science Honors Theses

Although many theory-focused computer science textbooks give a brief outline of a context-free grammar model of natural language, the approach is often vague and, in reality, greatly simplifies the English language’s grammatical complexities. When applied to commonly-seen sentences, these sentence parsing models often fall short. In this paper, I detail my process of creating a programmable natural language context-free grammar that is able to parse (i.e. diagram) many common sentence forms, as well as the research which influenced the design of this project. In order to create a grammar that recognized the intricacies of the English language, I also incorporated …

Applications Of Hidden Markov Models In Microarray Gene Expression Data, Huimin Geng, Xutao Deng, Hesham Ali

Computer Science Faculty Publications

Hidden Markov models (HMMs) are well developed statistical models to capture hidden information from observable sequential symbols. They were first used in speech recognition in 1970s and have been successfully applied to the analysis of biological sequences since late 1980s as in finding protein secondary structure, CpG islands and families of related DNA or protein sequences [1]. In a HMM, the system being modeled is assumed to be a Markov process with unknown parameters, and the challenge is to determine the hidden parameters from the observable parameters. In this chapter, we described two applications using HMMs to predict gene functions …

Wmu Mobile For Iphone, Christopher A. Ashbay, Justuce Reule, Tim Wickey

Honors Theses

Western Michigan University does not currently have a smart phone application. WMU Mobile for iPhone was created for WMU students as a mobile source for campus news, weather information, and athletics highlights. It also provides connections to various sources of WMU media, and allows users to access GPS maps of campus buildings. The app is designed to allow for future releases which may include allowing the user to view campus events by department and search campus maps. The WMU Mobile for iPhone is accessible on the iPhone, iPod Touch, and iPad, and is available for free through the Apple App …

Exploiting The Hard-Working Dwarf: Trojans With No Native Executable Code, James Oakley, Sergey Bratus

Computer Science Technical Reports

All binaries compiled by recent versions of GCC from C++ programs include complex data and dedicated code for exception handling support. The data structures describe the call stack frame layout in the DWARF format bytecode. The dedicated code includes an interpreter of this bytecode and logic to implement the call stack unwinding. Despite being present in a large class of programs -- and therefore potentially providing a huge attack surface -- this mechanism is not widely known or studied. Of particular interest to us is that the exception handling mechanism provides the means for fundamentally altering the flow of a …