Computer Sciences Commons^™

Sensor Authentication In Collaborating Sensor Networks, Jake Uriah Bielefeldt

Masters Theses

"In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator Oⁱ of Sensor Network S^{i …}

Argumentation Based Collaborative Software Architecture Design And Intelligent Analysis Of Software Architecture Rationale, Nagaprashanth Chanda

Masters Theses

"A growing model for software architecture defines it as a set of principle design decisions which drive system architects to design the architecture satisfying software requirements and architectural constraints. The design decision making process involves a group of stakeholders exchanging their viewpoints to address various concerns and to reach a consensus collaboratively. These architecture design decisions are usually made based on experiences since there aren't defined methods and models for architecture design. Each design decision yields a set of outcomes which impacts both the system architecture and the final product. As software product systems, tend to be large in size, …

Energy Disaggregation In Nialm Using Hidden Markov Models, Anusha Sankara

Masters Theses

"This work presents an appliance disaggregation technique to handle the fundamental goal of the Non-Intrusive Appliance Load Monitoring (NIALM) problem i.e., a simple breakdown of an appliance level energy consumption of a house. It also presents the modeling of individual appliances as load models using hidden Markov models and combined appliances as a single load model using factorial hidden Markov models. Granularity of the power readings of the disaggregated appliances matches with that of the readings collected at the service entrance. Accuracy of the proposed algorithm is evaluated using publicly released Tracebase data sets and UK-DALE data sets at various …

Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith

Masters Theses

"Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully …

Rote-Lcs Learning Classifier System For Classification And Prediction, Benjamin Daniels

Masters Theses

"Machine Learning (ML) involves the use of computer algorithms to solve for approximate solutions to problems with large, complex search spaces. Such problems have no known solution method, and search spaces too large to allow brute force search to be feasible. Evolutionary algorithms (EA) are a subset of machine learning algorithms which simulate fundamental concepts of evolution. EAs do not guarantee a perfect solution, but rather facilitate convergence to a solution of which the accuracy depends on a given EA's learning architecture and the dynamics of the problem.

Learning classifier systems (LCS) are algorithms comprising a subset of EAs. The …

Hyper-Heuristics For The Automated Design Of Black-Box Search Algorithms, Matthew Allen Martin

Masters Theses

"Within the field of Black-Box Search Algorithms (BBSAs), there is a focus on improving algorithm performance over increasingly diversified problem classes. However, these general purpose problem solvers have no guarantee to perform well on an arbitrary problem class that a practitioner needs to solve. The problem classes that the research in this thesis most applies to are difficult problems that are going to be solved multiple times. BBSAs tailored to one of these problem class can be expected to significantly outperform the more general purpose problem solvers, including canonical Evolutionary Algorithms (EAs). The first paper in this thesis explores a …

Design And Implementation Of A Broker For Cloud Additive Manufacturing Services, Venkata Prashant Modekurthy

Masters Theses

"The growing number of cloud Additive Manufacturing (AM) services, offered by different providers over the Internet, makes it challenging for consumers to compare these cloud AM services to select a service of their choice. In addition, it is even more challenging for consumers to compare these cloud AM services against their personal preferences. This is because, consumers personal preferences on multiple service attributes such as price, material, accuracy, and schedule, should be considered for cloud AM service selection. The decentralized nature of these cloud AM services coupled by the need to consider consumers personal preferences during cloud AM service selection, …

Cyber Security Research Frameworks For Coevolutionary Network Defense, George Daniel Rush

Masters Theses

"Cyber security is increasingly a challenge for organizations everywhere. Defense systems that require less expert knowledge and can adapt quickly to threats are strongly needed to combat the rise of cyber attacks. Computational intelligence techniques can be used to rapidly explore potential solutions while searching in a way that is unaffected by human bias.

Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation …

Aerial Vehicle Trajectory Design For Spatio-Temporal Task Satisfaction And Aggregation Based On Utility Metric, Amarender Reddy Mekala

Masters Theses

"Flight trajectories are mainly designed in order to make sure that the aerial vehicle reaches the destination point from the start point. In addition to that, the flight path is designed in such a way that the flight avoids dangerous zones and the maneuvers required for the path are practically feasible for the flight.

This thesis focuses on the aerial vehicle trajectory generation passing through a set of pre-defined way points while satisfying the task points sent by the ground base station in between the way points. Each specified waypoint is reached exactly at the specified location and time. Intermediate …

A Gaussian Mixture Model For Automated Vesicle Fusion Detection And Classification, Haohan Li

Masters Theses

"Accurately detecting and classifying vesicle-plasma membrane fusion events in fluorescence microscopy, is of primary interest for studying biological activities in a close proximity to the plasma membrane. In this paper, we present a novel Gaussian mixture model for automated identification of vesicle-plasma membrane fusion and partial fusion events in total internal reflection fluorescence microscopy image sequences. Image patches of fusion event candidates are detected in individual images and linked over consecutive frames. A Gaussian mixture model is fit on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. The estimated parameters of Gaussian functions over …

Classifying Idiomatic And Literal Expressions Using Vector Space Representations, Jing Peng, Anna Feldman, Hamza Jazmati

Department of Computer Science Faculty Scholarship and Creative Works

We describe an algorithm for automatic classification of idiomatic and literal expressions. Our starting point is that idioms and literal expressions occur in different contexts. Idioms tend to violate cohesive ties in local contexts, while literals are expected to fit in. Our goal is to capture this intuition using a vector representation of words. We propose two approaches: (1) Compute inner product of context word vectors with the vector representing a target expression. Since literal vectors predict well local contexts, their inner product with contexts should be larger than idiomatic ones, thereby telling apart literals from idioms; and (2) Compute …

Deforming Diamond, Ciprian Borcea, Ileana Streinu

Computer Science: Faculty Publications

For materials science, diamond crystals are almost unrivaled for hardness and a range of other properties. Yet, when simply abstracting the carbon bonding structure as a geometric bar-and-joint periodic framework, it is far from rigid. We study the geometric deformations of this type of framework in arbitrary dimension d, with particular regard to the volume variation of a unit cell.

Vast Challenge 2015: Mayhem At Dinofun World, Mark Whiting, Kristin Cook, Georges Grinstein, John Fallon, Kristen Liggett, Diane Staheli, R. Jordan Crouser

Computer Science: Faculty Publications

A fictitious amusement park and a larger-than-life hometown football hero provided participants in the VAST Challenge 2015 with an engaging yet complex storyline and setting in which to analyze movement and communication patterns. The datasets for the 2015 challenge were large—averaging nearly 10 million records per day over a three day period—with a simple straightforward structured format. The simplicity of the format belied a complex wealth of features contained in the data that needed to be discovered and understood to solve the tasks and questions that were posed. Two Mini-Challenges and a Grand Challenge compose the 2015 competition. Mini-Challenge 1 …

Functional Reactive Programming For Games, Peter Adewunmi Salu

Electronic Theses and Dissertations

We investigate the effectiveness of functional reactive programming for games. To accomplish this, we clone aa, an existing game, in Elm, a purely functional programming language. We find that functional reactive programming offers an excellent alternative to event driven programming in purely functional languages. Elm still needs more work if it aims to compete with JavaScript libraries. Games, which typically need several inputs at the same time, benefit from the first class status of Signals, which allow them to be combined.

Reasoning Over Taxonomic Change: Exploring Alignments For The Perelleschus Use Case, Nico M. Franz, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shaun Bowers, Bertram Ludäscher

Computer Science Faculty Scholarship

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted …

Japanese Computational Lexicon: A Computational Dictionary Of Japanese Verb Forms, Mayumi Kobayashi

Open Access Theses & Dissertations

This paper presents two main topics: a linguistic analysis of Japanese morphological lexicon focused on verb conjugation and a computational analysis of Japanese verb conjugation in Prolog programming. Prolog is one of the computer programming languages and is used to solve a problem logically with a number of statements called "clauses," which are defining various relationships of the entities. With respect to the linguistic aspect, this paper discusses Japanese verb formation, its conjugation patterns, twelve basic forms of Japanese verbs, and a Japanese morphophonemic process called “音便 (onbin)” by investigating 304 regular verbs and 2 irregular verbs. Among the several …

Disambiguating Company Names In Microblog Text Using Clustering For Online Reputation Management, Fernando Perez-Tellez, John Cardiff, Paolo Rosso, David Pinto

Articles

Twitter is used by millions of users to publish brief messages (tweets) with the purpose of sharing experiences and/or opinions about a product or service. There is a clear need for systems that can mine these messages in order to derive information about the collective thinking of twitterers (e.g. for opinion or sentiment analysis). Tweet analysis is a very important task because comments, opinions, suggestions, complaints etc. can be used for marketing strategies or for determining information on a company’s reputation. For this purpose, it is necessary to automatically establish whether a tweet refers to a company or not, when …

The Data Protection Credibility Crisis, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson, Orla Lynskey

Articles by Maurer Faculty

No abstract provided.

Preface To "Intertwingled: The Work And Influence Of Ted Nelson", Douglas R. Dechow, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

This is the preface to "Intertwingled: The Work and Influence of Ted Nelson", which examines and honors the work and influence of the computer visionary and re-imagines its meaning for the future. Emerging from a conference held in 2014 at Chapman University, it includes contributions from world-renowned computer scientists and media figures.

The full text of this book is available on an open access basis at Springer.

The blog for the Intertwingled Conference can be read here.

Adding Temporal Intention Dynamics To Goal Modeling: A Position Paper, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models for early phase requirements enable modelers to elicit stakeholders' intentions, analyze dependencies and select preferred alternatives. Standard analysis techniques provide options for analysis of static goal models but do not consider the dynamic environment that the model represents and do not evaluate the intentions over time. In this position paper, we illustrate that goal model analysis for early phase requirements can be improved by explicitly considering the intention dynamics of a potential system across multiple time scales.

Manipulating And Controlling For Personality Effects On Visualization Tasks, Alvitta Ottley, R. Jordan Crouser, Caroline Ziemkiewicz, Remco Chang

Computer Science: Faculty Publications

Researchers in human–computer interaction and visualization have recently been challenged to develop a better understanding of users’ underlying cognitive processes in order to improve system design and evaluation. While existing studies lay a critical foundation for understanding the role of cognitive processes and individual differences in visualization, concretizing the intuition that each user experiences a visual interface through an individual cognitive lens is only half the battle. In this article, we investigate the impact of manipulating users’ personality on observed behavior when using a visualization. In a targeted study, we demonstrate that personality priming can result in changes in behavior …

Geographic Relevance For Travel Search: The 2014-2015 Harvey Mudd College Clinic Project For Expedia, Inc., Hannah Long

Scripps Senior Theses

The purpose of this Clinic project is to help Expedia, Inc. expand the search capabilities it offers to its users. In particular, the goal is to help the company respond to unconstrained search queries by generating a method to associate hotels and regions around the world with the higher-level attributes that describe them, such as “family- friendly” or “culturally-rich.” Our team utilized machine-learning algorithms to extract metadata from textual data about hotels and cities. We focused on two machine-learning models: decision trees and Latent Dirichlet Allocation (LDA). The first appeared to be a promising approach, but would require more resources …

Whole-Lake Primary Production Calculator, Colin D. Leong

Browse all Theses and Dissertations

This work describes an implementation of a model for estimation of both benthic and phytoplanktonic primary production in lakes. The web application makes use of interpolation techniques to allow estimates of primary production using values for photosynthesis/irradiance parameters at only 5 depths. These estimates compare favorably in accuracy with estimates using values listed at over one hundred depths. Validation of the implementation was done by comparison with primary production results from the Northern Temperate Lakes Long Term Ecological Research database.

The Design, Implementation, And Refinement Of Wait-Free Algorithms And Containers, Steven Feldman

Electronic Theses and Dissertations

My research has been on the development of concurrent algorithms for shared memory systems that provide guarantees of progress. Research into such algorithms is important to developers implementing applications on mission critical and time sensitive systems. These guarantees of progress provide safety properties and freedom from many hazards, such as dead-lock, live-lock, and thread starvation. In addition to the safety concerns, the fine-grained synchronization used in implementing these algorithms promises to provide scalable performance in massively parallel systems. My research has resulted in the development of wait-free versions of the stack, hash map, ring buffer, vector, and a multi-word compare-and-swap …

Changing Cpu Frequency In Comd Proxy Application Offloaded To Intel Xeon Phi Co-Processors, Gary Lawson, Masha Sosonkina, Yuzhong Shen

Computational Modeling & Simulation Engineering Faculty Publications

Obtaining exascale performance is a challenge. Although the technology of today features hardware with very high levels of concurrency, exascale performance is primarily limited by energy consumption. This limitation has lead to the use of GPUs and specialized hardware such as many integrated core (MIC) co-processors and FPGAs for computation acceleration. The Intel Xeon Phi co-processor, built upon the MIC architecture, features many low frequency, energy efficient cores. Applications, even those which do not saturate the large vector processing unit in each core, may benefit from the energy-efficient hardware and software of the Xeon Phi. This work explores the energy …

The Module Isomorphism Problem Reconsidered, Peter A. Brooksbank

Faculty Journal Articles

Algorithms to decide isomorphism of modules have been honed continually over the last 30 years, and their range of applicability has been extended to include modules over a wide range of rings. Highly efficient computer implementations of these algorithms form the bedrock of systems such as GAP and MAGMA, at least in regard to computations with groups and algebras. By contrast, the fundamental problem of testing for isomorphism between other types of algebraic structures -- such as groups, and almost any type of algebra -- seems today as intractable as ever. What explains the vastly different complexity status of the …

Large-Scale Geometric Data Decomposition, Processing And Structured Mesh Generation, Wuyi Yu

LSU Doctoral Dissertations

Mesh generation is a fundamental and critical problem in geometric data modeling and processing. In most scientific and engineering tasks that involve numerical computations and simulations on 2D/3D regions or on curved geometric objects, discretizing or approximating the geometric data using a polygonal or polyhedral meshes is always the first step of the procedure. The quality of this tessellation often dictates the subsequent computation accuracy, efficiency, and numerical stability. When compared with unstructured meshes, the structured meshes are favored in many scientific/engineering tasks due to their good properties. However, generating high-quality structured mesh remains challenging, especially for complex or large-scale …

Combinatorially Interpreting Generalized Stirling Numbers, John Engbers, David Galvin, Justin Hilyard

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.

Exponentially Increasing Incidences Of Cutaneous Malignant Melanoma In Europe Correlate With Low Personal Annual Uv Doses And Suggests 2 Major Risk Factors, Stephen Merrill, Samira Ashrafi, Madhan Subramanian, Dianne E. Godar

Mathematics, Statistics and Computer Science Faculty Research and Publications

For several decades the incidence of cutaneous malignant melanoma (CMM) steadily increased in fair-skinned, indoor-working people around the world. Scientists think poor tanning ability resulting in sunburns initiate CMM, but they do not understand why the incidence continues to increase despite the increased use of sunscreens and formulations offering more protection. This paradox, along with lower incidences of CMM in outdoor workers, although they have significantly higher annual UV doses than indoor workers have, perplexes scientists. We found a temporal exponential increase in the CMM incidence indicating second-order reaction kinetics revealing the existence of 2 major risk factors. From epidemiology …

The Transmuted Exponentiated Generalized-G Family Of Distributions, Haitham M. Yousof, Ahmed Z. Afify, Morad Alizadeh, Nadeem Shafique Butt, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce a new class of continuous distributions called the transmuted exponentiated generalized-G family which extends the exponentiated generalized-G class introduced by Cordeiro et al. (2013). We provide some special models for the new family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Rényi and Shannon entropies, order statistics and probability weighted moments are derived. The estimation of the model parameters is performed by maximum likelihood. The flexibility of the proposed family is illustrated by means of an applications to real dataset.