Computer Sciences Commons^™

Detection Of Diabetic Foot Ulcers Using Svm Based Classification, Lei Wang, Peder Pedersen, Diane Strong, Bengisu Tulu, Emmanuel Agu, Qian He, Ronald Ignotz, Raymond Dunn, David Harlan, Sherry Pagoto

Emmanuel O. Agu

Diabetic foot ulcers represent a significant health issue, for both patients’ quality of life and healthcare system costs. Currently, wound care is mainly based on visual assessment of wound size, which suffers from lack of accuracy and consistency. Hence, a more quantitative and computer-based method is needed. Supervised machine learning based object recognition is an attractive option, using training sample images with boundaries labeled by experienced clinicians. We use forty sample images collected from the UMASS Wound Clinic by tracking 8 subjects over 6 months with a smartphone camera. To maintain a consistent imaging environment and facilitate the capture process …

Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks, Akshaye Dhawan, Michelle Tanco, Aaron Yeiser

Mathematics and Computer Science Faculty Publications

A Connected Dominating Set (CDS) of a graph representing a Wireless Sensor Network can be used as a virtual backbone for routing through the network. Since the sensors in the network are constrained by limited battery life, we desire a minimal CDS for the network, a known NP-hard problem. In this paper we present three randomized algorithms for constructing a CDS. We evaluate our algorithms using simulations and compare them to the two-hop K2 algorithm and two other greedy algorithms from the literature. After pruning, the randomized algorithms construct a CDS that are generally equivalent in size to those constructed …

Positive Influence Dominating Set Generation In Social Networks, Akshaye Dhawan, Matthew Rink

Mathematics and Computer Science Faculty Publications

Current algorithms in the Positive Influence Dominating Set (PIDS) problem domain are focused on a specific type of PIDS, the Total Positive Influence Dominating Set (TPIDS). We have developed an algorithm specifically targeted towards the non-total type of PIDS. In addition to our new algorithm, we adapted two existing TPIDS algorithms to generate PIDS. We ran simulations for all three algorithms, and our new algorithm consistently generates smaller PIDS than both existing algorithms, with our algorithm generating PIDS approximately 5% smaller than the better of the two existing algorithms.

Battle Bot Ai – Patriot Bot, James Johnston

Computer Engineering

An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.

Co-Rotational Finite Element Solid Simulation With Collisions, Patrick Riordan

Computer Science and Software Engineering

This paper is a tutorial on how to implement a deformable solid simulation with collisions based off of Matthias Mueller's Real Time Physics Course Notes. It covers the topics continuum mechanics, finite element analysis, implicit Euler integration, and handling collision.

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Computer Science Faculty Publications

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …

Multiple Instance Fuzzy Inference., Amine Ben Khalifa

Electronic Theses and Dissertations

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Fuzzy Inference Systems (MI-FIS). Fuzzy inference is a powerful modeling framework that can handle computing with knowledge uncertainty and measurement imprecision effectively. Fuzzy Inference performs a non-linear mapping from an input space to an output space by deriving conclusions from a set of fuzzy if-then rules and known facts. Rules can be identified from expert knowledge, or learned from data. In multiple instance problems, the training data …

Differentially Private Subspace Clustering, Yining Wang, Yu-Xiang Wang, Aarti Singh

Research Collection School Of Computing and Information Systems

Subspace clustering is an unsupervised learning problem that aims at grouping data points into multiple “clusters” so that data points in a single cluster lie approximately on a low-dimensional linear subspace. It is originally motivated by 3D motion segmentation in computer vision, but has recently been generically applied to a wide range of statistical machine learning problems, which often involves sensitive datasets about human subjects. This raises a dire concern for data privacy. In this work, we build on the framework of differential privacy and present two provably private subspace clustering algorithms. We demonstrate via both theory and experiments that …

Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea

Yuliya Lierler

Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, Renliang Gu, Aleksandar Dogandžić

Aleksandar Dogandžić

We develop a projected Nesterov’s proximal-gradient (PNPG) scheme for reconstructing sparse signals from compressive Poisson-distributed measurements with the mean signal intensity that follows an affine model with known intercept. The objective function to be minimized is a sum of convex data fidelity (negative log-likelihood (NLL)) and regularization terms. We apply sparse signal regularization where the signal belongs to a nonempty closed convex set within the domain of the NLL and signal sparsity is imposed using total-variation (TV) penalty. We present analytical upper bounds on the regularization tuning constant. The proposed PNPG method employs projected Nesterov’s acceleration step, function restart, and …

Skeleton Structures And Origami Design, John C. Bowers

Doctoral Dissertations

In this dissertation we study problems related to polygonal skeleton structures that have applications to computational origami. The two main structures studied are the straight skeleton of a simple polygon (and its generalizations to planar straight line graphs) and the universal molecule of a Lang polygon. This work builds on results completed jointly with my advisor Ileana Streinu. Skeleton structures are used in many computational geometry algorithms. Examples include the medial axis, which has applications including shape analysis, optical character recognition, and surface reconstruction; and the Voronoi diagram, which has a wide array of applications including geographic information systems …

Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, Xianhua Zeng, Wei Bian, Wei Liu, Jialie Shen, Dacheng Tao

Research Collection School Of Computing and Information Systems

Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary …

Extending The Teknomo-Fernandez Background Image Generation Algorithm On The Hsv Colour Space, Patricia Angela R. Abu, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strategy to produce a good background image very quickly. A previous study showed that the TF algorithm can be extended from the original 3 frames per tournament (T F 3) to T F 5 and T F 7, resulting in increased accuracies at a cost of increased processing times. In this study, we explore extending the T F 3, …

Implementing And Testing A Novel Chaotic Cryptosystem, Samuel Jackson, Scott Kerlin, Jeremy Straub

Jeremy Straub

Cryptography in the domain of small satellites is a relatively new area of research. Compared to typical desktop computers, small satellites have limited bandwidth, processing power, and battery power. Many of the current encryption schemes were developed for desktop computers and servers, and as such may be unsuitable for small satellites. In addition, most cryptographic research in the domain of small satellites focuses on hardware solutions, which can be problematic given the limited space requirements of small satellites.

This paper investigates potential software solutions that could be used to encrypt and decrypt data on small satellites and other devices with …

Prediction: The Quintessential Model Validation Test, Wayne Wakeland

Systems Science Friday Noon Seminar Series

It is essential to objectively test how well policy models predict real world behavior. The method used to support this assertion involves the review of three SD policy models emphasizing the degree to which the model was able to fit the historical outcome data and how well model-predicted outcomes matched real world outcomes as they unfolded. Findings indicate that while historical model agreement is a favorable indication of model validity, the act of making predictions without knowing the actual data, and comparing these predictions to actual data, can reveal model weaknesses that might be overlooked when all of the available …

Formal Models Of The Extension Activity Of Dna Polymerase Enzymes, Srujan Kumar Enaganti

Electronic Thesis and Dissertation Repository

The study of formal language operations inspired by enzymatic actions on DNA is part of ongoing efforts to provide a formal framework and rigorous treatment of DNA-based information and DNA-based computation. Other studies along these lines include theoretical explorations of splicing systems, insertion-deletion systems, substitution, hairpin extension, hairpin reduction, superposition, overlapping concatenation, conditional concatenation, contextual intra- and intermolecular recombinations, as well as template-guided recombination.

First, a formal language operation is proposed and investigated, inspired by the naturally occurring phenomenon of DNA primer extension by a DNA-template-directed DNA polymerase enzyme. Given two DNA strings u and v, where the shorter …

An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li

CSE Conference and Workshop Papers

In this paper, we introduce a new phylogenetic tree algorithm that generates phylogenetic trees by repeatedly inserting species one-by-one. The incremental phylogenetic tree algorithm can work on proteins or DNA sequences. Computer experiments show that the new algorithm is better than the commonly used UPGMA and Neighbor Joining algorithms.

The Effectiveness Of Using A Modified “Beat Frequent Pick” Algorithm In The First International Roshambo Tournament, Proceso L. Fernandez Jr, Sony E. Valdez, Generino P. Siddayao

Department of Information Systems & Computer Science Faculty Publications

In this study, a bot is developed to compete in the first International RoShamBo Tournament test suite. The basic “Beat Frequent Pick (BFP)” algorithm was taken from the supplied test suite and was improved by adding a random choice tailored fit against the opponent's distribution of picks. A training program was also developed that finds the best performing bot variant by changing the bot's behavior in terms of the timing of the recomputation of the pick distribution. Simulation results demonstrate the significantly improved performance of the proposed variant over the original BFP. This indicates the potential of using the core …

Functional Requirements Identification Using Item-To-Item Collaborative Filtering, Proceso L. Fernandez Jr, Reynald Jay F. Hidalgo

Department of Information Systems & Computer Science Faculty Publications

One of the most difficult tasks in the development of software is the identification of the functional requirements. A well-defined functional requirement will eventually map the success of a software project. A support tool that can recommend candidate functional requirements for a software project being developed will help software engineers to deliver the right software to the clients.
The purpose of this study is to determine whether a collection of previously developed software applications can serve as basis for the development of a model to identify functional requirements of a project to be developed. Completed software project documentations of Master …

Modeling Flood Risk For An Urban Cbd Using Ahp And Gis, Proceso L. Fernandez Jr, Generino P. Siddayao, Sony E. Valdez

Department of Information Systems & Computer Science Faculty Publications

The Central Business District (CBD) of a city is the activity center of the city, typically locating the main commercial and cultural establishments, as well as acting as the center point of the city’s transportation network. Flood risk assessment for a CBD is crucial for proper city planning and maintenance. In this study, we model the flood risk for the CBD of Tuguegarao City, which is located in northern Philippines. To accomplish this, we identified important flood-related factors whose data are either easily available or may be collected through some automated process that we developed. We then surveyed experts to …

Computational Approaches For Remote Monitoring Of Symptoms And Activities, Ferdaus Kawsar

Dissertations (1934 -)

We now have a unique phenomenon where significant computational power, storage, connectivity, and built-in sensors are carried by many people willingly as part of their life style; two billion people now use smart phones. Unique and innovative solutions using smart phones are motivated by rising health care cost in both the developed and developing worlds. In this work, development of a methodology for building a remote symptom monitoring system for rural people in developing countries has been explored. Design, development, deployment, and evaluation of e-ESAS is described. The system’s performance was studied by analyzing feedback from users. A smart phone …

Integrating Deep Learning With Correlation-Based Multimedia Semantic Concept Detection, Hsin-Yu Ha

FIU Electronic Theses and Dissertations

The rapid advances in technologies make the explosive growth of multimedia data possible and available to the public. Multimedia data can be defined as data collection, which is composed of various data types and different representations. Due to the fact that multimedia data carries knowledgeable information, it has been widely adopted to different genera, like surveillance event detection, medical abnormality detection, and many others. To fulfil various requirements for different applications, it is important to effectively classify multimedia data into semantic concepts across multiple domains. In this dissertation, a correlation-based multimedia semantic concept detection framework is seamlessly integrated with the …

A Study Of Pseudo-Periodic And Pseudo-Bordered Words For Functions Beyond Identity And Involution, Manasi Kulkarni

Electronic Thesis and Dissertation Repository

Periodicity, primitivity and borderedness are some of the fundamental notions in combinatorics on words. Motivated by the Watson-Crick complementarity of DNA strands wherein a word (strand) over the DNA alphabet \{A, G, C, T\} and its Watson-Crick complement are informationally ``identical", these notions have been extended to consider pseudo-periodicity and pseudo-borderedness obtained by replacing the ``identity" function with ``pseudo-identity" functions (antimorphic involution in case of Watson-Crick complementarity). For a given alphabet $\Sigma$, an antimorphic involution $\theta$ is an antimorphism, i.e., $\theta(uv)=\theta(v) \theta(u)$ for all $u,v \in \Sigma^{*}$ and an involution, i.e., $\theta(\theta(u))=u$ for all $u \in \Sigma^{*}$. In this thesis, …

Algorithms For Peptide Identification From Mixture Tandem Mass Spectra, Yi Liu

Electronic Thesis and Dissertation Repository

The large amount of data collected in an mass spectrometry experiment requires effective computational approaches for the automated analysis of those data. Though extensive research has been conducted for such purpose by the proteomics community, there are still remaining challenges, among which, one particular challenge is that the identification rate of the MS/MS spectra collected is rather low. One significant reason that contributes to this situation is the frequently observed mixture spectra, which result from the concurrent fragmentation of multiple precursors in a single MS/MS spectrum. However, nearly all the mainstream computational methods still take the assumption that the acquired …

Topographic Signatures Of Geodynamics, Samuel G. Roy

Electronic Theses and Dissertations

The surface of the Earth retains an imperfect memory of the diverse geodynamic, climatic, and surface transport processes that cooperatively drive the evolution of Earth. In this thesis I explore the potential of using topographic analysis and landscape evolution models to unlock past and/or present evidence for geodynamic activity. I explore the potential isolated effects of geodynamics on landscape evolution, particularly focusing on two byproducts of tectonic strain: rock displacement and damage. Field evidence supports a strong correlation between rock damage and erodibility, and a numerical sensitivity analysis supports the hypothesis that an order of magnitude weakening in rock, well …

Testing A Novel Cryptosystem For Use In Securing Small Satellite Communications, Samuel Jackson, Scott Kerlin, Jeremy Straub

Jeremy Straub

Cryptography in the domain of Small Satellites is a topic of growing importance. While large satellites are likely to have the hardware requirements to run common cryptographic algorithms, small satellites are extremely limited in both hardware capabilities, which limits the speed and security of cryptosystems implemented in software, and available physical space, which limits the ability to include cryptosystems implemented in hardware. However, small satellites are growing in popularity, and as such securing communications becomes a necessity for some. The Department of Defense is exploring the possibility of using CubeSats, a type of small satellite, in their operations, as are …

Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni

Dissertations and Theses

This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on …

Tweakable Ciphers: Constructions And Applications, Robert Seth Terashima

Dissertations and Theses

Tweakable ciphers are a building block used to construct a variety of cryptographic algorithms. Typically, one proves (via a reduction) that a tweakable-cipher-based algorithm is about as secure as the underlying tweakable cipher. Hence improving the security or performance of tweakable ciphers immediately provides corresponding benefits to the wide array of cryptographic algorithms that employ them. We introduce new tweakable ciphers, some of which have better security and others of which have better performance than previous designs. Moreover, we demonstrate that tweakable ciphers can be used directly (as opposed to as a building block) to provide authenticated encryption with associated …

The Autoproof Verifier: Usability By Non-Experts And On Standard Code, Carlo A. Furia, Christopher M. Poskitt, Julian Tschannen

Research Collection School Of Computing and Information Systems

Formal verification tools are often developed by experts for experts; as a result, their usability by programmers with little formal methods experience may be severely limited. In this paper, we discuss this general phenomenon with reference to AutoProof: a tool that can verify the full functional correctness of object-oriented software. In particular, we present our experiences of using AutoProof in two contrasting contexts representative of non-expert usage. First, we discuss its usability by students in a graduate course on software verification, who were tasked with verifying implementations of various sorting algorithms. Second, we evaluate its usability in verifying code developed …

Sails: Hybrid Algorithm For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Computing and Information Systems

The Team Orienteering Problem with Time Windows (TOPTW) is the extended version of the Orienteering Problem where each node is limited by a given time window. The objective is to maximize the total collected score from a certain number of paths. In this paper, a hybridization of Simulated Annealing and Iterated Local Search, namely SAILS, is proposed to solve the TOPTW. The efficacy of the proposed algorithm is tested using benchmark instances. The results show that the proposed algorithm is competitive with the state-of-the-art algorithms in the literature. SAILS is able to improve the best known solutions for 19 benchmark …