Physical Sciences and Mathematics 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 …

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 …

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 …

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 …

Performance Comparison Of Evolutionary Algorithms For Airfoil Design, Marcus Randall, Tim Rawlins, Andrew Lewis, Timoleon Kipouros

Marcus Randall

Different evolutionary algorithms, by their very nature, will have different search trajectory characteristics. Understanding these particularly for real world problems gives researchers and practitioners valuable insights into potential problem domains for the various algorithms, as well as an understanding for potential hybridisation. In this study, we examine three evolutionary techniques, namely, multi-objective particle swarm optimisation, extremal optimisation and tabu search. A problem that is to design optimal cross sectional areas of airfoils that maximise lift and minimise drag, is used. The comparison analyses actual parameter values, rather than just objective function values and computational costs. It reveals that the three …

Proceedings Of Naacl Hlt 2009: Short Papers , Pages 157–160, Boulder, Colorado, June 2009. C 2009 Association For Computational Linguistics Answer Credibility: A Language Modeling Approach To Answer Validation, Protima Banerjee, Hyoil Han

Hyoil Han

Answer Validation is a topic of significant interest within the Question Answering community. In this paper, we propose the use of language modeling methodologies for Answer Validation, using corpus-based methods that do not require the use of external sources. Specifically, we propose a model for Answer Credibility which quantifies the reliability of a source document that contains a candidate answer and the Question’s Context Model.

Metalogic Notes, Saverio Perugini

Saverio Perugini

A collection of notes, formulas, theorems, postulates and terminology in symbolic logic, syntactic notions, semantic notions, linkages between syntax and semantics, soundness and completeness, quantified logic, first-order theories, Goedel's First Incompleteness Theorem and more.

Statistics Notes, Saverio Perugini

Saverio Perugini

A collection of terms, definitions, formulas and explanations about statistics.

Query Analyzer And Manager For Complex Event Processing As A Service, Wilson Higashino, Cedric Eichler, Miriam A M Capretz, Thierry Monteil, M. Beatriz F. Toledo, Patricia Stolf

Wilson A Higashino

Complex Event Processing (CEP) is a set of tools and techniques that can be used to obtain insights from high-volume, high-velocity continuous streams of events. CEP-based systems have been adopted in many situations that require prompt establishment of system diagnostics and execution of reaction plans, such as in monitoring of complex systems. This article describes the Query Analyzer and Manager (QAM) module, a first effort toward the development of a CEP as a Service (CEPaaS) system. This module is responsible for analyzing user-defined CEP queries and for managing their execution in distributed cloud-based environments. Using a language-agnostic internal query representation, …

Evaluation Of Particle Swarm Optimization Applied To Grid Scheduling, Wilson Higashino, Miriam Capretz, M. Beatriz Toledo

Wilson A Higashino

The problem of scheduling independent users’ jobs to resources in Grid Computing systems is of paramount importance. This problem is known to be NP-hard, and many techniques have been proposed to solve it, such as heuristics, genetic algorithms (GA), and, more recently, particle swarm optimization (PSO). This article aims to use PSO to solve grid scheduling problems, and compare it with other techniques. It is shown that many often-overlooked implementation details can have a huge impact on the performance of the method. In addition, experiments also show that the PSO has a tendency to stagnate around local minima in high-dimensional …

Network And Energy-Aware Resource Selection Model For Opportunistic Grids, Izaias Faria, Mario Dantas, Miriam A M Capretz, Wilson Higashino

Wilson A Higashino

Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids; hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a …

Lightlda: Big Topic Models On Modest Compute Clusters, Jinhui Yuan, Fei Gao, Quirong Ho, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma

Fei Gao

When building large-scale machine learning (ML) programs, such as big topic models or deep neural nets, one usually assumes such tasks can only be attempted with industrial-sized clusters with thousands of nodes, which are out of reach for most practitioners or academic researchers. We consider this challenge in the context of topic modeling on web-scale corpora, and show that with a modest cluster of as few as 8 machines, we can train a topic model with 1 million topics and a 1-million-word vocabulary (for a total of 1 trillion parameters), on a document collection with 200 billion tokens -- a …

A Behavior-Reactive Autonomous System To Identify Pokémon Characters, Xu Cao, Bohan Zhang, Jeremy Straub, Eunjin Kim

Jeremy Straub

Pokémon is an entertainment franchise with a large fan base. This project uses well-known Pokémon characters to demonstrate the operations of a question selection system. Presented in the form of a game where the computer attempts to guess the user-selected character, the system attempts to minimize the number of questions required for this purpose by identifying questions that most constrain the decision space. The decision making process is refined based on actual user behavior.

Assessment Of The Impact Of Clothing And Environmental Conditions On Visible Light 3d Scanning, Pann Ajjimaporn, Jeremy Straub, Scott Kerlin

Jeremy Straub

The quality of models produced by visible light 3D scanners is influenced by multiple factors. To max-imize model accuracy and detail levels, the correct combination of lighting texture, subject posture and software usage must be selected. The work described herein has been performed to measure the effect of different lighting and envi-ronmental conditions on human 3D scanning results.

Work Done On The Operating Software For Openorbiter, Dayln Limesand, Timothy Whitney, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter Program aims to develop a tem-plate for a CubeSat spacecraft that can be used world-wide to reduce spacecraft development costs1. Unlike other approaches, which may require $50,000 in upfront hardware costs2 or $250,000 in design expenses2, an OPEN-class spacecraft can be built with a parts budget of under $5,0003. This aims to enable low-cost educa-tional missions and missions in developing regions4.

Theory Identity: A Machine-Learning Approach, Kai Larsen, Dirk Hovorka, Jevin West, James Birt, James Pfaff, Trevor Chambers, Zebula Sampedro, Nick Zager, Bruce Vanstone

Bruce Vanstone

Theory identity is a fundamental problem for researchers seeking to determine theory quality, create theory ontologies and taxonomies, or perform focused theory-specific reviews and meta-analyses. We demonstrate a novel machine-learning approach to theory identification based on citation data and article features. The multi-disciplinary ecosystem of articles which cite a theory's originating paper is created and refined into the network of papers predicted to contribute to, and thus identify, a specific theory. We provide a 'proof-of-concept' for a highly-cited theory. Implications for crossdisciplinary theory integration and the identification of theories for a rapidly expanding scientific literature are discussed.

Scheduling Algorithm Development For An Open Source Software Spacecraft, Calvin Bina, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter project at the University of North Dakota is working to develop a set of designs for a CubeSat class spacecraft as well as a working, modular collection of open source code that can be used by other CubeSat projects as a starting point for development. The availability of these designs and this codebase should foster accelerated development for other CubeSat projects, allowing those projects to focus their effort on their own application area, instead of reinventing the proverbial wheel. One aspect of this is to implement a task scheduler which will run on a Raspberry Pi flight computer …

Identifying Key Variables And Interactions In Statistical Models Of Building Energy Consumption Using Regularization, David Hsu

David Hsu

Statistical models can only be as good as the data put into them. Data about energy consumption continues to grow, particularly its non-technical aspects, but these variables are often interpreted differently among disciplines, datasets, and contexts. Selecting key variables and interactions is therefore an important step in achieving more accurate predictions, better interpretation, and identification of key subgroups for further analysis.

This paper therefore makes two main contributions to the modeling and analysis of energy consumption of buildings. First, it introduces regularization, also known as penalized regression, for principled selection of variables and interactions. Second, this approach is demonstrated by …

Nanosatellite Scheduling Using A Dictionary Module And A ‘Useful Trick’ With Coded Unsigned Integers, Monilito Castro, Jeremy Straub

Jeremy Straub

Schedulers for small spacecraft must satisfy the dual requirement of generating very efficient schedules while concurrently minimizing the resources required to create the schedule. This paper proposes a technique for searching for tasks that can be utilized to fill particular schedule locations. This approach is based on a modular system for storing important variables. This modular system has three important variables: t0, x0 and y0. The variable y is latitude and x is longitude. Time variable t is an integer and each unit represents a time quantum. They are related to each other by three functions Ft, Fx, and Fy. …

Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …

On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Zhongmei Yao

Previous analytical studies [12], [18] of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared to uniform selection of neighbors. In fact, the second strategy based on random walks on age-weighted graphs demonstrates that for lifetimes with infinite variance, the system …

Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang

Zhongmei Yao

Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …

Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

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 …

Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

Existing methods of measuring lifetimes in P2P systems usually rely on the so-called Create-BasedMethod (CBM), which divides a given observation window into two halves and samples users ldquocreatedrdquo in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we first derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent tradeoff …

Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov

Zhongmei Yao

Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work has shown that direct sampling of user lifetimes may lead to certain bias (arising from missed peers and round-off inconsistencies) and proposed a technique that estimates lifetimes based on sampled residuals. In this paper, however, we show that under non-stationary arrivals, which are often present in real systems, residual-based sampling does not correctly reconstruct user lifetimes and suffers a varying degree of bias, which in some cases makes estimation completely impossible. We overcome this problem using two contributions: a …

Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Zhongmei Yao

Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers frequently rely on host scanning for reconnaissance leading to penetration, IDS is often tasked with detecting scans and preventing them. However, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast scan techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a simple analytical model for the window-expiration rules of popular IDS tools (i.e., Snort and Bro) and utilize a …

In-Degree Dynamics Of Large-Scale P2p Systems, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov

Zhongmei Yao

This paper builds a complete modeling framework for understanding user churn and in-degree dynamics in unstructured P2P systems in which each user can be viewed as a stationary alternating renewal process. While the classical Poisson result on the superposition of n stationary renewal processes for n→∞ requires that each point process become sparser as n increases, it is often difficult to rigorously show this condition in practice. In this paper, we first prove that despite user heterogeneity and non-Poisson arrival dynamics, a superposition of edge-arrival processes to a live user under uniform selection converges to a Poisson process when …

Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao

Zhongmei Yao

Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …

Node Isolation Model And Age-Based Neighbor Selection In Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov

Zhongmei Yao

Previous analytical studies of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared with uniform selection of neighbors. In fact, the second strategy based on random walks on age-proportional graphs demonstrates that, for lifetimes with infinite variance, the system monotonically increases …