Physical Sciences and Mathematics Commons^™

The European Court Of Human Rights Ruling Against Britain's Policy Of Keeping Fingerprints & Dna Samples Of Criminal Suspects, K. Michael, Clive Harfield

Clive Harfield

In England and Wales, the Police and Criminal Evidence Act 1984 (the PACE) contained powers for the taking of fingerprints, and samples in the form of deoxyribonucleic acid (DNA). In 2001, Section 64(1A) of the PACE was substituted with Section 82 of the Criminal Justice and Police Act. The change to legislation meant that a suspect of a crime would have their fingerprints and samples permanently stored on the police national computer (PNC) even after having been acquitted. This paper critically analyses the circumstances of the landmark case of S. AND MARPER V. THE UNITED KINGDOM in two different contexts …

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Katina On Right Path To Test Tracking Technology, Courtney Trenwith, K. Michael

Professor Katina Michael

No abstract provided.

Towards Extending The Equilibrium Of Discrimination In The Internet To Its Fringes, Matthias Bärwolff

Matthias Bärwolff

The core insight to the history of the dynamics of limitations, restrictions, and discriminations on the Internet is that they are largely a corollary to the futility of obtaining an entirely 'neutral' design of the Internet that is both robust and scalable. The question then is how to arrange the necessary volume of discriminations so as to obtain a design as value free as possible, for only such a design can be in line with the premise of stipulating no values other than (1) good order at large, and (2) the appreciation of the pursuit of local purposes by individuals. …

Predicting Flavonoid Ugt Regioselectivity With Graphical Residue Models And Machine Learning., Arthur Rhydon Jackson

Electronic Theses and Dissertations

Machine learning is applied to a challenging and biologically significant protein classification problem: the prediction of flavonoid UGT acceptor regioselectivity from primary protein sequence. Novel indices characterizing graphical models of protein residues are introduced. The indices are compared with existing amino acid indices and found to cluster residues appropriately. A variety of models employing the indices are then investigated by examining their performance when analyzed using nearest neighbor, support vector machine, and Bayesian neural network classifiers. Improvements over nearest neighbor classifications relying on standard alignment similarity scores are reported.

Returns To Selecting Value Stocks In Australia – The Aby Filters, Bruce Vanstone, Tobias Hahn, Gavin Finnie

Bruce Vanstone

The development of the Financial Crisis throughout 2008 and into 2009 has caused many fund managers to question their Growth based investment models. Interest appears to be again rekindled in the traditional Value based models, where investment decisions are based on sound company fundamentals rather than abstract future growth expectations. This paper reviews a specific set of value based filters for selecting undervalued stocks which appeared in a series of papers published soon after the 2000 Dot-Com debacle. This paper documents the performance of these filters in the Australian stockmarket.

With Words That Last, Sean Nicholls, Leesha Mckenny, M.G. Michael, K. Michael

M. G. Michael

No abstract provided.

With Words That Last, Sean Nicholls, Leesha Mckenny, M.G. Michael, K. Michael

Professor Katina Michael

No abstract provided.

An Investigation Into Rewriting A Security Policy For Loreto College, Paul M. Mwai

Regis University Student Publications (comprehensive collection)

Computers as well as the networking environments in which they operate have evolved into highly sophisticated and complex systems. The intricacy of these systems and especially the relationship between them forms the greatest area of vulnerabilities for organizations. (Whitman and Mattord, 2004) Information needs to be transmitted to and from the organization, and thus may be vulnerable within certain stages along the communications line. If at any stage of the process, the information is compromised, it could have a negative impact on the entire organization. Protective measures such as disaster recover plans, encryption/ decryption, and information system security controls, can …

Realizing The Technical Advantages Of Star Transformation, Karen L. Darling

Regis University Student Publications (comprehensive collection)

Data warehousing and business intelligence go hand in hand, each gives the other purpose for development, maintenance and improvement. Both have evolved over a few decades and build upon initial development. Management initiatives further drive the need and complexity of business intelligence, while in turn expanding the end user community so that business change, results and strategy are affected at the business unit level. The literature, including a recent business intelligence user survey, demonstrates that query performance is the most significant issue encountered. Oracle's data warehouse 10g.2 is examined with improvements to query optimization via "best practice" through Star Transformation. …

Optimal Cryptographic Hardness Of Learning Monotone Functions, Dana Dachman-Soled, Homin K. Lee, Tal Malkin, Rocco A. Servedio, Andrew Wan, Hoeteck Wee

Publications and Research

Over the years a range of positive algorithmic results have been obtained for learning various classes of monotone Boolean functions from uniformly distributed random examples. Prior to our work, however, the only negative result for learning monotone functions in this model has been an information-theoretic lower bound showing that certain super-polynomial-size monotone circuits cannot be learned to accuracy 1/2+w(log n/ p n) (Blum, Burch, and Langford, FOCS’98). This is in contrast with the situation for nonmonotone functions, where a wide range of cryptographic hardness results establish that various “simple” classes of polynomial-size circuits are not learnable by polynomial-time algorithms.

In …

Scalable Multi-Core Model Checking Fairness Enhanced Systems, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Rapid development in hardware industry has brought the prevalence of multi-core systems with shared-memory, which enabled the speedup of various tasks by using parallel algorithms. The Linear Temporal Logic (LTL) model checking problem is one of the difficult problems to be parallelized or scaled up to multi-core. In this work, we propose an on-the-fly parallel model checking algorithm based on the Tarjan’s strongly connected components (SCC) detection algorithm. The approach can be applied to general LTL model checking or with different fairness assumptions. Further, it is orthogonal to state space reduction techniques like partial order reduction. We enhance our PAT …

Research In Semantic Web And Information Retrieval: Trust, Sensors, And Search, Krishnaprasad Thirunarayan

Kno.e.sis Publications

No abstract provided.

Identifying Interesting Instances For Probabilistic Skylines, Yinian Qi, Mikhail J. Atallah

Department of Computer Science Technical Reports

No abstract provided.

Large-Scale Distributed Coalition Formation, Daniel R. Karrels

Theses and Dissertations

The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the …

Bisecting Document Clustering Using Model-Based Methods, Aaron Samuel Davis

Theses and Dissertations

We all have access to large collections of digital text documents, which are useful only if we can make sense of them all and distill important information from them. Good document clustering algorithms that organize such information automatically in meaningful ways can make a difference in how effective we are at using that information. In this paper we use model-based document clustering algorithms as a base for bisecting methods in order to identify increasingly cohesive clusters from larger, more diverse clusters. We specifically use the EM algorithm and Gibbs Sampling on a mixture of multinomials as the base clustering algorithms …

Interactive Football Summarization, Brandon B. Moon

Theses and Dissertations

Football fans do not have the time to watch every game in its entirety and need an effective solution that summarizes them the story of the game. Human-generated summaries are often too short, requiring time and resources to create. We utilize the advantages of Interactive TV to create an automatic football summarization service that is cohesive, provides context, covers the necessary plays, and is concise. First, we construct a degree of interest function that ranks each play based on detailed, play-by-play game events as well as viewing statistics collected from an interactive viewing environment. This allows us to select the …

Successful And Abandoned Sourceforge.Net Projects In The Initiation Stage, Charles Schweik

National Center for Digital Government

[first paragraph] Chapter 6 provided an open source project success and abandonment dependent variable. Chapter 7 described data available in the Sourceforge.net repository and linked these data to various independent variable concepts and hypotheses presented in the theoretical part of this book. Chapter 7 also described the Classification Tree and Random Forest statistical approaches we use in this and the following chapter. This chapter presents the results of the Classification Tree analysis for successful and abandoned projects in the Initiation Stage, which in Chapter 3 (Figure 3.2), we defined as the period before and up to the time when a …

The Dependent Variable: Defining Open Source "Success" And "Abandonment" Using Sourceforge.Net Data, Charles Schweik

National Center for Digital Government

[first paragraph] From the very beginning of this research project, we understood that we needed to define what success meant in open source so that we could use that definition to create a dependent variable for our empirical studies. Does success mean a project has developed high quality software, or does it mean that the software is widely used? How might extremely valuable software that is used by only a few people, such as software for charting parts of the human genome, fit into this definition? In this chapter, we establish a robust success and abandonment measure that satisfies these …

Mri: Acquisition Of A High Performance Cluster For The University Of Maine Scientific Grid Portal, Phillip M. Dickens, Yifeng Zhu, Bruce E. Segee, James L. Fastook, Sudarshan S. Chawathe

University of Maine Office of Research Administration: Grant Reports

This project, acquiring a cluster to establish a scientific grid portal in Maine, aims to enable projects requiring large datasets. The work makes available to the wider community results such as widely-used whole-ice sheet models, tools for climate change research, prototype versions of object-based caching system (bundled with MPI-IO implementation developed at Argonne National Lab), the data management system, real-time animations, videos, etc. Additionally, the portal provides the larger community the compute power, storage capacity, and rendering engine to execute very high-resolution models, and receive animations and other visualized information in real time.

Broader Impact: The infrastructure enhances understanding of …

Fused Visible And Infrared Video For Use In Wilderness Search And Rescue, Dennis Eggett, Michael A. Goodrich, Bryan S. Morse, Nathan Rasmussen

Faculty Publications

Mini Unmanned Aerial Vehicles (mUAVs) have the potential to assist Wilderness Search and Rescue groups by providing a bird’s eye view of the search area. This paper proposes a method for augmenting visible-spectrum searching with infrared sensing in order to make use of thermal search clues. It details a method for combining the color and heat information from these two modalities into a single fused display to reduce needed screen space for remote field use. To align the video frames for fusion, a method for simultaneously pre-calibrating the intrinsic and extrinsic parameters of the cameras and their mount using a …

Noninvasive Estimation Of Pulmonary Artery Pressure Using Heart Sound Analysis, Aaron W. Dennis

Theses and Dissertations

Right-heart catheterization is the most accurate method for estimating pulmonary artery pressure (PAP). Because it is an invasive procedure it is expensive, exposes patients to the risk of infection, and is not suited for long-term monitoring situations. Medical researchers have shown that PAP influences the characteristics of heart sounds. This suggests that heart sound analysis is a potential noninvasive solution to the PAP estimation problem. This thesis describes the development of a prototype system, called PAPEr, which estimates PAP noninvasively using heart sound analysis. PAPEr uses patient data with machine learning algorithms to build models of how PAP affects heart …

Development And Implementation Of High-Throughput Snpgenotyping In Barley, Serdar Bozdag, Timothy J. Close, Prasanna R. Bhat, Stefano Lonardi, Yonghui Wu, Nils Rostoks, Luke Ramsay, Arnis Druka, Nils Stein, Jan T. Svensson, Steve Wanamaker, Mikeal L. Roose, Matthew J. Moscou, Shiaoman Chao, Rajeev K. Varshney, Peter Szucs, Kazuhiro Sato, Patrick M. Hayes, David E. Matthews, Andris Kleinhofs, Gary J. Muehlbauer, Joseph Deyoung, David F. Marshall, Kavitha Madishetty, Raymond D. Fenton, Pascal Condamine, Andreas Graner, Robbie Waugh

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background

High density genetic maps of plants have, nearly without exception, made use of marker datasets containing missing or questionable genotype calls derived from a variety of genic and non-genic or anonymous markers, and been presented as a single linear order of genetic loci for each linkage group. The consequences of missing or erroneous data include falsely separated markers, expansion of cM distances and incorrect marker order. These imperfections are amplified in consensus maps and problematic when fine resolution is critical including comparative genome analyses and map-based cloning. Here we provide a new paradigm, a high-density consensus genetic map of …

Biological Sequence Simulation For Testing Complex Evolutionary Hypotheses: Indel-Seq-Gen Version 2.0, Cory L. Strope

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Reconstructing the evolutionary history of biological sequences will provide a better understanding of mechanisms of sequence divergence and functional evolution. Long-term sequence evolution includes not only substitutions of residues but also more dynamic changes such as insertion, deletion, and long-range rearrangements. Such dynamic changes make reconstructing sequence evolution history difficult and affect the accuracy of molecular evolutionary methods, such as multiple sequence alignments (MSAs) and phylogenetic methods. In order to test the accuracy of these methods, benchmark datasets are required. However, currently available benchmark datasets have limitations in their sizes and evolutionary histories of the included sequences are unknown. These …

Comparison Of Threshold Selection Methods For Microarray Gene Co-Expression Matrices, Bhavesh R. Borate, Elissa J. Chesler, Michael A. Langston, Arnold M. Saxton, Brynn H. Voy

Faculty Publications and Other Works -- EECS

Abstract

Background

Network and clustering analyses of microarray co-expression correlation data often require application of a threshold to discard small correlations, thus reducing computational demands and decreasing the number of uninformative correlations. This study investigated threshold selection in the context of combinatorial network analysis of transcriptome data.

Findings

Six conceptually diverse methods - based on number of maximal cliques, correlation of control spots with expressed genes, top 1% of correlations, spectral graph clustering, Bonferroni correction of p-values, and statistical power - were used to estimate a correlation threshold for three time-series microarray datasets. The validity of thresholds was tested by …

Integrating Information Theory Measures And A Novel Rule-Set-Reduction Tech-Nique To Improve Fuzzy Decision Tree Induction Algorithms, Nael Mohammed Abu-Halaweh

Computer Science Dissertations

Machine learning approaches have been successfully applied to many classification and prediction problems. One of the most popular machine learning approaches is decision trees. A main advantage of decision trees is the clarity of the decision model they produce. The ID3 algorithm proposed by Quinlan forms the basis for many of the decision trees’ application. Trees produced by ID3 are sensitive to small perturbations in training data. To overcome this problem and to handle data uncertainties and spurious precision in data, fuzzy ID3 integrated fuzzy set theory and ideas from fuzzy logic with ID3. Several fuzzy decision trees algorithms and …

Erratum: Fast Incremental Mining Of Web Sequential Patterns With Plwap Tree (Data Mining And Knowledge Discovery Doi: 10.1007/S10618-009-0133-6), C. I. Ezeife, Yi Liu

Computer Science Publications

No abstract provided.

Biological Simulations And Biologically Inspired Adaptive Systems, Edgar Alfredo Duenez-Guzman

Doctoral Dissertations

Many of the most challenging problems in modern science lie at the interface of several fields. To study these problems, there is a pressing need for trans-disciplinary research incorporating computational and mathematical models. This dissertation presents a selection of new computational and mathematical techniques applied to biological simulations and problem solving: (i) The dynamics of alliance formation in primates are studied using a continuous time individual-based model. It is observed that increasing the cognitive abilities of individuals stabilizes alliances in a phase transition-like manner. Moreover, with strong cultural transmission an egalitarian regime is established in a few generations. (ii) A …