Computer Sciences Commons^™

Exploring Interaction Effects In Two-Factor Studies Using The Hiddenf Package In R., Christopher Franck, Jason A. Osborne

The R Journal

In crossed, two-factor studies with one observation per factor-level combination, interaction effects between factors can be hard to detect and can make the choice of a suitable statistical model difficult. This article describes hiddenf, an R package that enables users to quantify and characterize a certain form of interaction in two-factor layouts. When effects of one factor (a) fall into two groups depending on the level of another factor, and (b) are constant within these groups, the interaction pattern is deemed "hidden additivity" because within groups, the effects of the two factors are additive, while between groups the factors …

Gmdh: An R Package For Short Term Forecasting Via Gmdh-Type Neural Network Algorithms, Osman Dag, Ceylan Yozgatligil

The R Journal

Group Method of Data Handling (GMDH)-type neural network algorithms are the heuristic self organization method for the modelling of complex systems. GMDH algorithms are utilized for a variety of purposes, examples include identification of physical laws, the extrapolation of physical fields, pattern recognition, clustering, the approximation of multidimensional processes, forecasting without models, etc. In this study, the R package GMDH is presented to make short term forecasting through GMDH-type neural network algorithms. The GMDH package has options to use different transfer functions (sigmoid, radial basis, polynomial, and tangent functions) simultaneously or separately. Data on cancer death rate of Pennsylvania from …

The R Journal (August 2016) 8(1): Complete Issue, The R Foundation

The R Journal

Editorial, Michael Lawrence

Contributed Research Articles

metaplus: An R Package for the Analysis of Robust Meta-Analysis and Meta-Regression, Ken J. Beath

Gender Prediction Methods Based on First Names with genderizeR, Kamil Wais

Conditional Fractional Gaussian Fields with the Package FieldSim, Alexandre Brouste, Jacques Istas, and Sophie Lambert-Lacroix

rTableICC: An R Package for Random Generation of 22K and RC Contingency Tables, Haydar Demirhan

Maps, Coordinate Reference Systems and Visualising Geographic Data with mapmisc, Patrick E. Brown

Variable Clustering in High-Dimensional Linear Regression: The R Package clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, and Mickael Canouil

Stylometry with R: A Package for …

Siguria Në Cloud, Alborita Mehana

Theses and Dissertations

Cloud computing është një platform e vërtetuar për sigurimin e ofrimit të shërbimeve biznesore apo shërbimet e IT konsumatorëve përmes Internetit. Kështu që cloud computing është plotësisht teknologji e bazuar në internet ku të dhënat e klientit janë të ruajtura dhe ndara në qendra të të dhënave të një ofruesi të shërbimeve si: Google, Amazon, Salesforce.com dhe Microsoft etj. Sidoqoftë, cloud computing prezenton një nivel të shtuar të rrezikut sepse shërbimet thelbësore janë shpesh të transferuara tek pala e tretë, e cila e bënë më të vështirë ruajtjen e sigurisë dhe privatësin, mbështetjen e të dhënave dhe disponushmërinë e shërbimit, …

Sistemi I Integruar I Informimit Shëndetësor Në Kosovë, Emira Halimi

Theses and Dissertations

Informimi mbi shёndetin ёshtё shume i rëndësishëm. Informatat, përkatësisht të dhënat e strukturuara kanë rëndësi të lartë në diagnostifikimin, përkatësisht në vendimarrjen për të trajtuar pacientët nga perspektiva të ndryshme.

Falë evoluimit të teknologjisë informative, e-Health ka patur një ngritje të theksuar viteve të fundit, që synon të përmirësojë kujdesin shëndetësor rrënjësisht me fascilitimin e teknologjisë aktuale. Qëllimet dhe prioritetet në fushën e e-Health janë fillimi i shëndetshëm i jetës dhe mundësimi i qytetarëve që të bëjnë zgjedhjet e shëndetëshme në jetën e tyre të përditshme duke i mundësuar çasje më cilësore në kujdesin shëndetësor, efekte të dobishme në punën …

Teknologjitë E Cloud Storage Dhe Vlera E Tyre Për Bizneset, Mensur Latifi

Theses and Dissertations

Teknologjia informative është industri në rritje të vazhdueshme dhe të shpejtë. Është pjesë shumë e rëndësishme e përditshmërisë sonë dhe si e tillë paraqet interes global. Risitë e reja që dalin nga kjo industri kanë ndikim të madh në mbarë shoqërinë. Në shekullin në të cilin po jetojmë një nga risitë më të mëdha në mos më e madhja është e ashtuquajtura “Cloud”.

Ky kërkim do të shtjellojë teknologjitë Cloud dhe përdorimin e tyre nga kompanitë e ndryshme, anvantazhet dhe disavantazhet e përdorimit. Do të flitet më shumë për benefitet që nxjerrin bizneset apo kompanitë e ndryshme nga teknologjia Cloud, …

Dizajnimi Dhe Implementimi I Rrjetave Kompjuterike Në Kompani Të Vogla Dhe Të Mesme, Uran Kastrati

Theses and Dissertations

Me digjitalizimin e shumë shërbimeve, kompanitë e ndryshme duhet të konkurojnë me rivalë të ndryshëm komercial në shpejtësi dhe shërbime cilësore.

Dizajnimi dhe implementimi i një rrjeti kompjuterik te këto kompani duke marrë parasysh parametrat e cekur më lartë, qofshin kompani të vogla apo të mesme ndihmon që të menaxhimin më të mirefillt të komunikimit si dhe shërbimeve të tyre përkatëse. Në rastin tonë, një dizajnim i tillë në kompaninë “X” mundëson që të rritet qëndrueshmërinë e informatës dhe efikasitetin e shërbimeve që ofron kjo kompani, gjithashtu lehtësohet dhe shpejtohet procesi i komunikimit në mes të filialeve të ndryshme si …

Distributed Data Intensive Computing On Graph, Upa Gupta

Computer Science and Engineering Dissertations - Archive

Distributed frameworks, such as MapReduce and Spark, have been developed by industry and research groups to analyze the vast amount of data that is being generated on a daily basis. Many graphs of interest, such as the Web graph and Social Networks, increase their size daily at an unprecedented scale and rate. To cope with this vast amount of data, researchers have been using distributed processing frameworks to analyze these graphs extensively. Most of these graph algorithms are iterative in nature, requiring repetitive distributed jobs. This dissertation presents a new design pattern for a family of iterative graph algorithms for …

Personalization And Data Relation Exploration Using Predictive Analytics For The Production And Distributed Analysis System (Panda), Mikhail Titov

Computer Science and Engineering Dissertations - Archive

Efficient data distribution among computing centers is one of the biggest challenges in large-scale scientific distributed computing systems. Such data distribution issues include: i) the rational utilization of storage and computing resources, ii) the minimization of the completion time for data processing (which requires a reduction in redundant data transfers, and intelligent allocation of processing tasks), and iii) user experience enhancement, i.e., availability and fast access to the desired data, and discovery of new relevant data. In the literature and in practice, there have been significant new approaches to the improvement of workflow management to address the above described issues, …

Toward Automated Fact Monitoring And Checking, Naeemul Hassan

Computer Science and Engineering Dissertations - Archive

Public figures such as politicians make claims about "facts" all the time. Oftentimes there are false, exaggerated and misleading claims on important topics, due to careless mistakes and even deliberate manipulation of information. With technology and modern day media helping spread information to mass audiences through all types of channels, there is a pressing need for checking the veracity of factual claims important to the public. Journalists and citizens spend a good amount of time doing that. More and more dedicated platforms and institutes are being created for fact-checking. This nascent genre of investigative reporting has become a basic feature …

Techniques For Spatio-Temporal Analysis Of Trajectory Data, Praveen Kumar Tripathi

Computer Science and Engineering Dissertations - Archive

The goal of this thesis is to develop novel techniques for the analysis of spatio-temporal trajectory data. Recent advances in tracking devices such as Global Positioning System (GPS) and mobile phones have resulted in an abundance of spatio-temporal trajectory data. Because of the importance of both the space and time dimensions in trajectory data, different analysis techniques are needed. The analysis techniques explored in this thesis involve two variations: point based analysis and trajectory based analysis. Point based analysis has been done to identify the hot spots in the trajectory dataset (hurricane data). Here we consider the trajectory data as …

Improving Cloud Middlebox Infrastructure For Online Services, Rohan S. Gandhi

Open Access Dissertations

Middleboxes are an indispensable part of the datacenter networks that provide high availability, scalability and performance to the online services. Using load balancer as an example, this thesis shows that the prevalent scale-out middlebox designs using commodity servers are plagued with three fundamental problems: (1) The server-based layer-4 middleboxes are costly and inflate round-trip-time as much as 2x by processing the packets in software. (2) The middlebox instances cause traffic detouring en route from sources to destinations, which inflates network bandwidth usage by as much as 3.2x and can cause transient congestion. (3) Additionally, existing cloud providers do not support …

Ε-Kernel Coresets For Stochastic Points, Haitao Wang, Lingxiao Huang, Jian Li, Jeff Mark Phillips

Computer Science Faculty and Staff Publications

With the dramatic growth in the number of application domains that generate probabilistic, noisy and uncertain data, there has been an increasing interest in designing algorithms for geometric or combinatorial optimization problems over such data. In this paper, we initiate the study of constructing epsilon-kernel coresets for uncertain points. We consider uncertainty in the existential model where each point's location is fixed but only occurs with a certain probability, and the locational model where each point has a probability distribution describing its location. An epsilon-kernel coreset approximates the width of a point set in any direction. We consider approximating the …

Comparison Of Experimental And Theoretical Fully Differential Cross Sections For Single Ionization Of The 2s And 2p States Of Li By O⁸⁺ Ions, Ebrahim Ghanbari-Adivi, Daniel Fischer, Natalia Ferreira, Johannes Goullon, Renate Hubele, Aaron Laforge, Michael Schulz, Don H. Madison

Physics Faculty Research & Creative Works

This paper presents a full three-dimensional (3D) comparison between experiment and theory for 24 MeV O⁸⁺ single ionization of the 2s ground state of lithium and the 2p excited state. Two theoretical approximations are examined: the three-body continuum distorted-wave (3DW) and three-body continuum distorted-wave-eikonal initial state (3DW-EIS). Normally, there is a significant difference between these two approaches and the 3DW-EIS is in much better agreement with experiment. In this case, there is very little difference between the two approaches and both are in very good agreement with experiment. For the excited 2p state, the 3D cross sections would exhibit …

Contact Process With Temporal Disorder, Hatem Barghathi, Thomas Vojta, José A. Hoyos

Physics Faculty Research & Creative Works

We investigate the influence of time-varying environmental noise, i.e., temporal disorder, on the nonequilibrium phase transition of the contact process. Combining a real-time renormalization group, scaling theory, and large scale Monte-Carlo simulations in one and two dimensions, we show that the temporal disorder gives rise to an exotic critical point. At criticality, the effective noise amplitude diverges with increasing time scale, and the probability distribution of the density becomes infinitely broad, even on a logarithmic scale. Moreover, the average density and survival probability decay only logarithmically with time. This infinite-noise critical behavior can be understood as the temporal counterpart of …

Robust Algorithms For Estimating Vehicle Movement From Motion Sensors Within Smartphones, Ilyas Ustun

Computational Modeling & Simulation Engineering Theses & Dissertations

Building sustainable traffic control solutions for urban streets (e.g., eco-friendly signal control) and highways requires effective and reliable sensing capabilities for monitoring traffic flow conditions so that both the temporal and spatial extents of congestion are observed. This would enable optimal control strategies to be implemented for maximizing efficiency and for minimizing the environmental impacts of traffic. Various types of traffic detection systems, such as inductive loops, radar, and cameras have been used for these purposes. However, these systems are limited, both in scope and in time. Using GPS as an alternative method is not always viable because of problems …

Monte Carlo Convergence Analysis For Anisotropic Sampling Power Spectra, Gurprit Singh, Wojciech Jarosz

Computer Science Technical Reports

Traditional Monte Carlo (MC) integration methods use point samples to numerically approximate the underlying integral. This approximation introduces variance in the integrated result, and this error can depend critically on the sampling patterns used during integration. Most of the well known samplers used for MC integration in graphics, e.g. jitter, Latin hypercube (n-rooks), multi-jitter, are anisotropic in nature. However, there are currently no tools available to analyze the impact of such anisotropic samplers on the variance convergence behavior of Monte Carlo integration. In this work, we propose a mathematical tool in the Fourier domain that allows analyzing the variance, and …

Generating Technology Development Paths To The Desired Future Through System Dynamics Modeling And Simulation, Hongyi Chen, Jiang Yu, Wayne Wakeland

Complex Systems Faculty Publications and Presentations

Technology foresight is usually conducted by government or industry associations and can serve to provide companies with information on critical technologies that a country or industry intends to develop in the next ten to twenty years. For individual companies to benefit from foresight results and transform them into specific technology development plans, the relationships between the desired technologies and the dynamic business environment need to be understood. In this article, an innovation diffusion model implemented via system dynamics simulation is used to operationalize the link between foresight and planning. It helps company decision makers visualize the diffusion process of the …

Leveraging Static Analysis Tools For Improving Usability Of Memory Error Sanitization Compilers, Rigel Gjomemo, Phu Huu Phung, Edmund Ballou, Kedar S. Namjoshi, V. N. Venkatakrishnan, Lenore Zuck

Computer Science Faculty Publications

Memory errors such as buffer overruns are notorious security vulnerabilities. There has been considerable interest in having a compiler to ensure the safety of compiled code either through static verification or through instrumented runtime checks. While certifying compilation has shown much promise, it has not been practical, leaving code instrumentation as the next best strategy for compilation. We term such compilers Memory Error Sanitization Compilers (MESCs). MESCs are available as part of GCC, LLVM and MSVC suites. Due to practical limitations, MESCs typically apply instrumentation indiscriminately to every memory access, and are consequently prohibitively expensive and practical to only small …

Improving The Efficiency Of Ci With Uber-Commits, Matias Waterloo

School of Computing: Dissertations, Theses, and Student Research

Continuous Integration (CI) is a software engineering practice where developers break their coding tasks into small changes that can be integrated with the shared code repository on a frequent basis. The primary objectives of CI are to avoid integration problems caused by large change sets and to provide prompt developer feedback so that if a problem is detected, it can be easily and quickly resolved. In this thesis, we argue that while keeping changes small and integrating often is a wise approach for developers, the CI server may be more efficient operating on a different scale. In our approach, the …

Tool Comparison Of Semantic Parsers, Robert Hinh

Open Access Theses

Natural Language Processing (NLP) is a vital aspect for artificial intelligence systems to achieve integration into human lives, which has been a goal for researchers in this industry. While NLP focuses on an array of problems, semantic parsing will be specifically focused on throughout this paper. These parsers have been considerably targeted for improvement through the scientific community and demand for semantic parsers that achieve high accuracy has increased. There have been many approaches developed for this specific purpose and in this paper, a deep analysis was performed to compare the performance of semantic parsing systems. The implications of this …

Hardware Accelerated Authentication System For Dynamic Time-Critical Networks, Ankush Singla

Open Access Theses

The secure and efficient operation of time-critical networks, such as vehicular networks, smart-grid and other smart-infrastructures, is of primary importance in today’s society. It is crucial to minimize the impact of security mechanisms over such networks so that the safe and reliable operations of time-critical systems are not being interfered.

Even though there are several security mechanisms, their application to smart-infrastructure and Internet of Things (IoT) deployments may not meet the ubiquitous and time-sensitive needs of these systems. That is, existing security mechanisms either introduce a significant computation and communication overhead, or they are not scalable for a large number …

Using Ubiquitous Data To Improve Smartwatches' Context Awareness, Yuankun Song

Open Access Theses

Nowadays, more and more data is being generated by various software applications, services and smart devices every second. The data contains abundant information about people’s daily lives. This research explored the possibility of improving smartwatches’ context awareness by using common ubiquitous data. The researcher developed a prototype system consisting of an Android application and a web application, and conducted an experiment where 10 participants performed several tasks with the help of a smartwatch. The result showed a significant improvement of the smartwatch’s context awareness running the prototype application, which used ubiquitous data to automatically execute proper actions according to contexts. …

Detection Of Communication Over Dnssec Covert Channels, Nicole M. Hands

Open Access Theses

Unauthorized data removal and modification from information systems represents a major and formidable threat in modern computing. Security researchers are engaged in a constant and escalating battle with the writers of malware and other methods of network intrusion to detect and mitigate this threat. Advanced malware behaviors include encryption of communications between the server and infected client machines as well as various strategies for resilience and obfuscation of infrastructure. These techniques evolve to use any and all available mechanisms. As the Internet has grown, DNS has been expanded and has been given security updates. This study analyzed the potential uses …

Monitoring Dbms Activity To Detect Insider Threat Using Query Selectivity, Prajwal B. Hegde

Open Access Theses

The objective of the research presented in this thesis is to evaluate the importance of query selectivity for monitoring DBMS activity and detect insider threat. We propose query selectivity as an additional component to an existing anomaly detection system (ADS). We first look at the advantages of working with this particular ADS. This is followed by a discussion about some existing limitations in the anomaly detection system (ADS) and how it affects its overall performance. We look at what query selectivity is and how it can help improve upon the existing limitations of the ADS. The system is then implemented …

An Anomaly-Based Intrusion Detection System Based On Artificial Immune System (Ais) Techniques, Harish Valayapalayam Kumaravel

Open Access Theses

Two of the major approaches to intrusion detection are anomaly-based detection and signature-based detection. Anomaly-based approaches have the potential for detecting zero-day and other new forms of attacks. Despite this capability, anomaly-based approaches are comparatively less widely used when compared to signature-based detection approaches. Higher computational overhead, higher false positive rates, and lower detection rates are the major reasons for the same. This research has tried to mitigate this problem by using techniques from an area called the Artificial Immune Systems (AIS). AIS is a collusion of immunology, computer science and engineering and tries to apply a number of techniques …

A Study Of Security Issues Of Mobile Apps In The Android Platform Using Machine Learning Approaches, Lei Cen

Open Access Dissertations

Mobile app poses both traditional and new potential threats to system security and user privacy. There are malicious apps that may do harm to the system, and there are mis-behaviors of apps, which are reasonable and legal when not abused, yet may lead to real threats otherwise. Moreover, due to the nature of mobile apps, a running app in mobile devices may be only part of the software, and the server side behavior is usually not covered by analysis. Therefore, direct analysis on the app itself may be incomplete and additional sources of information are needed. In this dissertation, we …

Knowledge Modeling Of Phishing Emails, Courtney Falk

Open Access Dissertations

This dissertation investigates whether or not malicious phishing emails are detected better when a meaningful representation of the email bodies is available. The natural language processing theory of Ontological Semantics Technology is used for its ability to model the knowledge representation present in the email messages. Known good and phishing emails were analyzed and their meaning representations fed into machine learning binary classifiers. Unigram language models of the same emails were used as a baseline for comparing the performance of the meaningful data. The end results show how a binary classifier trained on meaningful data is better at detecting phishing …

Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam

Open Access Dissertations

Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose'' solution plans for the domain.

The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the …

Controlling For Confounding Network Properties In Hypothesis Testing And Anomaly Detection, Timothy La Fond

Open Access Dissertations

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like the total number of nodes or edges can lead to incorrect conclusions (e.g., false positives and false negatives). In this dissertation we describe the challenges that face …