Computer Sciences Commons^™

A Mixed Methods Study: Evaluating The Relationship Of Project Manager Competencies And It Project Management Methodologies, Keith A. Mcdermott

Open Access Theses

Determining skillsets that are particularly important to the development of an effective project manager can be useful for a variety of applications. These applications range from the hiring of a new project manager for an organization to continued training for current employees. Past research has called upon current project managers to rate what skillsets they see as important to the cultivation of an optimal or effective project manager. Additional research has expanded this idea to determine how skillsets vary between project managers and functional managers (El-Sabaa, 2001). While this research is certainly important, skillset grouping can be further explored. This …

Deep Collective Inference, John A. Moore

Open Access Theses

Collective inference is widely used to improve classification in network datasets. However, despite recent advances in deep learning and the successes of recurrent neural networks (RNNs), researchers have only just recently begun to study how to apply RNNs to heterogeneous graph and network datasets. There has been recent work on using RNNs for unsupervised learning in networks (e.g., graph clustering, node embedding) and for prediction (e.g., link prediction, graph classification), but there has been little work on using RNNs for node-based relational classification tasks. In this paper, we provide an end-to-end learning framework using RNNs for collective inference. Our main …

Inter-Color Npr Lines: A Comparison Of Rendering Techniques, Donald G. Herring

Open Access Theses

Renders of 3D scenes can feature lines drawn automatically along sharp edges between colored areas on object textures, in order to imitate certain conventional styles of hand-drawn line art. However, such "inter-color lines" have been studied very little. Two algorithms for rendering these lines were compared in this study - a faster one utilizing lines baked into the textures themselves and a more complex one that dynamically generated the lines in image space on each frame - for the purpose of determining which of the two better imitated traditional, hand-drawn art styles and which was more visually appealing. Test subjects …

Lightcraft Previzion In Distance Education, Perry L. Cox

Open Access Theses

Visual Effects has continued to progress at an astonishing rate and green screen technology can be seen in all aspects of the video industry from Hollywood blockbusters down to training videos and distance education.

As video technology has increased, so has the quality and capability of distance education. Purdue University has set itself to be at the forefront of distance education. This study looked to evaluate Purdue's investment in the Lightcraft Technology's Previzion system and its impact on distance education at Purdue. There were 65 initial participants and this study compared the impact of two separate videos on their learning. …

Tangible Interaction As An Aid For Object Navigation In 3d Modeling, Sanmathi Dangeti

Open Access Theses

This study introduced an interaction technique that used tangible interaction for 3D modeling. A hybrid interaction technique using a Kinect camera and a smartphone with a gyroscope was developed for the navigating objects in a 3D modeling software. It was then tested on 20 participants categorized as amateurs who had basic 3D/ CAD modeling experience and 20 participants categorized as the experts who had extensive experience working with the modeling software. This research study presents the need for existence of such interaction technique, gaps from the related previous studies, statistical findings from the current study and possible reasons for the …

Improving A Mesh Segmentation Algorithm Based On Non-Negative Matrix Factorization, Jisun Kang

Open Access Theses

3D Mesh segmentation is used in various applications such as object recognition, reconstruction, and analyzing structure of meshes. The method for 3D mesh segmentation based on sparse non-negative matrix factorization (NMF) was previously proposed. It represents a novel, and conceptually simpler, method than other comparable algorithms. However, this method still has potential to improve performance, results could have better consistency and uniqueness with faster computation time than the prior proposed algorithm. This study introduced several approaches to enhance the performance of the algorithm comprehensively: applying dierent update rule and initialization of factor matrices, and imposing sparseness to the factor matrices …

Video Annotation By Crowd Workers With Privacy-Preserving Local Disclosure, Apeksha Dipak Kumavat

Open Access Theses

Advancements in computer vision are still not reliable enough for detecting video content including humans and their actions. Microtask crowdsourcing on task markets such as Amazon Mechnical Turk and Upwork can bring humans into the loop. However, engaging crowd workers to annotate non-public video footage risks revealing the identities of people in the video who may have a right to anonymity.

This thesis demonstrates how we can engage untrusted crowd workers to detect behaviors and objects, while robustly concealing the identities of all faces. We developed a web-based system that presents obfuscated videos to crowd workers, and provides them with …

A Small-Scale Testbed For Large-Scale Reliable Computing, Jason R. St. John

Open Access Theses

High performance computing (HPC) systems frequently suffer errors and failures from hardware components that negatively impact the performance of jobs run on these systems. We analyzed system logs from two HPC systems at Purdue University and created statistical models for memory and hard disk errors. We created a small-scale error injection testbed—using a customized QEMU build, libvirt, and Python—for HPC application programmers to test and debug their programs in a faulty environment so that programmers can write more robust and resilient programs before deploying them on an actual HPC system. The deliverables for this project are the fault injection program, …

Computational Environment For Modeling And Analysing Network Traffic Behaviour Using The Divide And Recombine Framework, Ashrith Barthur

Open Access Dissertations

There are two essential goals of this research. The first goal is to design and construct a computational environment that is used for studying large and complex datasets in the cybersecurity domain. The second goal is to analyse the Spamhaus blacklist query dataset which includes uncovering the properties of blacklisted hosts and understanding the nature of blacklisted hosts over time.

The analytical environment enables deep analysis of very large and complex datasets by exploiting the divide and recombine framework. The capability to analyse data in depth enables one to go beyond just summary statistics in research. This deep analysis is …

A Framework For The Statistical Analysis Of Mass Spectrometry Imaging Experiments, Kyle Bemis

Open Access Dissertations

Mass spectrometry (MS) imaging is a powerful investigation technique for a wide range of biological applications such as molecular histology of tissue, whole body sections, and bacterial films , and biomedical applications such as cancer diagnosis. MS imaging visualizes the spatial distribution of molecular ions in a sample by repeatedly collecting mass spectra across its surface, resulting in complex, high-dimensional imaging datasets. Two of the primary goals of statistical analysis of MS imaging experiments are classification (for supervised experiments), i.e. assigning pixels to pre-defined classes based on their spectral profiles, and segmentation (for unsupervised experiments), i.e. assigning pixels to newly …

Visual Analytics Of Location-Based Social Networks For Decision Support, Junghoon Chae

Open Access Dissertations

Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on …

Combinatorial Algorithms For Perturbation Theory And Application On Quantum Computing, Yudong Cao

Open Access Dissertations

Quantum computing is an emerging area between computer science and physics. Numerous problems in quantum computing involve quantum many-body interactions. This dissertation concerns the problem of simulating arbitrary quantum many-body interactions using realistic two-body interactions. To address this issue, a general class of techniques called perturbative reductions (or perturbative gadgets) is adopted from quantum complexity theory and in this dissertation these techniques are improved for experimental considerations. The idea of perturbative reduction is based on the mathematical machinery of perturbation theory in quantum physics. A central theme of this dissertation is then to analyze the combinatorial structure of the perturbation …

Hybrid Stm/Htm For Nested Transactions In Java, Keith G. Chapman

Open Access Dissertations

Transactional memory (TM) has long been advocated as a promising pathway to more automated concurrency control for scaling concurrent programs running on parallel hardware. Software TM (STM) has the benefit of being able to run general transactional programs, but at the significant cost of overheads imposed to log memory accesses, mediate access conflicts, and maintain other transaction metadata. Recently, hardware manufacturers have begun to offer commodity hardware TM (HTM) support in their processors wherein the transaction metadata is maintained “for free” in hardware. However, HTM approaches are only best-effort: they cannot successfully run all transactional programs, whether because of hardware …

Low Rank Methods For Optimizing Clustering, Yangyang Hou

Open Access Dissertations

Complex optimization models and problems in machine learning often have the majority of information in a low rank subspace. By careful exploitation of these low rank structures in clustering problems, we find new optimization approaches that reduce the memory and computational cost.

We discuss two cases where this arises. First, we consider the NEO-K-Means (Non-Exhaustive, Overlapping K-Means) objective as a way to address overlapping and outliers in an integrated fashion. Optimizing this discrete objective is NP-hard, and even though there is a convex relaxation of the objective, straightforward convex optimization approaches are too expensive for large datasets. We utilize low …

Effective Memory Management For Mobile Environments, Ahmed Mohamed Abd-Elhaffiez Hussein

Open Access Dissertations

Smartphones, tablets, and other mobile devices exhibit vastly different constraints compared to regular or classic computing environments like desktops, laptops, or servers. Mobile devices run dozens of so-called “apps” hosted by independent virtual machines (VM). All these VMs run concurrently and each VM deploys purely local heuristics to organize resources like memory, performance, and power. Such a design causes conflicts across all layers of the software stack, calling for the evaluation of VMs and the optimization techniques specific for mobile frameworks.

In this dissertation, we study the design of managed runtime systems for mobile platforms. More specifically, we deepen the …

Securing Cloud-Based Data Analytics: A Practical Approach, Julian James Stephen

Open Access Dissertations

The ubiquitous nature of computers is driving a massive increase in the amount of data generated by humans and machines. The shift to cloud technologies is a paradigm change that offers considerable financial and administrative gains in the effort to analyze these data. However, governmental and business institutions wanting to tap into these gains are concerned with security issues. The cloud presents new vulnerabilities and is dominated by new kinds of applications, which calls for new security solutions. In the direction of analyzing massive amounts of data, tools like MapReduce, Apache Storm, Dryad and higher-level scripting languages like Pig Latin …

What Broke Where For Distributed And Parallel Applications — A Whodunit Story, Subrata Mitra

Open Access Dissertations

Detection, diagnosis and mitigation of performance problems in today's large-scale distributed and parallel systems is a difficult task. These large distributed and parallel systems are composed of various complex software and hardware components. When the system experiences some performance or correctness problem, developers struggle to understand the root cause of the problem and fix in a timely manner. In my thesis, I address these three components of the performance problems in computer systems. First, we focus on diagnosing performance problems in large-scale parallel applications running on supercomputers. We developed techniques to localize the performance problem for root-cause analysis. Parallel applications, …

Graphlet Based Network Analysis, Mahmudur Rahman

Open Access Dissertations

The majority of the existing works on network analysis, study properties that are related to the global topology of a network. Examples of such properties include diameter, power-law exponent, and spectra of graph Laplacians. Such works enhance our understanding of real-life networks, or enable us to generate synthetic graphs with real-life graph properties. However, many of the existing problems on networks require the study of local topological structures of a network.

Graphlets which are induced small subgraphs capture the local topological structure of a network effectively. They are becoming increasingly popular for characterizing large networks in recent years. Graphlet based …

Convicted By Memory: Automatically Recovering Spatial-Temporal Evidence From Memory Images, Brendan D. Saltaformaggio

Open Access Dissertations

Memory forensics can reveal “up to the minute” evidence of a device’s usage, often without requiring a suspect’s password to unlock the device, and it is oblivious to any persistent storage encryption schemes, e.g., whole disk encryption. Prior to my work, researchers and investigators alike considered data-structure recovery the ultimate goal of memory image forensics. This, however, was far from sufficient, as investigators were still largely unable to understand the content of the recovered evidence, and hence efficiently locating and accurately analyzing such evidence locked in memory images remained an open research challenge.

In this dissertation, I propose breaking from …

Differentially Private Data Publishing For Data Analysis, Dong Su

Open Access Dissertations

In the information age, vast amounts of sensitive personal information are collected by companies, institutions and governments. A key technological challenge is how to design mechanisms for effectively extracting knowledge from data while preserving the privacy of the individuals involved. In this dissertation, we address this challenge from the perspective of differentially private data publishing. Firstly, we propose PrivPfC, a differentially private method for releasing data for classification. The key idea underlying PrivPfC is to privately select, in a single step, a grid, which partitions the data domain into a number of cells. This selection is done using the exponential …

Divide And Recombined For Large Complex Data: Nonparametric-Regression Modelling Of Spatial And Seasonal-Temporal Time Series, Xiaosu Tong

Open Access Dissertations

In the first chapter of this dissertation, I briefly introduce one type of nonparametric regression method, namely local polynomial regression, followed by emphasis on one specific application of loess on time series decomposition, called Seasonal Trend Loess (STL). The chapter is closed by the introduction of D\&R; (Divide and Recombined) statistical framework. Data can be divided into subsets, each of which is applied with a statistical analysis method. This is an embarrassing parallel procedure since there is no communication between each subset. Then the analysis result for each subset are combined together to be the final analysis outcome for the …

Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

A Parallel 3d Phase-Field Simulation Of Multi-Grain Growth Based On The Full Thread Tree, Ya-Jun Yin, Min Wang, Jian-Xin Zhou, Dun-Ming Liao, Xu Shen, Tao Chen

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Computer-Aided Design Of Algorithms Of Pulsed Control Of Arc Welding Process Based On Numerical Simulation, Oksana I. Shpigunova, Anatoliy A. Glazunov

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Numerical Simulation Of The Through Process Of Aerospace Titanium Alloy Casting Filling, Solidification, And Hot Isostatic Pressing, Jian-Xin Zhou, Zhao Guo, Ya-Jun Yin, Chang-Chang Liu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Development And Computer Simulation Of A New Combined Energy-Saving Technological Process Of Production Of High-Quality Wire With Sub-Ultrafine-Grained Structure, Abdrakhman Naizabekov, Sergey Lezhnev, Evgeniy Panin, Igor Mazur

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Study On Growth Model Of Cellular Automata Method In Solidification Simulation, Zhao Guo, Jian-Xin Zhou, Ya-Jun Yin, Chang-Chang Liu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Generalizing The Quantum Dot Lab Towards Arbitrary Shapes And Compositions, Matthew A. Bliss, Prasad Sarangapani, James Fonseca, Gerhard Klimeck

The Summer Undergraduate Research Fellowship (SURF) Symposium

As applications in nanotechnology reach the scale of countable atoms, computer simulation has become a necessity in the understanding of new devices, such as quantum dots. To understand the various optoelectronic properties of these nanoparticles, the Quantum Dot Lab (QDL) has been created and powered by NEMO5 to simulate on multi-scale, multi-physics bases. QDL is easy to use by offering choices of different QD geometries such as shapes and sizes to the users from a predefined menu. The simplicity of use, however, limits the simulation of general QD shapes and compositions. A method to import generic strained crystalline and amorphous …

Ifly: Code Development For An App To Support Automating Entomological Data Collection, Michael P. Cosentino, Trevor Stamper

The Summer Undergraduate Research Fellowship (SURF) Symposium

We are developing a prototype entomological data-collection application called "iFly," which runs on a field-capable iPad device. In this phase, we tackled refining screens and introducing a database manager to streamline operations as info is entered, stored, retrieved and delivered. We used SQLite3 database in Apple's Xcode Integrated Development Environment (IDE). Xcode gives mixed programming results. Apple's iOS environment ensures functional and fairly error-free apps can be built. But the sophisticated Xcode IDE requires specialist developers and valuable project time is spent as new programmers learn key techniques. The iFly prototype was advanced with improved database integration; however, more work …

Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae

The Summer Undergraduate Research Fellowship (SURF) Symposium

Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …