Computer Sciences Commons^™

Towards Trustworthy Version Control Systems: Enhancing The Security Of Subversion, Ruchir Arya

Theses

Software development often relies on a Version Control System (VCS) to manage the source code, documentation and configuration of files. A VCS allows team development in which multiple developers can work simultaneously on source code updates. It also provides the ability to keep track of the historical changes made to the data over time, including the ability to retrieve previous versions of the source code in order to locate and fix bugs, and roll back to earlier versions in case the working version becomes buggy or unstable.

Apache Subversion (SVN) is a popular version control system that uses a client-server …

Advances In Mobile Video Networking, Qi Wang, Guojun Wang, Chrisos Grecos, Ansgar Gerlicher

All Faculty Scholarship for the College of the Sciences

Video applications have been increasingly dominating worldwide mobile network traffic in the last years. The growing popularity of smart phones and other mobile devices, on demand and surveillance video services, multimedia social networking, the latest advances in video coding and transmission, and the significant increase in mobile network capacity have all contributed to this global phenomenon. Both challenges and opportunities have emerged in multiple research disciplines involving video signal processing, 4G such as LTE (Long Term Evolution) and even 5G mobile networks, mobile cloud computing, Big Visual Data, mobile user experience, and so on. Research in these leading-edge areas has …

Representations And Models For Large-Scale Video Understanding, Du Le Hong Tran

Dartmouth College Ph.D Dissertations

In this thesis, we investigate different representations and models for large-scale video understanding. These methods include a mid-level representation for action recognition, a deep-learned representation for video analysis, a generic convolutional network architecture for video voxel prediction, and a new high-level task and benchmark of video comprehension. First, we present EXMOVES, a mid-level representation for scalable action recognition. The entries in EXMOVES representation are the calibrated outputs of a set of movement classifiers over spatial-temporal volumes of the input video. Each movement classifier is a simple exemplar-SVM trained on low-level features. Our EXMOVES requires a minimal amount of supervision while …

Study On The Application Of Information Technology In Inland Maritime Supervision, Chong He

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Important Considerations For Human Activity Recognition Using Sensor Data, Matt Buckner

Rose-Hulman Undergraduate Research Publications

Automated human activity recognition has received much attention in recent years due to increasing focus on interconnected devices in The Internet of Things (IoT) and the miniaturization and proliferation of sensor systems with the adoption of smartphones. In this work, we focus on the current status of human activity recognition across multiple studies, including methodology, accuracy of results, and current challenges to implementation. We include some preliminary work we have completed on a sensor system for classifying treadmill usage.

Real Time Activity Recognition Of Treadmill Usage Via Machine Learning, Nathan Blank, Matt Buckner, Christian Owen, Anna Scott

Rose-Hulman Undergraduate Research Publications

Our objective is to provide real-time classification of treadmill usage patterns based on accelerometer and magnetometer measurements. We collected data from treadmills in the Rose-Hulman Student Recreation Center (SRC) using Shimmer3 sensor units. We identified useful data features and classifiers for predicting treadmill usage patterns. We also prototyped a proof of concept wireless, real-time classification system.

Learning Loops: A Replication Study Illuminates Impact Of Hs Courses, Briana B. Morrison, Adrienne Decker, Lauren E. Margulieux

Computer Science Faculty Proceedings & Presentations

A recent study about the effectiveness of subgoal labeling in an introductory computer science programming course both supported previous research and produced some puzzling results. In this study, we replicate the experiment with a different student population to determine if the results are repeatable. We also gave the experimental task to students in a follow-on course to explore if they had indeed mastered the programming concept. We found that the previous puzzling results were repeated. In addition, for the novice programmers, we found a statistically significant difference in performance based on whether the student had previous programming courses in high …

On The Geodesic Centers Of Polygonal Domains, Haitao Wang

Computer Science Faculty and Staff Publications

In this paper, we study the problem of computing Euclidean geodesic centers of a polygonal domain P of n vertices. We give a necessary condition for a point being a geodesic center. We show that there is at most one geodesic center among all points of P that have topologically-equivalent shortest path maps. This implies that the total number of geodesic centers is bounded by the size of the shortest path map equivalence decomposition of P, which is known to be O(n^{10}). One key observation is a pi-range property on shortest path lengths when points are moving. With these observations, …

Effective Compiler Error Message Enhancement For Novice Programming Students, Brett Becker Dr, Graham Glanville

Faculty Research

Programming is an essential skill that all computing students must master. However programming can be difficult to learn. Compiler error messages are crucial for correcting errors, but are often difficult to understand and pose a barrier to progress for many novices. High frequencies of errors, particularly repeated errors, have been shown to be indicators of students who are struggling with learning to program. This study involves a custom IDE that enhances Java compiler error messages, intended to be more useful to novices than those supplied by the compiler. The effectiveness of this approach was tested in an empirical control/intervention study …

Geometric Inference With Microlens Arrays, Ian Schillebeeckx

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation explores an alternative to traditional fiducial markers where geometric

information is inferred from the observed position of 3D points seen in an image. We offer an alternative approach which enables geometric inference based on the relative orientation

of markers in an image. We present markers fabricated from microlenses whose appearance

changes depending on the marker's orientation relative to the camera. First, we show how

to manufacture and calibrate chromo-coding lenticular arrays to create a known relationship

between the observed hue and orientation of the array. Second, we use 2 small chromo-coding lenticular arrays to estimate the pose of …

Toward Autonomous Multi-Rotor Indoor Aerial Vehicles, Connor Brooks

Mahurin Honors College Capstone Experience/Thesis Projects

In this project, we worked to create an indoor autonomous micro aerial vehicle (MAV) using a multi-layer architecture with modular hardware and software components. We required that all computing was done onboard the vehicle during time of flight so that no remote connection of any kind was necessary for successful control of the vehicle, even when flying autonomously. We utilized environmental sensors including ultrasonic sensors, light detection and ranging modules, and inertial measurement units to acquire necessary environment information for autonomous flight. We used a three-layered system that combined a modular control architecture with distributed on-board computing to allow for …

Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.

McKelvey School of Engineering Graduate Student Theses & Dissertations

In human stool, a large population of bacterial genes and transcripts from hundreds of genera coexist with host genes and transcripts. Assessments of the metagenome and transcriptome are particularly challenging, since there is a great deal of sequence overlap among related species and related genes. We sequenced the total RNA content from stool samples in a neonate using previously-described methods. We then performed stepwise alignment of different populations of RNA sequence reads to different indices, including ribosomal databases, the human genome, and all sequenced bacterial genomes. Each pool of RNA at each alignment step was subjected to compression to assess …

Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo …

Practical Application Of Fast Disk Analysis For Selective Data Acquisition, Sergey Gorbov

LSU New Orleans Theses and Dissertations

Using a forensic imager to produce a copy of the storage is a common practice. Due to the large volumes of the modern disks, the imaging may impose severe time overhead which ultimately delays the investigation process. We proposed automated disk analysis techniques that precisely identify regions on the disk that contain data. We also developed a high performance imager that produces AFFv3 images at rates exceeding 300MB/s. Using multiple disk analysis strategies we can analyze a disk within a few minutes and yet reduce the imaging time of by many hours. Partial AFFv3 images produced by our imager can …

Integrative Approach For Inference Of Gene Regulatory Networks Using Lasso-Based Random Featuring And Application To Psychiatric Disorders, Dongchul Kim, Mingon Kang, Ashis Kumer Biswas, Chunyu Liu, Jean Gao

Computer Science Faculty Publications

Background

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization …

High Altitude Cosmic Ray Detection, Jordan D. Van Nest

2017 Academic High Altitude Conference

Cosmic rays are high energy atomic nuclei travelling near the speed of light that collide with atoms and molecules in Earth’s upper atmosphere (primarily with nitrogen and oxygen), breaking down into a shower of particles of various energies in the stratosphere. As they travel earthward, these particles continue to break down and lose energy which results in relatively little ionizing radiation reaching the surface. Due to the scattering of cosmic rays, the angle at which the rays enter the atmosphere can affect the number and energies of ionizing particles detected at various altitudes. When using a standard Geiger counter on …

What's All The Fuss About Coding?, Tim Bell

2009 - 2019 ACER Research Conferences

The idea of teaching ‘coding’ to school students has become popular, and the term appears in the names of many initiatives, such as Hour of Code and Code Club. But what do we really mean by ‘coding’, and why would you want every child to learn it? Won’t it be outdated soon? This paper looks at these issues, and why topics such as computer science are being taught to all students. This includes an assessment of misunderstandings around the idea of compulsory programming for every student, and the challenges that accompany the introduction of such topics into schools.

Acer Research Conference Proceedings (2016), Australian Council For Educational Research (Acer)

2009 - 2019 ACER Research Conferences

The focus of ACER’s Research Conference 2016 will be on what we are learning from research about ways of improving levels of STEM learning. Australia faces significant challenges in promoting improved science, technology, engineering and mathematics (STEM) learning in our schools. Research Conference 2016 will showcase research into what it will take to address these challenges, which include: the decline in Australian students’ mathematical and scientific ‘literacy’; the decline in STEM study in senior school; a shortage of highly qualified STEM subject teachers, and curriculum challenges. You will hear from researchers who work with teachers to engage students in studying …

Clawpack: Building An Open Source Ecosystem For Solving Hyperbolic Pdes, Donna Calhoun

Mathematics Faculty Publications and Presentations

Clawpack is a software package designed to solve nonlinear hyperbolic partial differential equations using high-resolution finite volume methods based on Riemann solvers and limiters. The package includes a number of variants aimed at different applications and user communities. Clawpack has been actively developed as an open source project for over 20 years. The latest major release, Clawpack 5, introduces a number of new features and changes to the code base and a new development model based on GitHub and Git submodules. This article provides a summary of the most significant changes, the rationale behind some of these changes, and a …

Creation Of A Conceptual Model For Adoption Of Mobile Apps For Shopping From E-Commerce Sites–An Indian Context, Vandana Ahuja, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

The changing marketing landscape has seen the advent and adoption of new tools like shopping apps for consumers. The conventional models which have studied Information Technology (IT) acceptance and adoption by consumers have found that adoption is a function of perceived usefulness and ease of usage. Other models have emphasised Quality, Enjoyment and Trust as significant determinants of the adoption of IT by consumers. Evolution in IT, changing consumer habits, changing demographics and consumer traits make it imperative to rethink pre-existing theories of acceptance and adoption of IT in the context of e-marketing. This paper focuses on the growth of …

Creating Art Patterns With Math And Code, Boyan Kostadinov

Publications and Research

The goal of this talk is to showcase some visualization projects that we developed for a 3-day Code in R summer program, designed to inspire the creative side of our STEM students by engaging them with computational projects that we developed with the purpose of mixing calculus level math and code to create complex geometric patterns. One of the goals of this program was to attract more minority and female students into applied math and computer science majors.

The projects are designed to be implemented using the high-level, open-source and free computational environment R, a popular software in industry for …

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 …

Stochastic Multiple Gradient Decent For Inferring Action-Based Network Generators, Qian Wu, Viplove Arora, Mario Ventresca

The Summer Undergraduate Research Fellowship (SURF) Symposium

Networked systems, like the internet, social networks etc., have in recent years attracted the attention of researchers, specifically to develop models that can help us understand or predict the behavior of these systems. A way of achieving this is through network generators, which are algorithms that can synthesize networks with statistically similar properties to a given target network. Action-based Network Generators (ABNG)is one of these algorithms that defines actions as strategies for nodes to form connections with other nodes, hence generating networks. ABNG is parametrized using an action matrix that assigns an empirical probability distribution to vertices for choosing specific …

Haptic Foot Feedback For Kicking Training In Virtual Reality, Hank Huang, Hong Tan

The Summer Undergraduate Research Fellowship (SURF) Symposium

As means to further supplement athletic performances increases, virtual reality is becoming helpful to sports in terms of cognitive training such as reaction, mentality, and game strategies. With the aid of haptic feedback, interaction with virtual objects increases by another dimension, in addition to the presence of visual and auditory feedback. This research presents an integrated system of a virtual reality environment, motion tracking system, and a haptic unit designed for the dorsal foot. The prototype simulates a scenario of virtual kicking and returns haptic response upon collision between the user’s foot and virtual object. The overall system was evaluated …

Classifying Pattern Formation In Materials Via Machine Learning, Lukasz Burzawa, Shuo Liu, Erica W. Carlson

The Summer Undergraduate Research Fellowship (SURF) Symposium

Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated materials often reveal complex pattern formation that occurs on multiple length scales. We have shown in two disparate correlated materials that the pattern formation is driven by proximity to a disorder-driven critical point. We developed new analysis concepts and techniques that relate the observed pattern formation to critical exponents by analyzing the geometry and statistics of clusters observed in these experiments and converting that information into critical exponents. Machine learning algorithms can be helpful correlating data from scanning probe experiments to theoretical models …

Gdd(Growth Degree Day) Module For Vinsense Visual Analytics System, Pradeep K. Lam, David Ebert , Phd, Jiawei Zhang

The Summer Undergraduate Research Fellowship (SURF) Symposium

Limited resources and increasing costs require vineyards to develop optimized methods of planting, growing, and harvesting crops in order to ensure max yield and stay competitive in the marketplace. Data from sensors planted within the soil paired with weather reports and observation data from farmers could help develop competitive farming strategies. While automatic computation models are usually a black box that cannot explain how the input data are transformed into output, the farmers require an approach that allows them to interactively manipulate and supervise the computation process. The VinSense project was developed for this purpose. In this paper, we focus …

Analyzing Sports Training Data With Machine Learning Techniques, Rehana Mahfuz, Zeinab Mourad, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In the sports industry, there has not been enough effort in analyzing the personalized monitoring data of athletes collected during training sessions. This research is an attempt to find meaningful patterns in the Purdue Women’s Soccer training data that could help the coach design more efficient training sessions. We are specifically interested in studying this problem as an unsupervised learning problem. Our initial attempt is to cluster the players as well as drills into groups using k-means, c-means and spectral clustering algorithms, combined with feature transformation and reduction steps. These basic algorithms serve as a benchmark to measure performance improvements …

Definition Of A Method For The Formulation Of Problems To Be Solved With High Performance Computing, Ramya Peruri

Master of Science in Computer Science Theses

Computational power made available by current technology has been continuously increasing, however today’s problems are larger and more complex and demand even more computational power. Interest in computational problems has also been increasing and is an important research area in computer science. These complex problems are solved with computational models that use an underlying mathematical model and are solved using computer resources, simulation, and are run with High Performance Computing. For such computations, parallel computing has been employed to achieve high performance. This thesis identifies families of problems that can best be solved using modelling and implementation techniques of parallel …