Computer Sciences Commons^™

Inference Of Development Activities From Interaction With Uninstrumented Applications, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Ahmed E. Hassan

Research Collection School Of Computing and Information Systems

Studying developers’ behavior in software development tasks is crucial for designing effective techniques and tools to support developers’ daily work. In modern software development, developers frequently use different applications including IDEs, Web Browsers, documentation software (such as Office Word, Excel, and PDF applications), and other tools to complete their tasks. This creates significant challenges in collecting and analyzing developers’ behavior data. Researchers usually instrument the software tools to log developers’ behavior for further studies. This is feasible for studies on development activities using specific software tools. However, instrumenting all software tools commonly used in real work settings is difficult and …

Region-Aware Reflection Removal With Unified Content And Gradient Priors, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Wen Gao, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections in images taken through the glass is of broad application to various image processing and computer vision tasks. Existing single image-based solutions heavily rely on scene priors such as separable sparse gradients caused by different levels of blur, and they are fragile when such priors are not observed. In this paper, we notice that strong reflections usually dominant a limited region in the whole image, and propose a region-aware reflection removal approach by automatically detecting and heterogeneously processing regions with and without reflections. We integrate content and gradient priors to jointly achieve missing contents restoration, as …

Automatically Conceptualizing Social Media Analytics Data Via Personas, Jung S.G., Salminen J., An J., Kwak H., Jansen B.J.

Research Collection School Of Computing and Information Systems

Social media analytics is insightful but can also be difficult to use within organizations. To address this, we present Automatic Persona Generation (APG), a system and methodology for quantitatively generating personas using large amounts of online social media data. The APG system is operational, deployed in a pilot version with several organizations in multiple industry verticals. APG uses a robust web and stable back-end database framework to process tens of millions of user interactions with thousands of online digital products on multiple social media platforms, including Facebook and YouTube. APG identifies both distinct and impactful audience segments for an organization …

Dynamic Pricing In Spatial Crowdsourcing: A Matching-Based Approach, Yongxin Tong, Libin Wang, Zimu Zhou, Lei Chen, Bowen Du, Jieping Ye

Research Collection School Of Computing and Information Systems

In spatial crowdsourcing, requesters submit their task-related locations and increase the demand of a local area. The platform prices these tasks and assigns spatial workers to serve if the prices are accepted by requesters. There exist mature pricing strategies which specialize in tackling the imbalance between supply and demand in a local market. However, in global optimization, the platform should consider the mobility of workers; that is, any single worker can be the potential supply for several areas, while it can only be the true supply of one area when assigned by the platform. The hardness lies in the uncertainty …

How Does Developer Interaction Relate To Software Quality? An Examination Of Product Development Data, Subhajit Datta

Research Collection School Of Computing and Information Systems

Industrial software systems are being increasingly developed by large and distributed teams. Tools like collaborative development environments (CDE) are used to facilitate interaction between members of such teams, with the expectation that social factors around the interaction would facilitate team functioning. In this paper, we first identify typically social characteristics of interaction in a software development team: reachability, connection, association, and clustering. We then examine how these factors relate to the quality of software produced by a team, in terms of the number of defects, through an empirical study of 70+ teams, involving 900+ developers in total, spread across 30+ …

Crrn: Multi-Scale Guided Concurrent Reflection Removal Network, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks. Non-learning based methods utilize different handcrafted priors such as the separable sparse gradients caused by different levels of blurs, which often fail due to their limited description capability to the properties of real-world reflections. In this paper, we propose the Concurrent Reflection Removal Network (CRRN) to tackle this problem in a unified framework. Our proposed network integrates image appearance information and multi-scale gradient information with human perception inspired loss function, and is trained on a new dataset with 3250 reflection images …

Effect Of Temporality, Physical Activity, And Cognitive Load On Spatiotemporal Vibrotactile Pattern Recognition, Qin Chen, Simon T. Perrault, Quentin Xavier Louis Roy, Lonce Wyse

Research Collection School Of Computing and Information Systems

Previous research demonstrated the ability for users to accurately recognize Spatiotemporal Vibrotactile Patterns (SVP): sequences of vibrations on different motors occurring either sequentially or simultaneously. However, the experiments were only run in a lab setting and the ability for users to recognize SVP in a real-world environment remains unclear. In this paper, we investigate how several factors may affect recognition: (1) physical activity (running), (2) cognitive task (i.e. primary task, typing), (3) distribution of the vibration motors across body parts and (4) temporality of the patterns. Our results suggest that physical activity has very little impact, specifically compared to cognitive …

Scale Impacts Elicited Gestures For Manipulating Holograms: Implications For Ar Gesture Design, Tran Pham, Jo Vermeulen, Anthony Tang, Lindsay Macdonald

Research Collection School Of Computing and Information Systems

Because gesture design for augmented reality (AR) remains idiosyncratic, people cannot necessarily use gestures learned in one AR application in another. To design discoverable gestures, we need to understand what gestures people expect to use. We explore how the scale of AR affects the gestures people expect to use to interact with 3D holograms. Using an elicitation study, we asked participants to generate gestures in response to holographic task referents, where we varied the scale of holograms from desktop-scale to room-scale objects. We found that the scale of objects and scenes in the AR experience moderates the generated gestures. Most …

Covariance Pooling For Facial Expression Recognition, D. Acharya, Zhiwu Huang, D. Paudel, Gool L. Van

Research Collection School Of Computing and Information Systems

Classifying facial expressions into different categories requires capturing regional distortions of facial landmarks. We believe that second-order statistics such as covariance is better able to capture such distortions in regional facial features. In this work, we explore the benefits of using a manifold network structure for covariance pooling to improve facial expression recognition. In particular, we first employ such kind of manifold networks in conjunction with traditional convolutional networks for spatial pooling within individual image feature maps in an end-to-end deep learning manner. By doing so, we are able to achieve a recognition accuracy of 58.14% on the validation set …

Where Does Google Find Api Documentation?, Christoph Treude, Maurício Aniche

Research Collection School Of Computing and Information Systems

The documentation of popular APIs is spread across many formats, from vendor-curated reference documentation to Stack Overflow threads. For developers, it is often not obvious from where a particular piece of information can be retrieved. To understand this documentation landscape, we systematically conducted Google searches for the elements of ten popular APIs. We found that their documentation is widely dispersed among many sources, that GitHub and Stack Overflow play a prominent role among the search results, and that most sources are quick to document new API functionalities. These findings inform API vendors about where developers find documentation about their products, …

Deep Adversarial Subspace Clustering, Pan Zhou, Yunqing Hou, Jiashi Feng

Research Collection School Of Computing and Information Systems

Most existing subspace clustering methods hinge on self-expression of handcrafted representations and are unaware of potential clustering errors. Thus they perform unsatisfactorily on real data with complex underlying subspaces. To solve this issue, we propose a novel deep adversarial subspace clustering (DASC) model, which learns more favorable sample representations by deep learning for subspace clustering, and more importantly introduces adversarial learning to supervise sample representation learning and subspace clustering. Specifically, DASC consists of a subspace clustering generator and a quality-verifying discriminator, which learn against each other. The generator produces subspace estimation and sample clustering. The discriminator evaluates current clustering performance …

Examining The Learnability Of Auditory Displays: Music, Earcons, Spearcons, And Lyricons, Kay Tislar, Zackery Duford, Brittany Nelson, Madeline Peabody, Myounghoon Jeon

Michigan Tech Publications, Part 1

Auditory displays are a useful platform to convey information to users for a variety of reasons. The present study sought to examine the use of different types of sounds that can be used in auditory displays—music, earcons, spearcons, and lyricons—to determine which sounds have the highest learnability when presented in sequences. Participants were self-trained on sound meanings and then asked to recall meanings after listening to sequences of varying lengths. The relatedness of sounds and their attributed meanings, or the intuitiveness of the sounds, was also examined. The results show that participants were able to learn and recall lyricons and …

Jupyterlab_Voyager: A Data Visualization Enhancement In Jupyterlab, Ji Zhang

Master's Theses

With the emergence of big data, scientific data analysis and visualization (DAV) tools are critical components of the data science software ecosystem; the usability of these tools is becoming extremely important to facilitate next-generation scientific discoveries. JupyterLab has been considered as one of the best polyglot, web-based, open-source data science tools. As the next phase of extensible interface for the classic iPython Notebooks, this tool supports interactive data science and scientific computing across multiple programming languages with great performances. Despite these advantages, previous heuristics evaluation studies have shown that JupyterLab has some significant flaws in the data visualization side. The …

An Empirical Study Of Alias Analysis Techniques, Andrew T. Tran

Master's Theses

As software projects become larger and more complex, software optimization at that scale is only feasible through automated means. One such component of software optimization is alias analysis, which attempts to determine which variables in a program refer to the same area in memory, and is used to relocate instructions to improve performance without interfering with program execution. Several alias analyses have been proposed over the past few decades, with varying degrees of precision and time and space complexity, but few studies have been conducted to compare these techniques with one another, nor to measure with program data to confirm …

Tessellated Voxelization For Global Illumination Using Voxel Cone Tracing, Sam Thomas Freed

Master's Theses

Modeling believable lighting is a crucial component of computer graphics applications, including games and modeling programs. Physically accurate lighting is complex and is not currently feasible to compute in real-time situations. Therefore, much research is focused on investigating efficient ways to approximate light behavior within these real-time constraints.

In this thesis, we implement a general purpose algorithm for real-time applications to approximate indirect lighting. Based on voxel cone tracing, we use a filtered representation of a scene to efficiently sample ambient light at each point in the scene. We present an approach to scene voxelization using hardware tessellation and compare …

Real-Time Object Removal In Augmented Reality, Tyler Dahl

Master's Theses

Diminished reality, as a sub-topic of augmented reality where digital information is overlaid on an environment, is the perceived removal of an object from an environment. Previous approaches to diminished reality used digital replacement techniques, inpainting, and multi-view homographies. However, few used a virtual representation of the real environment, limiting their domains to planar environments.

This thesis provides a framework to achieve real-time diminished reality on an augmented reality headset. Using state-of-the-art hardware, we combine a virtual representation of the real environment with inpainting to remove existing objects from complex environments.

Our work is found to be competitive with previous …

Bird Abundance At Bird Feeders In Response To Temperature, Wind Speed And Precipitation During The Winter Season, Siddhant Kahal

Master's Theses

The goal of this project is to explore how 23 different bird species respond to 3 climatic attributes. These attributes are lower than average temperatures, wind speed and precipitation level. Information about the bird species and all of the data associated with them is provided by Project FeederWatch (PFW). This is a citizen based survey study that provides key information about bird species abundance through the use of backyard and community feeders. The study volunteers from across the United States and Canada monitor these bird feeders and note important information about the species such as the number of individuals seen. …

Acceleration Of Jaccard's Index Algorithm For Training To Tag Damage On Post-Earthquake Images, Kyle John Mulligan

Master's Theses

There are currently different efforts to use Supervised Neural Networks (NN) to automatically label damages on images of above ground infrastructure (buildings made of concrete) taken after an earthquake. The goal of the supervised NN is to classify raw input data according to the patterns learned from an input training set. This input training data set is usually supplied by experts in the field, and in the case of this project, structural engineers carefully and mostly manually label these images for different types of damage. The level of expertise of the professionals labeling the training set varies widely, and some …

Influencing Exploration In Actor-Critic Reinforcement Learning Algorithms, Andrew R. Gough

Master's Theses

Reinforcement Learning (RL) is a subset of machine learning primarily concerned with goal-directed learning and optimal decision making. RL agents learn based on a reward signal discovered from trial and error in complex, uncertain environments with the goal of maximizing positive reward signals. RL approaches need to scale up as they are applied to more complex environments with extremely large state spaces. Inefficient exploration methods cannot sufficiently explore complex environments in a reasonable amount of time, and optimal policies will be unrealized resulting in RL agents failing to solve an environment.

This thesis proposes a novel variant of the Actor-Advantage …

Exploring The Role Of Semi-Supervised Deep Reinforcement Learning And Ensemble Methods In Support Of The Internet Of Things, Mehdi Mohammadi

Dissertations

Smart services are an important element of the Internet of Things (IoT) ecosystem where insights are drawn from raw data through the use of machine learning techniques. However, the pathway to develop IoT smart services is complicated as IoT data presents several challenges for machine learning, including handling big data, shortage of labeled data, and the need to benefit from the spatio-temporal relations hidden in the training data.

In this dissertation, after reviewing the state-of-the-art deep learning (DL) and deep reinforcement learning (DRL) techniques and their use in support of IoT applications, this study proposes to extend DRL to semi-supervised …

Assessing Relevance Of Tweets For Risk Communication, Xiaohui Liu, Bandana Kar, Chaoyang Zhang, David M. Cochran

Faculty Publications

Although Twitter is used for emergency management activities, the relevance of tweets during a hazard event is still open to debate. In this study, six different computational (i.e. Natural Language Processing) and spatiotemporal analytical approaches were implemented to assess the relevance of risk information extracted from tweets obtained during the 2013 Colorado flood event. Primarily, tweets containing information about the flooding events and its impacts were analysed. Examination of the relationships between tweet volume and its content with precipitation amount, damage extent, and official reports revealed that relevant tweets provided information about the event and its impacts rather than any …

On The Automation Of Cyber Experimentation, Dhanish Mehta

Theses and Dissertations

There are a variety of tools available to users to perform cyber experimentation, and many of them automate some aspects of the experimentation lifecycle. However, they either support a minimal subset of the tools across various experimentation environments, or solve a particular problem in the cyber experiment lifecycle. In pursuit of making cyber experimentation easier and more efficient, we introduce a new framework that can design, create, execute and analyze experiments and is agnostic of the underlying environments. We show the effectiveness of our framework by presenting a prototype implementation and perform two case studies using the prototype implementation. We …

Probabilistic Programming For Theory Of Mind For Autonomous Decision Making, Iris Rubi Seaman

Theses and Dissertations

As autonomous agents (such as unmanned aerial vehicles, or UAVs) become more ubiquitous, they are being used for increasingly complex tasks. Eventually, they will have to reason about the mental state of other agents, including those agents' beliefs, desires and goals – so-called Theory of Mind – and make decisions based on that reasoning. We describe increasingly complex theory of mind models of a UAV pursuing an intruder, and show that (1) there is a natural Bayesian formulation to reasoning about the uncertainty inherent in our estimate of another agent's mental state, and that (2) probabilistic programming is a natural …

Evaluating The Usability Of Two-Factor Authentication, Kendall Ray Reese

Theses and Dissertations

Passwords are the dominant form of authentication on the web today. However,many users choose weak passwords and reuse the same password on multiple sites, thus increasing their vulnerability to having their credentials leaked or stolen. Two-factor authentication strengthens existing password authentication schemes against impersonation attacks and makes it more difficult for attackers to reuse stolen credentials on other websites. Despite the added security benefits of two-factor authentication, there are still many open questions about its usability. Many two-factor authentication systems in widespread usage today have not yet been subjected to adequate usability testing. Previous comparative studies have demonstrated significant differences …

Critical Parameters In A Computational Model Of Tgf-Beta-Induced Epithelial Mesenchymal Transition., Mario J. Mendez, Seth H. Weinberg

Biology and Medicine Through Mathematics Conference

No abstract provided.

Virtual Smarts - Optimizing The Coalescing Of People For Collective Action Within Urban Communities, Stephen Thomas Ricken

Dissertations

Despite the importance of individuals coming together for social group-activities (e.g., pick-up volleyball), the process by which such groups coalesce is poorly understood, and as a consequence is poorly supported by technology. This is despite the emergence of Event-Based Social Network (EBSN) technologies that are specifically designed to assist group coalescing for social activities. Existing theories focus on group development in terms of norms and types, rather than the processes involved in initial group coalescence. This dissertation addresses this gap in the literature through four studies focusing on understanding the coalescing process for interest-based group activities within urban environments and …

Reflections On Building Dartdraw: A React + Redux Vector-Based Graphics Editor, Elisabeth G. Pillsbury

Dartmouth College Undergraduate Theses

In this paper, I discuss some of the design challenges I encountered while contributing to DartDraw, a React-Redux drawing application modeled after MacDraw. The features I worked on include: zoom, pan, grid, ruler, and arrowheads.

Overlaying Virtual Scale Models On Real Environments Without The Use Of Peripherals, George Hito

Dartmouth College Undergraduate Theses

The Architecture, Engineering, and Construction (AEC) industries have become increasingly reliant on detailed 3D modeling software and visualization tools. In the past few years, the arrival of effective and relatively cheap virtual reality has transformed the workflows of people in these professions. Augmented reality (AR) is poised to have a similar if not greater effect. For that to occur, the transition into using this technology must be seamless and straightforward. In particular, a clear bridge should be made between Computer Aided Design (CAD) models and their corresponding real-world environments. Using Unity and Microsoft's Hololens, I developed a method of automatically …

High Performance Cloud Computing On Multicore Computers, Jianchen Shan

Dissertations

The cloud has become a major computing platform, with virtualization being a key to allow applications to run and share the resources in the cloud. A wide spectrum of applications need to process large amounts of data at high speeds in the cloud, e.g., analyzing customer data to find out purchase behavior, processing location data to determine geographical trends, or mining social media data to assess brand sentiment. To achieve high performance, these applications create and use multiple threads running on multicore processors. However, existing virtualization technology cannot support the efficient execution of such applications on virtual machines, making them …

Ipv6 Security Issues In Linux And Freebsd Kernels: A 20-Year Retrospective, Jack R. Cardwell

Dartmouth College Undergraduate Theses

Although IPv6 was introduced in 1998, its adoption didn't begin to take off until 2012. Furthermore, its vulnerabilities haven't received as much attention as those of IPv4. As such, there is potential to exploit these vulnerabilities. With the amount of IPv6 traffic rapidly increasing, these exploits present real-world consequences. This paper aims to re-evaluate the security of IPv6 stack implementations in FreeBSD and Linux kernels, specifically FreeBSD 11.1 and Ubuntu Linux 4.13. It contributes to the literature in three ways. We first reproduce ten vulnerabilities from existing research to determine whether known bugs have been patched. Then, we examine two, …