Digital Commons Network^™

Deepfrag-K: A Fragment-Based Deep Learning Approach For Protein Fold Recognition, Wessam Elhefnawy, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

Background: One of the most essential problems in structural bioinformatics is protein fold recognition. In this paper, we design a novel deep learning architecture, so-called DeepFrag-k, which identifies fold discriminative features at fragment level to improve the accuracy of protein fold recognition. DeepFrag-k is composed of two stages: the first stage employs a multi-modal Deep Belief Network (DBN) to predict the potential structural fragments given a sequence, represented as a fragment vector, and then the second stage uses a deep convolutional neural network (CNN) to classify the fragment vector into the corresponding fold.

Results: Our results show that DeepFrag-k yields …

Divide And Slide: Layer-Wise Refinement For Output Range Analysis Of Deep Neural Networks, Chao Huang, Jiameng Fan, Xin Chen, Wenchao Li, Qi Zhu

Computer Science Faculty Publications

In this article, we present a layer-wise refinement method for neural network output range analysis. While approaches such as nonlinear programming (NLP) can directly model the high nonlinearity brought by neural networks in output range analysis, they are known to be difficult to solve in general. We propose to use a convex polygonal relaxation (overapproximation) of the activation functions to cope with the nonlinearity. This allows us to encode the relaxed problem into a mixed-integer linear program (MILP), and control the tightness of the relaxation by adjusting the number of segments in the polygon. Starting with a segment number of …

A User Study Of A Wearable System To Enhance Bystanders’ Facial Privacy, Alfredo J. Perez, Sherali Zeadally, Scott Griffith, Luis Y. Matos Garcia, Jason A. Mouloud

Computer Science Faculty Publications

The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped with cameras which enable users to take pictures and record videos anytime they need to do so. In many such cases, bystanders’ privacy is not a concern, and as a result, audio and video of bystanders are often captured without their consent. We present results from a user study in which 21 participants were asked to use a wearable system called …

Effect Of Implementing Subgoals In Code.Org's Intro To Programming Unit In Computer Science Principles, Lauren E. Margulieux, Briana Baker Morrison, Baker Franke, Hari Ramilison

Computer Science Faculty Publications

The subgoal learning framework has improved performance for novice programmers in higher education, but it has only started to be applied and studied in K-12 (primary/secondary). Programming education in K-12 is growing, and many international initiatives are attempting to increase participation, including curricular initiatives like Computer Science Principles and non-profit organizations like Code.org. Given that subgoal learning is designed to help students with no prior knowledge, we designed and implemented subgoals in the introduction to programming unit in Code.org's Computer Science Principles course. The redesigned unit includes subgoal-oriented instruction and subgoal-themed pre-written comments that students could add to their programming …

Secure Authentication And Privacy-Preserving Techniques In Vehicular Ad-Hoc Networks (Vanets), Dakshnamoorthy Manivannan, Shafika Showkat Moni, Sherali Zeadally

Computer Science Faculty Publications

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that …

Timing Of Maximal Weight Reduction Following Bariatric Surgery: A Study In Chinese Patients, Ting Xu, Chen Wang, Hongwei Zhang, Xiaodong Han, Weijie Liu, Junfeng Han, Haoyong Yu, Jin Chen, Pin Zhang, Jianzhong Di

Computer Science Faculty Publications

Introduction: Bariatric surgery is a well-received treatment for obesity with maximal weight loss at 12–36 months postoperatively. We investigated the effect of early bariatric surgery on weight reduction of Chinese patients in accordance with their preoperation characteristics.

Materials and Methods: Altogether, 409 patients with obesity from a prospective cohort in a single bariatric center were enrolled retrospectively and evaluated for up to 4 years. Measurements obtained included surgery type, duration of diabetic condition, besides the usual body mass index data tuple. Weight reduction was expressed as percent total weight loss (%TWL) and percent excess weight loss (%EWL).

Results: RYGB or …

Iot Privacy And Security: Challenges And Solutions, Lo'ai A. Tawalbeh, Fadi Muheidat, Mais Tawalbeh, Muhannad Quwaider

Computer Science Faculty Publications

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new …

Interactive Free-Viewpoint Video Generation, Yanru Wang, Zhihao Huang, Hao Zhu, Wei Li, Xun Cao, Ruigang Yang

Computer Science Faculty Publications

Background

Free-viewpoint video (FVV) is processed video content in which viewers can freely select the viewing position and angle. FVV delivers an improved visual experience and can also help synthesize special effects and virtual reality content. In this paper, a complete FVV system is proposed to interactively control the viewpoints of video relay programs through multimedia terminals such as computers and tablets.

Methods

The hardware of the FVV generation system is a set of synchronously controlled cameras, and the software generates videos in novel viewpoints from the captured video using view interpolation. The interactive interface is designed to visualize the …

Reducing Withdrawal And Failure Rates In Introductory Programming With Subgoal Labeled Worked Examples, Lauren E. Margulieux, Briana B. Morrison, Adrienne Decker

Computer Science Faculty Publications

Background

Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have automatized. The subgoal learning framework has been used in programming and other fields to breakdown procedural problem solving into smaller pieces that novices can grasp more easily, but it has only been used in short-term interventions. In this study, the subgoal learning framework was implemented throughout a semester-long introductory programming course …

A Semi-Automated Technique For Transcribing Accurate Crowd Motions, Alexander Fuchsberger, Brian Ricks, Zhicheng Chen

Computer Science Faculty Publications

We present a novel technique for transcribing crowds in video scenes that allows extracting the positions of moving objects in video frames. The technique can be used as a more precise alternative to image processing methods, such as background-removal or automated pedestrian detection based on feature extraction and classification. By manually projecting pedestrian actors on a two-dimensional plane and translating screen coordinates to absolute real-world positions using the cross ratio, we provide highly accurate and complete results at the cost of increased processing time. We are able to completely avoid most errors found in other automated annotation techniques, resulting from …

How Secure Having Iot Devices In Our Homes?, Debora Estrada, Lo'ai A. Tawalbeh, Robert Vinaja

Computer Science Faculty Publications

Nowadays, technology has evolved to be in our daily lives to assist in making our lives easier. We now have technology helping us in our lives at home. Devices used to create our “smart home” have done a great deal in making our lives at home less burdensome, but sadly, these devices have secured our personal lives to be more accessible to outsiders. In this paper, the security of home smart devices and their communication will be researched by using other academic articles to support facts found. The operation of the devices will be discussed along with security risks and …

A Cost Analysis Of Internet Of Things Sensor Data Storage On Blockchain Via Smart Contracts, Yesem Kurt Peker, Xavier Rodriguez, James Ericsson, Suk Jin Lee, Alfredo J. Perez

Computer Science Faculty Publications

Blockchain is a developing technology that can be utilized for secure data storage and sharing. In this work, we examine the cost of Blockchain-based data storage for constrained Internet of Things (IoT) devices. We had two phases in the study. In the first phase, we stored data retrieved from a temperature/humidity sensor connected to an Ethereum testnet blockchain using smart contracts in two different ways: first, appending the new data to the existing data, storing all sensor data; and second, overwriting the new data onto the existing data, storing only a recent portion of the data. In the second phase, …

Experiential Learning In The Technology Disciplines February 2020, Patricia Sendall, Christopher S. Stuetzle, Zachary A. Kissel, Tahir Hameed

Computer Science Faculty Publications

Learning-by-doing has long been a tradition in the technology disciplines. It is the "hands-on" work, combined with student reflection, feedback and assessment, that reinforces theory into practice. Over the past 40 years, experiential learning (EL) in higher education has grown beyond in-class assignments to include internships, cooperative education, team-based learning, project-based learning, community engagement, service learning, international and study-away experiences, capstone projects and research opportunities. This paper provides an overview of experiential education theory and practice in the undergraduate technology disciplines, and presents examples of how experiential learning practices have evolved over time at a medium-sized institution in the Northeast …

Experiential Learning Framework For Smaller Computer Science Programs, Zachary A. Kissel, Christopher S. Stuetzle

Computer Science Faculty Publications

Experiential learning (EL) permeates the Computer Science discipline. This work seeks to codify EL practices for computer science pedagogy into ve key pillars. These pillars have been successfully applied at a small to mid-sized college within the heavily competitive Boston area. This paper further describes how a computer science department may eectively implement the pillars in their own curriculum.

Icedge: When Edge Computing Meets Information-Centric Networking, Spyridon Mastorakis, Abderrahmen Mtibaa, Jonathan Lee, Satyajayant Misra

Computer Science Faculty Publications

In today’s era of explosion of Internet of Things (IoT) and end-user devices and their data volume, emanating at the network’s edge, the network should be more in-tune with meeting the needs of these demanding edge computing applications. To this end, we design and prototype Information-Centric edge (ICedge), a general-purpose networking framework that streamlines service invocation and improves reuse of redundant computation at the edge. ICedge runs on top of Named-Data Networking, a realization of the Information-Centric Networking vision, and handles the “low-level” network communication on behalf of applications. ICedge features a fully distributed design that: (i) enables users to …

The Curious Case Of Loops, Briana B. Morrison, Lauren E. Margulieux, Adrienne Decker

Computer Science Faculty Publications

Background and Context

Subgoal labeled worked examples have been extensively researched, but the research has been reported piecemeal. This paper aggregates data from three studies, including data previously unreported, to holistically examine the effect of subgoal labeled worked examples across three student populations and across different instructional designs.

Objective

By aggregating the data, we provide more statistical power for somewhat surprising yet replicable results. We discuss which results generalize across populations, focusing on a stable effect size for subgoal labels in programming instruction.

Method

We use descriptive and inferential statistics to examine the data collected from different student populations and …

Multi-Class Twitter Data Categorization And Geocoding With A Novel Computing Framework, Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon

Computer Science Faculty Publications

This study details the progress in transportation data analysis with a novel computing framework in keeping with the continuous evolution of the computing technology. The computing framework combines the Labeled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy on publicly available Twitter data in determining transportation-related events to provide reliable information to travelers. The analytical approach includes analyzing tweets using text classification and geocoding locations based on string similarity. A case study conducted for the New York City and its surrounding areas demonstrates the feasibility of the analytical approach. Approximately 700,010 tweets are analyzed …

A Saliency-Driven Video Magnifier For People With Low Vision, Ali Selman Aydin, Shirin Feiz, Iv Ramakrishnan, Vikas Ashok

Computer Science Faculty Publications

Consuming video content poses significant challenges for many screen magnifier users, which is the “go to” assistive technology for people with low vision. While screen magnifier software could be used to achieve a zoom factor that would make the content of the video visible to low-vision users, it is oftentimes a major challenge for these users to navigate through videos. Towards making videos more accessible for low-vision users, we have developed the SViM video magnifier system [6]. Specifically, SViM consists of three different magnifier interfaces with easy-to-use means of interactions. All three interfaces are driven by visual saliency as a …

Streaming Analytics And Workflow Automation For Dfs, Yasith Jayawardana, Sampath Jayarathna

Computer Science Faculty Publications

Researchers reuse data from past studies to avoid costly re-collection of experimental data. However, large-scale data reuse is challenging due to lack of consensus on metadata representations among research groups and disciplines. Dataset File System (DFS) is a semi-structured data description format that promotes such consensus by standardizing the semantics of data description, storage, and retrieval. In this paper, we present analytic-streams – a specification for streaming data analytics with DFS, and streaming-hub – a visual programming toolkit built on DFS to simplify data analysis work-flows. Analytic-streams facilitate higher-order data analysis with less computational overhead, while streaming-hub enables storage, retrieval, …

Smart Communities: From Sensors To Internet Of Things And To A Marketplace Of Services, Stephan Olariu, Nirwan Ansari (Editor), Andreas Ahrens (Editor), Cesar Benavente-Preces (Editor)

Computer Science Faculty Publications

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government that seeks to create a sustainable human-centric society by putting to work recent advances in technology: sensor networks, edge computing, IoT ecosystems, AI, Big Data, robotics, to name just a few. The main contribution of this work is a vision of how these technological advances can contribute, directly or indirectly, to making Society 5.0 reality. For this purpose we build on a recently-proposed concept of Marketplace of Services that, in our view, will turn out to be one of the cornerstones of Society 5.0. Instead of …

A Genome-Wide Association Study Of Cocaine Use Disorder Accounting For Phenotypic Heterogeneity And Gene–Environment Interaction, Jiangwen Sun, Henry R. Kranzler, Joel Gelernter, Jinbo Bi

Computer Science Faculty Publications

Background: Phenotypic heterogeneity and complicated gene-environment interplay in etiology are among the primary factors that hinder the identification of genetic variants associated with cocaine use disorder. Methods: To detect novel genetic variants associated with cocaine use disorder, we derived disease traits with reduced phenotypic heterogeneity using cluster analysis of a study sample (n = 9965). We then used these traits in genome-wide association tests, performed separately for 2070 African Americans and 1570 European Americans, using a new mixed model that accounted for the moderating effects of 5 childhood environmental factors. We used an independent sample (918 African Americans, 1382 European …

Extreme Ultraviolet Quasar Colours From Galex Observations Of The Sdss Dr14q Catalogue, Daniel E. Vanden Berk, Sarah C. Wesolowski, Mary J. Yeckley, Joseph M. Marcinik, Jean M. Quashnock, Lawrence M. Machia, Jian Wu

Computer Science Faculty Publications

The rest-frame far to extreme ultraviolet (UV) colour–redshift relationship has been constructed from data on over 480,000 quasars carefully cross-matched between SDSS Data Release 14 and the final GALEX photometric catalogue. UV matching and detection probabilities are given for all the quasars, including dependencies on separation, optical brightness, and redshift. Detection limits are also provided for all objects. The UV colour distributions are skewed redward at virtually all redshifts, especially when detection limits are accounted for. The median GALEX far-UV minus near-UV (FUV − NUV) colour–redshift relation is reliably determined up to z ≈ 2.8, corresponding to rest-frame wavelengths as …

Gabapentin Drug Misuse Signals: A Pharmacovigilance Assessment Using The Fda Adverse Event Reporting System, Rachel Vickers-Smith, Jiangwen Sun, Richard J. Charnigo, Michelle R. Lofwall, Sharon L. Walsh, Jennifer R. Havens

Computer Science Faculty Publications

Background: Although there have been increasing reports of intentional gabapentin misuse, epidemiological evidence for the phenomenon is limited. The purpose of this study was to determine whether there are pharmacovigilance abuse signals for gabapentin.

Methods: Using FDA Adverse Events Reporting System reports from January 1, 2005 to December 31, 2015, we calculated pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayes geometric mean) for abuse-related adverse event (AR-AE)-gabapentin pairs. Loglinear modeling assessed the frequency of concurrent reporting of abuse-related and abusespecific AEs (AS-AEs) associated with gabapentin. Findings were compared to a positive (pregabalin) and …

Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano

Computer Science Faculty Publications

Background: As more protein atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. Methods: We applied a histogram-based outlier score (HBOS) to six sets of cryo-EM atomic structures and five sets of X-ray atomic structures, including one derived from X-ray data with better than 1.5 Å resolution. Cryo-EM data sets contain structures released by December 2016 and those released between 2017 and 2019, derived from resolution ranges 0–4 Å and 4–6 Å respectively. Results: The distribution of HBOS values in five sets of X-ray structures show that HBOS is sensitive distinguishing …

A Heuristic Baseline Method For Metadata Extraction From Scanned Electronic Theses And Dissertations, Muntabir H. Choudhury, Jian Wu, William A. Ingam, Edward A. Fox

Computer Science Faculty Publications

Extracting metadata from scholarly papers is an important text mining problem. Widely used open-source tools such as GROBID are designed for born-digital scholarly papers but often fail for scanned documents, such as Electronic Theses and Dissertations (ETDs). Here we present a preliminary baseline work with a heuristic model to extract metadata from the cover pages of scanned ETDs. The process started with converting scanned pages into images and then text files by applying OCR tools. Then a series of carefully designed regular expressions for each field is applied, capturing patterns for seven metadata fields: titles, authors, years, degrees, academic programs, …

Shari- An Integration Of Tools To Visualize The Story Of The Day, Shawn M. Jones, Alexander C. Nwala, Martin Klein, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

Tools such as google news and flipboard exist to convey daily news, but what about the news of the past? In this paper, we describe how to combine several existing tools and web archive holdings to convey the “biggest story” for a given date in the past. StoryGraph clusters news articles together to identify a common news story. Hypercane leverages ArchiveNow to store URLs produced by Story-Graph in web archives. Hypercane analyzes these URLs to identify the most common terms, entities, and highest quality images for social media storytelling. Raintale then takes the output of these tools to produce a …

Mementoembed And Raintale For Web Archive Storytelling, Shawn M. Jones, Martin Klein, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

For traditional library collections, archivists can select a representative sample from a collection and display it in a featured physical or digital library space. Web archive collections may consist of thousands of archived pages, or mementos. How should an archivist display this sample to drive visitors to their collection? Search engines and social media platforms often represent web pages as cards consisting of text snippets, titles, and images. Web storytelling is a popular method for grouping these cards in order to summarize a topic. Unfortunately, social media platforms are not archive-aware and fail to consistently create a good experience for …

Tmvis: Visualizing Webpage Changes Over Time, Abigail Mabe, Dhruv Patel, Maheedhar Gunnam, Surbhi Shankar, Mat Kelly, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

TMVis is a web service to provide visualizations of how individual webpages have changed over time. We leverage past research on summarizing collections of webpages with thumbnail-sized screenshots and on choosing a small number of representative archived webpages from a large collection. We offer four visualizations: Image Grid, Image Slider, Timeline, and Animated GIF. Embed codes for the Image Grid and Image Slider can be produced to include these visualizations on separate webpages. This tool can be used to allow scholars from various disciplines, as well as the general public, to explore the temporal nature of webpages.

Repurposing Visual Input Modalities For Blind Users: A Case Study Of Word Processors, Hae-Na Lee, Vikas Ashok, I.V. Ramakrishnan

Computer Science Faculty Publications

Visual 'point-and-click' interaction artifacts such as mouse and touchpad are tangible input modalities, which are essential for sighted users to conveniently interact with computer applications. In contrast, blind users are unable to leverage these visual input modalities and are thus limited while interacting with computers using a sequentially narrating screen-reader assistive technology that is coupled to keyboards. As a consequence, blind users generally require significantly more time and effort to do even simple application tasks (e.g., applying a style to text in a word processor) using only keyboard, compared to their sighted peers who can effortlessly accomplish the same tasks …

Towards Making Videos Accessible For Low Vision Screen Magnifier Users, Ali Selman Aydin, Shirin Feiz, Vikas Ashok, Iv Ramakrishnan

Computer Science Faculty Publications

People with low vision who use screen magnifiers to interact with computing devices find it very challenging to interact with dynamically changing digital content such as videos, since they do not have the luxury of time to manually move, i.e., pan the magnifier lens to different regions of interest (ROIs) or zoom into these ROIs before the content changes across frames.

In this paper, we present SViM, a first of its kind screen-magnifier interface for such users that leverages advances in computer vision, particularly video saliency models, to identify salient ROIs in videos. SViM's interface allows users to zoom in/out …