Computer Sciences Commons^™

A Novel Penalty-Based Wrapper Objective Function For Feature Selection In Big Data Using Cooperative Co-Evolution, A.N.M. Bazlur Rashid, Mohiuddin Ahmed, Leslie F. Sikos, Paul Haskell-Dowland

Research outputs 2014 to 2021

The rapid progress of modern technologies generates a massive amount of high-throughput data, called Big Data, which provides opportunities to find new insights using machine learning (ML) algorithms. Big Data consist of many features (also called attributes); however, not all these are necessary or relevant, and they may degrade the performance of ML algorithms. Feature selection (FS) is an essential preprocessing step to reduce the dimensionality of a dataset. Evolutionary algorithms (EAs) are widely used search algorithms for FS. Using classification accuracy as the objective function for FS, EAs, such as the cooperative co-evolutionary algorithm (CCEA), achieve higher accuracy, even …

Use Of Landsat Imagery To Map Spread Of The Invasive Alien Species Acacia Nilotica In Baluran National Park, Indonesia, Sutomo Sutomo, Eddie Van Etten, Rajif Iryadi

Research outputs 2014 to 2021

© 2020 Seameo Biotrop. In the late 1960s, Acacia nilotica was introduced to Baluran National Park to establish fire breaks which would prevent the spread of fire from Baluran Savanna to the adjacent teak forest. However, A. nilotica has spread rapidly and has threatened the existence of Baluran Savanna as it has caused an ecosystem transition from an open savanna to a closed canopy of A. nilotica in some areas. This study is one of the few that examines A. nilotica invasion in Baluran National Park through remote sensing. Land cover dynamics were quantified using a supervised classification approach on …

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 …

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 …

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 …

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, …

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, …

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 …

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 …

Sail: Saliency-Driven Injection Of Aria Landmarks, Ali Selman Aydin, Shirin Feiz, Vikas Ashok, Iv Ramakrishnan

Computer Science Faculty Publications

Navigating webpages with screen readers is a challenge even with recent improvements in screen reader technologies and the increased adoption of web standards for accessibility, namely ARIA. ARIA landmarks, an important aspect of ARIA, lets screen reader users access different sections of the webpage quickly, by enabling them to skip over blocks of irrelevant or redundant content. However, these landmarks are sporadically and inconsistently used by web developers, and in many cases, even absent in numerous web pages. Therefore, we propose SaIL, a scalable approach that automatically detects the important sections of a web page, and then injects ARIA landmarks …

Rotate-And-Press: A Non-Visual Alternative To Point-And-Click, Hae-Na Lee, Vikas Ashok, I. V. Ramakrishnan

Computer Science Faculty Publications

Most computer applications manifest visually rich and dense graphical user interfaces (GUIs) that are primarily tailored for an easy-and-efficient sighted interaction using a combination of two default input modalities, namely the keyboard and the mouse/touchpad. However, blind screen-reader users predominantly rely only on keyboard, and therefore struggle to interact with these applications, since it is both arduous and tedious to perform the visual 'point-and-click' tasks such as accessing the various application commands/features using just keyboard shortcuts supported by screen readers.

In this paper, we investigate the suitability of a 'rotate-and-press' input modality as an effective non-visual substitute for the visual …

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 …

Psu At Clef-2020 Arqmath Track: Unsupervised Re-Ranking Using Pretraining, Shaurya Rohatgi, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

This paper elaborates on our submission to the ARQMath track at CLEF 2020. Our primary run for the main Task-1: Question Answering uses a two-stage retrieval technique in which the first stage is a fusion of traditional BM25 scoring and tf-idf with cosine similarity-based retrieval while the second stage is a finer re-ranking technique using contextualized embeddings. For the re-ranking we use a pre-trained robertabase model (110 million parameters) to make the language model more math-aware. Our approach achieves a higher NDCG0 score than the baseline, while our MAP and P@10 scores are competitive, performing better than the best submission …

Smartcitecon: Implicit Citation Context Extraction From Academic Literature Using Unsupervised Learning, Chenrui Gao, Haoran Cui, Li Zhang, Jiamin Wang, Wei Lu, Jian Wu

Computer Science Faculty Publications

We introduce SmartCiteCon (SCC), a Java API for extracting both explicit and implicit citation context from academic literature in English. The tool is built on a Support Vector Machine (SVM) model trained on a set of 7,058 manually annotated citation context sentences, curated from 34,000 papers in the ACL Anthology. The model with 19 features achieves F₁=85.6%. SCC supports PDF, XML, and JSON files out-of-box, provided that they are conformed to certain schemas. The API supports single document processing and batch processing in parallel. It takes about 12–45 seconds on average depending on the format to process a …

Acknowledgement Entity Recognition In Cord-19 Papers, Jian Wu, Pei Wang, Xin Wei, Sarah Rajtmajer, C. Lee Giles, Christopher Griffin

Computer Science Faculty Publications

Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F₁=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to …

Detecting Faces With Covid Protection Masks From Images Shot In Public Places Using Neural Networks, Hangkai Wang

Chulalongkorn University Theses and Dissertations (Chula ETD)

Since 2019, Covid-19 has become a common problem affecting all mankind. The disease has successfully spread all over the world. Wearing a mask can practically protect the infection. Thus, detecting people wearing and not wearing masks in public is essential. However, there is still some room to improve detection accuracy of the present methods. In this paper, the transfer learning model and FR-TSVM model are used to study the latest data of pneumonia epidemic situation in Covid-19. First, a data set of 11600 facial images wearing masks and not wearing masks in public was collected for training, testing, and validation. …

Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant

Walden Dissertations and Doctoral Studies

Spine and related disorders represent one of the most common causes of pain and disability in the United States. Imaging represents an important diagnostic procedure in spine care. Imaging studies contain actionable data and insights undetectable through routine visual analysis. Convergent advances in imaging, artificial intelligence (AI), and radiomic methods has revealed the potential of multiscale in vivo interrogation to improve the assessment and monitoring of pathology. AI offers various types of decision support through the analysis of structured and unstructured data. The primary purpose of this qualitative exploratory case study was to identify the potential impacts of AI solutions …

Exploring Strategies For Recruiting And Retaining Diverse Cybersecurity Professionals, Vivian Lyon

Walden Dissertations and Doctoral Studies

The cyber threat landscape has led some cybersecurity leaders to focus on a holistic approach encompassing people, processes, and technology to make their government agencies and organizations more responsive to a more diverse and inclusive cyber workforce to protect critical infrastructure from hackers or cybercriminals intent on causing harm. This qualitative multiple case study used Schein’s organizational culture theory to explore strategies used by cybersecurity leaders to attract, recruit, and retain diverse cybersecurity professionals to effectively and efficiently protect sensitive systems from rising cyber threats. The study's population consisted of cybersecurity leaders from 3 government agencies and 9 organizations in …

Strategies For The Development Of It Disaster Recovery Plans In The Manufacturing Industry, Michael Landry Sartwell

Walden Dissertations and Doctoral Studies

Information technology (IT) leaders have reported technology disruptions because of natural disasters, terror attacks, or adversarial threats. Information technology leaders are concerned with technology disruptions, as these disruptions are costing organizations as much as $22,000 per minute. Grounded in Zachman’s framework, the purpose of this qualitative multiple case study was to explore strategies IT managers in the manufacturing industry use to develop IT disaster recovery (DR) plans to support business operations. The participants included 3 manufacturing IT professionals, 2 Department of Defense manufacturing infrastructure specialists, and 1outsourcing contractor, each from firms located in the central United States who successfully developed …

Factors Influencing Cloud Computing Adoption By Small Firms In The Payment Card Industry, Marie Njanje Tambe

Walden Dissertations and Doctoral Studies

Technology acceptance is increasingly gaining attention in research considering the continuous exploits of innovation and various derived advantages. Cloud computing (CC) has shown to be the ideal solution for aligning information technology with business strategies. However, small to medium-sized enterprises (SMEs) in the payment card industry are reluctantly adopting this technology despite the benefits. This correlational study aims at investigating whether security, cost effectiveness, or regulatory compliance influence CC adoption by U.S. SMEs in the payment card sector. The study builds on the technology-organization-environment (TOE) framework and uses a previously validated instrument to assess CC adoption by decision-makers in U.S. …

Developing Cloud Computing Infrastructures In Developing Countries In Asia, Daryoush Charmsaz Moghaddam

Walden Dissertations and Doctoral Studies

Developing Cloud Computing Infrastructures in Developing Countries in Asia

by

Daryoush Charmsaz Moghaddam

MS, Sharif University, 2005

BS, Civil Aviation Higher Education Complex, 1985

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Information Technology

Walden University

March 2020

Exploring Software Testing Strategies Used On Software Applications In The Government, Angel Diane Cross

Walden Dissertations and Doctoral Studies

Developing a defect-free software application is a challenging task. Despite many years of experience, the intense development of reliable software remains a challenge. For this reason, software defects identified at the end of the testing phase are more expensive than those detected sooner. The purpose of this multiple case study is to explore the testing strategies software developers use to ensure the reliability of software applications in the government contracting industry. The target population consisted of software developers from 3 government contracting organizations located along the East Coast region of the United States. Lehman’s laws of software evolution was the …

Strategies To Lower Security Risks Involving Medical Devices In Patient Care, Brittany Latonia Thigpen

Walden Dissertations and Doctoral Studies

Insufficient security and design strategies used during the analysis phase of medical device software development can lead to possible cybersecurity vulnerabilities with patient data. The purpose of this qualitative exploratory multiple case study was to explore strategies software developers use to implement security measures to protect patient information collected, sent, and stored by medical devices. The population for this study included software developers whose primary focus was on the security aspect of medical software in three software companies in the Baton Rouge, LA, area. The data collection process included semistructured interviews with 10 software developers and reviewing 16 organizational documents. …

Exploring Cybersecurity Awareness And Training Strategies To Protect Information Systems And Data, Michael Hanna

Walden Dissertations and Doctoral Studies

Ineffective security education, training, and awareness (SETA) programs contribute to compromises of organizational information systems and data. Inappropriate actions from users due to ineffective SETA programs may result in legal consequences, fines, reputational damage, adverse impacts on national security, and criminal acts. Grounded in social cognitive theory, the purpose of this qualitative multiple case study was to explore strategies hospitality organizational information technology (IT) leaders utilized to implement SETA successfully. The participants were organizational IT leaders from four organizations in Hampton Roads, Virginia. Data collection was performed using telephone and video teleconference interviews with organizational IT leaders (n = 6) …

Strategies To Mitigate The Effects Of Identity Theft In The Hospitality Industry, Patricia Lee Jirsa

Walden Dissertations and Doctoral Studies

Leaders in the U.S. hospitality industry experience significant losses in profitability, increased mitigation cost, and reduced revenues because of business and consumer identity theft. Grounded in the fraud triangle theory and the fraud diamond theory, the purpose of this qualitative multiple-case study was to explore strategies leaders in the hospitality industry use to mitigate identity theft. A purposeful sample of 5 leaders of 5 different hospitality businesses in Montana participated in the study. Data were collected through semistructured interviews, member checking, and a review of company documents. During data analysis using Yin’s 5-step process, 3 key themes emerged: a new …

Relationship Between Specific Security Concerns And Cio Intention To Adopt Cloud, Johnathan Francis Van Houten

Walden Dissertations and Doctoral Studies

Cloud computing adoption rates have not grown commensurate with several well-known and substantially tangible benefits such as horizontal distribution and reduced cost, the latter both in terms of infrastructure and specialized personnel. The lack of adoption presents a challenge to both service providers from a sales perspective and service consumers from a usability focus. The purpose of this quantitative correlational study utilizing the technological, organizational, and environmental framework was to examine the relationship between shared technology (ST), malicious insiders (MI), account hijacking, data leakage, data protection, service partner trust (SP), regulatory concerns and the key decision-makers intention to adopt cloud …

Strategies Used In Ehealth Systems Adoption, Joshua Adams

Walden Dissertations and Doctoral Studies

Failure to adopt an interoperable eHealth system limits the accurate communication exchange of pertinent health-care-related data for diagnosis and treatment. Patient data are located in disparate health information systems, and the adoption of an interoperable eHealth system is complex and requires strategic planning by senior health care IT leaders. Grounded in DeLone and McLean’s information system success model, the purpose of this qualitative case study was to explore strategies used by some senior information technology (IT) health care leaders in the successful adoption of an eHealth system. The participants were 8 senior health care IT leaders in the eastern United …

Strategies To Implement Big Data Analytics In Telecommunications Organizations, Delton Aneato

Walden Dissertations and Doctoral Studies

Information Technology (IT) leaders who do not invest in big data projects may struggle to gain a competitive advantage and business insights to improve performance. Grounded in the Kotter’s change and Six Sigma models, the purpose of this qualitative multiple case study was to explore strategies IT leaders used to implement big data analytics successfully. The participants comprised 4 IT leaders from 2 telecommunication organizations in the United States of America, who effectively used strategies to promote and maximize competitive advantage using big data analytics. Data were collected from semistructured interviews, company documents, and project-related documents and were analyzed using …

The Challenges Of Adopting Cloud Computing In Nigerian Government Organizations, Ayodele Adegbenga Bakare

Walden Dissertations and Doctoral Studies

Several technical challenges prevent the adoption of cloud computing by government organizations in Nigeria. Information technology (IT) leaders in the Nigerian government are concerned about this problem because the lack of cloud computing adoption may prevent the Nigerian government from taking advantage of cloud-based information systems to improve its service delivery to citizens and businesses. Grounded in the technology acceptance model, the purpose of this quantitative correlational study was to examine if IT administrators’ perception of data security and perception of fault tolerance can predict their intentions to adopt cloud computing. Data were collected from 79 IT administrators in government …