Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

A Brief Bibliometric Survey Of Explainable Ai In Medical Field, Nilkanth Mukund Deshpande, Shilpa Shailesh Gite

Library Philosophy and Practice (e-journal)

_{^{Background: This study aims to analyze the work done in the field of explainability related to artificial intelligence, especially in the medical field from 2004 onwards using the bibliometric methods.}}

_{^{Methods: different articles based on the topic leukemia detection were retrieved using one of the most popular database- Scopus. The articles are considered from 2004 onwards. Scopus analyzer is used for different types of analysis including documents by year, source, county and so on. There are other different analysis tools such as VOSviewer Version 1.6.15. This is used for the analysis of different units such as co-authorship, co-occurrences, citation analysis …}}

Owsnet: Towards Real-Time Offensive Words Spotting Network For Consumer Iot Devices, Bharath Sudharsan, Sweta Malik, Peter Corcoran, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Every modern household owns at least a dozen of IoT devices like smart speakers, video doorbells, smartwatches, where most of them are equipped with a Keyword spotting(KWS) system-based digital voice assistant like Alexa. The state-of-the-art KWS systems require a large number of operations, higher computation, memory resources to show top performance. In this paper, in contrast to existing resource-demanding KWS systems, we propose a light-weight temporal convolution based KWS system named OWSNet, that can comfortably execute on a variety of IoT devices around us and can accurately spot multiple keywords in real-time without disturbing the device's routine functionalities.

When OWSNet …

Evaluation Of State-Of-The-Art Nlp Deep Learning Architectures On Commonsense Reasoning Task, Guo Rui (Justin) Lee

Honors Theses

The goal of this project was to explore modern neural network technology in the application of discerning and generating statements that are ‘reasonable’, in what is known as commonsense reasoning. We built off of the work of Saeedi et al. In their work on the 2020 SemEval task, Commonsense Validation and Explanation (ComVE). SemEval is a workshop that creates a variety of semantic evaluation tasks to examine the state of the art in the practical application of natural language processing. This particular task involved three sections: task A, Validation, in which a program tries to select which of two statements …

Cognitive Digital Twins For Smart Manufacturing, Muhammad Intizar Ali, Pankesh Patel, John G. Breslin, Ramy Harik, Amit Sheth

Publications

Smart manufacturing or Industry 4.0, a trend initiated a decade ago, aims to revolutionize traditional manufacturing using technology-driven approaches. Modern digital technologies such as the Industrial Internet of Things (IIoT), Big Data Analytics, Augmented/Virtual Reality, and Artificial Intelligence (AI) are the key enablers of new smart manufacturing approaches. The digital twin is an emerging concept whereby a digital replica can be built of any physical object. Digital twins are becoming mainstream; many organizations have started to rely on digital twins to monitor, analyze, and simulate physical assets and processes. The current use of digital twins for smart manufacturing is largely …

Human-Machine Communication: Complete Volume. Volume 2

Human-Machine Communication

This is the complete volume of HMC Volume 2.

Side Channel Attack Counter Measure Using A Moving Target Architecture, Jithin Joseph

Electrical and Computer Engineering ETDs

A novel countermeasure to side-channel power analysis attacks called Side-channel Power analysis Resistance for Encryption Algorithms using DPR or SPREAD is investigated in this thesis. The countermeasure leverages a strategy that is best characterized as a moving target architecture. Modern field programmable gate arrays (FPGA) architectures provide support for dynamic partial reconfiguration (DPR), a feature that allows real-time reconfiguration of the programmable logic (PL). The moving target architecture proposed in this work leverages DPR to implement a power analysis countermeasure to side-channel attacks, the most common of which are referred to as differential power analysis (DPA) and correlation power analysis …

Non-Linear Dimensionality Reduction Using Auto-Encoder For Optimized Malaria Infected Blood Cell Classifier, Aayush Dhakal

Honors Theses

Neural Networks have been widely used in the problem of Medical Image Analysis. However, when dealing with large images, deep networks easily exhaust computer resources, which in turn hinders training. This paper shows the efficacy of using Auto-Encoders as a dimensionality reduction tool to increase the efficiency of a Malaria Infected Blood Cell Image classifier. We show that using an autoencoder, we can reduce the dimensionality of large blood cell images effectively such that the features in the new space retain all the essential information from the original input. Then we show that the new features obtained from the autoencoder …

Machine Learning Meets Internet Of Things: From Theory To Practice, Bharath Sudharsan, Pankesh Patel

Publications

Standalone execution of problem-solving Artificial Intelligence (AI) on IoT devices produces a higher level of autonomy and privacy. This is because the sensitive user data collected by the devices need not be transmitted to the cloud for inference. The chipsets used to design IoT devices are resource-constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing complex problem-solving AI (usually an ML model) on IoT devices. Since there is a high potential for building intelligent IoT devices, in this tutorial, we teach researchers and developers; (i) How to …

Recent Trends In Cloud Computing And Edge Computing, Sonali Deshpande, Nilima Kulkarni

Library Philosophy and Practice (e-journal)

Background: This study aims to analyze the work done in domain of cloud computing and edge computing using artificial intelligence from 2015 to 2021. Recent research shows the bibliometric methods are useful for such kind of analysis. Thus in this paper analysis is carried out using the bibliometric methods.

Methods: different articles on edge computing and edge intelligence were retrieved using one of the most popular database- Scopus. The research articles are considered between 2015 to 2021. Scopus analyzer is used for getting some analysis results such as documents by year, source, country and so on. VOSviewer Version 1.6.16 is …

Second Version On A Centralized Approach To Reducing Burnouts In The It Industry Using Work Pattern Monitoring Using Artificial Intelligence Using Mongodb Atlas And Python, Sasibhushan Rao Chanthati

Harrisburg University Other Works

Industry burnout is interlinked with cultural, individual, physical, or emotional exhaustion, and social factors, the resolution of which requires the technology-driven trends in the workplace and the technologies such as work pattern monitoring and Artificial Intelligence that can deal with large amounts of data. Industries face a gigantic problem i.e., employee burnout which can charge a firm loss in numerous hours and thousands of dollars every year. The more advanced companies use work pattern monitoring using Artificial Intelligence to make their employees work more professionally. In this research my attempts to understand the development and leadership, on the effects of …

Coding Club, Nicole Livingston, Madalyn Meyer

Honors Program: Expanded Learning Clubs

Lesson plans for an about 12-week club designed to introduce middle schoolers to coding using Scratch. By the end of the club, every student will have made a game they can share with the class and have learned basic coding and game creation tools. Students can also miss classes or join late and still be able to join and enjoy the club with a different focus lesson every week.

How The Power Of Machine – Machine Learning, Data Science And Nlp Can Be Used To Prevent Spoofing And Reduce Financial Risks, Sasibhushan Rao Chanthati

Harrisburg University Other Works

This paper discusses the potential of machine learning, data science, and natural language processing (NLP) in mitigating the incidence of spoofing and financial risks hinged on cyber threats. Another one is spoofing; it is the act of impersonating legitimate entities to gain unauthorized information and it is indeed a threat to the public and companies to some extent. The research introduces two primary methodologies to combat spoofing: an email filtering system using a machine learning algorithm and an encryption and decryption system using a Caesar Cipher and Python programming language. It distinguishes between approved domains and unapproved domains by using …

On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead

Engineering Faculty Articles and Research

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can …

Analysis Of Recent Trends In Malware Attacks On Android Phone: A Survey Using Scopus Database, Sonali Kothari Tidke, Vijayshri Khedkar

Library Philosophy and Practice (e-journal)

In past few years, smartphone use has shifted from professional access to personal need. Smartphone has now become an essential requirement to perform day to day activities. This has made smartphones unsecured and vulnerable to cyber threats and malware attacks. This study is also focused on finding intersection between malware attacks and Android OS considering Android as the most widely used mobile OS. A comprehensive search is conducted on Scopus Database for peer-reviewed articles. The study is carried out on bibliometric data of the considered articles to generate a highly useful concept map.

Review And Analysis Of Failure Detection And Prevention Techniques In It Infrastructure Monitoring, Deepali Arun Bhanage, Ambika Vishal Pawar, K Kotecha

Library Philosophy and Practice (e-journal)

Maintaining the health of IT infrastructure components for improved reliability and availability is a research and innovation topic for many years. Identification and handling of failures are crucial and challenging due to the complexity of IT infrastructure. System logs are the primary source of information to diagnose and fix failures.

In this work, we address three essential research dimensions about failures, such as the need for failure handling in IT infrastructure, understanding the contribution of system-generated log in failure detection and reactive & proactive approaches used to deal with failure situations.

This study performs a comprehensive analysis of existing literature …

Towards A Blockchain Assisted Patient Owned System For Electronic Health Records, Tomilayo Fatokun, Avishek Nag, Sachin Sharma

Articles

Security and privacy of patients’ data is a major concern in the healthcare industry. In this paper, we propose a system that activates robust security and privacy of patients’ medical records as well as enables interoperability and data exchange between the different healthcare providers. The work proposes the shift from patient’s electronic health records being managed and controlled by the healthcare industry to a patient-centric application where patients are in control of their data. The aim of this research is to build an Electronic Healthcare Record (EHR) system that is layered on the Ethereum blockchain platform and smart contract in …

Pomegranate: Procedural 3d Tree Creation Via User-Defined L-Systems, Jeremy Berchtold

Computer Science and Software Engineering

Pomegranate creates procedural 3D trees based on a user-specified template. The template supports randomness and allows users to generate an entire forest of unique trees from a single template. The output trees are a single closed mesh without intersecting geometry (with the exception of leaves). Additionally, the output contains a skeletal rig used for animating the trees. Pomegranate produces textured trees that can use either a realistic or stylized look, as well as supporting different mesh densities for games or film. Since this project uses a procedural workflow, artists can quickly create and make edits to their trees. This increase …

Accelerating Point Set Registration For Automated Aerial Refueling, Ryan M. Raettig

Theses and Dissertations

The goal of AAR is to control the tanker boom to safely refuel a receiving aircraft with no input or aid from the boom operator. To achieve this, the pose of the receiver relative to the tanker must be known. Point set registration is a fundamental issue used to estimate the relative pose of an object in an environment. However, it's likely a computational bottleneck of a vision processing pipeline. In addition, the matching of each sensed point with a closest truth point, nearest neighbor matching, is the most costly portion of the point set registration process. For this reason, …

Analysis Of Recent Trends In Continuous Sign Language Recognition Using Nlp, Vijayshri Nitin Khedkar, Sonali Kothari Dr, Aarohi Prasad, Arunima Mishra, Varun Saha, Vinay Kumar

Library Philosophy and Practice (e-journal)

Oralism is an ideology and practice that advocates communication that is based solely on speech. This practice is encouraged from a pretty early age in our country. As a consequence, the hard of hearing are constantly forced to negotiate with schools, colleges, organisations, workspaces, and families that don’t acknowledge the need and preference for sign language over oral languages. This results in inconsideration of an entire community for admissions, jobs and general social position. We aim to close that communication gap a little and take a step towards fighting the stigma associated with Sign Language. The aim is to provide …