Digital Commons Network^™

A Secure Cross-Domain Authentication Scheme Based On Threshold Signature For Mec, Lei Chen, Chong Guo, Bei Gong, Muhammad Waqas, Lihua Deng, Haowen Qin

Research outputs 2022 to 2026

The widespread adoption of fifth-generation mobile networks has spurred the rapid advancement of mobile edge computing (MEC). By decentralizing computing and storage resources to the network edge, MEC significantly enhances real-time data access services and enables efficient processing of large-scale dynamic data on resource-limited devices. However, MEC faces considerable security challenges, particularly in cross-domain service environments, where every device poses a potential security threat. To address this issue, this paper proposes a secure cross-domain authentication scheme based on a threshold signature tailored to MEC’s multi-subdomain nature. The proposed scheme employs a (t,n) threshold mechanism to bolster system resilience and security, …

Bmis 270.50: Mis Foundations For Business - Introduction To Mis, David R. Firth

University of Montana Course Syllabi, 2021-2025

No abstract provided.

The Lived Experiences Of High School Humanities Teachers As They Utilize An Lms To Facilitate And Support Students' Learning: A Phenomenological Study, Jamie L. Onorato

Doctoral Dissertations and Projects

High school humanity teachers at Big Wave High School utilize the Learning Management System (LMS), Canvas, in their 1:1 program, which this phenomenological study aimed to explore and better understand its role in the blended learning environment. The theories that guided this study are Slavich and Zimbardo’s transformational teaching theory and Bandura’s social cognitive theory of self-efficacy, which help the understanding of how evolving technology can be used in the field of education and therefore guided this study to explore the central research question: What are the lived experiences of high school teachers as they utilize LMS to facilitate and …

Method, System, And Computer Program Product For Determining A Carbon Foot Print Of Related Merchant Items, Sean Terribilini, Farrukh Umarov, Kaitlyn Sandford, Robert Juan King Lee

Defensive Publications Series

The present disclosure relates to a method that includes receiving a user input comprising a product identifier of a product, determining at least one related product based on the product identifier and at least one factor using a machine learning model, wherein the at least one factor comprises a source of the product, a source of the at least one related product, a predefined budget, past transaction history of the user, and carbon foot print of the product and the at least one related product, and providing data associated with the at least one related product and a total carbon …

Can Smart Supply Chain Bring Agility And Resilience For Enhanced Sustainable Business Performance?, Mahak Sharma, Rose Antony, Ashu Sharma, Tugrul Daim

Engineering and Technology Management Faculty Publications and Presentations

Purpose

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

Design/methodology/approach

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices …

Hybrid Time Series Forecasting Model For Provisioning Of Cloud Resources., Hp Inc

Defensive Publications Series

Predictive modeling or Forecasting is to predict the future using (time series related or other) data we have in hand. Cloud Infrastructure as a solution facilitates pay-as-you-use execution environments that scale transparently to the user. There is continuous challenge of configuring cloud infrastructure to provide maximal performance while minimizing the cost of resources used. This disclosure focuses time series data modeling to predict business requirements of a Cloud Platform and its application to daily infrastructure management. Such prediction can guide system design and deployment decisions such as scaling, scheduling, and capacity planning. Combining best two models on minimum variance approach …

Data Loss Prevention System Using Embeddings From An Ai Model, Amit Verma

Defensive Publications Series

A data loss prevention (DLP) system and method can use embeddings generated from possibly confidential data to determine if the data does, in fact, contain confidential data. The possibly confidential data is obtained from a software application, network firewall, cloud service, or other computing component. The system generates an embedding based on the possibly confidential data and compares the embedding to one or more embeddings stored in a data store. The stored embeddings are embeddings generated from known confidential data. Responsive to the generated embedding being above a threshold similarity to a stored embedding, the system may cause a DLP …

Integrated Key Management Block, Jeff Andersen, Charles Kunzman, Chris Sabol, Andrés Lagar-Cavilla, Amber Huffman

Defensive Publications Series

Encrypted data on a storage device (e.g., flash memory, hard disk drives, etc.) that is stolen or accessed by an attacker can be read by the attacker by using the onboard media encryption keys (MEK) to decrypt it. This disclosure describes a component, referred to as a key management block (KMB), that can be integrated into a storage device controller. The KMB provides services for generating and encrypting MEKs. The KMB enables a cloud service provider to have both host entropy and customer entropy for customer MEKs, such that decryption of a given section of customer data requires both the …

The Future Of Academic Reference Services In The Age Of Artificial Intelligence: An Overview, Lili Li, Kay Coates

Library Faculty Presentations

The purpose of this study explores the deep impact of ChatGPT on reference services in academic libraries. Based on the identified research literature, this study used the method of descriptive content analysis to evaluate the general capabilities of generative AI applications, such as ChatGPT, to transform reference services in academic libraries. With the homepage of the Georgia Southern University Libraries, two experienced librarians examined the potential of generative AI applications like ChatGPT to impact future reference services in ever-changing academic libraries. Based on the word limit, this study only focused on a few key areas of reference services, such as …

Discontent In The World City Of Singapore, Gordon Tan, Jessie P. H. Poon, Orlando Woods

Research Collection College of Integrative Studies

A burgeoning literature on ‘left behind’ places has emerged that captures the backlash against globalisation and highlights the locales that lag world cities. This paper integrates the ‘left behind’ and world cities literatures through the lens of discontent in the context of Singapore, using sentiment analysis and topic modelling as well as interviews with local professionals to unpack the multidimensional aspects of discontent. Focusing on the Singapore–India Comprehensive Economic Cooperation Agreement that spurred discontent directed at foreign Indian professionals, we show that the worlding generated by transnational flows has accentuated intra-urban inequality through racialisation and spatialisation of financial business and …

Getting Published And Raising Research Visibility, Pin Pin Yeo

Research Collection Library

Embarking on publishing your research can be exciting yet daunting. This seminar will guide you through crafting a compelling paper, navigating the submission process, and enhancing your paper's visibility. Learn what editors and reviewers seek, how to select the right journal, and how to publicise your research effectively. Whether you're a seasoned researcher or new to publishing, join us to amplify the impact of your work and share your discoveries with the world.

A New Update Is Ready To Be Installed: The Ever-Increasing Advancement Of The Video Game Industry., Tristen Schubert, Patrynna Mensah, Colin Lara, Nicholas Wasztyl

ENGL 1102 Showcase

The topics being discussed in this anthology all have a deep connection to video games and talk about the different aspects of the video game industry. This includes the way that video game narratives have changed, how video games use psychology to immerse their players, to how video games are able to be played through new services such as cloud gaming, and even how copyright works when it comes to video games. With all this in mind, this anthology strives to inform our readers about aspects of the video game industry that are crucial to its overall success.

System And Method For Interchangeable Virtual Currency In An Electronic Payment Processing Network, Akshay Chopra, Robert Juan King Lee, Kaitlyn Sandford, Dimitrios Kalogirou, Farrukh Umarov

Defensive Publications Series

The present disclosure includes a system and method for interchangeable virtual currency in an electronic payment processing network. The method includes receiving a transaction request initiated by a point-of-sale (POS) device including a payment device identifier and a transaction amount in a fiat currency. The method also includes determining a virtual currency identifier associated with the transaction request based on the payment device identifier. The method further includes determining an issuer system based on the payment device identifier and transmitting a transaction authorization request to the issuer system including the transaction amount and the virtual currency identifier. The method further …

Second April 2024 Faculty Senate Packet, University Of Nebraska At Kearney Faculty Senate

Faculty Senate Packets

No abstract provided.

The Implications Of Artificial Intelligence On Junior Auditors, Kaye Ragasajo

Senior Honors Theses

The aim of this paper is to explore the evolving intersection of financial statement auditing and artificial intelligence (AI). A timeline of AI adoption in auditing is traced, detailing its impact on audit processes and the contemporary role of junior auditors. Challenges faced by junior auditors are identified, with an emphasis on the potential benefits and ethical concerns surrounding AI integration. Recommendations for adapting to AI's emergence and addressing challenges are provided. The analysis underscores the need for industry-wide collaboration, regulatory adjustments, and the cultivation of digital ethics. As AI continues to reshape auditing, future trends expected within the profession …

User-Driven Data Privacy Protection In An Iot Environment, Nivetha B, Frank Michaud, Rahul Kata, Pranetha Priya R, Ganesh Paramasivan

Defensive Publications Series

Techniques are presented herein that enhance user data privacy in an Internet of things (IoT) environment. Aspects of the techniques introduce a third actor into such an environment – apart from a user and an IoT device – whose sole purpose is to empower a user to protect their own data. Such a data Custodian or Sanitizer may collect inputs from a user through a software as a service (SaaS) solution and then leverage the capabilities of the extended Berkeley Packet Filter (eBPF) to apply those inputs to an IoT device.

Second April 2024 Academic Affairs Minutes, University Of Nebraska At Kearney Academic Affairs Committee

Academic Affairs Committee Minutes

No abstract provided.

A Strategic Evaluation Of Educational Continuity For Accessibility During Uncertainty In An Educational Practicum, Mathew Nicho, Hussein Fakhry, Emad Bataineh, Shini Girija

All Works

Students from economically disadvantaged nations (EDN) face significant challenges in accessing high-quality education and securing global internships due to inadequate resources, funding, and infrastructure. The COVID-19 pandemic has highlighted the potential of online platforms for providing accessible, remote education and internship opportunities, aligning with UNESCO's sustainability education objectives. Using the SWOT analysis tool within the context of the experiential learning-driven integrated reflective cycle model (IRC), the research compares onsite and online internship types in higher education to identify areas where interventions can be applied to enhance the online internship experience. The study analyzed 42 interns, both on-site (OSIs) and online …

Remote Work Admist The Covid-19 Outbreak: Insights From An Ensemble Community-Based Keyword Network Analysis, Carlo Drago, Luisa Errichiello

Fondazione Eni Enrico Mattei Working Papers

COVID-19’s rapid shift to remote working has sparked interest in synthetizing the growing body of research in order to gain a comprehensive understanding into the scholarship structure of the field. This study explores the issue of pandemic-induced remote working from a multidisciplinary perspective, paving the way for further investigation and effective decision-making. A co-occurrence network analysis of keywords in scientific articles is employed to comprehensively analyze the international literature on pandemic-induced remote working. We use bibliometric analysis, network centrality measures, and community detection algorithms to identify key concepts, trends, and interconnections within the pandemic-induced research landscape. As a result of …

Dynamic Credit Limit Adjustemnt System, Palakh Shangle Visa

Defensive Publications Series

The present disclosure relates to a Dynamic Credit Limit Adjustment System which is an innovative financial technology solution designed to transform the way credit limits are managed by financial institutions. Utilizing advanced artificial intelligence (AI) and machine learning algorithms, this system dynamically adjusts an individual's credit limit in real-time based on a comprehensive analysis of their financial data. This system integrates various financial indicators such as income changes, spending patterns, payment history, and current economic trends to provide a more accurate and responsive credit limit. By doing so, it addresses the limitations of traditional credit limit assignment methods, which are …

Performing Distributed Quantum Calculations In A Multi-Cloud Architecture Secured By The Quantum Key Distribution Protocol, Jose Luis Lo Huang, Vincent C. Emeakaroha

Department of Computer Science Publications

Quantum computing (QC) is an emerging area that yearly improves and develops more advances in the number of qubits and the available infrastructure for public users. Nowadays, the main cloud service providers (CSP) are implementing different mechanisms to support access to their quantum computers, which can be used to perform small experiments, test hybrid algorithms and prove quantum theories. Recent research work have discussed the low capacity of using quantum computers in a single CSP to perform quantum computation that are needed to solve different experiments for real world problems. Thus, there are needs for computing powers in the form …

St. Cloud State University Employee Scholarship Bibliography [2023], Thomas D. Steman

Employee Scholarship Bibliographies

No abstract provided.

Prediction Of Cardiovascular Risk Factors From Retinal Fundus Photographs: Validation Of A Deep Learning Algorithm In A Prospective Non-Interventional Study In Kenya, Tom White, Viknesh Selvarajah, Fredrik Wolfhagen, Nils Svangård, Gayathri Mohankumar, Peter Fenici, Kathryn Rough, Nelson Onyango, Mansoor Saleh, Innocent Abayo

Haematology and Oncology, East Africa

Aim: Hypertension and diabetes mellitus (DM) are major causes of morbidity andmortality, with growing burdens in low-income countries where they are underdiag-nosed and undertreated. Advances in machine learning may provide opportunities toenhance diagnostics in settings with limited medical infrastructure.

Materials and Methods: A non-interventional study was conducted to develop andvalidate a machine learning algorithm to estimate cardiovascular clinical and labora-tory parameters. At two sites in Kenya, digital retinal fundus photographs were col-lected alongside blood pressure (BP), laboratory measures and medical history. Theperformance of machine learning models, originally trained using data from the UKBiobank, were evaluated for their ability to estimate …

Improving Prenatal Diagnosis Through Standards And Aggregation., Michael H Duyzend, Pilar Cacheiro, Julius O B Jacobsen, Jessica Giordano, Harrison Brand, Ronald J Wapner, Michael E Talkowski, Peter N Robinson, Damian Smedley

Faculty Research 2024

Advances in sequencing and imaging technologies enable enhanced assessment in the prenatal space, with a goal to diagnose and predict the natural history of disease, to direct targeted therapies, and to implement clinical management, including transfer of care, election of supportive care, and selection of surgical interventions. The current lack of standardization and aggregation stymies variant interpretation and gene discovery, which hinders the provision of prenatal precision medicine, leaving clinicians and patients without an accurate diagnosis. With large amounts of data generated, it is imperative to establish standards for data collection, processing, and aggregation. Aggregated and homogeneously processed genetic and …

Towards Robust Iot Security: A Blockchain Design With Attribute-Based Encryption, Bryan Ikei, Hanna Thiry, Shengjie Xu

Research & Publications

Internet of Things (IoT) data and devices face significant security concerns. It is well-known that IoT security standards and frameworks have yet to be established due to variations with IoT developers and manufacturers agreeing on fundamental design methods to address IoT security and its limited computational resources. This research aims to determine how security standards and frameworks can be better implemented to enhance IoT security. Specifically, this research investigates whether implementing an encryption scheme such as attribute-based encryption (ABE) along with blockchain, a distributed ledger technology (DLT), strengthens the security of IoT data and devices. In this context, an encryption …

State Constitutional Limitations To Cities Taxing The Digital Economy, Lauren Shores Pelikan

Faculty Publications

The digital economy’s rapid evolution, most recently with the rise of artificial intelligence, demands a reevaluation of state constitutional limitations on local taxation of digital transactions. Citizens have long feared excessive or unfair tax burdens, hence the adoption of constitutional amendments that prohibit legislators from increasing taxes or imposing new taxes without a public vote. However, these constitutional limitations are now preventing cities from taxing digital transactions that are taking over the economy. This is a serious financial problem for cities whose traditional sources of tax revenue, such as sales taxes and property taxes, are dwindling due to the digitalizing …

Examining The Role Of Immersive Technologies In Preparing Preservice Elementary Teachers: Augmented Reality, Integrated Stem, Teaching Self-Efficacy, And Technology Self-Efficacy, Deef Allah Al Shorman

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

This dissertation, utilizing a mixed-methods approach within a design-based research (DBR) framework, investigated the impact of augmented reality (AR) technology on the self-efficacy of preservice elementary teachers (PSTs) in integrated STEM teaching and technology. Incorporating both a pilot study and a subsequent dissertation study, the research specifically focused on the effects of AR GeoGebra. The key results that emerged from the pilot and dissertation studies highlight AR's potential to significantly enhance PSTs' STEM teaching self-efficacy. In both studies, the treatment group that engaged with AR GeoGebra showed substantial improvements in integrated STEM teaching self-efficacy. Additionally, in both studies, participants from …

Species Abundance Modelling Of Arctic-Boreal Zone Ducks Informed By Satellite Remote Sensing, Michael Allan Merchant, Michael Battaglia, Nancy H. French, Kevin Smith, Howard V. Singer, Llwellyn Armstrong, Vanessa B. Harriman, Stuart Slattery

Michigan Tech Publications, Part 2

The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ commonly use static (time invariant) habitat covariates to inform predictions, such as wetland type and extent maps. For the first time in this region, we developed species abundance models using high-resolution, time-varying wetland inundation data produced using satellite remote sensing methods. This data captured metrics of surface water extent and inundated vegetation in the …

Insights Into Privacy Protection Research In Ai, Shasha Yu

School of Professional Studies

This paper presents a systematic bibliometric analysis of the artificial intelligence (AI) domain to explore privacy protection research as AI technologies integrate and data privacy concerns rise. Understanding evolutionary patterns and current trends in this research is crucial. Leveraging bibliometric techniques, the authors analyze 8,322 papers from the Web of Science (WoS) database, spanning 1990 to 2023. The analysis highlights IEEE Transactions on Knowledge and Data Engineering and IEEE Access journals as highly influential, the former being an early contributor and the latter emerging as a pivotal source. The study demonstrates substantial disparities in scientific productivity across countries. Specifically, the …

Optimizing Data Access Using Symbolic Links And Machine Learning, Puneet Mahajan

Defensive Publications Series

Traditional data management practices replicate data across data centers and regions to ensure availability and performance. Such data replication can result in high operational costs, complex data management, inefficient resource utilization, etc. This disclosure describes techniques that address the inefficiencies and complexities of existing cloud storage and data access mechanisms by leveraging the simplicity and efficiency of symbolic links for data tables and by dynamically optimizing data access based on usage patterns discovered using machine learning. Unnecessary data replication is reduced, leading to simplified data management, efficient resource utilization, and lower operational costs. Data access in distributed environments is made …