Digital Commons Network^™

Cross-Model Watermarking Via Discriminative Samples For Secure Authentication, Juan Zhao, Yudao Sun, Zhihai Yang, Cai Xu, Hongji Chen, Fan Zhang, Jianxin Li

Research outputs 2022 to 2026

Deep neural networks on cloud platforms face growing security threats, with AI services increasingly relying on heterogeneous models for the same task to meet diverse user needs. Existing methods fail to distinguish benign modifications from malicious attacks in cross-model scenarios. To address this challenge, we propose a non-intrusive cross-model watermarking method that generates discriminative samples as universal keys, enabling authentication without altering model parameters or architectures. Specifically, we introduce a margin enhancement loss to amplify confidence gaps between benign and malicious behaviors, ensuring high transferability across models. Both theoretical analysis and experimental results demonstrate the high efficacy of our proposed …

Evaluating Response Calculation Methods For Thin And Volume Analog Holographic Wavefront Sensors, Emma Branigan, Andrew Lambert, Andreas Zepp, Szymon Gladysz, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Research Outputs: 2025-Present

The modal analog holographic wavefront sensor (AHWFS) is a low-cost and high-speed solution for wavefront sensing. It uses a phase biasing approach, where a pair of holograms are biased with a known phase delay/advance. The aberration magnitude is determined by measuring the diffracted beam intensities from the hologram pair. Both thin and volume phase transmission holograms can be used. Thin gratings produce multiple diffracted orders, while volume gratings direct light into a single order. Sensor response is measured using photodiodes or cameras, though thin holograms require a small region of interest for sensitivity to changing aberration magnitudes. This work compares …

Efficient Smooth Tensor Train And Tensor Ring Completion For Image Classification Enhancement, Salman Ahmadi-Asl, Roman V. Garaev, Rustam A. Lukmanov, Naeim Rezaeian, Asad Masood Khattak, Manuel Mazzara

All Works

This paper deals with studying the data completion problem for enhancing the image classification task under the pixel removal scenario. In some applications, it happens that a part of the pixels of a given image is lost due to several issues, such as corruption by outliers or artifacts and/or incompleteness due to imprecise data acquisition. This issue results in a completely wrong classification outcome using Deep Neural Networks (DNNs). In this paper we investigate the benefit of data completion in enhancing the classification accuracy of the DNN models to build more robust and stable DNN models. To this end, we …

Variations In Extreme Wet Days During The Ond Rainy Season In Tanzania And Their Linkages To Atmospheric-Oceanic Anomalies, Philemon Henry, Paul Ts Limbu

Tanzania Journal of Science

Extreme rainfall remains one of the leading natural disasters in Tanzania, affecting the majority of citizens and the country’s economy. Understanding the seasonal patterns and associated atmospheric and oceanic anomalies could help mitigate their impacts. The current study investigates changes in seasonal extreme wettest days (EWDs) rainfall in Tanzania and the associated atmospheric and oceanic anomalies during October-December (OND), from 1981 to 2020. EWD is defined as days when daily rainfall meets or exceeds the 99^th percentile. Singular value decomposition (SVD), Mann-Kendall, t-test, and Pettitt test methods were applied in this study. The results indicate that approximately 2 EWD …

A Novel Approach To Calculating Expected Total Fetal Lung Volume In Fetuses With Isolated Congenital Diaphragmatic Hernia And Fetal Growth Restriction: A Theoretical Computational Simulation, Morcos Hanna, Jonathan Davies, Amaryllis Fernandes, Pamela M Ketwaroo, Amy R Mehollin-Ray, Roopali Donepudi, Alice King, Joseph Hagan, Sundeep G Keswani, Sharada H Gowda, Caraciolo J Fernandes

Faculty, Staff and Students Publications

Objectives: Congenital diaphragmatic hernia (CDH) often coexists with fetal growth restriction (FGR). The observed-to-expected (O/E) total fetal lung volume (TFLV) is used to assess CDH severity, predict outcomes, and direct fetal interventions. Expected TFLV measurements traditionally rely only on gestation age (GA). This simulation assesses how incorporating weight-adjusted GA norms affects O/E TFLV calculations in patients with isolated CDH and FGR.

Methods: A simulated dataset (n=1,005) utilized published mean fetal weight and TFLV references. Computer-generated variables included observed weights (3rd-10th %ile), O/E TFLV (10-65 %), and percent liver herniation (0-42 %). GA estimates were corrected by weight and used to …

Correcting For The Inflated Adult Population Denominator In An English Nationwide Health Care Cohort: Database Analysis Study, Sudhir Venkatesan, Mark Joy, Gavin Jamie, Debasish Kar, Robert Williams, Xuejuan Fan, Wilhelmine Meeraus, Ruby S.M. Tsang, Kathryn S. Taylor, Sylvia Taylor, F. D. Richard Hobbs, Sneha N. Anand, Chris Robertson, Simon De Lusignan

Peninsula Medical School

Background:Electronic health care databases are widely used for epidemiological studies. However, they may contain inactive records of individuals no longer participating in the health care system. These inactive records create a methodological challenge as they systematically appear as unexposed with no recorded outcomes. Given the widespread health care system engagement during the COVID-19 pandemic, the English National Health Service (NHS), which hosts a national pandemic planning and research dataset with linkage to COVID-19 vaccination and emergency care data, makes it an ideal setting to identify the extent of overrepresentation due to inactive health care records and assess ways to mitigate …

Process-Driven Manufacturability Constraints In Design For Wire Arc Additive Manufacturing, Monsuru Ramoni, Sampson Gholston, Albert E. Patterson

Manufacturing & Industrial Engineering Faculty Publications

Wire arc additive manufacturing (WAAM) has emerged as a useful option for large-scale metal additive manufacturing. It has gained widespread use in the aerospace industry and other applications that require large and complex custom parts. The process is a combination of a precise control system and a welding process, typically GTAW or MIG welding. It is a member of the directed energy deposition (DED) family of AM processes. Compared with many metal AM processes, it is relatively simple and cost-effective but almost always requires a significant amount of postprocessing before parts can be used. The AM-based nature of the process …

Determinant Of Import In Indonesia, Muhamad Yunanto, Henny Medyawati

Jurnal Ekonomi dan Studi Pembangunan

Trade activities, particularly import, remain an interesting area of research. Therefore, this research aims to analyze the effect of inflation, Gross Domestic Product (GDP), Bank Indonesia interest rate (BI Rate), and exchange rates on Indonesian import. Quarterly time series data from 2010-2022 were obtained from Bank Indonesia and the Central Bureau of Statistics. Data was then analyzed using the Vector Error Correction Model (VECM) as the estimation tool. The results showed that GDP, interest rate, exchange rate, and inflation rate had a positive effect on import in the short and long term. A key contribution of this research was the …

Is Trade Openness A Supportive Instrument For Human Development: A New Look On Newly Industrialized Economies, Tufail Hussain, Teguh Yudo Wicaksono

Jurnal Ekonomi dan Studi Pembangunan

Formulating policies to enhance human well-being requires an urgent need to understand the drivers of human well-being. Therefore, the current study has proposed the socio-economic factors to investigate the main and moderate role of trade openness on Human Development for newly industrialized economies over 1990-2021. The current study shows the association between gross national income, urbanization, trade openness, labor force participation, foreign direct investment, and financial development. This study employs the fully modified and dynamic ordinary least squares for the reliable outcome. Empirical findings show that gross national income, urbanization, financial development, and labor force participation increase human development. Likewise, …

Educator Perceptions On Preparing Students For A Biology I State Assessment, Lila Grooms

Walden Dissertations and Doctoral Studies

The problem addressed through this study was that 9th and 10th grade students’ Biology I state assessment scores continued to decline in a suburban South Carolina school district. The purpose of this basic qualitative study was to explore biology teachers’ perceptions of the low success rates on the Biology I state assessment and to identify recommendations for improvement. Vygotsky’s social constructivism theory provided the conceptual framework, emphasizing the role of social engagement and collaborative learning environments. Semistructured interviews with nine high school biology teachers were conducted and using Braun and Clark’s thematic analysis approach. Themes revealed that teachers are: (a) …

Bimw: Blockchain-Enabled Innocuous Model Watermarking For Secure Ownership Verification, Xinyun Liu, Ronghua Xu

Michigan Tech Publications

The integration of artificial intelligence (AI) and edge computing gives rise to edge intelligence (EI), which offers effective solutions to the limitations of traditional cloud-based AI; however, deploying models across distributed edge platforms raises concerns regarding authenticity, thereby necessitating robust mechanisms for ownership verification. Currently, backdoor-based model watermarking techniques represent a state-of-the-art approach for ownership verification; however, their reliance on model poisoning introduces potential security risks and unintended behaviors. To solve this challenge, we propose BIMW, a blockchain-enabled innocuous model watermarking framework that ensures secure and trustworthy AI model deployment and sharing in distributed edge computing environments. Unlike widely applied …

User Privacy In The Digital Playground: An In-Depth Investigation Of Facebook Instant Games, Sideeq Bello

LSU Master's Theses

Amid growing concerns over data privacy in web and mobile applications, this study aims to assess the privacy mechanisms in instant games on Facebook, a platform with approximately 3.03 billion monthly active users and a substantial repository of personal data. Instant Games have become increasingly popular due to their ease of access and social integration features. Investigating these games can provide insights into privacy mechanisms and practices, thereby informing the development of more fair, compliant, and user privacy-centric gaming experiences. Thus, this study proposes an integrated analytical framework that leverages a combination of descriptive, memory, and network analysis techniques to …

Sustainable Robotic Construction: A Computational Particle Packing Approach For The Development Of Sustainable, Low-Cement 3d Printable Materials, Aranya Aumit Paul

LSU Master's Theses

Construction 3D Printing (C3DP) holds great potential for automated construction but faces key challenges, including the high Portland cement content of its printing materials. The high cement content raises material costs, causes shrinkage and thermal cracking, and increases its carbon footprint. This study introduces a novel hybrid computational pipeline that combines image based automated gradation analysis with 2D stochastic particle packing simulation, to design low-cement printable materials with minimal experimental testing. The image-based gradation system achieved a mean absolute error under 3.64% across six fine and coarse aggregate types. The particle packing simulation demonstrated an average error of less than …

Grade 6–8 Teacher Perceptions Regarding Teacher Resiliency Factors In A Northeastern State’S Public Middle Schools, Melanie Totten-Jonas

Walden Dissertations and Doctoral Studies

Teacher attrition presents a significant challenge for Northeastern State Middle School Districts (NSMSD), threatening educational stability and student outcomes. This qualitative study examined Grade 6–8 teachers’ perceptions of resilience as a factor influencing their decisions to remain in the teaching profession. Grounded in resilience theory, the study explored how teachers overcame professional challenges and identified supports that promoted retention, addressing a gap in existing research. Using a basic qualitative design, semistructured interviews were conducted with 14 purposefully selected middle school teachers from NSMSD. Reflexive thematic analysis using open coding revealed five key themes: individual resilience factors, relational supports and collegial …

Special Education High School Teachers’ Challenges With Implementing Social Emotional Learning, Ebonye Young

Walden Dissertations and Doctoral Studies

The problem that this study investigated was that special education high school teachers (SEHSTs) struggled with implementing social emotional learning (SEL) into their teaching of core subjects in Maryland high schools. The purpose of this basic qualitative study was to explore SEHSTs’ perceptions of the challenges with implementing SEL into core subject areas. The conceptual framework that grounded this study was Argyris and Schon’s theory of action. Using a basic qualitative design, 10 SEHSTs participated in semistructured interviews. Participants were Maryland licensed high school special educators with a range of experience in teaching co-taught classes. Coding and thematic analysis were …

High School Instructional Staff Perspectives On Effective Strategies For Increasing Enrollment In The Career And Technical Education Pathway, Briana O'Brien

Walden Dissertations and Doctoral Studies

The problem addressed in this study was the challenges of enrolling students in the career and technical education (CTE) pathway at a northeastern high school, despite local and national commitments to expanding CTE opportunities. The purpose of this basic qualitative study was to explore high school instructional staff perceptions of the challenges in enrolling students in the CTE pathway and the strategies they suggest would increase enrollment. The study was grounded in the conceptual framework of the concerns-based adoption model and the expectancy-value theory, which allowed for an understanding of staff concerns, motivations, and perceptions in relation to student enrollment …

Qualitative Insights Into The Complexity Of Calling: Moving Beyond Quantitative Boundaries, Jeannel King

The Qualitative Report

Why are deeply personal and lived experiences often reduced to standardized measurements? Calling is one such experience. Although widely recognized as complex, personal, and contextually shaped, the concept of calling has most often been researched through quantitative methods over the past two decades. This study employed qualitative content analysis (QCA) to examine how calling was researched across 267 peer-reviewed journal articles, trace methodological patterns, and consider how those choices influence the field’s conceptualizations of the construct. The analysis integrated deductive coding of methodological features and inductive identification of conceptual themes, refined through abductive synthesis. This hybrid strategy positioned the study …

Excessive Expulsions And School Suspensions Of Black Children, Lasharee O. Rogers

Walden Dissertations and Doctoral Studies

While national and state-level literature has documented racial inequities in school discipline, limited research has focused on how these policies are specifically implemented and perceived within the Charlotte Metropolitan Statistical Region School. The purpose of this basic qualitative study was to examine factors related to higher rate of expulsions and school suspensions of Black high school students in the CMSR Schools in comparison to their peers through the lens of the critical race theory. This research was used to engage teachers and administrators on current school suspension and expulsion policies while encouraging modifications to those policies that warranted equity and …

Parental Ses And Geographic Location As Predictors Of Graduations In Southeastern High Schools Before And After Covid-19, Marcy J. Watkins

Walden Dissertations and Doctoral Studies

African American students in the United States have long faced systemic barriers to high school completion, which were further intensified by the COVID-19 pandemic. The purpose of this quantitative, correlational-predictive study was to examine the extent to which parental SES and school location predict graduation outcomes among African American students in southeastern public high schools from 2019 to 2024. Grounded in Bandura’s social learning theory, the study explored how environmental and socioeconomic contexts influence academic achievement. Three research questions guided the study: (1) To what extent do parental SES and location combined predict the number of African American graduates? (2) …

Protocol For Assessing And Managing Radon Gas Exposure Risks In Caves: A Case Study Of Altamira And Paleolithic Cave Art Of Northern Spain World Heritage Site, Sergio Sanchez-Moral, Javier Lario, Soledad Cuezva, Juan Carlos Cañaveras, Tamara Martín-Pozas, Angel Fernández-Cortés

International Journal of Speleology

Exposure to radon and its progeny poses a significant health risk for workers in tourist caves. Implementing protective measures is challenging due to increasingly strict gas concentration and dose limits in new regulations. This study evaluates the annual effective radiation doses received by workers and researchers, considering seasonal and spatial radon variability. Radon levels, temperature, and ventilation patterns were continuously monitored for at least one year in each cave. Results show significant radon fluctuations influenced by seasonal ventilation regimes driven by thermal gradients between the cave and external atmosphere. Using International Commission on Radiological Protection guidelines, the study calculates the …

Integrating Seismic Survey Data With Zoning Maps For Enhanced Urban Safety And Structural Resilience, Shemsi Mustafa, Visar Krelani, Besian Sinani, Hazir Çadraku

UBT International Conference

Designing a safe and earthquake-resistant environment in seismically active regions requires detailed consideration of the seismic characteristics of urban areas. This study reviews the current frameworks for earthquake risk resistance in urban areas, highlighting the critical role of integrating seismic survey data with seismic zoning maps. Such integration is essential for designers to enhance resident safety and minimize structural damage. Therefore, it is necessary to holistically integrate seismic, geotechnical, geological, topographic, and design data to provide architects and planners with relevant and practical information for construction and land-use planning. Despite this, many cities in Kosovo, located in active seismic zones, …

Generating Arithmetic And Geometric Sequences In Java: A Mathematical Approach, Anjesa Gashi, Hizer Leka

UBT International Conference

This paper demonstrates how mathematical sequences, particularly arithmetic and geometric sequences, can be implemented in programming using Java arrays. In mathematics, sequences are ordered sets of numbers following a specific pattern, whereas in computer science, these sequences can be implemented as arrays. The main goal is to show the similarities between mathematics and programming. A simple Java program generates arithmetic and geometric arrays automatically, allowing students to visualize patterns and understand how to apply mathematical principles in code. This paper explains the process of writing the Java program and provides examples of output arrays. This approach solidifies the understanding of …

Traınıng And Development Of Varıous Open-Source Artıfıcıal Intellıgence Models For Busıness Process Automatıon, Senada Bushati Hoxha, Besmir Guma

UBT International Conference

AI is reshaping traditional businesses into sustainable operations, so it can be used to optimize resource utilization, automate processes for improved efficiency This study aims to explore the potential of open-source artificial intelligence (AI) models for automating and streamlining business processes. Focusing on a company offering a wide range of digital services (websites, applications, ERP, CRM, marketing), the study develops and trains two different AI models, specific to the needs of the business. The main goal is to create an AI “agent” that can interpret natural language commands and activate pre-configured automations through the n8n platform. These automated operations include …

Data Science Against Human Trafficking: Evidence From North Macedonia, Krenar Mehmeti, Shkurte Luma Osmani, Florinda Imeri, Agon Memeti

UBT International Conference

Human trafficking is a severe yet often underreported crime in North Macedonia. With the rapid growth of technology and communication platforms, traffickers have shifted recruitment and exploitation strategies online. This project explores the patterns and trends of human trafficking in Republic of North Macedonia through and through the lens of using Data Mining and Different visual analytics. By using a structured dataset containing Victim demographics, the types of exploitation, recruitment methods and other different attributes, the analysis is Focused on identifying vulnerable groups, especially the individuals of age 18-25 and underage minors. Advanced visualizations have revealed the distribution of trafficking …

An Empirical Analysis Of Requirements For An Automated Elearning Platform: The Case Of Teachers In Kosova, Bleona Çitaku, Faton Kabashi, Lamir Shkurti, Mirlinda Selimaj

UBT International Conference

This paper examines the need for developing an automated e-learning platform that supports adaptive learning for students in Kosovo. Using a mixed-methods approach—both quantitative and qualitative—the responses of 50 teachers were analyzed to understand their perceptions and the challenges associated with using platforms such as Google Classroom, Moodle, and Zoom. The findings indicate that, although there is significant potential to enhance teaching practices, key obstacles remain, including low student engagement and technological difficulties. The study suggests the development of a personalized platform powered by artificial intelligence to improve student participation and the overall effectiveness of distance learning.

Prime Numbers Through The Ages: Implementing The Sieve Of Eratosthenes In Java, Vesë Vrellaku, Hizer Leka, Alma Novoberdaliu

UBT International Conference

The Sieve of Eratosthenes is one of the oldest yet most efficient algorithms for finding prime numbers up to a given limit. This paper presents an analytical and practical implementation of the sieve, focusing on its mathematical foundations and optimized algorithmic behavior using the Java programming language. The aim is to demonstrate how ancient mathematical logic continues to be applicable in modern computational practices. The study outlines the basic sieve method, explores three critical optimizations that reduce time complexity, and evaluates the algorithm's performance in different scenarios. Moreover, this work contrasts the classical approach with similar prime-finding algorithms and emphasizes …

Socializing Math Equally? Exploring Gendered Assumptions In The Home Learning Environment, Besjanë Krasniqi, Susan Sonnenchein, Michele Stites, Emma Snyder

UBT International Conference

Although many parents believe they treat their children the same, subtle gender differences in how they support math learning may go unnoticed. This study examined how parents perceive their math socialization practices and whether they believe these would differ if their child were a different gender. Forty primary caregivers (88% mothers) of children aged 4–9 were interviewed about the home math environment. While all parents stated that math is equally important for boys and girls, 40% framed this around gender equality, 68% mentioned universal relevance, and 10% mentioned gendered differences in math ability. When asked how their behavior might change …

The Role Of Artificial Intelligence In Enhancing Public Awareness And Communication On Indoor Radon Risk, Margarita Kuqali, Ylli Kaçiu, Gazmend Nafezi, Frank Holzwarth

UBT International Conference

Radon is a naturally occurring radioactive gas and the second leading cause of lung cancer, particularly among non-smokers. Despite its health risks, public awareness of indoor radon exposure remains low in many countries, including Kosovo. Traditional risk communication often struggles to engage diverse populations or adapt to modern digital habits. This paper explores the potential of artificial intelligence (AI) to enhance radon awareness through intelligent communication tools. Natural language processing (NLP) and AI-powered chatbots can deliver instant, personalized, and accessible information tailored to different languages, literacy levels, and cultural contexts. Additionally, sentiment analysis of social media can detect misconceptions and …

The Role Of Artificial Intelligence In Developing Interactive And Intelligent Web Applications, Shkurte Zhegrova, Faton Kabashi, Mirlinda Selimaj, Vehebi Sofiu, Laura Gjikokaj

UBT International Conference

This study explores the integration of Artificial Intelligence (AI) into web programming, a field that has been rapidly transformed by the advancement of modern technologies. AI represents not only a relatively new and revolutionary innovation but also a crucial factor shaping the future of humanity, raising both opportunities for progress and concerns about potential workforce replacement in certain domains. The research begins with an overview of the history and evolution of AI, followed by an examination of its role in optimizing processes, addressing technical challenges, and enhancing user experiences in web development. With capabilities such as processing large datasets, learning …

Machine Learning -Project Data Analysis: Linear, Multiple, And Logistic Regression Diamond Price Prediction Diamond Price Category Prediction, Ardian Uka, Teuta Shala

UBT International Conference

The research presented here focuses into the use of machine learning techniques to predict diamond price and diamond price category prediction, based on key properties like: carat, cut, color, clarity, and physical dimensions. The study uses a structured dataset with both numerical and categorical characteristics to train and assess regression and classification algorithms. The project's goal is to create an accurate forecasting system that will benefit diamond market stakeholders through data preprocessing, visualization, and model comparison. The expected outcomes include obtaining a predicted accuracy of at least 80%, identifying the most influential features influencing diamond pricing, and determining the best-performing …