Digital Commons Network^™

A Systematic Review Of Audio Deepfake Detection Techniques For Digital Investigation, Mahra Alnaqbi, Richard Adeyemi Ikuesan

All Works

Deepfake technology has been driven by advanced machine learning and revolutionized multimedia creation by synthesizing hyper-realistic content. It includes images, videos, and audio. While its creative applications in entertainment and accessibility are significant, the technology also poses critical risks, especially in fraud, disinformation, and identity theft. Audio deepfakes are a subset of this phenomenon that replicate human voices with enhanced precision, mimicking tone, accent, and subtle vocal nuances. This has raised concerns in security-sensitive domains like voice authentication and forensic investigations. This systematic literature review (SLR) adopts PRISMA guidelines to explore the state-of-the-art in audio deepfake detection. It examines existing …

Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan

All Works

Globally, age-related macular degeneration (AMD) remains a main cause of irreversible vision loss. Recently, deep learning models have primarily focused on classifying fundus images for early detection of AMD progression. However, existing models rarely address the generation of future progression-aware fundus images, particularly when complete real longitudinal follow-up scans are unavailable. This limitation makes it difficult to track retinal changes over time and highlights the need for generative models capable of producing realistic drusen-level structural variations. To address these issues, a novel deep learning-based FIG-GAN model is to generate synthetic future fundus images from baseline inputs. Multi-Attention U-Net (MAU-Net) is …

Reimagining Sustainable Sulfur Concrete: A Systematic Review Of Sulfur, Waste Integration, And Durability, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa Elgamal

All Works

Sulfur concrete (SC) - a thermoplastic, waterless composite in which molten sulfur-based binder replaces Portland cement - is attracting growing research attention as a sustainable construction alternative capable of superior performance in chemically aggressive environments. This systematic literature review synthesises evidence from 127 sources (2000–2025), examining three interlinked dimensions: (i) the role of waste and industrial by-product materials as aggregate and filler substitutes; (ii) the influence of aggregate type, morphology, and grading on mechanical and microstructural performance; and (iii) durability under acid, saline, and freeze-thaw exposures. A transparent, PRISMA-aligned screening and classification protocol - here used as a structured review …

A Performance-Optimized V2v Task Offloading Framework For Real-Time Vehicular Communication, Tariq Qayyum, Asadullah Tariq, Ikbal Taleb, Mohamed Adel Serhani, Zouheir Trabelsi

All Works

As vehicular applications become increasingly complex, their computational demands often exceed the capabilities of individual vehicles. Vehicular Edge Computing (VEC) alleviates this limitation by enabling task delegation to nearby edge resources; however, high mobility, dynamic topology, and fluctuating vehicle density make real-time offloading decisions challenging. To address these issues, we propose a performance-optimized Vehicle-to-Vehicle (V2V) task offloading framework for dense and dynamic Vehicular Ad-hoc Networks (VANETs). The framework follows a two-stage design: (i) context-aware edge-node selection based on live topology capture via periodic beaconing, and (ii) cumulative score-based dynamic priority queuing at the selected edge node. The priority score jointly …

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Kindergarten Teachers’ Perceptions Of Instructional Approaches For Teaching Sequencing Concepts: Worksheet, Hands-On, And Beebot-Integrated Lessons, Savannah P. Partin

Electronic Theses and Dissertations

The purpose of this qualitative multiple-case study was to explore kindergarten teachers’ perceptions of three instructional approaches for teaching sequencing concepts: worksheet-based instruction, hands-on manipulative instruction, and BeeBot-integrated instruction. Sequencing is a foundational early literacy skill that supports reading comprehension, story retelling, and understanding the order of events. Although sequencing is commonly taught through traditional instructional methods, limited research has examined how kindergarten teachers perceive the use of educational robotics as a tool for literacy instruction. The study was guided by constructivist theory, sociocultural theory, and developmental systems theory. Participants included six kindergarten teachers from a public elementary school in …

Evolving Ai Integration In Complex Medical Decision-Making And Multidisciplinary Transplant Care: A Systematic Review Of Human-Ai Collaboration, Rachel L. Dzieran, Cihan H. Dagli, Robert J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: Artificial intelligence (AI) in healthcare has evolved dramatically from early expert systems, which were initially considered replacements for clinical judgment, to today's collaborative frameworks that aim to augment physician decision-making. This evolution is particularly crucial in domains such as transplant surgery, where decisions carry irreversible consequences and require the integration of complex, often ambiguous data. Drawing on peer-reviewed literature from 2019 to 2025, we conducted a systematic review that analyzed key elements distinguishing successful human-AI partnerships from those that fail. Recent Findings: The ideal balance incorporates human expertise into AI systems through weighted integration approaches, rather than …

Aluminium Based Hydrotalcite Like Compounds For Direct Lithium Extraction: A Critical Review On Crystallography And Structure Selectivity Design, Amin Sarmadi, Yasaman Boroumand, Mohammad Mahdi A. Shirazi, Magdalena Wajrak, Shayan Abrishami, Matthew Myers, Muhammad Rizwan Azhar, Amir Razmjou

Research outputs 2022 to 2026

The accelerating demand for lithium is intensifying interest in direct lithium extraction (DLE) technologies that minimise the environmental footprint of conventional solar evaporation ponds. Among sorbent-based DLE concepts, aluminium based hydrotalcite like compounds (Al-HTlc), particularly lithium aluminium layered double hydroxide (LiAl-LDH), are considered the most mature sorbent options, offering facile lithium (Li+) recovery and high selectivity in highly saline chloride based solutions. Both properties arise from a distinct intercalation mechanism wherein Li+ and its counter-anions (e.g. Cl− or SO42−) are co-intercalated into the crystal structure upon brine exposure. Li+ selectivity arises partly from a steric match between Li+ (ionic radius …

A Consolidated Mössbauer Spectrum For Undisturbed Soils From Gusev Crater, Mars, Paulo De Souza

Research outputs 2022 to 2026

Mossbauer analyses from MIMOS II data collected on Mars provided breakthrough insights into iron mineralogy of the planet’s surface. Resulting from limited measurement time, science operations were divided among multiple instruments, restricting the detection of minor Fe-bearing mineral phases (below 5% WSA). MIMOS II records Mössbauer spectra at 10 K intervals, and to enhance signal to noise ratios, spectra from different intervals were combined, when applicable. For instance, temperature variations between 190 K and 270 K in basaltic samples do not significantly impact the spectra, allowing data from all intervals to be integrated. By combining MIMOS II data from various …

Characterization Of Droplet Size And Their Distribution Using Low Operating Conditions In A Rotary Bell Cup Spray-Field Via Shadowgraph, Murad Ali Channa, Mehdi Khiadani, Yasir M. Al-Abdeli

Research outputs 2022 to 2026

This study characterises droplet size and distribution across axial (x/D) and radial (r/D) locations in the spray field of a rotary bell-cup atomizer under low operating conditions. Shadowgraph was used to measure droplet size and distribution at 16 dimensionless locations in both directions. Two low rotational-speed ranges, 3–3.5 krpm (case I) and 8–8.5 krpm (case II), were achieved using shaping-air of 30–100 L/min under turning-air of 50 and 60 L/min, respectively, at a constant flow rate of 0.5 L/min. The Sauter mean droplet diameter ranged from ∼ 45–98 µm in case I and narrowed to ∼ 45–85 µm in case …

Dataset For Integrity Attacks On Time Synchronized Synchrophasor Data, Taylah Griffiths, Mohiuddin Ahmed, Chadni Islam

Research outputs 2022 to 2026

Phasor measurement units, also known as synchrophasors, are a vital component within smart grids to determine the stability of the grid. These devices send synchrophasor data to phasor data concentrators that collate and analyse the data. Recently, synchrophasor communication data has become beneficial for the research community. However, datasets covering cyberattacks on synchrophasor data are not public. Having access to this data would aid in investigating mitigations against cyberattacks. This paper describes a public specialized dataset, known as ECU-PMU-FDI/TSA. The dataset contains synchrophasor communication data for cybersecurity mitigation testing. Three hours of communication data was captured, from a simulated testbed. …

Suicide Ideation Detection Using Social Media Data And Ensemble Machine Learning Model, Erol Kina, Jin Ghoo Choi, Abid Ishaq, Rahman Shafique, Monica Gracia Villar, Eduardo Silva Alvarado, Isabel De La Torre Diez, Imran Ashraf

Research outputs 2022 to 2026

Identifying the emotional state of individuals has useful applications, particularly to reduce the risk of suicide. Users’ thoughts on social media platforms can be used to find cues on the emotional state of individuals. Clinical approaches to suicide ideation detection primarily rely on evaluation by psychologists, medical experts, etc., which is time-consuming and requires medical expertise. Machine learning approaches have shown potential in automating suicide detection. In this regard, this study presents a soft voting ensemble model (SVEM) by leveraging random forest, logistic regression, and stochastic gradient descent classifiers using soft voting. In addition, for the robust training of SVEM, …

Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni

Research outputs 2022 to 2026

This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of …

Natural Gas Hydrate Production And Co2 Storage Via Clathrate Hydrates: Challenges And Opportunities, Abdirahman Hassan Mohamed, Aliyu Adebayo Sulaimon, Haylay Tsegab, Bhajan Lal, Stefan Iglauer, Muhammad Ali

Research outputs 2022 to 2026

One of the most demanding environmental and economic challenges of this era is that of supplying the increasing global energy demand while reducing and neutralizing the CO2 footprint. In this regard, the provision of a secure and diversified energy supply and the sequestration of CO2 into geological formations are currently of great significance. However, the buoyant nature of CO2 under the temperature and pressure conditions of typical geological sites leads to the risk of CO2 leakage, and thus necessitates long-term monitoring. Therefore, the hydrate-based sequestration of CO2 beneath oceanic sediments has become a desirable alternative to conventional geologic sequestration in …

Over A Century Of Global Decline In The Growth Performance Of Marine Fishes, Helen F. Yan, Hannah V. Watkins, Alexandre C. Siqueira, David R. Bellwood

Research outputs 2022 to 2026

Human-driven pressures are causing large-scale changes in the ecologies and life histories of fishes. Growth performance is a composite life-history trait that captures the trade-off between two fundamental traits: growth and body size. Here, we assess the impacts of fishing and temperature on the growth performance of marine teleost fishes globally over the last century. Using 7683 growth curves encompassing 1479 species, we find a global pattern of decline in growth performance from 1908 onwards, with the greatest declines in commercially valuable fishes. Indeed, managed fisheries experienced a 9% decline in growth performance over the last century, which can equate …

Switching Configurations For Reconfigurable Battery Packs: A Review, Kenneth Tetteh Akiti, Quoc Viet Phung, Iftekhar Ahmad, Daryoush Habibi

Research outputs 2022 to 2026

Conventional Battery Energy Storage Systems (BESS) are designed with fixed cell topologies, where the electrical connection between cells remains unchanged throughout their life. Although Battery Management Systems (BMS) and conventional cell-balancing techniques are employed to monitor and maintain performance, they often fail to address key challenges such as uneven cell aging, capacity mismatch, and fault isolation that arise especially during the second life of a battery pack. These limitations can result in reduced efficiency, reduced reliability, and shortened battery life. As large-scale battery packs become increasingly common in Electric Vehicles (EVs), smart grids, robotics, and renewable energy systems, the limitations …

Design Of Automatic Security System Based Internet Of Things At The Museum, Rahmat Ageng Yuwana, Nuryake Fajaryati, Ferry Jie

Elinvo (Electronics, Informatics, and Vocational Education)

This research aims to determine the procedures for developing an Internet of Things (IoT)-based Automatic Security System as a security device for museum objects and to test its feasibility based on user feedback in museums. The Design Thinking model used consists of five stages: Empathize (understanding the user’s perspective), Define (gathering information on the encountered problems), Ideate (generating innovative ideas), Prototype (creating a prototype of the obtained ideas, ensuring the functionality of each device feature, and validating the product through expert judgment for feedback and product revision), and Testing (evaluating the system’s feasibility using Usability standards based on ISO/IEC 9241-11, …

We All Read: Adapting An Early Literacy Program For Children With Developmental Differences And Their Families, Rachel Podl

Graduate School of Professional Psychology: Doctoral Papers and Masters Projects

Children with developmental differences face elevated risk for early literacy delays, while their caregivers experience significant difficulty accessing appropriate and supportive resources. This paper describes an adaptation of WeRead, an existing story-time and psychoeducation program through the University of Denver's Baby S.T.E.P.S. Lab, for children ages 0–7 with developmental differences and their caregivers. The program integrated a neurodiversity-affirming read-aloud, a strengths-based art activity, movement and music, caregiver psychoeducation on visual schedules, and collaboration with four community partners. The event drew approximately 65 attendees. A post-program survey, though limited by few responses, indicated that caregivers valued the program's accessibility, community partnerships, …

Lithium Titanate-Functionalized Mixed Matrix Polymer Membrane For High-Performance Osmotic Energy Conversion, Rockson Kwesi Tonnah, Yasaman Boroumand, Milad Razbin, Mostafa Vahdani, Amir Razmjou, Mohsen Asadnia

Research outputs 2022 to 2026

Reverse electrodialysis (RED) offers a promising route to harvest osmotic energy from salinity gradients, yet practical implementation is hindered by the lack of scalable, high-performance ion-selective membranes that combine efficient ion transport with mechanical robustness and environmental sustainability. Here, we report a mixed matrix membrane composed of polyethersulfone (PES), polyvinylpyrrolidone (PVP), and lithium titanium oxide (Li₂TiO₃, LTO) that addresses these challenges through biomimetic ion transport channels. The strategic integration of LTO nanoparticles introduces ion-exchange sites and oxygen-rich PES ether linkages to create preferential cation transport pathways that mimic biological ion channels. This mixed matrix design delivers over three-fold cation conduction, …

Mechanically Stabilized Porous Aerophilicity Unlocks Ampere-Rate Transport-Limited Co2 Electroreduction To Ethylene, Ahmed Badreldin, Lanxin Guo, Carter Racine, Gabriella Smith, Shaoqin Chen, Shengyao Wang, Baiyu Zhang, Mohammed Majdoub, Ahmed Al-Ostaz, Yun Hang Hu, Qingsheng Wang, Ying Li

Michigan Tech Publications

Gas-fed electrochemical CO2 reduction (CO2R) to multicarbon products is fundamentally constrained by mass-transport limitations that suppress selectivity and stability at industrially relevant current densities. Here, we demonstrate that these bottlenecks can be overcome by engineering a porous aerophilic polymer microenvironment around a simple CuxO electrocatalyst without altering the intrinsic catalyst. By systematically replacing conventional PFSA ionomers with mixed aerophilic binders and applying a mild thermal treatment, we construct mechanically stabilized, gas-accessible overlayers that regulate the local gas-liquid microenvironment balance at the three-phase boundary (TPB). This approach drives a dramatic enhancement in ethylene production, increasing the partial current density from 135 …

Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration, Ziqiang Liu, Fujian Tang, Yufang He, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Liquefied petroleum gas (LPG) is a highly flammable fuel widely used for cooking, heating and transportation, making real-time leak detection essential for preventing fire, explosion, and suffocation hazards. In this study, a room-temperature no-core fiber (NCF) sensor coated with CoFe_1.96La_0.04O₄/LaFeO₃ heterostructures was developed for LPG detection. The heterostructures were characterized using XRD, Raman spectroscopy, SEM, TEM, XPS, PL spectroscopy, and UV–vis spectroscopy. Experimental results showed that La incorporation and heterostructure formation refined the particles size, improved surface accessibility, and modulated the electronic structure and band gap, thereby enhancing LPG adsorption, carrier redistribution, and …

The Missouri Miner, November 10, 2016

The Missouri Miner Newspaper

No abstract provided.

Going With The Flow: Peptide Affinity Membranes For High-Throughput, High-Yield Purification Of Adenovirus And Lentiviral Vectors, Yuxuan Wu, Arianna Minzoni, Aishwarya Gangadhar, William Smith, Eduardo Barbieri, Irfan Ismail, Luke Remmler, Michael A. Daniele, Stefano Menegatti

Michigan Tech Publications

Membrane chromatography offers a compelling alternative to packed-bed resins for viral vector purification, as its open porosity and convective mass transport eliminate diffusive mass transfer limitations, enabling processing at substantially shorter residence times. Yet, the translation of affinity ligands from resins to membranes is challenged by the low density of reactive groups, which constrains functional ligand loading and limits binding capacity. Seeking to overcome this limitation, this study presents a method for functionalizing cellulose membranes with peptide affinity ligands and demonstrates its application to the purification of adenovirus serotype 5 (AdV5), VSV-G and Cocal pseudotyped lentiviral vectors (LVVs), and adeno-associated …

Immunomodulatory Role Of Muc5ac In Lung Cancer Progression, Julia G. Kim

Summer Research Program Abstracts

No abstract provided.

Prototyping Pinhole Collimators For Imaging Irradiated Nuclear Fuel, Narrie Loftus, Ashish Avachat, Joseph T. Graham, Ryan Fronk, Jordan Fox, Rachel Shaffer, Seth Kilby

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

Collimator design and fabrication is a costly and time-consuming process that does not lend itself to simplified testing. This manuscript presents an approach for the rapid prototyping of sub-millimeter pinhole collimators for nuclear fuel applications using low-melting-point, high-mass-density materials. Multiple collimators were fabricated to test collimator parameters and properties, including acceptance angle, aperture diameter, and magnification. The fabricated collimators were paired with a position-sensitive CdZnTe detector to determine the detector response convolved with the collimator. Preliminary analysis using these collimators showed that they were effective in collimating multi-energy gamma laboratory sources. Radiography was performed to confirm magnification and determine coarse …

Spatialimaginer: Towards Adaptive Visual Imagination For Spatial Reasoning, Yian Li, Yang Jiao, Bin Zhu, Tianwen Qian, Shaoxiang Chen, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language models. Despite promising performance, recent multimodal large language models (MLLMs) often exhibit fragile reasoning traces in spatial intelligence tasks that involve consistent spatial state recognition. We argue that these failures stem from a mismatch between the spatial recognition mechanism and the text-only reasoning behavior of these MLLMs. Effective spatial reasoning requires low-level geometric structure to be faithfully preserved and updated throughout the reasoning process, whereas textual representations tend to abstract away precisely these critical details. …

Semantic-Structural Decoupling: Disentangling Semantic Attention From Structural Bias In The Attention Manifold, Pengkun Jiao, Bin Zhu, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

The empirical success of attention mechanism in Multimodal Large Language Models (MLLMs) often obscures its inherent, subtle flaws. Specifically, MLLMs consistently exhibit disproportionate attention toward certain semantically uninformative visual tokens, a phenomenon termed "register" or "Visual Attention Sinks." While existing inference intervention methods attempt to identify these sink tokens and redistribute their attention weights, such approaches typically treat these tokens in isolation and suffer from computational inefficiency. Instead, we reframe this phenomenon as a generalized textual bias exerted over visual features that extends beyond isolated sink tokens. From this perspective, a pervasive structural bias leads to the dilution of the …

Tribal Federalism: Expanding The Indian Gaming Paradigm, Adam Crepelle

Michigan Law Review

Federalism has long been celebrated for its ability to foster policy innovation, transforming states into “laboratories of democracy.” Yet, federalism discourse has largely neglected Indian tribes, the third sovereign in the American constitutional order. Tribes regularly implement novel policies. However, tribal policy innovation is hindered by uncertainty over whether tribes or states govern Indian country activities.

The most influential framework for determining the scope of tribal versus state regulatory power in Indian country is derived from the Supreme Court’s opinion in California v. Cabazon Band of Mission Indians—the case that launched Indian gaming. Cabazon held that tribes cannot permit …

Scalpels, Not Hatchets: Beyond Access Bans And Toward A Design-Based Framework For Social Media Regulation, Case Thomason

Michigan Law Review

State legislatures have enacted more than a dozen statutes restricting minors’ access to social media platforms in response to mounting evidence of harm to minors’ mental health. Nearly every one of these laws has been struck down in federal court before taking effect. The problem is structural, in that lawmakers have been using hatchets rather than scalpels to address this issue. Hatchets are sweeping, access-based restrictions that condition minors’ access to platforms on age verification or parental consent. In contrast, scalpels are precise, design-based regulations that target specific platform features such as infinite scroll, push notifications, and engagement-maximizing recommendation algorithms …

Analyzing Developer Discussions On Eu And Us Privacy Legislation Compliance In Github Repositories, Georgia M. Kapitsaki, Maria Papoutsoglou, Christoph Treude, Ioanna Theophilou

Research Collection School Of Computing and Information Systems

Context: Privacy legislation has impacted the way software systems are developed, prompting practitioners to update their implementations. Specifically, the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have forced the community to focus on users’ data privacy. Objectives: Relying on the vast amount of data on developer issues available in GitHub repositories, our aim is to gather empirical evidence on the issues developers of Open Source Software discuss to comply with privacy legislation. Method: We examined such discussions by mining and analyzing 32,820 issues from GitHub repositories. We partially analyzed the dataset automatically to identify …