Digital Commons Network^™

Enhancing Diagnostic Accuracy: A Hybrid Approach To Mitigate Speckle And Rician Noise In Medical Images, Naveenkumar Jayakumar, Saurabh Saoji, Sagar V. Joshi, Hemlata Mane, Roshni Narkhede, Shrikant Jadhav

Faculty Research, Scholarly, and Creative Activity

This research explores the detrimental effects of Rician and speckle noise in medical imaging, particularly within MRI and radiographic modalities. Such noise can significantly obscure critical details, potentially leading to misdiagnoses and inaccurate measurements. Rician noise candidly dangles on the signal strength. Removing this noise affects the origial information in image that makes this noise removal perplexing. On other hand speckle noise is visualised like granular clog in ultrasound imageries. It creates ambiguous details and edges in the images. To address this challenge, the study introduces a novel hybrid method implemented in Java. The method employs a frequency-based decomposition approach …

Teacher Use Of Rubrics To Assess Claim, Evidence And Reasonings In The High School Science Classroom, Brianna Finnegan

Dissertations and Theses @ UNI

This qualitative study examines how high school science teachers in an eastern Iowa high school utilize rubrics to assess students’ claims, evidence, and reasoning (CER) in the science classroom. The research investigates the methodology teachers employ in assessing student proficiency using their own rubrics they have created. Data were collected through think-aloud interviews with participating teachers as they evaluated and scored CER examples. Analysis of interview data involved inductive coding to identify common themes and categories, shedding light on teacher’s scoring practices, rubric construction, and perceptions of student proficiency and rubric validity.

Findings reveal that teachers often weigh evidence and …

Student Understanding Of Divergence And Curl In Upper-Division Electromagnetism, J. Toby Stuckey, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

The purpose of this paper is to understand and characterize student thinking about the physics concepts of divergence and curl in the context of upper-division electromagnetism for physics majors. We interviewed five students at a west coast university who had taken at least one semester of upper-division electricity and magnetism. The interview prompted students to describe divergence and curl in multiple representations (visually, mathematically, qualitatively). Our analysis identified that students can notice but struggle to resolve discrepancies between the mathematical calculations and the graphical representations of vector fields. We illustrate examples of when students appear to have a disconnect between …

A 30-Year Time Series Analysis Of The Impact Of Climate Change On Corn Yield In Iowa Using The Autoregressive Distributed Lag Model – 1992 To 2022, Tesleem Ajisafe

Dissertations and Theses @ UNI

Climate change poses significant socio-economic challenges globally, notably altering weather patterns and increasing the frequency and severity of extreme weather events (Seneviratne et al. 2021). This study investigates the impact of climate change on corn yield in Iowa from 1992 to 2022, using the autoregressive distributed lag (ARDL) model to analyze time series data on temperature, precipitation, and corn yield at the county level. Iowa, the leading corn producer in the US (Xu, Twine, & Girvetz 2016), has experienced an 8% increase in precipitation from 1873 to 2008, with notable effects in the eastern region (“Climate Change,” n.d.). A detrending …

Boxes And Tangled Tetrahedra, Hidefumi Katsuura

Faculty Research, Scholarly, and Creative Activity

The twin tetrahedron of a given tetrahedron is obtained by circumscribing it by a parallelepiped. However, in general, it is not easy to construct a box that circumscribes a tetrahedron. Actually, constructing a box is equivalent of finding two tangled tetrahedra. We first establish a theorem to construct tangled tetrahedra circumscribed in a box with concurrent diagonals. This generalizes the idea of twin tetrahedra circumscribed in a parallelepiped. And we show that two tetrahedra are twins if and only if they are tangled with concurrent diagonals at the centroid of one of the tetrahedra. We establish a theorem in order …

Assessing And Understanding Soil Characteristics​, Amy Papineau

UNH Cooperative Extension

No abstract provided.

2024 Directory Of Landscape Professionals Trained In Ecological Landscaping For Water Quality Protection, Julia Peterson

UNH Cooperative Extension

No abstract provided.

Blackout (2011) By John Rocco, Peter Shea

Picture Books

In this Caldecott Honor Book, Blackout, a hot urban night takes an interesting turn when the power goes out and an urban family -- each busy with something that requires electricity -- discover new things about themselves and their community.

Generalized Time Domain Prediction Model For Motor Imagery-Based Wheelchair Movement Control, Z. T. Al-Qaysi, M. S. Suzani, Nazre Bin Abdul Rashid, Reem D. Ismail, M. A. Ahmed, Rasha A. Aljanabi, Veronica Gil-Costa

Mesopotamian Journal of Big Data

Brain-computer interface (BCI-MI)-based wheelchair control is, in principle, an appropriate method for completely paralyzed people with a healthy brain. In a BCI-based wheelchair control system, pattern recognition in terms of preprocessing, feature extraction, and classification plays a significant role in avoiding recognition errors, which can lead to the initiation of the wrong command that will put the user in unsafe condition. Therefore, this research's goal is to create a time-domain generic pattern recognition model (GPRM) of two-class EEG-MI signals for use in a wheelchair control system. This GPRM has the advantage of having a model that is applicable to unknown …

Effective Land Use Classification Through Hybrid Transformer Using Remote Sensing Imagery, Muhammad Zia Ur Rehman, Syed Mohammed Shamsul Islam, Anwaar Ulhaq, David Blake, Naeem Janjua

Research outputs 2022 to 2026

Recent advances in deep learning for hyperspectral image (HSI) classification have shown exceptional performance in resource management and environmental planning through land use classification. Despite these successes, challenges continue to persist in land use classification due to the complex topology of natural and man-made structures. The uneven distribution of land cover introduces spectral-spatial variability, causing inter- and intra-class similarity. To address this issue, this study adopts a hybrid approach that combines convolutional neural networks (CNNs) and a transformer model. The technique comprises three key components: a spectral-spatial convolutional module (SSCM), a spatial attention module (SAM), and a transformer module. Each …

Generation Expansion Planning In Isolated Power Systems: A Robust Approach With Dunkelflaute Assessment, Taraneh Ghanbarzadeh, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

Generation expansion planning is vital for decarbonizing power systems and ensuring a reliable and sustainable energy future. Strategically adding new generation and grid capacity is essential for supporting a seamless transition to renewable energy while reducing greenhouse gas emissions. However, achieving the optimal capacity mix of energy resources to ensure network reliability and economic efficiency presents significant challenges, particularly for isolated electricity grids. These challenges are exacerbated during periods of low renewable generation and due to the inherent intermittency of weather-dependent energy resources. This paper presents a comprehensive approach to optimizing long-term expansion planning for an isolated electricity grid, focusing …

Education For Profit In The Era Of Xi: Biopower, Resistance And China’S Double Reduction Policy, Wei Zhang, Le Wang, Christine Cunningham, Zhen Liu

Research outputs 2022 to 2026

This study aims to advance the understanding of for-profit Chinese education during the tenure of Chairman Xi Jinping. Notably, Xi has recently targeted the privately operated, for-profit before-and-after school supplementary tutoring industry, commonly referred to as “Shadow Education”. In 2021, the introduction of the Double Reduction policy abruptly prohibited most SE businesses. Our research seeks to elucidate the impacts of this sudden policy shift on Chinese parents’ perceptions and decision-making regarding their children’s education and supplementary learning opportunities. Conducted in 2022 across mainland China, our study engaged 195 parents through an online survey followed by two focus group interviews. The …

Work-Integrated Learning In The Humanities, Arts And Social Sciences: Where To From Here?, Denise Jackson, Elizabeth Cook

Research outputs 2022 to 2026

Amidst increasing pressures on Humanities, Arts, and Social Sciences (HASS) disciplines regarding graduate career readiness, this study examines HASS student participation in work-integrated learning (WIL) and its impacts on employability and short-term employment outcomes, using data from the Australian Graduate Outcomes Survey from 2020 to 2023. The research examined the extent of participation across WIL types (work-based, non-workplace and global) and its influence on graduates’ perceived employability and employment outcomes (full-time employment and perceived overqualification), while investigating demographic differences using descriptive analysis and logistic regression models. Results indicated rising WIL participation yet identified disparities by activity type and among student …

Measuring The Effectiveness Of Ai Tools In Clinical Research And Writing: A Case Study In Healthcare, Sani Salisu, Osamah Mohammed Alyasiri, Hussain A. Younis, Thaeer Mueen Sahib, Ahmed Hussein Ali, Ameen A. Noor, Israa M. Hayder

Mesopotamian Journal of Artificial Intelligence in Healthcare

This article investigates the capabilities and limitations of ChatGPT, a natural language processing (NLP) tool, and large language models (LLMs), developed from advanced artificial intelligence (AI). Designed to help computers understand and produce text understandable by humans, ChatGPT is particularly aimed at general scientific writing and healthcare research applications. Our methodology involved searching the Scopus database for ’type 2 diabetes’ and ’T2 diabetes’ articles from reputable journals. After eliminating duplicates, we used ChatGPT to formulate conclusions for each selected article by inputting their structured abstracts, excluding the original conclusions. Additionally, we tested ChatGPT’s response to simple misuse scenarios. Our findings …

Machine Learning Helps In Quickly Diagnosis Cases Of "New Corona", Maad M. Mijwil, Ioannis Adamopoulos, Pramila Pudasaini

Mesopotamian Journal of Artificial Intelligence in Healthcare

Machine learning is considered one of the most significant techniques that play a vital role in diagnosing the Coronavirus. It is a set of advanced algorithms capable of analysing medical data and identifying patterns and behaviours of diseases. It is used to interpret medical images, giving details of each image with high accuracy and efficiency, such as chest X-ray images. These algorithms are trained on a large set of images to recognise patterns that indicate the presence of infection with the Coronavirus (COVID-19). This article will provide a brief overview of the importance of machine learning in diagnosing COVID-19 by …

Evaluating If Ghana's Health Institutions And Facilities Act 2011 (Act 829) Sufficiently Addresses Medical Negligence Risks From Integration Of Artificial Intelligence Systems, George Benneh Mensah, Pushan Kumar Dutta

Mesopotamian Journal of Artificial Intelligence in Healthcare

With artificial intelligence (AI) integrated increasingly to enhance personalized diagnosis and data-driven treatment recommendations, this analysis examines the legal sufficiency of Ghana’s Health Institutions and Facilities Act 2011 (Act 829) to address medical negligence risks from reliance on AI systems in clinical settings. The CREAC framework structures evaluating gaps where existing health regulations may lack clarity for emerging issues of accountability. Explanation contextualizes the probabilistic nature of AI inferences and how general principles of medical negligence could have ambiguous application currently if erroneous AI contributions result in patient harm. Application to a hypothetical scenario assesses if adequate protections for appropriate …

Covid-19 Diagnosis Using Deep Learning Approaches: A Systematic Review, Tarza Hasan Abdullah, Berivan Hasan Abdullah

Mesopotamian Journal of Artificial Intelligence in Healthcare

The utilisation of deep learning techniques has witnessed a surge in popularity within the realm of medical image analysis, particularly in the context of identifying COVID-19. Following the occurrence of the COVID-19 pandemic, extensive investigations have been conducted to identify the existence of Sars-Cov-2 through the utilisation of several deep learning algorithms. The objective of this study is to conduct a comprehensive review of deep learning techniques utilised for the detection of COVID-19. "Can deep learning methodologies serve as a viable substitute for radiologists in the diagnostic process of COVID-19?" is the research inquiry. In order to compile research articles …

Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The accurate prediction and classification of medical data, such as Hepatitis C, play a significant role in upgrading symptomatic accuracy and treatment planning. This study utilized progressed machine learning algorithms, including RF, SVR, and Gradient Boosting, to analyze features and predict outcomes viably. By coordination robust preprocessing strategies and feature engineering, the models tended to missing values and categorical transformations, enabling exact predictions from complex datasets. The models accomplished high accuracy and unwavering quality in execution, as prove by comparative measurements and validation results. These discoveries highlight the potential of machine learning in increasing clinical decision-making and emphasize the require …

A Comprehensive Review On Cryptographic Techniques For Securing Internet Of Medical Things: A State-Of-The-Art, Applications, Security Attacks, Mitigation Measures, And Future Research Direction, Wamusi Robert, Asiku Denis, Adebo Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish, Guma Ali

Mesopotamian Journal of Artificial Intelligence in Healthcare

As healthcare becomes increasingly dependent on the Internet of Medical Things (IoMT) infrastructure, it is essential to establish a secure system that guarantees the confidentiality and privacy of patient data. This system must also facilitate the secure sharing of healthcare information with other parties within the healthcare ecosystem. However, this increased connectivity also introduces cybersecurity attacks and vulnerabilities. This comprehensive review explores the state-of-the-art in the IoMT, security requirements in the IoMT, cryptographic techniques in the IoMT, application of cryptographic techniques in securing the IoMT, security attacks on cryptographic techniques, mitigation strategies, and future research directions. The study adopts a …

Feminist Evaluation Using Feminist Participatory Action Research: Guiding Principles And Practices, Kaisha Crupi, Naomi Joy Godden

Research outputs 2022 to 2026

There is a lack of instructional literature on how to conduct a feminist evaluation to highlight and transform systemic issues in gendered and intersecting power relations. Feminist Participatory Action Research (FPAR) enables a process for conducting community-driven, -led and -owned feminist evaluations that drive social justice actions. By undertaking a critical review of existing literature, this article presents guiding principles and practices in how to conduct a feminist evaluation using FPAR. These principles and practices provide a framework for those who are seeking an evidence base for transformative social justice action in communities, particularly those who are working with complexity …

Attitudes And Perceptions Towards Privacy And Surveillance In Australia, Aleatha J. Shanley

Theses: Doctorates and Masters

Understanding attitudes towards privacy and surveillance technologies used to enhance security objectives is a complex, but crucial aspect for policy makers to consider. Historically, terrorism-related incidents justified the uptake of surveillance practices. More recently however, biosecurity concerns have motivated nation-states to adopt more intrusive surveillance measures. There is a growing body of literature that supports the public’s desire to maintain privacy despite fears of biological or physical threats.

This research set out to explore attitudes towards privacy and surveillance in an Australian context. Throughout the course of this endeavour, the COVID-19 pandemic emerged bringing with it a variety of track …

A Wreck Of Seabirds: Entrapment And Isolation Within The Australian Coastal Gothic Landscape, Karleah May Olson

Theses: Doctorates and Masters

This thesis explores the concepts of entrapment and isolation as they relate to the Australian Gothic literary mode and coastal landscapes. It does so through a creative work, a novel entitled A Wreck of Seabirds, and an accompanying exegesis, which examines these concepts alongside the shift of the Gothic to Australian landscapes and ultimately to coastal settings, and their representation in fiction. It examines ways in which elements and tropes of the Gothic are utilized in Australian Coastal fiction, particularly through depictions and metaphors of entrapment and isolation. A Wreck of Seabirds is an Australian Coastal Gothic novel set in …

From Grain To Malt: Tracking Changes Of Ultra-Low-Gluten Barley Storage Proteins After Malting, Mahya Bahmani, Angéla Juhász, Utpal Bos, Mitchell G. Nye-Wood, Malcolm Blundell, Crispin A. Howitt, Michelle L. Colgrave

Research outputs 2022 to 2026

Barley (Hordeum vulgare L.) is a major cereal crop produced globally. Hordeins, the major storage proteins in barley, can trigger immune responses leading to celiac disease or symptoms associated with food allergy. Here, proteomics approaches were employed to investigate the proteome level changes of grain and malt from the malting barley cultivar, Sloop, and single-, double- and triple hordein-reduced lines. The triple hordein-reduced line is an ultra-low gluten barley cultivar, Kebari®. Using discovery proteomics, 2,688 and 3,034 proteins in the barley and malt samples were detected respectively. Through the application of targeted proteomics, a significant reduction in the quantity …

Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of …

Accretion Of Warm Chondrules In Weakly Metamorphosed Ordinary Chondrites And Their Subsequent Reprocessing, Alexander M. Ruzicka, Richard C. Hugo, Jon M. Friedrich, Michael Tyler Ream

Geology Faculty Datasets

To better understand chondrite accretion and subsequent processes, the textures, crystallography, deformation, and compositions of some chondrite constituents in ten lithologies of different cluster texture strength were studied in seven weakly metamorphosed (Type 3) and variably shocked ordinary chondrites (Ragland—LL3 S1, Tieschitz—H/L3 S1, NWA 5421—LL3 S2, NWA 5205—LL3 S2, NWA 11905—LL3-5 S3, NWA 5781—LL3 S3, NWA 11351—LL3-6 S4) using optical and electron microscopy and microtomography techniques. Results support a four-stage model for chondrite formation. This includes 1) limited annealing following collisions during chondrule crystallization and rapid cooling in space prior to accretion, as evidenced by olivine microstructures consistent with dislocation …

Heating Capacity And Biocompatibility Of Hybrid Nanoparticles For Magnetic Hyperthermia Treatment, Aline Alexandrina Gomes, Thalita Marcolan Valverde, Vagner De Oliveira Machado, Emanueli Do Nascimento Da Silva, Daniele Alves Fagundes, Fernanda De Paula Oliveira, Erico Freitas, José Domingos Ardisson, José Maria Da Fonte Ferreira, Junnia Alvarenga De Carvalho Oliveira, Eliza Rocha Gomes, Caio Fabrini Rodrigues, Alfredo Miranda De Goes, Rosana Zacarias Domingues, Ângela Leão Andrade

Michigan Tech Publications

Cancer is one of the deadliest diseases worldwide and has been responsible for millions of deaths. However, developing a satisfactory smart multifunctional material combining different strategies to kill cancer cells poses a challenge. This work aims at filling this gap by developing a composite material for cancer treatment through hyperthermia and drug release. With this purpose, magnetic nanoparticles were coated with a polymer matrix consisting of poly (L-co-D,L lactic acid-co-trimethylene carbonate) and a poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) triblock copolymer. High-resolution transmission electron microscopy and selected area electron diffraction confirmed magnetite to be the only iron oxide in the sample. Cytotoxicity …

A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …

A Segmentation Approach For Predicting Plane Wave Coupling To Pcb Structures, Shengxuan Xia, James Hunter, Aaron Harmon, Ahmed M. Hassan, Victor Khilkevich, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Evaluating the far-field radio frequency (RF) susceptibility of electronic devices often depends on extensive testing or full wave simulations. These methods are effective when complete system information is available but require substantial time and resources to evaluate a large number of variations in system configurations, where trace routings, integrated circuit (IC) package styles, trace terminations, arrival angle, and polarization of incoming wave, etc., are varied from one configuration to another. The goal of the following article is to develop simulation techniques for studying the statistical characteristics of coupling to typical printed circuit board (PCB) structures. Simulation time can be reduced …

Adaptive Resilient Control For A Class Of Nonlinear Distributed Parameter Systems With Actuator Faults, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a new model-based fault resilient control scheme for a class of nonlinear distributed parameter systems (DPS) represented by parabolic partial differential equations (PDE) in the presence of actuator faults. A Luenberger-like observer on the basis of nonlinear PDE representation of DPS is developed with boundary measurements. A detection residual is generated by taking the difference between the measured output of the DPS and the estimated one given by the observer. Once a fault is detected, an unknown actuator fault parameter vector together with a known basis function is utilized to adaptively estimate the fault dynamics. A novel …

Meta-Icvi: Ensemble Validity Metrics For Concise Labeling Of Correct, Under- Or Over-Partitioning In Streaming Clustering, Niklas M. Melton, Sasha Petrenko, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Understanding the performance and validity of clustering algorithms is both challenging and crucial, particularly when clustering must be done online. Until recently, most validation methods have relied on batch calculation and have required considerable human expertise in their interpretation. Improving real-time performance and interpretability of cluster validation, therefore, continues to be an important theme in unsupervised learning. Building upon previous work on incremental cluster validity indices (iCVIs), this paper introduces the Meta- iCVI as a tool for explainable and concise labeling of partition quality in online clustering. Leveraging a time-series classifier and data-fusion techniques, the Meta- iCVI combines the outputs …