Digital Commons Network^™

Regularization By Deep Learning In Signal Processing, Carlos Ramirez Villamarin, Erwin Suazo, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we explore a new idea of using deep learning representations as a principle for regularization in inverse problems for digital signal processing. Specifically, we consider the standard variational formulation, where a composite function encodes a fidelity term that quantifies the proximity of the candidate solution to the observations (under a physical process), and a second regularization term that constrains the space of solutions according to some prior knowledge. In this work, we investigate deep learning representations as a means of fulfilling the role of this second (regularization) term. Several numerical examples are presented for signal restoration under …

The Polyglutamine Domain Is The Primary Driver Of Seeding In Huntingtin Aggregation, Adam Skeens, Chathuranga Siriwardhana, Sophia E. Massinople, Michelle M. Wunder, Zachary L. Ellis, Kaitlyn M. Keith, Tyler Girman, Shelli L. Frey, Justin Legleiter

Chemistry Faculty Publications

Huntington’s Disease (HD) is a fatal, neurodegenerative disease caused by aggregation of the huntingtin protein (htt) with an expanded polyglutamine (polyQ) domain into amyloid fibrils. Htt aggregation is modified by flanking sequences surrounding the polyQ domain as well as the binding of htt to lipid membranes. Upon fibrillization, htt fibrils are able to template the aggregation of monomers into fibrils in a phenomenon known as seeding, and this process appears to play a critical role in cell-to-cell spread of HD. Here, exposure of C. elegans expressing a nonpathogenic N-terminal htt fragment (15-repeat glutamine residues) to preformed htt-exon1 fibrils induced …

The Effect Of Ethanol Treatment On The Protein Content Of Difi Exosomes, Kenzie Rushing

[Archive] Belmont University Research Symposium (BURS)

Colorectal cancer (CRC) is the second most common cause of cancer death in the United States in both men and women combined, second only to lung cancer.1 CRC metastasis is the primary cause of mortality largely due to therapy resistant cancer cells.2 Therefore, detection before metastasis is of great importance and could potentially lead to earlier detection and decreased mortality. Extracellular vesicles (EVs), including exosomes, are lipid bound vesicles secreted by cells3 that are involved in cell-cell communication and have been found to promote CRC progression and metastasis.4 The proteome of exosomes is thought to reflect that of the originating …

2024 March 14 - Academic Council Agenda And Minutes, Academic Council, East Tennessee State University

Academic Council Agenda and Minutes

No abstract provided.

2024 March 14 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Explainable Ai Using Assumption-Alignment Tracking On Multiple Algorithms, Darien Campbell

Undergraduate Honors Theses

Autonomous robots are becoming increasingly prevalent in our everyday lives. In order for humans to effectively take advantage of automated systems, robots need to understand their limitations across different environment states, recognize when they need user assistance, and effectively communicate their assessments to human users. The ability of AI systems to communicate their decision process is referred to as Explainable AI.

Research has already been done on how a robot should evaluate its proficiency to predict how well it can perform a task [1]. This thesis explores current Social Science research on how humans explain their own behaviors. These insights …

Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan

Turkish Journal of Electrical Engineering and Computer Sciences

This study aims to perform fast fault diagnosis and intelligent protection in an active distribution network (ADN) with high renewable energy penetration. Several time-domain simulations are carried out in EMTP-RV to extract time-synchronized current and voltage data. The Stockwell transform (ST) was used in MATLAB/SIMULINK to preprocess these input datasets to train the adaptive fault diagnosis deep convolutional neural network (AFDDCNN) for fault location identification, fault type identification, and fault phase-detection for different penetration levels. Based on the AFDDCNN output, the intelligent protection scheme (IDOCPS) generates the signal for isolating a faulty section of the ADN. An intelligent fault diagnosis …

Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a fast antenna phase optimization scheme to enable microwave power focusing for breast cancer hyperthermia. The power focusing is achieved through the maximization of the deposited electric field on the target malignant tumor tissue. To do so, a malignant breast tumor, the surrounding breast medium, and the skin of the breast are modeled as a cylindrical structure composed of eccentric cylinders, and electric field distribution is computed analytically in terms of cylindrical harmonics. This approach minimized the computational cost and simplified the breast medium model. To ensure applicability across various breast types, the dielectric properties (DPs) of …

Atomic Comagnetometer Gyroscopes For Inertial Navigation Systems: A Review, Murat Salim Karabinaoglu, Bekir Çakir, Mustafa Engin Başoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, developments in quantum sensing, laser, and atomic sensor technologies have also enabled advancement in the field of quantum navigation. Atomic-based gyroscopes have emerged as one of the most critical atomic sensors in this respect. In this review, a brief technology statement of spin exchange relaxation free (SERF) and nuclear magnetic resonance (NMR) type atomic comagnetometer gyroscope (CG) is presented. Related studies in the literature have been gathered, and the fundamental compositions of CGs with technical basics are presented. A comparison of SERF and NMR CGs is provided. A basic simulation of SERF CG was carried out because …

Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Domain generalization (DG) techniques strive to attain the ability to generalize to an unfamiliar target domain solely based on training data originating from the source domains. Despite the increasing attention given to learning from multiple training domains through the application of various forms of invariance across those domains, the enhancements observed in comparison to ERM are nearly insignificant under specified evaluation rules. In this paper, we demonstrate that the disentanglement of spurious and invariant features is a challenging task in conventional training since ERM simply minimizes the loss and does not exploit invariance among domains. To address this issue, we …

Lower Data Attacks On Advanced Encryption Standard, Orhun Kara

Turkish Journal of Electrical Engineering and Computer Sciences

The Advanced Encryption Standard (AES) is one of the most commonly used and analyzed encryption algorithms. In this work, we present new combinations of some prominent attacks on AES, achieving new records in data requirements among attacks, utilizing only 2 4 and 2 16 chosen plaintexts (CP) for 6-round and 7-round AES 192/256, respectively. One of our attacks is a combination of a meet-in-the-middle (MiTM) attack with a square attack mounted on 6-round AES-192/256 while another attack combines an MiTM attack and an integral attack, utilizing key space partitioning technique, on 7-round AES-192/256. Moreover, we illustrate that impossible differential (ID) …

Self-Esteem Among Adults With Adhd Symptoms, Dana Richelieu

Walden Dissertations and Doctoral Studies

This study assessed if attention deficit hyperactivity disorder (ADHD) treatment, ADHD symptoms, social support, gender, coping, and educational attainment predicted self-esteem among adults. It differed from previous research on this topic because it included participants with ADHD symptoms compared to those with formal ADHD diagnoses. Grounded in Leary and Baumeister’s sociometer theory, the study involved using a nonexperimental correlational survey research design to assess this issue. A sample of 272 adult participants living in the United States were recruited. A multiple regression analysis revealed ADHD symptoms, social support, and coping were statistically significant predictors of self-esteem, while ADHD treatment, gender, …

Effects Of Unobservable Bus States On Detection And Localization Of False Data Injection Attacks In Smart Grids, Moheb Abdelmalak

USF Tampa Graduate Theses and Dissertations

In an era increasingly marked by sophisticated cyber-attacks, this thesis investigates the critical issue of bus unobservability in smart grids and its impact on the effectiveness of cyber-attack detection and localization models. Given that unobservability is a prevalent challenge in smart grids due to various factors, researchers have developed numerous algorithms for optimal Phasor Measurement Unit (PMU) placement under scenarios of limited observability. However, these models primarily focus on enhancing network observability, often without considering whether this placement optimally facilitates attack detection. This research is driven by the hypothesis that a deeper understanding of the effects of unobservable buses can …

Wmu Board Of Trustees Formal Session ,March 14, 2024, Wmu Board Of Trustees

WMU Board of Trustees Meetings

Acceptance of the Agenda

Approval of the Minutes

Remarks by the Chair Pro-Tem

Remarks by the President

Updates by the Faculty Senate President

Updates by the Western Student Association President

Capital Intern Program Presentation: Cultivating a Leader: WMU Student's Journey in the

Capital Intern Program

Public Comments Regarding Action Items

Action Items

Consent Items

• Liquor License – Multiple Events
• Curriculum Proposals
• Personnel Report
• Annuity and Life Income Funds Performance Report
• Operating Cash Investment Performance Report

General Public Comments

Deep Learning Approaches For Cancer Prognosis Prediction Using Histopathological, Omics, And Clinical Data, Shuai Jiang

Dartmouth College Ph.D Dissertations

Accurate prediction of patient outcomes is crucial for shared clinical decision-making, treatment planning, and patients' psychological adjustment. Histopathological features of cancer, including tumor size, lymph node involvement, and metastasis, are commonly incorporated into survival prediction models, underscoring the prognostic value of whole slide images (WSIs). Concurrently, studies have highlighted the significance of omics data, such as transcriptomics, in providing valuable insights into cancer prognosis.

The emerging deep learning methods have brought new opportunities in biomedical informatics. Despite a growing body of studies on the application of deep learning methods for predicting prognosis using WSIs, the results are varied, primarily due …

Improving Human Recognition Of Deepfakes, Jeremy Mumford

Undergraduate Honors Theses

This thesis is focused on deepfakes, a new term given to fake videos and images generated by deep learning algorithms and models. Deepfakes pose a considerable threat to society by raising the bar for quality in misinformation while also lowering the amount of skill and effort required. Deepfakes threaten to undermine democratic societies by swaying public opinion through misinformation. While many researchers are working hard to develop automated tools to combat deepfakes, this thesis used a 10-item IRB approved survey to examine whether two separate interventions could successfully improve an individual’s ability to recognize deepfakes. Demographic differences in recognizing deepfakes …

Alternative Robust Ways Of Witnessing Nonclassicality In The Simplest Scenario, Massy Khoshbin, Lorenzo Catani, Matthew Leifer

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this paper we relate notions of nonclassicality in what is known as the simplest nontrivial scenario (a prepare and measure scenario composed of four preparations and two binary-outcome tomographically complete measurements). Specifically, we relate the established method developed by Pusey [M. F. Pusey, Phys. Rev. A 98, 022112 (2018)] to witness a violation of preparation noncontextuality, that is not suitable in experiments where the operational equivalences to be tested are specified in advance, with an approach based on the notion of bounded ontological distinctness for preparations, defined by Chaturvedi and Saha [A. Chaturvedi and D. Saha, Quantum …

Single Dual-Specific Anti-Pd-L1/Tgf-Β Antibody Synergizes With Chemotherapy As Neoadjuvant Treatment For Pancreatic Ductal Adenocarcinoma: A Preclinical Experimental Study, Haoxiang Zhang, Jiaoshun Chen, Jianwei Bai, Jing Zhang, Shaoyi Huang, Liang Zeng, Pengfei Zhou, Qiang Shen, Tao Yin

School of Medicine Faculty Publications

AIMS: Chemotherapy resistance is an important cause of neoadjuvant therapy failure in pancreatic ductal adenocarcinoma (PDAC). BiTP is a single antibody that can simultaneously and dually target transforming growth factor-beta (TGF-β) and programmed cell death 1 ligand 1 (PD-L1). We attempted in this study to investigate the efficacy of BiTP in combination with first-line chemotherapy in PDAC. METHODS: Preclinical assessments of BiTP plus gemcitabine and nab-paclitaxel were completed through a resectable KPC mouse model (C57BL/6J). Spectral flow cytometry, tissue section staining, enzyme-linked immunosorbent assays, Counting Kit-8, transwell, and Western blot assays were used to investigate the synergistic effects. RESULTS: BiTP …

Exploring Student Self-Assessment In General Education: A Pilot Study Using Surveying Tools, Cristo E. Yáñez León, James Lipuma, Jeremy P. Reich, Yi Meng

STEM for Success Resources

PResented at: Congreso Internacional de Investigación Academia Journals Tláhuac 2023 Venue: Instituto Tecnológico de Tláhuac II, CDMX, México Date: September 13-14, 2023.

This research article delves into an innovative pilot study examining student self-assessment in the realm of General Education Requirements (GER) within a STEM-focused university. Employing a tailored survey based on AAC&U VALUE Rubrics and utilizing a 5-point Likert scale, the study contributes to the Middle States Commission on Higher Education (MSCHE) accreditation review. Our findings explore the congruence between self-assessed student awareness and institutional benchmarks, shedding light on the efficacy of out-of-course pre-and post-tests. The research unveils pivotal …

Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Technological developments in industrial areas also impact unmanned aerial vehicles (UAVs). Recent improvements in both software and hardware have significantly increased the use of many UAVs in social and military fields. In particular, the widespread use of these vehicles in social areas such as entertainment, shipping, transportation, and delivery and military areas such as surveillance, tracking, and offensive measures has accelerated the research on swarm systems. This study examined the previous investigations on swarm UAVs and aimed to create a more efficient algorithm. The effectiveness of the proposed algorithm was compared with other leader-based applications. A swarm consisting of 5 …

Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different …

Label-Aware Distance Mitigates Temporal And Spatial Variability For Clustering And Visualization Of Single-Cell Gene Expression Data, Shaoheng Liang, Jinzhuang Dou, Ramiz Iqbal, Ken Chen

Faculty, Staff and Student Publications

Clustering and visualization are essential parts of single-cell gene expression data analysis. The Euclidean distance used in most distance-based methods is not optimal. The batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces large between-group distance and obscures the true identities of cells. To solve this problem, we introduce Label-Aware Distance (LAD), a metric using temporal/spatial locality of the batch effect to control for such factors. We validate LAD on simulated data as well as apply it to a mouse retina development dataset and a lung dataset. We also found the utility of our …

A Historical Contingency Hypothesis For Population Ecology, Sarah Hoy, Rolf O. Peterson, John A. Vucetich

Michigan Tech Publications

Assessments of historical contingency have advanced our understanding of adaptive radiation and community ecology, but little attention has been given to assessing the importance of historical contingency in population ecology. An obstacle has been the unmet need to conceptualize historical contingencies for populations in a manner that allows for their explanatory power to be assessed and quantified so that it can be directly compared with the explanatory power of statistical models representing other hypotheses or theory-based explanations. Here we conceptualize historical contingencies as a series of random events characterized by (1) significant legacy effects that are comparable in length to …

Montana Kaimin, March 14, 2024, Students Of The University Of Montana, Missoula

Montana Kaimin, 1898-present

Student newspaper of the University of Montana, Missoula.

Utilizing Machine Learning Techniques For Accurate Diagnosis Of Breast Cancer And Comprehensive Statistical Analysis Of Clinical Data, Myat Ei Ei Phyo

USF Tampa Graduate Theses and Dissertations

Breast cancer represents a formidable malignancy, presenting a substantial threat to global health and individual well-being. Conventionally, it is widely held that the prognosis for breast cancer patients hinges predominantly upon the timing of diagnosis and the extent of cancer progression, typically delineated by its stage. However, emerging evidence from robust regression and machine learning analyses challenges this prevailing notion. The results indicate that survival months cannot be solely attributed to diagnosis and socio-economic factors. Instead, additional variables such as existing diseases and treatment complexities may contribute to the intricate landscape of breast cancer outcomes.

This research aims to delve …

Exploring Educational Equity: An Ethnographic Case Study Of Non-Profit Initiatives In Early Childhood Education, Jovana Jovanovic

USF Tampa Graduate Theses and Dissertations

Quality early childhood education is acknowledged as a crucial factor in paving the way for academic success and societal contribution. Childhood experiences greatly influence individual life trajectories, significantly shaping future endeavors. This research delves into the intricate dynamics between socioeconomic status (SES), educational outcomes, and non-profit organizations, emphasizing the challenges faced by students from economically disadvantaged backgrounds. While factors such as limited resources, financial constraints, and substandard living conditions have been linked to negative consequences on educational attainment, this research seeks to understand the specific role of non-profits in enhancing educational opportunities. By shedding light on collaborative efforts between local …

Nutrient Removal Of Biochar Amended Modified Bioretention Systems Treating Nursery Runoff, Nicholas Richardson

USF Tampa Graduate Theses and Dissertations

Excess inputs of nutrients, such as nitrogen and phosphorus, to surface water bodies can lead to the presence of harmful algal blooms (HABs). HABs can damage their surrounding environments and the economies dependent on them. Nutrient pollution can be properly controlled and monitored at point-sources, such as wastewater treatment plants, but is more difficult to control for non-point sources, such as fertilizer runoff. One form of fertilizer runoff that remains overlooked is runoff from plant nurseries. Controlled release fertilizers (CRFs) embedded in plant containers at nurseries can leach excess nutrients into the runoff. For nurseries in Florida, best management practices …

Investigating Gulf Coast Aquifer System: Stratigraphy Reconstruction, Inverse Modeling, And Groundwater Stress Assessment, Shuo Yang

LSU Doctoral Dissertations

The Mississippi Embayment aquifer system (MEAS) and the Coastal Lowlands aquifer system (CLAS) provide substantial groundwater resources for human activities in the U.S. Gulf Coastal Plain. However, the overexploitation has led to groundwater depletion in the MEAS and the CLAS, threatening sustainable groundwater use. Such concern highlights the crucial need for an advanced understanding of stratigraphy and groundwater in these aquifer systems, which is essential for effective regional groundwater management. This dissertation presents a comprehensive investigation of MEAS and CLAS in the Louisiana and southwestern Mississippi region, encompassing three fundamental dimensions: stratigraphy reconstruction, groundwater modeling, and groundwater stress assessments. A …

In-Person, Hybrid, Or Remote: Exploring The Effectiveness Of Teacher Practices On Student Performance During The Covid-19 Pandemic, Ashley M. Segalla

LSU Doctoral Dissertations

Schools and universities had to make unexpected changes beginning in Spring 2020 because of the COVID-19 pandemic. In Spring 2021, one university in the southern region of the United States implemented hybrid teaching formats in College Algebra courses, where students attended half of the classes in-person, and the remaining half of classes were attended synchronously and remotely. The purpose of this mixed methods study was to determine if students’ attendance methods (virtual or in-person) impacted their academic performance in the course. Additionally, the study sought to determine how students and the instructor felt student performance was impacted by hybrid attendance. …

Method For Securely Merging Uniform Lists, Peter Rindal Visa, Srinivasan Raghuraman Visa, Gayathri Annapurna Garimella Visa

Defensive Publications Series

Present disclosure the present disclosure is directed to secure computation and data encryption. In particular, the present disclosure is directed to secure computation that enables computation while keeping data encrypted. More particularly, the present disclosure is directed to a secure protocol that can merge two encrypted lists given that they are ordered. In a modern data analysis process, data is transferred to, stored in, and computed by a server. During these three processes, encryption protects the data when it is transferred and stored.