Digital Commons Network^™

Line Impedance Identification Of Three‑Phase Unbalanced Low‑Voltage Distribution Network Based On Hierarchical Deconstruction And Phase Recursion, Yue Chen, Jian Zhao

Journal of Electric Power Science and Technology

The large-scale integration of distributed photovoltaics and electric vehicles exacerbates the three-phase imbalance in low-voltage distribution network (LVDN), which further leads to issues such as current in neutral wire and voltage fluctuations, preventing the simplification of three-phase line impedance identification into three independently solved single-phase networks with unified power flow. For this reason, a set of line impedance identification methods based on hierarchical deconstruction and phase recursion are proposed, addressing the issue of neutral line current imbalance using the principle of child node voltage correlation. Firstly, three layers are obtained through hierarchical deconstruction: the substation layer, branch layer, and user …

Topology Identification Of Low-Voltage Distribution Network Based On Latent Tree Model And Cluster Search, Hengchao Zhang, Jun Cao, Qiuying Shen

Journal of Electric Power Science and Technology

Topology information is the foundation of advanced analysis functions in distribution network, such as power flow calculation, state estimation, and fault diagnosis. Due to the inability of some nodes in the low-voltage distribution network to upload their own operational status, the existence of these implicit nodes poses a huge challenge to topology identification. This paper proposes a topology identification method for low-voltage distribution networks based on latent tree model and cluster search. Firstly, a Bayesian network with embedded implicit nodes is proposed, which is defined as a latent tree model to provide probabilistic representation for all possible low-voltage distribution network …

Battery Capacity Degradation Prediction Of Large‑Scale Energy Storage Power Station Based On Binary Neural Network, Hang Yang, Yiguo Guo, Xiaoqing Huang, Putong Wen, Dan Xie, Qibin Bo, Yimu Fu, Jingxuan Li

Journal of Electric Power Science and Technology

The number of battery cells in a large-scale energy storage power station is enormous. The conventional convolutional neural networks achieve high prediction accuracy for battery capacity degradation. However, they have high demand for computational resources, which limits their application in practical battery management systems of energy storage power stations. To solve this problem, this paper proposes a battery capacity degradation prediction method based on a binary neural network. First, a lightweight model is designed by binarizing the network weights and activation functions, using the discharge capacity-voltage curve of the battery as input to output the cumulative distribution function values of …

Multi‑Stage Constant‑Current Charging Method Of Electric Vehicle Considering User Charging Law, Shuai Yang, Xiaoping Liu, Minqi Yu, Hanjun Deng, Rui Huang, Mouhai Liu

Journal of Electric Power Science and Technology

The rapid charging method of lithium-ion batteries for electric vehicles should also consider the influence of users’ behavior habits when considering the traditional goals such as balancing the safety, life, and charging time of the batteries. In this paper, a multi-stage constant-current charging method considering users’ behavior habits is proposed. First, Monte Carlo method is used to simulate users’ charging behaviors, and thus the state of charge (SOC) range of users’ optimal willingness to achieve is determined. Then, the dynamic equations of charging time and energy loss are established. Finally, the charging mode to obtain optimal charging current is determined …

Dewey And Merleau-Ponty: Science, Experience, And Nature, Michael Timm

Center for Dewey Studies Essay Award

This paper defends comparisons between pragmatist and phenomenological philosophies of science by comparing Dewey and Merleau-Ponty’s philosophies of science or scientific method. Merleau-Ponty might be said to “answer the phenomenological tradition’s criticism of naturalism” from within the Husserlian phenomenological tradition itself, revindicating the consensus between pragmatism and phenomenology set forth by Rosenthal and Bourgeois. In the absence of an argument that “methodological inconsistency” amounts to methodological illegitimacy, phenomenology ought not reject pragmatist philosophies of science because the Husserlian phenomenological tradition espouses a relative naturalism not unlike pragmatist naturalism. More importantly, this consensus with pragmatism sustains phenomenology’s own critique of scientism.

Development Of Recommendations For The Future Of Telehealth Use Among Sexual And Gender Minorities (Sgm), Jeffrey A. Wilhite

Dissertations and Theses

It is now well-documented that sexual and gender minoritized individuals (SGMs) face consistent stigmatization from not just the health care system, but also from overarching community, federal, and societal entities. Subsections of the SGM community, like gay men for example, face higher rates of eating disorders, certain cancers, alcoholism, mental illness and even obesity, when compared to heterosexual counterparts. Many of these challenges could be exacerbated by current political administration efforts to silence the community. Ensuring access to clinical care is one way of preserving the health and livelihood of the community. Telehealth, or synchronous, remote based clinical care, can …

Micayla Augustyn V. Wall Township Board Of Education

2025 Decisions

USDC for the District of New Jersey

Micayla Augustyn V. Wall Township Board Of Education

2025 Decisions

USDC for the District of New Jersey

A Cascading Effects Model Of Early Sensory Development In Autism, Natalie Russo, Carissa J. Cascio, Grace T. Baranek, Tiffany G. Woynaroski, Zachary J. Williams, Shulamite A. Green, Roseann Schaaf

Department of Occupational Therapy Faculty Papers

Autism has historically been defined by the presence of differences in social communication and restricted, repetitive patterns of behavior, interests, or activities (RRBs). Since 2013 when the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders was published, sensory features were added as one of the polythetic restricted and repetitive behavior diagnostic criteria of autism, though it has remained understudied. Here, we summarize theory and research to provide support for the perspective that early sensory functions and experiences play a primary role in autism and have downstream effects on social communication and repetitive behavioral features of autism. The …

Gardner-Webb Student-Athletes Reese Jones And Theo Drescher Receive Christenberry Award, Office Of University Communications

Gardner-Webb NewsCenter Archive

The Big South Conference announced that a league record-tying 12 student-athletes have been awarded the Conference’s prestigious George A. Christenberry Award for Academic Excellence. The award is given to a graduating male and female student-athlete who attain the highest GPA during their undergraduate collegiate careers.

Prevalence And Predictors Of Intimate Partner Violence Against Men In Kisumu Slums, Kenya, Elizabeth Akello Odemba, Edward A. Frongillo Jr. Ph.D., Sheri D. Weiser

Faculty Publications

Background

Men in sub-Saharan Africa experience intimate partner violence, with few reporting their cases to the legal authorities or coming out for assistance. Consequently, data on the prevalence and drivers of intimate partner violence in different parts of sub-Saharan Africa are inadequate. Therefore, this study was designed to investigate the prevalence and predictors of intimate partner violence against men in Kisumu slums, Kenya.

Methods

This retrospective cross-sectional study included 398 randomly selected men in intimate relationships aged 18–54 years and residing in Kisumu slums. The sampling frame used was from Community Health Volunteers covering the area of study. Data collection …

Spatial Analysis Of La Nana Bayou Watershed To Assess Stream Health, Rylee G. Gabbert

Electronic Theses and Dissertations

The purpose of this study was to evaluate the feasibility of using land cover mapping to identify water quality indicators within a river basin, assessing whether this method provides greater efficiency compared to traditional field-based water quality testing. Land cover mapping has efficiently monitored environmental changes by detecting alterations within specific areas. With the La Nana Bayou Watershed positioned in the heart of Nacogdoches City, an urbanized environment; it is subject to human induced alterations that can negatively affect the natural functionality of its system. When water quality indicators are successfully related to land cover maps, changes within the landscape …

Ensemble-Based Binding Free Energy Profiling And Network Analysis Of The Kras Interactions With Darpin Proteins Targeting Distinct Binding Sites: Revealing Molecular Determinants And Universal Architecture Of Regulatory Hotspots And Allosteric Binding, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS allostery remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to dissect how engineered DARPin proteins K27, K55, K13, and K19 engage KRAS through diverse molecular mechanisms ranging from effector mimicry to conformational restriction and allosteric modulation. Mutational scanning across all four DARPin systems identifies a core set of evolutionarily constrained residues …

Benchmarking Energy And Performance Of Parallel Machine Learning Models Using Hardware And Software Power Meters, Urooj Asgher, Tania Malik

SAML-25 Workshop on Statistical and Machine Learning

The growing reliance on machine learning algorithms across domains such as healthcare, transportation, and finance has led to their increased deployment on high-performance computing platforms. While performance optimization remains a central concern, energy efficiency is emerging as a critical design consideration, particularly in light of global sustainability goals. This study presents a comparative analysis of the energy consumption and performance of serial and parallel implementations of four machine learning algorithms, K-means clustering, Ant Colony Optimization, Logistic Regression, and Random Search. Experiments were conducted on an HPC testbed using both hardware-based and software-based power meters to measure energy consumption. The results …

Partitioning Around Medoids On Product Spaces: A Clustering Approach For Cylindrical Data, Yahia Hammami, Houyem Demni, Amor Messaoud, Giovanni C. Porzio

SAML-25 Workshop on Statistical and Machine Learning

Clustering is a common unsupervised task in data analysis and machine learning. It deals with finding clusters of objects that are characterized by the highest similarity within the same cluster and the highest dissimilarity between different clusters. One of the most used algorithms in clustering is the popular Partitioning Around Medoids (PAM), also known as k-medoids [4, 5]. The algorithm imposes the center of clusters to be some of the data points, and it looks for a minimal value of the sum of the dissimilarity to all the objects. One of the recognized properties of such a method is its …

Improving Node Classification For Graphs Withweak Feature Signals: A Similarity-Entropy Aggregation Approach, Brian Daniel Bernhardt, Chiara Marciano, Mario Rosario Guarracino

SAML-25 Workshop on Statistical and Machine Learning

Graph Neural Networks (GNNs) have established themselves as powerful tools for graph-structured data. However, when feature separability among nodes is low, conventional neighborhood aggregation strategies often result in performance degradation due to over-smoothing and noisy information propagation. In this work, we introduce a novel GNN framework that refines the aggregation process by integrating feature similarity and neighborhood entropy into node message passing. Unlike standard models that uniformly aggregate neighbor information, this new model dynamically adjusts neighbor influence, prioritizing nodes with high similarity and low entropy. We evaluate the model on synthetic graphs generated using the Stochastic Block Model (SBM), varying …

Dealing With Large Data Sets: The Data Nugget Subset Selection Approach, Vipin Kumar, Simona Balzano, Giovanni C. Porzio

SAML-25 Workshop on Statistical and Machine Learning

Analysing big data has always been a major issue because its massive volume poses significant challenges for traditional analytical techniques. When the number of instances is extremely large, existing approaches become computationally infeasible due to the complexity of many algorithms, along with memory and time constraints inherent in processing large datasets. In such cases, using a subset of the data is considered a more practical solution, and analyses are typically performed over a simple random sample drawn from the entire dataset. Various subsampling methods have been proposed to address these issues. However, they often fall short in producing representative subsamples …

A Statistical Approach To Portfolio Optimization Using Copula-Garch Models For European Investments, Jegors Fjodorovs

SAML-25 Workshop on Statistical and Machine Learning

This study explores portfolio optimization using copula functions and GARCH models, focusing on the European stock market. Traditional mean-variance methods often miss dynamic dependencies and tail risks. By applying copula-GARCH models—particularly the Student’s t copula with eGARCH—we better capture volatility asymmetries and tail dependencies. Conditional Value at Risk (CVaR) is used to evaluate downside risk across 10,000 simulated portfolios using high-performance computing. Results show that copula- GARCH models, especially eGARCH, consistently outperform traditional methods in risk-adjusted returns, offering improved risk management.

Analysis Of Distributed Generator Consumption Capacity Of Distribution Networks Considering System Flexibility, Bo Tang, Yilong Liu, Ruijin Zhu, Xuejiao Gong

Journal of Electric Power Science and Technology

With the continuous growth of electricity demand, the high penetration level of renewable energy has become a trend in the development of distribution networks. However, the large-scale integration of distributed generators (DGs) has results in more prominent problems of power flow, congestion, and voltage fluctuations, which brings challenges to the flexible operation of distribution networks. At the same time, it is necessary to further consider the capacity of lines and the voltage deviation of terminal nodes, so that distribution networks can still retain schedulable space, that is, system flexibility. Therefore, it is necessary to rationally analyze the DG consumption capacity …

Pace Financing: A Legal Guide To Energy And Water Efficiency Funding, James P. Cargas

PEEL Alumni Scholarship

No abstract provided.

Greater West Dayton Incubator Has New Director, University Of Dayton

News Releases

The University of Dayton has named alumna, educator, community advocate and entrepreneur Juanita-Michelle Darden as director of the Greater West Dayton Incubator.

The Overlooked Witness Memory Risk, Sue Provenzano, Sarah Brown-Schmidt

Faculty Publications By Year

No abstract provided.

Gaussian Iterative Power Flow Algorithm For Distribution Network Considering Affine Model Of Distributed Generation, Xinghua Huang, Gonglin Zhang, Feixiong Chen, Han Wu, Yuanliang Fan, Shichuan Chen, Hongbin Wu

Journal of Electric Power Science and Technology

Affine power flow calculation is an effective method for uncertainty analysis in power systems. With the increasing integration of distributed generation (DG), the existing Gaussian iterative affine power flow algorithm faces challenges in dealing with distribution networks that incorporate DG controlled by different strategies. To address these problems, a Gaussian iterative power flow algorithm for a distribution network that integrates an affine model for DG is proposed. Firstly, an uncertainty power flow model is established based on affine arithmetic, and a Gaussian iterative model for the affine power flow model is constructed. Secondly, the affine models for DG under different …

Distribution Network Fault Segment Location Based On Gaf‑Resnet50, Yuxuan Shi, Yanhui Xi, Weijie Zhang

Journal of Electric Power Science and Technology

Distribution lines are an integral part of modern power system, which directly influence the safety and stability of power supply. Distribution network fault location can be classified into precise fault location and fault segment location. Considering the complexity of distribution network structure, this paper proposes a fault segment location method based on Gramian angular field (GAF)-ResNet50. The one-dimensional time series is converted into a two-dimensional GAF image by the GAF algorithm, and the deeper-level fault features of the signal are extracted from the GAF image by using the framework of residual neural network so that the fault areas can be …

Low‑Carbon Economic Scheduling For Virtual Power Plants Considering Proton Exchange Membrane Electrolyzers For Oxygen‑Enriched Combustion And Waste Heat Utilization, Dongmei Huang, Yu Tao, Wenbo Zhang, Anduo Hu, Jinzhong Sun, Yuan Sun

Journal of Electric Power Science and Technology

In order to improve the utilization rate of clean energy and achieve low-carbon and economic operation of the power system, this paper constructs an optimal scheduling model of virtual power plants (VPPs) that aggregate wind power, photovoltaic power, oxygen‑enriched combustion, gas turbine, waste heat recovery and utilization system, and proton exchange membrane electrolyzer (PEMEL). Firstly, the electrolyzer, methanation, and proton exchange membrane fuel cell (PEMFC) are modeled from the perspective of waste heat recovery and utilization, considering the joint operation of electrolyzers and oxygen-enriched combustion power plants. Next, from the perspective of oxygen-enriched combustion power plants, the feasibility of achieving …

Unbalanced Circulating Current Injection Control Of Three‑Phase Mmc, Yufei Yue, Luhang He, Libang Wang, Yawen Zhang

Journal of Electric Power Science and Technology

Modular multilevel converters (MMCs) have the problem of three-phase internal power imbalance, which easily leads to the damage of system stability and the increase of system loss. To address internal power imbalance of MMCs, this paper analyzes this problem and proposes a control method based on the injection of positive and negative sequence circulating current. The proposed method mainly includes four parts: the extraction of positive and negative sequence circulating current; the calculation of circulating current command value; the calculation of the number of input sub-modules; the acquisition of trigger signal. By injecting the extracted positive and negative sequence circulating …

United Through Reading: Longitudinal Evaluation 18-Month Findings, Erica M. Hawvermale, Cassidy J. Cooper, Bonnie Chapman Beers

Institute for Veterans and Military Families

This report details the findings from the first eighteen months of a longitudinal evaluation of United Through Reading's (UTR) programs and services across four outcome areas: 1) child literacy, 2) child wellbeing, 3) adult wellbeing, and 4) family connection.

Utah Farmers Market Consumer Preferences For Local Cut Flowers, Alison Bingham, Kynda R. Curtis, Makaylie Langford

All Current Publications

In this fact sheet, we review the results of a 2024 study examining consumer preferences for local cut flowers at Utah farmers markets. Study data were collected in person via Qualtrics at six farmers markets across northern Utah, with 51 total responses. We discuss farmers market consumer purchasing preferences, familiarity with labeling programs, and preferred flower colors and varieties. Additionally, the factors influencing consumer decisions when purchasing cut flowers, as well as the product information they rely on, are discussed. Overall, the information in this fact sheet will assist cut flower growers in making informed decisions regarding production methods and …

Ud History: The Central Women’S Organization, Ava Merriman

University Libraries Blog Archive

Ava Merriman ’25 traces the trajectory of women enrolled on campus and how the coeducational environment took shape.

Medicare Advantage Dominance In Puerto Rico’S Healthcare System: Exploring Its Financial Landscape, Marketing Strategies And Quality Measures Using The Commercial Determinants Of Health Framework, Sergio Andrés Rivera-Rodríguez

Dissertations and Theses

Over time, Medicare Advantage (MA) has seen an increase in enrollment in the United States and Puerto Rico. This program, which is the privatized version of traditional Medicare, has faced critiques in recent years for being focused on profit maximization and reducing accessibility to Medicare beneficiaries. In Puerto Rico, the majority of Medicare beneficiaries (95%) choose a MA plan over traditional Medicare. Despite being the primary financier of healthcare in Puerto Rico and covering populations that require extensive healthcare services, individuals over 65 and those with disabilities, there are still numerous research gaps about the MA industry. This dissertation examines …