Digital Commons Network^™

Framework For Robustness Against Divergent Voltage Drops And High Clock Divergence, Google Case Managers Picozzi, Prateek Pendyala

Defensive Publications Series

A framework providing a dual-metric topology assessment evaluates hold-timing vulnerabilities on paths experiencing high divergence and associated voltage drop gradients. The framework utilizes loop delay tolerance and differential drop tolerance metrics to identify fragile paths and apply proactive verification early in the physical design cycle.

Machine Learning-Based Hybrid System With Multi-Scale Spatial-Temporal Power Grid Attention For Real-Time Dynamic Ir-Drop Prediction, Google Case Managers Picozzi, Vishant Gotra, Prateek Pendyala

Defensive Publications Series

A machine learning-based hybrid system can utilize multi-scale spatial-temporal power grid attention for real-time dynamic ohmic (IR)-drop prediction. The system employs a two-stage hierarchical architecture combining convolutional neural networks to capture global spatial hotspot contexts and gradient-boosted decision trees to predict instance-specific magnitudes. By shifting from a traditional batch verification process to a real-time predictive approach, the system significantly accelerates design convergence while maintaining high accuracy.

Virtual Power-Aware Spatial Tiling Framework For Automatic Test Pattern Generation, Google Case Managers Picozzi, Mayank Parasrampuria, Vishant Gotra

Defensive Publications Series

The disclosed technology introduces an artificial intelligence-based spatial partitioning framework for integrated circuit testing. By extracting physical and electrical features from design instances, the system constructs optimized virtual tiles to manage power constraints dynamically during structural testing. The methodology utilizes machine learning refinement techniques to maintain load balancing and spatial contiguity, allowing test pattern generation tools to operate with granular, region-specific power awareness that aligns with the underlying power distribution network.

Tourism, Institutions, And The Paradox Of Inclusion: How Institutional Quality Moderates Tourism’S Impact On Inclusive Growth In High-Income European Countries, Saqib Munir, Abdul Ghaffar, Mushab Rashid

Arab Economic and Business Journal

Inclusive economic growth in high-income European economies remains contested despite strong institutions and advanced tourism sectors, with limited understanding of how institutional quality and gender-inclusive governance condition the tourism–inclusivity nexus. This study examines the independent and interactive effects of tourism development, institutional quality, gender-inclusive governance, digital infrastructure, environmental sustainability, and income inequality on inclusive economic growth across 15 European countries over 2000–2024. Using World Bank and WGI data, a panel ARDL framework, supported by FMOLS robustness checks is applied to capture dynamic long- and short-run relationships among mixed-order integrated variables. Results indicate that tourism development (β = 5.351, p < 0.001) and institutional quality (β = 8.029, p < 0.001) decisively enhance inclusive growth, yet their interaction exerts a significant negative effect (β = –5.271, p < 0.001), suggesting over-regulation may dampen tourism’s inclusivity potential. Environmental sustainability also contributes positively (β = 0.164, p < 0.001), while income inequality shows a counterintuitive long-run positive association (β = 0.026, p < 0.001). Gender-inclusive governance has a small but significant positive effect (β = 0.005, p = 0.004), whereas digital infrastructure is statistically insignificant. These findings extend institutional economics and endogenous growth theory by revealing governance flexibility as critical to unlocking inclusive tourism benefits, and they inform SDG 8 and 10 policies by advocating balanced regulatory frameworks, renewable energy investment, and targeted redistributive mechanisms in advanced economies.

Sosiologi Perundang-Undangan Dan Pemanfaatannya, Jufrina Rizal

Jurnal Hukum & Pembangunan

Abstract

Pembaharuan Hukum Terhadap Pasal 26 Ayat (I) Uud Negara Republik Indonesia Tahun 1945, Fatmawati Fatmawati

Jurnal Hukum & Pembangunan

Abstract

Perlindungan Program Komputer Menurut Hukum Hak Kekayaan Intelektual, Afifah Kusumadara

Jurnal Hukum & Pembangunan

Abstract

Posisi Hukum Badan Pengadilan Pajak Dalam Sistem Hukum Indonesia, Tri Hayati

Jurnal Hukum & Pembangunan

Abstract

Ketentuan Forward-Statements Di Pasar Modal, Bismar Nasution

Jurnal Hukum & Pembangunan

Abstract

Kinerja Polri Pasca Polri Mandiri, Farouk Muhammad

Jurnal Hukum & Pembangunan

Abstract

Groundwater Laws And Regulations: Survey Of Twenty-One U.S. States, Rebekah Acosta-Hueston, Abigail Adkins, Khadija Alibhai, Olivia Alland, Matthew C. Allen, Dan Archibald, Jeffrey Berk, John Broussard, Justin Cias, Bradford Eckhart, Blakely Fahning, Jackson Field, Michael Flores, Ellen Earl Gillis, Emma Golightly, Merrick Hayashi, David Hernandez, Kate Keithley, Matthew Maslanka, Erin Milliken, Lucas Mylet, Abigail Nichols, James O’Donnell, James Osteen, Connor Pabich, Cheryl Patterson, Rhyan Phillips, Sarah Rathmell, Margaret Reed, Laura Smith, Kelsi Sorrells, Brooke Thoendel, Ani Tookoian, Sandhya Wagle, Margaret Ward, Mackenzie Watson, Carolyn Wheeler, Ashley Wilde

EENRS Program Reports & Publications

This report constitutes the third and final volume in an ongoing project designed to explore and articulate the groundwater quantity laws and regulations of all fifty U.S. states that could then be used for comparative research. This particular report presents surveys for twenty-one states from across the country. The first volume featured thirteen state surveys while the second volume contained sixteen additional state surveys. Both can be found on the project website at: https://www.law.tamu.edu/US-Groundwater-Laws.

Professor Gabriel Eckstein at Texas A&M University School of Law and Professor Amy Hardberger at Texas Tech University School of Law developed an analytical rubric …

A Practical Guide For Teaching With Generative Ai In Sport Management, Geoffre Sherman, David Pierce

Journal of Applied Sport Management

Generative artificial intelligence (GenAI) is reshaping how sport management educators design assignments, evaluate student work, and develop professional competencies. This article presents a practical pedagogical framework that integrates GenAI tools within the Design Council's Double Diamond process—Discover, Define, Develop, and Deliver—to scaffold student thinking across project-based courses. Rather than positioning GenAI as a replacement for student reasoning, the model treats it as a collaborator in roles such as a research assistant, clarifier, creative teammate, and editor. Fluency in prompt engineering is developed progressively through structured exercises that emphasize verification, iteration, and critical evaluation of model outputs. Two complementary assessments—the Prompt …

Toward Greater Wellbeing: Student-Guided Strategies For Improving Sport And Recreation Engagement, Vinu Selvaratnam, Laura Wood, Ryan Snelgrove

Journal of Applied Sport Management

Despite widespread recognition of campus recreation as a key contributor to student well-being, many university students remain underactive, even when programming is available. This study explores student-generated strategies for improving participation in campus recreation, drawing on open-ended responses from 182 undergraduates at a large Canadian university. Using thematic content analysis and chi-square comparison, we examine how suggestions differ between students who report being sufficiently active and those who do not. Seven core themes emerged, with underactive students more likely to identify structural barriers such as inconvenient scheduling, limited facility access, and insufficient communication. These suggestions are interpreted through the Leisure …

Exploration Of Leadership Competencies In College Athletes: An Impact Of Student-Athlete Advisory Committee On Leadership Development, Karina Jolly, Alison Fridley, Jake Simms, Chris Corr, Sarah Stokowski

Journal of Applied Sport Management

The Student-Athlete Advisory Committee (SAAC) is designed to engage college athletes in decision-making processes that influence the NCAA and its member institutions. College athletes provide personal insight into the NCAA intercollegiate athletic experience, thereby influencing policy. SAAC participation prompts the application of transferable sport-specific skills such as leadership and work ethic in a professional setting. This study explores SAAC’s impact on the leadership competencies of college athletes. Results reveal that college athletes who participate in SAAC scored higher on three of the nine leadership factors examined. These findings highlight the importance of leadership programming tailored for college athletes, with SAAC …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

Dementia Detection In Low-Resource Languages: Evaluating Translation-Assisted Transfer Learning For Multilingual Clinical Assessment, Kylar A. Deloach

Honors Theses

Alzheimer's disease (AD) is a growing global health concern, with millions of people affected worldwide and cases expected to rise significantly in the coming decades. Early detection is critical for patient treatment and care, and recent advances in natural language processing (NLP) have shown promise in identifying linguistic markers associated with AD. However, most existing work has focused on English, leaving speakers of other languages with limited access to such tools. This study investigates how effective AD detection models trained on English data are at transferring to Greek, a low-resource language with limited dementia-related speech data available. We propose a …

Cylindrical Versus Spherical Self-Similar Capillary Cavity Collapse, Karl Cardin, Christophe Josserand, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Drop tower experiments have been performed to study the capillary collapse of large high-aspect-ratio cavities. Cavities are formed by momentarily impinging the free surface of a liquid bath with a jet of air in the microgravity environment of a drop tower. The collapse may give rise to a jet and three distinct jetting regimes are identified. Simulations are performed to further investigate the phenomena. The abrupt emergence of a thin high velocity jet is observed experimentally and numerically at a specific initial cavity aspect ratio. Different power laws are identified in different regions of the cavity during the collapse providing …

Shift In Perspective: Fostering Empathy Through Medical Student Immersion In Emergency Nursing Role, Alison Bryant Md, Lauren Wendell Md, Anne Huyler Md, Sara Nelson Md, Mhpe, Sadie Robinson Md, Heather Currier Rn, Nicole Robillard Rn

Costas T. Lambrew Research Retreat 2026

Medical Education Experience Designed to Improve the Nurse-Doctor Relationship

● Expose medical students to skillset and knowledge base of the emergency department nurse

● Acquisition of a small subset of nursing skills

● Increase empathy and respect for the emergency department nurse

● Improve interprofessional communication

Off The Rails: A Fusion Project Combining Bluegrass And Celtic Fiddle Music, Kate Ward

Composition/Recording Projects

The American culture of fiddle playing is rooted in fiddle styles from Ireland, Scotland, and England as a result of fiddle tunes being brought to America via immigrants from the British Isles.  Despite many of the fiddling styles prevalent today being rooted in the same traditions, each has unique technical and compositional distinctions.  This paper explores the technical, compositional, and cultural components of bluegrass and Celtic music and how they can be fused together. This project combines elements of both styles in unique ways to create a natural fusion born out of submersion in each genre.

Review Of Research On Entry Path And Safety Assessment Of Equipotential Live Working On Extra-High Voltage/Ultra-High Voltage Transmission Lines, Peng Li, Li He, Lingxuan Gan, Tao Xie, Houming Shen, Tian Wu

Journal of Electric Power Science and Technology

With the transformation of China 's energy structure and the accelerated construction of new power systems, extra-high voltage/ultra-high voltage transmission projects are gradually being developed into a backbone network to achieve cross-regional energy deployment and support new energy consumption. In this context, as equipotential live working is the core technology to ensure the uninterrupted operation of power grids, the optimization of entry paths and dynamic safety assessment for it become the key focus of current research. Firstly, the key technology systems of equipotential live working on extra-high voltage/ultra-high voltage transmission lines are systematically reviewed, and a complete research framework is …

Risk Assessment Of Power System Frequency Based On Dynamic Inertia Factor, Jie Fu, Qian Zhang

Journal of Electric Power Science and Technology

Against the background of the continuous integration of a high proportion of renewable energy into the power system, the system inertia provided by traditional synchronous units shows a continuous downward trend, which significantly increases the risk of power system frequency instability. A frequency risk assessment method based on the dynamic inertia contribution factor (DICF) is proposed to solve the problem of insufficient spatiotemporal resolution in traditional static inertia assessment. By defining the dynamic equivalent inertia, the real-time contribution of each unit to the system inertia is quantified, and the weighted inertia-risk index (WIRI) is constructed. Combined with the frequency deviation …

Method For Enhancing Resilience Of Smart Grids Based On Adaptive Graph Attention Multi-Agent Reinforcement Learning, Peng Chang, Yun Wang, Fei Meng, Qing Wang, Yang Sun

Journal of Electric Power Science and Technology

Enhancing the resilience of smart grids is crucial for maintaining the security and reliability of power systems. An adaptive graph attention multi-agent reinforcement learning (AGA-MARL) method is proposed, through which the learning efficiency and collaborative ability of the system in complex grid environments are improved by an adaptive learning rate and a dynamic task allocation mechanism, thereby enhancing the resilience and interpretability of smart grids. First, adaptive multi-agent deep reinforcement learning (AMA-DRL) and dynamic spatial-temporal graph convolutional networks (DST-GCN) are combined to enhance the information interaction among multiple agents and utilize the dynamic graph structure to capture the complex dependencies …

Risk Identification And Load Transfer Calculation Method For Distribution Network Framework Considering New Energy Access, Ji Su, Tao Chen, Yu Duan, Zhantao Gao, Wei Yang, Yuqiao Ou

Journal of Electric Power Science and Technology

Driven by the "dual carbon" target, it has become a trend for an extremely high proportion of new energy to be integrated into the distribution network. The random "bidirectional flow" of power flow in the distribution network has a great impact on its operational safety. It is urgent to identify the network framework risks and load transfer methods of the distribution network. A risk identification and load transfer calculation method for the distribution network framework considering the integration of new energy is proposed. First, a risk identification method for the distribution network with a high proportion of new energy access …

A Risk Assessment Method For Three-Phase Unbalance In Distribution Transformer Areas Considering Zero-Sequence Current, Mo Shi, Yingting Luo, Xin Li, Bin Zhang, Bowei Wei, Shenzhou Zhou, Qin Yan, Rui Ma

Journal of Electric Power Science and Technology

With the significant growth of seasonal loads such as agriculture and tourism, power equipment failures and power outages caused by the three-phase unbalance problem in distribution transformer areas become major challenges in the operation and maintenance of distribution networks. Therefore, it is urgent to strengthen the assessment of three-phase unbalance in distribution transformer areas. To address the problems of few evaluation indices and single weight distribution methods for three-phase unbalance in existing distribution transformer areas, a risk assessment method for three-phase unbalance in distribution transformer areas considering zero-sequence current is proposed based on the traditional three-phase unbalance evaluation method for …

Identification Method For High-Resistance Ground Faults In Distribution Networks Based On Traveling Wave Fault Feature Difference And Rmt Model, Junjie Shi, Daoyi Gu, Feng Deng, Pengyu Qi, Junwen Luo, Ruijun Li, Chang Tang

Journal of Electric Power Science and Technology

When a high-resistance grounding fault occurs in a distribution network, the fault signal is weak, and traditional methods based on single-feature extraction are prone to causing protection maloperation. In response, this paper introduces an effective identification method for high-resistance ground faults in distribution networks based on differential features of traveling wave voltage signals and a "retentive network meets vision transformer" (RMT) model. Initially, the traveling wave voltage signal is extracted to implement wavelet packet time-frequency features, and the differences in the time-frequency domain responses between high-resistance ground faults and normal disturbance conditions are visualized. Then, a composite RMT model integrating …

Low-Error Carbon Monitoring Method For Industrial Users Based On Equipment Sta Tus Identification, Yutao Xu, Zongyi Wang, Zhuk Ui Tan, Yun Zhao, Qihui Feng, Ziwen Cai

Journal of Electric Power Science and Technology

A low-error carbon monitoring method base d on equipment status identification is proposed to solve the problem of insufficient accuracy in existing carbon monitoring methods for industrial users. Firstly, an equipment status identification model based on temporal convolutional network-gated recurrent unit (TCN-GRU) is built to accurately identify the operating status of key carbon-emitting equipment for industrial users. Secondly, genetic algorithms (GAs) are introduced to dynamically optimize the parameters of the fully connected layer in the model, enhancing the classifier's identification capability for equipment with high carbon emissions. Finally, low-error carbon emission monitoring is achieved based on the optimized status identification …

Analysis Method For Power System Ine Rtia Intervals With Coupled Uncertainty Of New Energy Output, Xuebin Wang, Guobin Fu, Kaix Uan Yang, Qixuan Wen, Rui Song, Yunfeng Wen

Journal of Electric Power Science and Technology

The large-scale grid connection of new energy leads to the continuous compression of the start-up capacity of synchronous power sources, and the system faces the risk of low-inertia operation. Existing deterministic inertia trend assessment methods ignore the time-varying impact of random new energy fluctuations on unit commitment, which may lead to the misjudgment of inertia adequacy. In this regard, an analysis method for power system inertia intervals is proposed to realize a panoramic portrayal of inertia boundaries by coupling the uncertainty of new energy output. First, a confidence interval is constructed based on probability modeling of wind and solar power …

Identification Method For Control Parameters Of Grid-Connected Photovoltaic System Based On Sensitivity Characteristic Analysis, Yunhe Chen, Peiqiang Li, Jiajie Xiao

Journal of Electric Power Science and Technology

Accurate identification of fault control parameters is the basis for establishing an accurate simulation model of a grid-connected photovoltaic system. The dynamic coupling of multiple control links and the low sensitivity of some parameters lead to a low overall identification accuracy of control parameters. To address this problem, an identification method for control parameters of a grid-connected photovoltaic system based on sensitivity characteristic analysis is proposed in this paper. Firstly, a method of injecting disturbances into the measurement signals on the secondary side of the system is proposed to decouple the dynamics of multiple controllers. Secondly, a sensitivity algorithm is …

Research On Monitoring Strategy For Direct Power Supply Of Distributed Photovoltaic Power Sources, Shidong Chen, Shuai Yang, Xing He, Minqi Yu, Rui Huang

Journal of Electric Power Science and Technology

The randomness and intermittency of the output of distributed photovoltaic power sources pose significant challenges to the stable operation and power quality of distribution networks. In this paper, a method based on affinity propagation clustering algorithm (APCA) is proposed to effectively identify the direct power supply situations of photovoltaic power sources. Unlike traditional methods, photovoltaic power sources in the same station area are selected by this algorithm, which reduces the influence of factors such as climate and light intensity and improves the accuracy and operability of the algorithm. First, correlation coefficients are used to screen out photovoltaic power sources with …

Research On Multi-Time Scale Fast Voltage Control Strategy For Regional Power Grids With Large-Scale New Energy Collection, Zimin Zhu, Xiaoyun Wang, Yu Duan, Xiaofang Wu, Jian Ma, Xiaoyu Deng

Journal of Electric Power Science and Technology

To address the problems of frequent voltage fluctuations and significantly increased voltage control complexity caused by high-proportion new energy connected to the power grid, a voltage control strategy considering fast response and fine regulation capabilities is constructed for large-scale new energy collection areas, combined with the requirements of multi-time scale voltage regulation, to realize the joint control between devices with discrete response characteristics (CB) and devices with continuous regulation capabilities (SVC). According to the day-ahead expected results, coarse adjustment of discrete reactive power devices is realized by this strategy in the day-ahead stage; robust reinforcement learning is utilized in the …