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Articles 7921 - 7950 of 197093

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Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard Aug 2025

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

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Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand Aug 2025

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

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Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand Aug 2025

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …

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Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand Aug 2025

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

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Humanizing Cities As An Approach For Solving Cities' Problems To Be More Livable, Kareem Mahrous Ali Aug 2025

Humanizing Cities As An Approach For Solving Cities' Problems To Be More Livable, Kareem Mahrous Ali

Mansoura Engineering Journal

Most people around the world want to move from the countryside to the cities or from one city to another that provides them with all their human needs for a better life. The dream may come true for them or turn into a nightmare for reasons related to general problems facing most cities in the world, such as the high cost of living and the absence of social justice, these problems cause an increase in poor families, or the issue of refugees and the inability of some cities to welcome them, the energy crisis, and the challenges of climate change …

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Recent Progress And Scientific Challenges In Wire-Arc Additive Manufacturing Of Metallic Multi-Material Structures, Sainand M. Jadhav, Sambhaji Kusekar, Akash Belure, Satyavan Digole, Abhijeet Mali, Muralimohan Cheepu, Manoj Mugale, Suhas Alkunte, Duckbong Kim Aug 2025

Recent Progress And Scientific Challenges In Wire-Arc Additive Manufacturing Of Metallic Multi-Material Structures, Sainand M. Jadhav, Sambhaji Kusekar, Akash Belure, Satyavan Digole, Abhijeet Mali, Muralimohan Cheepu, Manoj Mugale, Suhas Alkunte, Duckbong Kim

Faculty Articles

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by …

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3d Printing Of Short Fiber Reinforced Polypropylene: Novel Lattice Architucture And Material Characterization, Mohammad Ghazi Alshneeqat Aug 2025

3d Printing Of Short Fiber Reinforced Polypropylene: Novel Lattice Architucture And Material Characterization, Mohammad Ghazi Alshneeqat

Thesis/ Dissertation Defenses

This study explores the enhanced compressive behavior of 3D-printed single and double gyroid solid-networks lattices. Where the double gyroids are constructed from two intertwined single gyroid structures. These structures were designed by nTop implicit modeling tool and then fabricated by material extrusion additive manufacturing method at optimized printing parameters, including optimized nozzle temperature and raster angle. The main objective of this study is to reveal the compressive behavior of the novel double gyroid lattice structure and then to tailor its response through variable gyroid heights. Standard polymer tests were performed, considering thermogravimetric analysis, to confirm the thermal stability of the …

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Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye Aug 2025

Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye

Faculty Publications

Stable and reproducible reference electrodes (REs) are essential for electrochemical systems operating in high-temperature molten salts, where consistent control of potential is required. This study uses three different solutes to investigate the development and evaluation of REs in eutectic LiCl-KCl at 773 K. The solutes tested were NiCl2, AgCl, and NiO, each prepared at multiple concentrations to assess stability, reproducibility, and saturation. Electrochemical stability was measured over three days using chronopotentiometry (CP), followed by open circuit potential (OCP), with cyclic voltammetry (CV) also integrated to monitor changes in electrochemical behavior over time. The CP-OCP approach established a Li+/Li redox potential, …

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Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye Aug 2025

Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye

Faculty Publications

Stable and reproducible reference electrodes (REs) are essential for electrochemical systems operating in high-temperature molten salts, where consistent control of potential is required. This study uses three different solutes to investigate the development and evaluation of REs in eutectic LiCl-KCl at 773 K. The solutes tested were NiCl2, AgCl, and NiO, each prepared at multiple concentrations to assess stability, reproducibility, and saturation. Electrochemical stability was measured over three days using chronopotentiometry (CP), followed by open circuit potential (OCP), with cyclic voltammetry (CV) also integrated to monitor changes in electrochemical behavior over time. The CP-OCP approach established a Li …

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Dissolution Mechanism Of Nonionic Polyether Surfactants In Supercritical Co2, Ning Xu, Yanling Wang, Baojun Bai, Shizhang Cui, Zan Gao, Yu Zhang, Di Li, Wenjing Shi, Wenhui Ding, Peixu Ma Aug 2025

Dissolution Mechanism Of Nonionic Polyether Surfactants In Supercritical Co2, Ning Xu, Yanling Wang, Baojun Bai, Shizhang Cui, Zan Gao, Yu Zhang, Di Li, Wenjing Shi, Wenhui Ding, Peixu Ma

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polyoxyethylene ether is an efficient CO2-philic compound with significant potential applications in CO2 flooding, which requires CO2-philic surfactants with high solubility in supercritical CO2 (scCO2). This study elucidates the molecular and atomic-level dissolution mechanism of the fatty alcohol polyoxyethylene ether (AEO) in scCO2 by combining phase-behavior experiments and molecular dynamics simulations. The solubility of AEO in scCO2 is measured using a semiconductor laser. AEO containing three polyoxyethylene (EO) groups exhibited the highest solubility in scCO2.The solubility of AEO in scCO2 decreased with an increase in the number …

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Köppen-Geiger Climate Effects On F-15 Readiness Spares Package Parts, Maximus A. Fan Aug 2025

Köppen-Geiger Climate Effects On F-15 Readiness Spares Package Parts, Maximus A. Fan

Theses and Dissertations

Readiness Spares Packages (RSP) are critical to deployed operations. Future demands of the Air Force require squadrons to operate in different climate environments from home stations. RSPs can sustain aircraft maintenance operations for up to 30 days. Currently, failure rates of parts within the RSP are assumed to be constant. This research aims to explore whether there is a difference in F-15 RSP failure rates when Koeppen climate classifications are taken into effect. The Koeppen-Geiger system classifies area climates based on the geography, elevation, and location. The history of operations and diversity of F-15 locations make the aircraft an ideal …

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The Innovative Technique For Obtaining The Solutions Of Jeffery Hamel Nano-Fluids Flow Problem, Haedir Abd Alrazak Namoos, Abeer Majeed Jasim Aug 2025

The Innovative Technique For Obtaining The Solutions Of Jeffery Hamel Nano-Fluids Flow Problem, Haedir Abd Alrazak Namoos, Abeer Majeed Jasim

Iraqi Journal for Computer Science and Mathematics

The study of heat transfer in nanofluid flows is increasingly important in many engineering, medical, and industrial applications. These fluids offer enhanced thermal cooling properties compared to conventional fluids. The research problem lies in the challenges of solving the Jeffrey-Hammel flow model for nanofluids, which includes coupled nonlinear differential equations that describe the thermal and hydrodynamic behavior of this type of flow, taking into account the influence of multiple factors such as the type, size, and concentration of nanoparticles. This research aims to propose a new hybrid analytical technique that combines the Laplace transform and the q-homotopy analysis technique with …

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Optimized Hybrid Watermarking: Dual-Scheme Strategies For Enhanced Robustness, Ooi Jessie, Liew Siau Chuin, Syifak Izhar Bt Hisham, Khor Hui Liang, Khoo Bee Ee, Jasni Mohamad Zain Aug 2025

Optimized Hybrid Watermarking: Dual-Scheme Strategies For Enhanced Robustness, Ooi Jessie, Liew Siau Chuin, Syifak Izhar Bt Hisham, Khor Hui Liang, Khoo Bee Ee, Jasni Mohamad Zain

Iraqi Journal for Computer Science and Mathematics

Digital watermarking is crucial in content identification and copyright protection, particularly multimedia and medical imaging. This paper introduces two novel hybrid watermarking methods, Entropy-Guided Singular Embedding (EGSE) and Entropy-Guided Hybrid Embedding (EGHE), that improve upon existing techniques by integrating entropy-based adaptive block selection with Particle Swarm Optimization (PSO) for dynamic embedding strength determination. Unlike traditional methods, which rely on fixed embedding regions or manual parameter tuning, the proposed approaches automatically identify high-entropy regions to embed watermark signals, ensuring stronger resistance to distortion while maintaining image quality. EGSE employs Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD), whereas EGHE enhances …

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Retracted: Efficient Multi-User Computation Offloading And Reducing Latency In Mobile-Edge Computing For Iot Applications, Sarmad T. Abdul-Samad, Osamah Al-Hwaidi, Ali Abd Al-Rasool Muslem Aug 2025

Retracted: Efficient Multi-User Computation Offloading And Reducing Latency In Mobile-Edge Computing For Iot Applications, Sarmad T. Abdul-Samad, Osamah Al-Hwaidi, Ali Abd Al-Rasool Muslem

Iraqi Journal for Computer Science and Mathematics

Mobile Edge Computing (MEC) is an inventive paradigm for computing that has the potential to notably diminish latency and energy consumption by transferring computationally demanding jobs to edge clouds near intelligent mobile users. This investigation aims to reduce offloading and latency between multiple users and edge computing in the context of Internet of Things (IoT) applications in the fifth generation (5G) by utilizing an optimization algorithm called the Bald Eagle Search Optimization Algorithm. Although employing deep learning methods might increase time consumption and computational complexity, an edge computing system enables devices to transfer their demanding jobs to edge servers, decreasing …

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Retracted: Iot Flow Parameters Classification Based On Machine Learning Techniques, El-Sayed M. El-Kenawy, Marwa M. Eid, Ban Salman Shukur, Amel Ali Alhussan, Doaa Sami Khafaga Aug 2025

Retracted: Iot Flow Parameters Classification Based On Machine Learning Techniques, El-Sayed M. El-Kenawy, Marwa M. Eid, Ban Salman Shukur, Amel Ali Alhussan, Doaa Sami Khafaga

Iraqi Journal for Computer Science and Mathematics

In recent years, there has been a highly remarkable convergence of artificial intelligence (AI) and the Internet of Things (IoT), which has made rapid progress in smart city initiatives by developing smart devices for such cities. Since these devices are increasingly diversified, they require a resilient communication network to demonstrate high performance in managing consistent traffic flows. A machine learning model intended for identifying network parameters from diverse devices, in addition to proposing modifications meant for network performance enhancement, is developed in this study. In relation to packet data as a network traffic parameter, employing gateway devices can facilitate its …

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Retracted: Metaguard: A Federated Learning Approach To Hybrid Xgboost And Meta-Learning Models For Proactive Cyber Threat Hunting, Shatha H. Jafer Al-Khalisy, Ghada Al-Kateb Aug 2025

Retracted: Metaguard: A Federated Learning Approach To Hybrid Xgboost And Meta-Learning Models For Proactive Cyber Threat Hunting, Shatha H. Jafer Al-Khalisy, Ghada Al-Kateb

Iraqi Journal for Computer Science and Mathematics

In an increasingly interconnected world, cybersecurity threats have become more sophisticated, necessitating advanced, scalable, and privacy-preserving solutions. MetaGuard emerges as a novel framework that integrates federated learning with hybrid machine learning models, specifically XGBoost and meta-learning, to enhance proactive cyber threat detection. This framework offers a robust, distributed approach to cybersecurity, ensuring high detection accuracy while preserving user privacy through the implementation of differential privacy and homomorphic encryption. MetaGuard leverages distributed nodes to collaboratively train a global model, enabling rapid adaptation to new threats without the need for centralized data aggregation. Experimental evaluations using the CYBER-2024 dataset demonstrate that MetaGuard …

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2015, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2015, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2015 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2019, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2019, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2019 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2014, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2014, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2014 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2017, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2017, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2017 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2018, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2018, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2018 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2020, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2020, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2020 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2021, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2021, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2021 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2022, Shelbie Wickett, Ana Dyreson Aug 2025

Hourly Simulated Power Production Data With Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2022 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata.

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Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren Aug 2025

Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren

Journal of System Simulation

Abstract: Traditional scene generation methods for maritime target recognition consider only the effects of different environments on the generated scene data, while overlooking the changes in scene information caused by sensor detection parameters, resulting in a lack of accuracy and authenticity in generated scenes. To address this issue, a detection parameter-based scene generation method for maritime target recognition was proposed. For the task of maritime target recognition, key detection parameters affecting scene generation quality and essential scene features were analyzed. An association relationship modeling method based on Bayesian networks was proposed to construct a mapping relationship model between scene features …

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Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang Aug 2025

Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang

Journal of System Simulation

Abstract: A multi-source information fusion approach based on the dempster-shafer (D-S) evidence theory with a fuzzy reward-penalty mechanism was proposed to address the issues of underreporting and false reporting in the early prediction of ship fires. PyroSim was utilized to construct a ship's laboratory model for fire simulation. Variations in carbon monoxide, temperature, and smoke concentration were recorded for data acquisition, followed by the application of a sigmf function for membership assignment. By leveraging the classical D-S theory, a reward-penalty mechanism was applied in weighted evidence fusion. Reward-penalty factors were utilized to differentiate various basic probability assignments, with unified belief …

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Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng Aug 2025

Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng

Journal of System Simulation

Abstract: The preliminary design of the overall operation performance of diesel engines cannot be guided by actual vehicle driving tests, which hinders the improvement of the power development level and efficiency of special vehicles. By using the virtual visual simulation engine Unity3D, two virtual driving scenario models were established: a flat road scenario and an undulating road scenario. Based on the speed characteristic parameters of the engine, a diesel engine's operation performance output model was constructed. Combined with the transmission system model and the longitudinal dynamics model of the vehicle's center of mass, a straight vehicle driving dynamics model was …

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Polymeric Nanocarriers Functionalized With Peptides For Improved Glioblastoma Targeting And Blood–Brain Barrier Permeability, Cristian Antonio Wieczorek Villas Boas, Aaron Priester, Buck E. Rogers, Anthony J. Convertine Aug 2025

Polymeric Nanocarriers Functionalized With Peptides For Improved Glioblastoma Targeting And Blood–Brain Barrier Permeability, Cristian Antonio Wieczorek Villas Boas, Aaron Priester, Buck E. Rogers, Anthony J. Convertine

Materials Science and Engineering Faculty Research & Creative Works

We report the synthesis of polymeric conjugates designed to penetrate the blood–brain barrier (BBB) and selectively bind glioblastoma (GBM) cells through reversible addition–fragmentation chain transfer (RAFT) polymerization. The resulting materials were engineered to contain peptide macromonomers for cell-specific targeting and integrated DOTA units to facilitate radiolabeling with copper-64 (64Cu), yielding radiolabeled conjugates with greater than 95% radiochemical purity. In biodistribution assessments conducted in mice, C1C2 peptide-conjugated polymers showed significantly improved accumulation in brain tissue, supported by brain perfusion analyses confirming efficient BBB penetration. Additionally, flow cytometry evaluations demonstrated specific affinity of GBM-targeted polymer formulations toward U87 glioblastoma cells. …

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Carbon-Infiltrated Carbon Nanotube Coated Ti6al4v Substrate Tensile And Torsion Raw Data, Jacquelyn Monroe, Brian Jensen Aug 2025

Carbon-Infiltrated Carbon Nanotube Coated Ti6al4v Substrate Tensile And Torsion Raw Data, Jacquelyn Monroe, Brian Jensen

ScholarsArchive Data

This data set contains the raw tensile and torsional Instron measurements reported in Carbon-Infiltrated Carbon Nanotube Coating Effect on Bacterial Resistance and Ti6Al4V Substrate Material Properties. The data in these files was used to generate the stress–strain curves presented in the study.

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Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei Aug 2025

Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei

Journal of System Simulation

Abstract: In order to improve the accuracy of load forecasting and fully extract the hidden relationships between load and other characteristic factors, a load forecasting method based on dual-attention temporal convolutional LSTM network (DA-TCLSNet) was proposed. Correlation analysis was conducted on the dataset using the maximum information coefficient method to perform feature screening to reduce the computational cost of the model. The model input was constructed using a sliding window. The DATCLSNet forecasting model was constructed. The temporal convolutional layer extracted dependencies at different time scales and captured the nonlinear characteristics among variables such as load and weather. The multi-head …

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