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Articles 2851 - 2880 of 195898
Full-Text Articles in Engineering
Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang
Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang
Journal of System Simulation
Abstract: To address the challenges of high data acquisition costs of test data on dynamic characteristics between tires and soft terrain and low speed of numerical calculation for unmanned vehicles in complex terrestrial environments, a modeling method of unmanned vehicle dynamics based on a neural network was proposed. Tire-terrain contact dynamics models were built by using discrete element method (DEM) simulations for tire-terrain contact and experimental data, thereby creating a dataset of tire contact forces for various tire materials in terrestrial environments. The neural network was applied to regressively learn the dataset, and a nonlinear neural network tire model was …
Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments, Dayong Liu, Zhiming Dong, Weidong Zhang, Wenjun Zhang, Jiancheng Gao
Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments, Dayong Liu, Zhiming Dong, Weidong Zhang, Wenjun Zhang, Jiancheng Gao
Journal of System Simulation
Abstract: The intelligence level of virtual forces is a key factor affecting the credibility and effectiveness of tactical confrontation simulations. To address the current lack of a testing and evaluation system, a method for testing and evaluating the intelligence level of virtual forces based on operational experiments is proposed. Guided by operational experiment theory, the method stimulates the intelligent behavior of virtual forces by constructing dynamic confrontation environments, and collects, calculates, analyzes, and evaluates their intelligence performance data according to a systematic process. The overall architecture, logical functional modules, and basic evaluation process of the method are designed. A "4M" …
Biomass Fuel Processing, Mineral Matter Engineering, And Ash Phase Equilibria For Deposition Control In Coal To Biomass Boiler Conversion, Spencer Bandi
Theses and Dissertations
As the conversion of coal utility boilers to 100% biomass combustors gains traction, understanding the interconnected impacts of harvesting and storage methods, fuel preparation, and thermochemical ash behavior is critical. This study evaluates miscanthus, switchgrass, and corn stover, targeting a < 1000 µm particle size through minimal (shredders/hammer mills) and heavy (pelletizing) pre-treatment. While heavy pre-treatment failed in a coal mill, minimal pre-treatment succeeded. Miscanthus (forage-harvested/silage-bagged) proved optimal, exhibiting minimal exogenous mineral accumulation up to (1.26 w%) and the smoothest mechanical feeding (deviation < 9%) due to its low particle aspect ratio. Conversely, baled switchgrass and corn stover accumulated up to 9.23 w% mineral matter and exhibited severe feeding resistance (>17% deviation) driven by fibrous, high-aspect-ratio morphologies. During combustion, agricultural residues yield low ash fusion temperatures (AFTs), generating deposits two to three times stronger than coal. To mitigate this severe fouling, mineral additives (coal fly ash, lime, and cement kiln dust) were injected. These additives effectively raised bulk AFTs and reduced deposit tenacity by up to 73%. Specifically, 2 w% …
Swosu Research And Scholarly Activity Fair 2026, Swosu Office Of Sponsored Programs
Swosu Research And Scholarly Activity Fair 2026, Swosu Office Of Sponsored Programs
SWOSU Research and Scholarly Activity Fair Programs
On behalf of the University Research and Scholarly Activity Committee (URSAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University, we are pleased to welcome you to the Thirty-Fourth SWOSU Research and Scholarly Activity Fair.
Uptake And Fate Of Silver And Zinc Engineered Nanoparticles In Maize Under Single And Binary Dosing Soil Ecosystems, Lei Xu, Qingbo Yang, Xingmao Ma, Honglan Shi, John Yang, Hu Yang, Samira Mahdi, Ying Wang, Young Shin Jun
Uptake And Fate Of Silver And Zinc Engineered Nanoparticles In Maize Under Single And Binary Dosing Soil Ecosystems, Lei Xu, Qingbo Yang, Xingmao Ma, Honglan Shi, John Yang, Hu Yang, Samira Mahdi, Ying Wang, Young Shin Jun
Chemistry Faculty Research & Creative Works
Recent agricultural applications of engineered metallic nanoparticles (ENPs) have raised concerns about their uptake and fate in plants. To understand this critical issue, this study investigated the fate and uptake of silver (Ag) and zinc oxide (ZnO) ENPs in maize (Zea mays L.) after single or binary ENP exposure in soil. Results indicated that both Zn and Ag elemental concentrations in roots increased with increasing ENP dosage. Ag NPs in the tissues were detected, but not Zn NPs. Ag NP concentration was 3 times higher in the roots than in the shoots at low Ag NP dosing, while Ag NP …
Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects, Bo Sun, Yi Ren, Silin Wang, Qi Liu, Zhidong Li
Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects, Bo Sun, Yi Ren, Silin Wang, Qi Liu, Zhidong Li
Journal of System Simulation
Abstract: Traditional system verification methods face significant challenges in terms of efficiency, coverage, and traceability. To address these issues, this paper introduced model-based system verification (MBSV), which deeply integrated verification activities within the model-based systems engineering model system and evolution process. It presented the foundational logic of MBSV and proposed a multiview unified verification modeling strategy based on system modeling language (SysML), integrating requirements, structure, behavior, and constraints. The paper discussed the algorithms for selecting representative paths and reducing equivalent classes to enhance verification efficiency, the principles of test path search, as well as the intelligent path search mechanism based …
Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications, Laichunyang Peng, Fei Ye, Xiaoming Guo, Jinglin Zhou
Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications, Laichunyang Peng, Fei Ye, Xiaoming Guo, Jinglin Zhou
Journal of System Simulation
Abstract: General-purpose large language models lack training on X language-specific corpora, and traditional fine-tuning methods lack targeted adaptation to the interdisciplinary integration and multimodule coupling of X language, resulting in problems such as non-standard syntax and semantic deviation in generated code. To address these issues, this paper systematically proposed the definition and integrated architecture of a large language model for X language simulation. Modeling subclasses were defined according to the disciplines and classes of X language, and dedicated adapters were constructed for each subclass. By merging their weights during the inference phase, the incremental integration of multi-domain modeling skills was …
Space-Ground Integrated Collaborative Positioning Algorithm And Simulation For Trajectory Enhancement, Juhui Wei, Xinyong Zhang, Jiongqi Wang, Xuanying Zhou, Zhangming He
Space-Ground Integrated Collaborative Positioning Algorithm And Simulation For Trajectory Enhancement, Juhui Wei, Xinyong Zhang, Jiongqi Wang, Xuanying Zhou, Zhangming He
Journal of System Simulation
Abstract: To address the challenges of low credibility, weak consistency, and poor accuracy in the information of trajectory results from space-based and ground-based passive time difference positioning simulation systems, a space-ground integrated collaborative positioning method was proposed for trajectory enhancement. By analyzing the operating principle of the time difference positioning system, the influencing factors that measure positioning accuracy in different feature dimensions were obtained; spline smoothing was employed for data alignment between space-based and ground-based systems; a spline-constrained parametric trajectory model was proposed to further enhance the stability; an error-sensitive feature selection framework for improving simulation consistency was constructed to …
Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping, Binhao Liang, Jingxuan Wei, Fengqin Liang
Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping, Binhao Liang, Jingxuan Wei, Fengqin Liang
Journal of System Simulation
Abstract: The decision variable dimension of large-scale multi-objective optimization problems can reach hundreds or even thousands. For existing large-scale multi-objective evolutionary algorithms based on decision variable analysis, which usually consume a large amount of computational resources for grouping and fail to consider the interactions between convergence-related variables and diversity-related variables, a large-scale multi-objective evolutionary algorithm based on multi-region adaptive dynamic grouping was proposed. The algorithm employed a Gaussian mixture model to partition the decision space into multiple regions; within each region, feature vectors were constructed for each decision variable, and spectral clustering was utilized to perform grouping. To validate …
Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation, Long Qin, Hesong Huang, Lujia Yin, Chuan Ai, Qi Zhang, Xinmeng Li
Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation, Long Qin, Hesong Huang, Lujia Yin, Chuan Ai, Qi Zhang, Xinmeng Li
Journal of System Simulation
Abstract: To solve the problems faced by the adversarial competition mode of agents, including difficult development and deployment, low resource utilization, poor reusability, and difficulty in accessing reinforcement learning algorithms, a new agent simulation training platform was designed. The software components of the competition platform were decoupled based on cloud-native technology; a high-performance simulation engine for the competition environment was proposed; a new method of an embedded reinforcement learning model for an intelligent control terminal was designed, with multiple online and offline policy-based reinforcement learning algorithms set. The experiment demonstrates that the development and deployment of the system is efficient, …
State Monitoring Of Nuclear Power Connection Sleeve Quality Inspection Equipment Driven By Digital Twin, Yandong Nan, Jinda Zhu, Xinbin Lu, Zhiying Qin, Dandan Qi, Zhiheng Ding
State Monitoring Of Nuclear Power Connection Sleeve Quality Inspection Equipment Driven By Digital Twin, Yandong Nan, Jinda Zhu, Xinbin Lu, Zhiying Qin, Dandan Qi, Zhiheng Ding
Journal of System Simulation
Abstract: To address the problems of delayed state perception, single monitoring dimension, and insufficient visualization in the quality inspection equipment for nuclear power connection sleeves, a state monitoring method driven by digital twin was proposed. A digital twin-based collaborative state monitoring framework for the inspection equipment was constructed. Based on the OPC UA technology, a multi-source information interconnection model was established. A finite state machine model was employed to discretize and logically drive the inspection process, and a hierarchical verification strategy was proposed to establish a multi-dimensional motion state monitoring mechanism. A surrogate model coupling the radial basis interpolation function …
Dynamic Model-Driven Verification Framework For Modular Aerial Bomb Systems, Wenlong Li, Shuhan Sang, Yusheng Liu, Haiyan He, Zan Liang, Wenqiang Yuan, Biao Niu, Weifeng Luo
Dynamic Model-Driven Verification Framework For Modular Aerial Bomb Systems, Wenlong Li, Shuhan Sang, Yusheng Liu, Haiyan He, Zan Liang, Wenqiang Yuan, Biao Niu, Weifeng Luo
Journal of System Simulation
Abstract: To address the problems of high verification costs, difficulty in covering dynamic behaviors, and lack of quantitative closed loops in the design stage of modular complex equipment, a dynamic model-driven modular system verification framework was proposed. Based on model-based systems engineering (MBSE) modeling, a structural coupling quantification model was constructed using the number of interfaces, signal interaction frequency, and dependency intensity. Dynamic tests were conducted in high-fidelity virtual simulation to collect data; performance rating for indicators such as accuracy, response, and stability, as well as system's comprehensive rating, were obtained, and the rating feedback was used for iterative optimization. …
Simulation On Water Hammer Characteristics Of Bipropellant Attitude And Orbit Control Propulsion System, Xianwei Lang, Yantao Wang, Fang Zhang, Yizhen Zu, Xinyu Zhang, Weibin Xiang
Simulation On Water Hammer Characteristics Of Bipropellant Attitude And Orbit Control Propulsion System, Xianwei Lang, Yantao Wang, Fang Zhang, Yizhen Zu, Xinyu Zhang, Weibin Xiang
Journal of System Simulation
Abstract: To address the water hammer problem in bipropellant attitude and orbit control propulsion systems during start-up, shutdown, and periodic operation, the water hammer characteristics under different operating conditions are investigated using simulation methods. The water hammer characteristics of annular and branched propellant delivery lines are compared, and the effects of multiengine interactions under various operating conditions, as well as the influence of water hammer on engine performance, are analyzed. The results show that the attenuation rate of pressure fluctuation in the annular pipeline system is significantly higher than that in the branch pipeline system. Under the condition of multi-cycle …
Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching, Cheng'en Pu, Yumin Lai, Rui Shi, Yan Liao, Kezi Meng, Lifeng Qu
Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching, Cheng'en Pu, Yumin Lai, Rui Shi, Yan Liao, Kezi Meng, Lifeng Qu
Journal of System Simulation
Abstract: To address the problem that the positioning precision of the inertial navigation system cannot meet the requirements of autonomous positioning when the aircraft flies, an autonomous positioning method with spatial translation based on circular scanning scene matching of SAR was proposed. The spatial translation positioning model of the aircraft was established according to the position of the ground matching points obtained by single point and single circular scanning scene matching of SAR, the oblique distance between the matching points and the aircraft, and the inertial measurement information of the aircraft. The characteristic information of the matching point sequence was …
Design And Application Of Collaborative Simulation System For Satellite Constellation Flight Missions, Dong Yan, Hanzhe Yang, Fangfang Jiang, Chengbao Liu, Peng Zhang
Design And Application Of Collaborative Simulation System For Satellite Constellation Flight Missions, Dong Yan, Hanzhe Yang, Fangfang Jiang, Chengbao Liu, Peng Zhang
Journal of System Simulation
Abstract: To meet the requirements of the collaborative drill for the ground operation and control system of the satellite constellation, as well as the verification and evaluation of in-orbit complex missions, the design ideas and implementation methods of the collaborative simulation system for satellite constellation flight missions were proposed. By adopting the time correction mechanism of the time-scale distributor, the time synchronization problem among the simulation nodes and the operation and control simulation system was solved. By adopting the communication technology based on improved PDXP + UDP, the problem of cross-node data interface and inter-satellite communication simulation was resolved. A …
Optimization Of Air Defense And Antimissile Firepower Resource Allocation Based On Adaptive Hybrid Evolution, Wei Liu, Delong Chen, Ze Liu, Rui Wang, Kaiwen Li, Tao Zhang
Optimization Of Air Defense And Antimissile Firepower Resource Allocation Based On Adaptive Hybrid Evolution, Wei Liu, Delong Chen, Ze Liu, Rui Wang, Kaiwen Li, Tao Zhang
Journal of System Simulation
Abstract: Air defense and antimissile firepower resource allocation is a core optimization problem in modern defense systems. Under complex conditions such as spatiotemporal constraints and firepower resource limitations, this problem involves the optimal configuration of limited interceptors and belongs to the class of NP-hard multi-constrained combinatorial optimization problems. This paper established a comprehensive mathematical model encompassing range constraints, time window constraints, feasibility matrices, and interception probability models. To address the high-dimensional nonlinearity of the problem, an adaptive hybrid evolutionary algorithm (AHEA) was proposed. The algorithm integrated problem-aware initialization, adaptive parameter control, seven specialized neighborhood search operators, and an adaptive strategy …
Research On Control Of Coaxial Dual-Rotor Unmanned Aerial Vehicle Based On Improved Reaching Law, Xinhang Chen, Xiaodong Ling, Chengchang Lang, Shijun Zheng, Yiqi Tang
Research On Control Of Coaxial Dual-Rotor Unmanned Aerial Vehicle Based On Improved Reaching Law, Xinhang Chen, Xiaodong Ling, Chengchang Lang, Shijun Zheng, Yiqi Tang
Journal of System Simulation
Abstract: To address the issues of significant chattering, slow convergence speed, and large overshoot in the control system of a coaxial dual-rotor unmanned aerial vehicle, a control method based on an improved double-power and hyperbolic function integral sliding mode reaching law was proposed. A novel reaching law was designed to achieve fast convergence when the system state is far from the sliding surface and smooth transition when approaching the sliding surface, thereby enhancing the overall convergence speed of the system and ensuring that the system reaches the sliding surface within a finite time. The saturation characteristic of the hyperbolic function …
Mechanism Analysis Of Parasitic Torque In Electric Loading Systems, Xiaozhe Sun, Zhenyu Fu, Zhaoke Xu, Jianxin Li
Mechanism Analysis Of Parasitic Torque In Electric Loading Systems, Xiaozhe Sun, Zhenyu Fu, Zhaoke Xu, Jianxin Li
Journal of System Simulation
Abstract: To address the issues of sources and mechanisms of parasitic torque in electric loading systems for aircraft actuator loads, a functional model of the electric loading system was established. Numerical simulations and Monte Carlo methods were employed to analyze the sources of parasitic torque and its primary influencing factors. The influence mechanisms and degrees of the system's external inputs and internal disturbances on parasitic torque were analyzed and validated through single-parameter and multi-parameter analyses. The results indicate that parasitic torque is predominantly influenced by factors such as loading command frequency, sensor signal bias, and loading motor parameters. In particular, …
Auv Path Planning Integrating Local-Global Strategies In Unknown Environments, Wenlong Meng, Yanbo Pu, Ya Gong
Auv Path Planning Integrating Local-Global Strategies In Unknown Environments, Wenlong Meng, Yanbo Pu, Ya Gong
Journal of System Simulation
Abstract: Existing path planning algorithms often struggle to efficiently explore and generate high-quality trajectories. To address this issue, this paper proposes a path planning algorithm that integrates local-global strategies. By employing the rolling window technique, the global one-time path planning problem is transformed into an iterative process of multiple local planning stages. During the global exploration phase, the rolling window is used to determine high-level path branches and to identify branch waypoints, thereby refining the calculation of local paths. In the local exploration phase, an improved RRT-Connect algorithm is proposed, which combines adaptive circular sampling with dynamic step length to …
Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li
Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li
Journal of System Simulation
Abstract: In view of the problems of incomplete elements and missing architecture in the research of target characteristics of target missiles, this paper introduced the panoramic view, operational view, and capability view models in the DoDAF from the perspective of system engineering. According to the view development sequence of "panoramic description, operational decomposition, and capability matching", a target characteristic architecture of the target missile was constructed, which included target elements such as maneuvering characteristics and infrared radiation characteristics. The mapping relationship among "operational layer, capability layer, and target characteristic layer" of the target missile was obtained, and the architecture was …
Overall Design Method Of Low Earth Orbit Communication Satellite Based On Mbse, Jiace Shang, Rui Zhang, Ya Dai, Hua Zhu, Siqi Hu, Linqiang Ge, Chenguang Shi
Overall Design Method Of Low Earth Orbit Communication Satellite Based On Mbse, Jiace Shang, Rui Zhang, Ya Dai, Hua Zhu, Siqi Hu, Linqiang Ge, Chenguang Shi
Journal of System Simulation
Abstract: Drawing on the model-centric design philosophy of model-based systems engineering (MBSE), this study constructs a model architecture suitable for the design and analysis of low Earth orbit communication satellites. This architecture adopts a multi-dimensional matrix approach. Vertically, it traverses the mission layer, system layer, satellite general design layer, and subsystem layer, achieving top-down hierarchical decoupling. Horizontally, it establishes a comprehensive view mapping mechanism covering the domains of requirements, functions, structure, and performance. Integrating the characteristics of product development, a modeling process covering the entire lifecycle—from mission demonstration and overall design to subsystem design and integration verification—has been established. The …
Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance, Guorong Wang, Haishun Deng, Ziming Kou, Xuanxuan Yan, Zhixiang Huang
Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance, Guorong Wang, Haishun Deng, Ziming Kou, Xuanxuan Yan, Zhixiang Huang
Journal of System Simulation
Abstract: To solve the problem of material demand fluctuation and different time windows in auxiliary transportation of underground mines, a routing optimization method for material distribution considering fuzzy demand and time tolerance was proposed. Based on the fuzzy credibility theory, uncertain demand was constrained by fuzzy chance constraints, and a multi-objective routing optimization model for underground mine auxiliary transportation was constructed with the objectives of minimizing the total operating cost of vehicles and maximizing time tolerance. A multi-objective genetic algorithm with mixed dominance strength was designed to solve the model. By calculating the deviation difference of Pareto frontier solutions, …
A Bilstm+Attention Method For Predicting The Intentions Of Air Combat Targets Based On Multi-Feature Continuous Time Series, Qiuni Li, Dong Wang, Chaozhe Wang, Zongcheng Liu
A Bilstm+Attention Method For Predicting The Intentions Of Air Combat Targets Based On Multi-Feature Continuous Time Series, Qiuni Li, Dong Wang, Chaozhe Wang, Zongcheng Liu
Journal of System Simulation
Abstract: To achieve advance prediction of enemy target intention, a three-layer air combat intention prediction method based on multi-feature continuous time series and BiLSTM+Attention, including trajectory prediction, threat assessment, and intention prediction was proposed. To prevent the onesidedness of intention prediction results caused by state information at a single moment, prediction was carried out from multiple state features and trajectory information in a continuous time series. An LSTM neural network was used to predict the trajectory of the target aircraft, and the threat assessment of the target aircraft before and after the prediction was conducted. The BiLSTM + Attention model …
Analysis For Predicting Surface Temperature And Combustion Of Heavy-Duty, Pre-Chamber-Enabled, Hydrogen Engines, Tony Spezia
Analysis For Predicting Surface Temperature And Combustion Of Heavy-Duty, Pre-Chamber-Enabled, Hydrogen Engines, Tony Spezia
Master's Theses (2009 -)
Hydrogen as an alternative fuel shows great promise to help reduce greenhouse gas emissions from heavy duty engines. However, the challenge for hydrogen engines is that hydrogen has very different combustion properties compared to conventional hydrocarbon fuels. Hydrogen has very high flame speeds, very low ignition energy, and very wide flammability limit. These properties result in hydrogen engines being prone to abnormal combustion. Abnormal combustion makes hydrogen engines difficult to control or can cause catastrophic damage to the engine, so it is important to avoid conditions where abnormal combustion occurs. Hot spots along the combustion chamber walls are often the …
Edgecube -- An Iot Edge-Sensor Node For Tiny Machine Learning Applications, Nathan Gerard Timmins
Edgecube -- An Iot Edge-Sensor Node For Tiny Machine Learning Applications, Nathan Gerard Timmins
Master's Theses (2009 -)
This thesis presents a novel internet-of-things (IoT) edge device, EdgeCube, a compact embedded system that combines a microcontroller unit (MCU) and a field-programmable gate array (FPGA). The proposed platform explores a trade-off between the performance gains achievable through FPGA-based acceleration and the associated increases in cost and power consumption. The primary contributions of this thesis include (1) the design of a compact hybrid MCU–FPGA edge architecture intended for vision workloads, (2) a streaming MCU-to-FPGA data path using SPI for frame transfer, and (3) an end-to-end hardware prototype and evaluation on an embedded inference task. Designed for IoT vision applications, EdgeCube …
Expanding The Convergence Canon: Indigenous Knowledge Systems And Place-Based Convergence Research In Lake Superior’S Keweenaw Bay, Usa, Melissa Baird, Valoree Gagnon, Judith Perlinger, Noel Urban, Larissa A. Juip, Kelly Kamm, Evelyn Ravindran, Caren Ackley, Cassandra M. Reed-Vandam
Expanding The Convergence Canon: Indigenous Knowledge Systems And Place-Based Convergence Research In Lake Superior’S Keweenaw Bay, Usa, Melissa Baird, Valoree Gagnon, Judith Perlinger, Noel Urban, Larissa A. Juip, Kelly Kamm, Evelyn Ravindran, Caren Ackley, Cassandra M. Reed-Vandam
Michigan Tech Publications
This study presents results from an NSF-funded convergence research project conducted in partnership with the Keweenaw Bay Indian Community (KBIC) in Michigan’s Upper Peninsula, USA. While convergence research frameworks often emphasize deep integration, we argue that participatory, place-based, and community-led convergence requires maintaining an integrity of difference. Through a systematic literature review, surveys and semi-structured interviews, we examined how team members operationalized convergence research and the Tribal Landscape System (TLS) framework. Across these data sources, convergence emerged as a negotiated practice shaped by distinct roles, institutional responsibilities, and long-term partnership commitments. Our findings demonstrate that ethical engagement, adaptive collaboration, and …
Physiobridge: Physiology-Constrained Self-Supervised Foundation Model For Cross-Device Ecg–Ppg Learning With Conformal Risk Control, Abbas Alzubaidi, Ali Al-Shuwaili, Ali Al-Bayaty
Physiobridge: Physiology-Constrained Self-Supervised Foundation Model For Cross-Device Ecg–Ppg Learning With Conformal Risk Control, Abbas Alzubaidi, Ali Al-Shuwaili, Ali Al-Bayaty
Electrical and Computer Engineering Faculty Publications and Presentations
Wearable and bedside sensors continuously generate electrocardiograms (ECG), photoplethysmograms (PPG), and related physiological waveforms that could enable earlier detection of deterioration and more personalized care. However, current deep learning pipelines in biomedical signal processing often remain taskand device-specific, degrade under domain shift (new hospitals, sensors, skin tones, motion), and provide limited uncertainty information for safety-critical decisions. We propose PhysioBridge, a foundation-model approach that learns a shared representation space for ECG and PPG via self-supervised pretraining and explicit physiology constraints, then supports downstream adaptation with distribution-free risk control. PhysioBridge introduces (i) multi-rate patch tokenization that preserves clinically meaningful morphology across heterogeneous …
Improving The Circuit Realization Of Grover’S Quantum Search Algorithm By Replacing Hadamard With √ × Gates, Ali Al-Bayaty, Ali Al-Shuwaili, Abbas Alzubaidi, Marek Perkowski
Improving The Circuit Realization Of Grover’S Quantum Search Algorithm By Replacing Hadamard With √ × Gates, Ali Al-Bayaty, Ali Al-Shuwaili, Abbas Alzubaidi, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
Jozsa, Bernstein-Vazirani, and Grover, utilize Hadamard gates to create uniform superposition states for the input qubits of an oracle. However, Hadamard gates are non-native (non-supported) gates in all real quantum computers. For this reason, Hadamard gates are considered cost-expensive gates when realizing (transpiling) such algorithms into a real quantum computer. This paper introduces a new methodology for cost-effective transpilation of Grover’s algorithm into real quantum computers, by replacing all Hadamard gates with √ X gates. In quantum computing, the Hadamard and √ X gates create uniform superposition states of a qubit on the Xaxis and Y-axis of the Bloch sphere, …
Evaluating The Impact Of Residential Landscape Audits Using 5-Second Water Use Data, Mahmud Aveek, Camilo J. Bastidas Pacheco, David E. Rosenberg, Jeffery S. Horsburgh, Kelly Kopp, Belize A. Lane
Evaluating The Impact Of Residential Landscape Audits Using 5-Second Water Use Data, Mahmud Aveek, Camilo J. Bastidas Pacheco, David E. Rosenberg, Jeffery S. Horsburgh, Kelly Kopp, Belize A. Lane
Civil and Environmental Engineering Student Research
We used 5-s water use data to evaluate the effectiveness of residential landscape water audits in summer 2022. Fifty-nine households in two northern Utah cities were monitored for 2–5 weeks before and 3–10 weeks after an audit. We found that the distribution of weekly irrigation volumes postaudit was statistically less than the distribution preaudit (significant at the 1.9E10-5 level). Collectively, the participants reduced their landscape irrigation water use by approximately 379,000 L per week (100,300 gal per week; 0.3 acre-feet per week). We also analyzed changes in irrigation event volume, duration, frequency, and the number of days between events at …
Interpretable Machine Learning For Predicting Splitting Strength Of Asphalt Concrete: Insights From Shap Analysis, Jianglei Xing, Xiao Tan, Yihao Li, Dongzhao Jin, Pengwei Guo, Yuhuan Wang, Huiya Niu
Interpretable Machine Learning For Predicting Splitting Strength Of Asphalt Concrete: Insights From Shap Analysis, Jianglei Xing, Xiao Tan, Yihao Li, Dongzhao Jin, Pengwei Guo, Yuhuan Wang, Huiya Niu
Michigan Tech Publications
This paper proposes an interpretable machine learning approach for predicting the splitting strength of asphalt concrete and supporting data-driven mixture design. A database consisting of 296 samples was constructed, and 14 input variables related to asphalt properties, aggregate gradation, and fiber characteristics were selected for modeling. Eight machine learning models, namely TabPFN, ANN, SVR, RF, XGBoost, LightGBM, FLAML, and FT-Transformer, were developed and compared. The results show that all eight models achieved satisfactory predictive capability, whereas TabPFN overall achieved the best performance in the Monte Carlo cross-validation, with the lowest average RMSE of 0.34 ± 0.10, the lowest average MAE …