Engineering Commons^™

Multi-Scenario Multi-Satellite Mission Planning Method Based On Adaptive Large Neighborhood Search, Xiutian Li, Ling Wang, Yingwu Chen, Lining Xing, Yingguo Chen

Journal of System Simulation

Abstract: To further improve the execution efficiency of remote sensing satellites, an integrated optimization framework combining adaptive large neighborhood search (ALNS) and a constraint programming-boolean satisfiability problem (CP-SAT) solver monitor was proposed, addressing the challenges of complex constraints, dynamic scale, and resource heterogeneity in multi-scenario multi-satellite mission planning. A unified multi-objective mixed-integer programming model was established, coupling heterogeneous constraints of point targets and area tasks. A time-domain rolling mechanism dynamically decomposed the problem scale, and a priority screening strategy enhanced the search efficiency of ALNS. Solution feasibility was verified in real time through the CP-SAT monitor. Results show that compared …

Dynamic Data Driven Simulation Based On Macro-Microscopic Hierarchical Simulation Models, Xu Xie, Yuqing Ma

Journal of System Simulation

Abstract:This paper proposed a dynamic data driven simulation approach based on macro-microscopic hierarchical simulation models. This approach enabled the measurement data from the real system to affect the macroscopic simulation and microscopic simulation in sequence and made the two simulations evolve together so that it could provide decision makers with the state evolution prediction of the real system at the macroscopic level to assist decision making and provide a microscopic testbed similar to the real system, on which decision makers could deduce and evaluate their strategies. This paper established a formal description of the approach and designed a data …

Research On High-Performance Optimization Methods For Fastdds In Heterogeneous Real-Time Simulation, Congping Liu, Wei Song, Jian Fang, Fei Liu

Journal of System Simulation

Abstract:FastDDS faces limitations under high-frequency data streams, such as lock contention, performance overhead from frequent context switching, and configuration complexity of multiple nodes under strict real-time constraints, which affect the experimental efficiency. This paper proposed a performance optimization method based on a batch-scalable circular queue (BSCQ). The approach replaced the traditional mutex mechanism with a lock-free algorithm to reduce lock contention and avoid deadlocks, while batch processing improved data locality, cache hit rates, and memory utilization, effectively reducing data transmission delay and improving system throughput. Hazard pointers were introduced to ensure safe memory management during batch processing and eliminate …

Reflections On Innovative Approaches To Autonomous Simulation Software, Feng Tian

Journal of System Simulation

Abstract: Given China's weak foundation in simulation software, simply replicating the development paths of these global leading companies offers limited potential for leapfrog development. Based on an analysis of pitfalls in the independent innovation of domestic simulation software, this paper proposed and elaborated on six strategic approaches: avoiding established paths, aligning with national realities, pursuing extreme performance, leveraging special needs to advance technology, building new systems from the ground up, and embracing artificial intelligence (AI)-native architectures. These strategies aim to provide new perspectives for the independent innovation and development of domestic simulation software.

Enhanced Restoration Of Covid-19 Ct Scan Images Utilizing Advanced Wiener Filtering Techniques, Warqaa Shaher Alazawee, Marwa Subhi Ibrahim, Raghda Salam Al Mahdawi, Ali Albu-Rghaif, Ahmed Sabri Altaie

Iraqi Journal for Computer Science and Mathematics

COVID-19, caused by the SARS-CoV-2 virus, was declared a global pandemic by the World Health Organization (WHO) and rapidly spread worldwide from late 2019. While Reverse Transcription Polymerase Chain Reaction (RT-PCR) is the primary diagnostic tool, its sensitivity ranges from only 60% to 70%, leading to false negatives. Computed Tomography (CT) imaging has emerged as a valuable alternative for accurate diagnosis; however, the quality of CT images is often degraded by motion-induced blur and additive noise, particularly in children, individuals with mental health conditions, or those with phobias of CT scans. This study aims to enhance COVID-19 CT image quality …

Motionfusion: A Robust Ensemble Learning Framework For Accurate Sensor-Based Human Activity Recognition, Hussein K. Almulla, Hussam J. Mohammed, Alaa S. Al-Waisy, Shumoos Al-Fahdawi, Ahmed Adnan Had, Bourair Al-Attar

Iraqi Journal for Computer Science and Mathematics

Human activity Recognition (HAR) has emerged as an important research area due to its potential applications in health, sport, and recreation. The widespread availability of smartphone sensors has facilitated data collection for HAR systems. Although machine learning and deep learning models have proven to be effective in detecting human activity from sensor data, their performance may be limited, this study proposes MotionFusion which is an ensemble learning model to increase HAR accuracy utilizing accelerometer and gyroscope data from a smartphone. By combining Histogram-Based Gradient Boosting, Random Forest, and Extra Trees models with a Support Vector Machine classifier and using feature …

Retracted: A Quantum Convolutional Neural Network Approach For Early And Accurate Diagnosis Of Parkinson's Disease, Aiesha Mahmoud Ibrahim, Mazin Abed Mohammed, Omar Al-Boridi

Iraqi Journal for Computer Science and Mathematics

Parkinson's disease (PD) is a progressive neurological disorder that primarily affects individuals over the age of 55. It is characterized by a range of motor and non-motor symptoms that can significantly impact various aspects of daily life. Despite notable advancements in medical science, there is currently no permanent cure or definitive treatment for PD. This therapeutic gap underscores the critical importance of early diagnosis, which remains a major focus of ongoing research. Due to the disease's gradual progression, PD symptoms may take years to fully develop, making early detection essential for improving patient outcomes and quality of life. Moreover, the …

Retracted: Solving Time-Fractional Nonlinear Variable-Order Delay Pdes Using Feedforward Neural Networks, Hala S. Alruhaili, Adel S. Hussain, Abdullah M. S. Ajlouni, Funda Türk, Emad A. Az-Zo’Bi, Mohammad A. Tashtoush

Iraqi Journal for Computer Science and Mathematics

This study presents an innovative application of Feedforward Neural Networks ‘FNNs’ to solve Variable-Order Fractional Partial Differential Equations ‘VO-FPDEs’ with time delays. Utilizing the Caputo definition, the variable-order fractional derivatives are approximated in terms of integer-order derivatives. The problem is reformulated as a system of partial differential equations with delay terms, which is then addressed using ‘FNNs’ to achieve explicit approximate solutions. Comprehensive error and convergence analyses validate the method’s precision and reliability. The effectiveness of the proposed approach is highlighted through numerical examples, with graphical and tabular representations showcasing minimal absolute errors and robust convergence. These results demonstrate the …

The Future Of Intelligent Industrial Systems: Plc, Node-Red, And Iot/Iiot, Firas Ahmed Hussein, Mohammad Tariq Yaseen, Mohammed Obaid Mustafa

AUIQ Technical Engineering Science

Integrating Programmable Logic Controllers (PLCs) with Node-RED and IoT/IIoT has emerged as a transformative technique for developing intelligent industrial systems as industrial automation improves. This narrative review brings together more than 70 research sources on industrial PLC, Node-RED, IoT, and IIoT applications. Case studies, experimental implementations, and industry reports are used to discover trends, challenges, and opportunities. The review focuses on three main topics: PLCs in modern industrial systems and their evolution and integration with IoT/IIoT; Node-RED as a middleware for industrial automation and its ability to connect PLCs to cloud and edge computing; and IIoT and smart manufacturing and …

Communication Assistance Using A Large Language Model, Justin Y. Li

Electrical and Computer Engineering Senior Theses

The number of people diagnosed with Autism Spectrum Disorder is growing annually at a rapid pace. Autistic people are known to have multiple problems with communication, requiring assistance and coaching which is already limited in availability due to the amount of training required. At the same time, there has been a recent exponential rise in usage of LLMs like ChatGPT which is widely available. This project aims to prototype a solution using ChatGPT to provide communication assistance to those diagnosed with autism. The project would record voice input through a microphone and transcribe it into text. The text would be …

Recent Advances In Modelling Of Frost Formation For Mechanical Systems, Yong Tao

Mechanical Engineering Faculty Publications

The physics underlying frost and ice formation has been extensively studied over the past few decades, with significant contributions to our understanding of this phenomenon. These insights have primarily been applied to engineering systems with refrigerated surfaces, such as refrigerators, freezers and heat pumps of various sizes. Despite considerable progress, the dynamic and complex mechanisms governing frost and ice formation remain an active area of research, as competing factors continue to challenge predictive accuracy. The increasing interest from stakeholders in reducing energy consumption and carbon footprints in mechanical systems further underscores the importance of advancing modelling and simulation capabilities in …

A Predictive Framework For Early Detection And Personalised Monitoring Of Parkinson’S Disease Using Artificial Intelligence And Large Language Models, Priyadharshini S

Theses and Dissertations

Parkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.

The research begins by analysing T2-weighted 3D …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

An Acoustofluidic Device For Sample Preparation And Detection Of Small Extracellular Vesicles, Jessica F. Liu, Jianping Xia, Joseph Rich, Shuaiguo Zhao, Kaichun Yang, Brandon Lu, Ying Chen, Tiffany Wen Ye, Tony Jun Huang

Faculty Publications

Small extracellular vesicles (sEVs) have emerged as powerful vectors for liquid biopsy, offering a noninvasive window into the dynamic physiological and pathological states of the body. However, to fully leverage the clinical potential of sEV biomarkers, it is imperative to develop robust and efficient technologies for their isolation and analysis. In this study, we introduce a novel sharp-edge acoustofluidic platform designed for rapid and effective sample preparation, coupled with sensitive detection of specific sEV populations based on their surface markers. Our approach utilizes acoustically activated sharp-edge microstructures to concentrate bead-bound sEVs within the microfluidic device, facilitating immediate visualization by fluorescence …

Solar Absorption Cooling Systems – A Case Study In Egypt, Hesham Safwat, Iman El-Mahallawi

Mechanical Engineering

Climate change with Egypt’s increasingly hot weather and plans towards energy transition, addressing an approach for clean HVAC (Heating, Ventilation, and Air Condition) solutions is becoming requisite. This paper examines the potential of utilizing solar absorption cooling systems in institutional buildings by presenting a case study of a proposed solar absorption cooling system for a library building with an area of 4402 m2, located at the British University in Egypt. The proposed solution is to replace 30% of the existing conventional air conditioning units with a hot-water driven single-effect absorption chiller powered by solar thermal vacuum tube solar collectors, coupled …

Stokes-Dependent Droplet Collection Efficiency On A Naca 0012 Airfoil From Droplet-Informed Simulations With Statistical Overloading, Arash Shad, Hashnayne Ahmed, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60≤⁢𝑈≤⁢240 m s−1 and the chord length of the airfoil in the range 0.5≤⁢𝑐≤⁢2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision …

A Rigorous Framework For An Improved Messinger/Myers Model Of Ice Accretion Under Conditions Of Variable Property And Unsteady Aircraft Icing, Hashnayne Ahmed, Arash Shad, ‪Nadim Zgheib, S. A. Sherif, S. Balachandar

Mechanical Engineering Faculty Publications

We analyse the Messinger/Myers model by critically evaluating simplifying assumptions through a rigorous formulation of the rime ice accretion process. We explore the effects of both constant and variable ice density and thermal conductivity, along with the effects of sublimation from the ice surface. The effects of key factors such as droplet impact rate, ambient temperature relative to the freezing temperature and the temperature difference between the ambient air and the airfoil surface are examined. Under these varying conditions, the present rigorous formulation is used to assess the significance of unsteady effects, variable ice properties and sublimation. We observe that …

Numerical Simulation Of Frost Formation And Heat Transfer On Fin-And-Tube Heat Exchangers In Turbulent Cross-Flow, Mahsan Farzaneh, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050≤𝑅⁢𝑒𝐷,avg≤4800, with the characteristic …

Fresh And Mechanical Properties Of Self-Compacting Concrete Using Kaolin Limestone Blend And Hybrid Slag Blend, Selesca Devi S

Theses and Dissertations

This study examined the consequences of mono and hybrid natural fibers on the mechanical and fresh properties of self-compacting concrete (SCC), in response to the growing demand for environmentally friendly building materials. In mono fiber, Abaca fiber (AF) at 0.25% and 0.5% dosage, basalt fiber (BF) from 0.25% to 2% at 0.25% increments, and sisal fiber (SiF) from 0.25% to 1.5% at 0.25% increments were evaluated through slump flow diameter, T500, compressive and tensile strength. AF at 0.25% ensured good flow with 6.6% and 4.16% higher compressive and tensile strength over 0.5% AF. SiF up to 1% improved strength but …

Enhancing Winter Climate Simulations Of The Great Lakes: Insights From A New Coupled Lake–Ice–Atmosphere (Cliav1) System On The Importance Of Integrating 3d Hydrodynamics With A Regional Climate Model, Pengfei Xue, Chenfu Huang, Yafang Zhong, Michael Notaro, Miraj Kayastha, Xing Zhou, Chuyan Zhao, Christa Peters-Lidard, Carlos Cruz, Eric Kemp

Michigan Tech Publications

The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States due to their vast thermal inertia, moisture source potential, and complex heat and moisture flux dynamics. This study presents a newly developed coupled lake–ice–atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA) Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulations of the Great Lakes’ winter climate. By integrating 3D lake hydrodynamics, CLIAv1 demonstrates superior performance in …

Retrospective Study And Predictive Modeling Of The Impact Of Social Determinants Of Health On Sepsis Outcomes, Mwembezi Aaron Nyelele

LSU Doctoral Dissertations

Sepsis, a life-threatening organ failure caused by the body’s abnormal and harmful response to an infection, remains a major global and national health challenge. In the United States, it contributes significantly to hospital mortality and imposes a substantial economic burden, with billions spent annually on treatment. Early diagnosis is difficult due to the nonspecific nature of sepsis symptoms, often leading to delays in care and poorer outcomes. As the incidence and severity of sepsis rise, identifying factors that influence outcomes is increasingly critical. Emerging research has shown that Social Determinants of Health (SDOH), including economic stability, education, neighborhood and built …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

Mode Engineering And Functional Enhancement In Piezoelectric-On-Silicon Mems Resonators With Magnetic Field Sensing Applications, Ugur Guneroglu

USF Tampa Graduate Theses and Dissertations

This dissertation significantly advances the field of micro-electro-mechanical systems (MEMS) resonators by exploring novel post-fabrication tuning techniques, electrode configuration effects, and innovative sensor applications for thin-film piezoelectric-on-silicon (TPoS) resonator devices. Driven by the increasing demand for tunable, high-precision and robust MEMS resonators in radio frequency (RF) applications such as sensing, timing, and filtering, this research aim to provide foundational knowledge and practical solutions for overcoming existing technological limitations. The dissertation is organized into three main research thrusts, each addressing critical challenges and opportunities in the design, fabrication, and application of TPoS MEMS resonators.

The first research thrust investigates an innovative …

Bonding Ss316l And In625 Through Laser Powder Bed Fusion And Directed Energy Deposition: A Comparative Tensile Analysis, Christopher J. Bettencourt, Nadia Kouraytem

Mechanical and Aerospace Engineering Student Publications and Presentations

Directed Energy Deposition (DED) was used to deposit Inconel 625 (IN625) onto 316L stainless steel (SS316L) substrates fabricated by Laser Powder Bed Fusion. Tensile properties of the resulting multi-material specimens were compared to those of the individual alloys. Two bonding approaches were evaluated: a direct transition and a 50/50 intermediate layer formed by blending equal parts of each alloy during deposition. The multi-material specimens demonstrated higher yield strength than the single alloys. However, samples with the 50/50 transition exhibited brittle failure at the joint, whereas the direct transition behaved more ductile. Scanning Electron Microscopy revealed microcracks at the interface of …

The Reactivation Of Moucharaby As Light Ornaments Through Digital Design, Noha Gamal Said, Amal Abu Daya

Mansoura Engineering Journal

Ornaments are considered essential part of architecture, contributing to the atmosphere and sense of place through its diverse visual effects. The Moucharaby is one of the traditional architectural elements that requires technical, professional, and artisanal knowledge to exist. It is closely related to light, affecting the privacy of the space and controlling the movement of the eye. Despite the disappearance of both elements: ornaments and Moucharaby from the modern architectural scene, the recent sustainability trends, parametric design, and modern technologies offer an opportunity to revive these elements. The article describes the experiential methodology of an intensive workshop that took place …

Security Analysis Of Encrypted Mempool, Prabal Das

Master’s Dissertations

With the rapid growth of Decentralized Finance (DeFi), the challenge of Maximum Extractable Value (MEV) has become increasingly significant-particularly on Ethereum. MEV allows malicious actors to manipulate transaction order within blocks, enabling exploitative strategies such as frontrunning and sandwich attacks. In response, recent research has proposed encrypted mempools, which conceal trans- action content until after ordering is finalized, thereby reducing the exploitable surface for MEV. This thesis investigates encrypted mempool, specifically the Shutter protocol, a threshold encryption-based approach designed to mitigate MEV by hiding transac- tion contents during the mempool phase. We analyze its core architecture, under- lying cryptographic mechanisms, …

Vibration-Based Detection For The Monitoring Of Neonatal Bcpap Respiratory Support To Minimize Duration Of Disconnections, Kaitlyn G. Calabresi, Meera R. Bhat, Lavinia L. Kong, Eli J. Foster, Jonathan Wang, Sangeeta Koilada, Angela Mak, Aastha Kapadia, Niam Mohseni, W. Keith Leung, Suneetha Desiraju, Constanza Miranda

School of Medicine Faculty Publications

Bubble continuous positive airway pressure (bCPAP) is a minimally invasive respiratory support for neonates experiencing respiratory distress syndrome (RDS). It exerts continuous, oscillatory air pressure to encourage lung function and development. Neonates’ movement may cause disconnections at the nasal interface. These disconnections are characterized by the cessation of bubbling at the bCPAP respiratory circuit output and frequently go unnoticed until hypoxia develops. Common Neonatal Intensive Care Unit (NICU) bCPAP systems lack a built-in alarm or accessory device to monitor for disconnections. As a result, nursing personnel must exercise extreme caution utilizing current bCPAP procedure. If a neonate is disconnected, it …

Advancing Eye-Gaze Writing Systems With Computer Vision, And Dynamic Text Suggestions, Walid Abdallah Shobaki

Theses and Dissertations

Eye gaze writing, a novel interaction modality, has the potential to revolutionize communication for individuals with limited mobility. In our research, we investigated the deep learning algorithms efficiency for real-time eye gaze writing. We have compared many algorithms' performance in many computer vision areas, such as object detection in which we used first YOLOv8, the second algorithm SSD, and the third algorithm is Faster R-CNN, the second computer vision area is the image segmentation in which we used DeepLab and U-Net, and the last computer vision area is self-supervised learning we have used SimCLR algorithm. By evaluating these models on …

Digital Twins For Circular Economy Optimization: A Framework For Sustainable Engineering Systems, Shubham Gupta

Harrisburg University Other Works

This paper introduces sustainable engineering systems built using digital twin technology and circular economy principles. This research presents a framework for monitoring, modeling, and making decisions in real timusing virtual replicas of physical products, processes, and systems in product lifecycles. A digital twin was used to show that through a digital twin, waste was reduced by 27%, energy consumption was reduced by 32%, and the resource recovery rate increased to 45%. The proposed approach under the framework employs various machine learning algorithms, IoT sensor networks, and advanced data analytics to support closed-loop flows of materials. The results show how digital …

Aeroponic System Optimization For Butterhead Lettuce Growth And Future Sustainability Using Flow Blurring Atomization: An Overview, Taylor J. Johnson

Beyond: Undergraduate Research Journal

The global population has grown by 6 billion people over the last century and is trending toward 9.7 billion people by the year 2050. Agriculture accounts for 70% of global fresh water usage. Technology must be developed to accommodate the increase of food production demanded by the growing global population and the subsequent increase in water usage. Aeroponic technology is a water-efficient vertical farming technology that can reduce water usage by 90% by suspending plant roots in air within a controlled chamber and supplying atomized droplets of a water-nutrient solution directly to the roots.

This study simultaneously tests six droplet …