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Articles 18901 - 18930 of 291673
Full-Text Articles in Physical Sciences and Mathematics
Recdreamer: Consistent Text-To-3d Generation Via Uniform Score Distillation, Chenxi Zheng, Yihong Lin, Bangzhen Liu, Xuemiao Xu, Yongwei Nie, Shengfeng He
Recdreamer: Consistent Text-To-3d Generation Via Uniform Score Distillation, Chenxi Zheng, Yihong Lin, Bangzhen Liu, Xuemiao Xu, Yongwei Nie, Shengfeng He
Research Collection School Of Computing and Information Systems
Current text-to-3D generation methods based on score distillation often suffer from geometric inconsistencies, leading to repeated patterns across different poses of 3D assets. This issue, known as the Multi-Face Janus problem, arises because existing methods struggle to maintain consistency across varying poses and are biased toward a canonical pose. While recent work has improved pose control and approximation, these efforts are still limited by this inherent bias, which skews the guidance during generation. To address this, we propose a solution called RecDreamer, which reshapes the underlying data distribution to achieve more consistent pose representation. The core idea behind our method …
The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun
The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun
Research Collection School Of Computing and Information Systems
We revisit two fundamental decentralized optimization methods, Decentralized Gradient Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We consider two settings and demonstrate that incorporating local update steps can reduce communication complexity. Specifically, for $\mu$-strongly convex and $L$-smooth loss functions, we proved that local DGT achieves communication complexity {}{$\tilde{\mathcal{O}} \Big(\frac{L}{\mu(K+1)} + \frac{\delta + {}{\mu}}{\mu (1 - \rho)} + \frac{\rho }{(1 - \rho)^2} \cdot \frac{L+ \delta}{\mu}\Big)$}, where $K$ is the number of additional local update}, $\rho$ measures the network connectivity and $\delta$ measures the second-order heterogeneity of the local losses. Our results reveal the tradeoff between communication and …
Financial Named Entity Recognition: How Far Can Llm Go?, Yi-Te Lu, Yintong Huo
Financial Named Entity Recognition: How Far Can Llm Go?, Yi-Te Lu, Yintong Huo
Research Collection School Of Computing and Information Systems
The surge of large language models (LLMs) has revolutionized the extraction and analysis of crucial information from a growing volume of financial statements, announcements, and business news. Recognition for named entities to construct structured data poses a significant challenge in analyzing financial documents and is a foundational task for intelligent financial analytics. However, how effective are these generic LLMs and their performance under various prompts are yet need a better understanding. To fill in the blank, we present a systematic evaluation of state-of-the-art LLMs and prompting methods in the financial Named Entity Recognition (NER) problem. Specifically, our experimental results highlight …
Synthesis And Characterization Of Eco-Engineered Hollow Fe2o3/Carbon Nanocomposite Spheres: Evaluating Structural, Optical, Antibacterial, And Lead Adsorption Properties, Islam Gomaa
Nanotechnology Research Centre
This work presents a facile mechano-thermal route for the synthesis of carbon-decorated, hollow, mesoporous α-Fe2O3 microspheres. Comprehensive characterization (XRD, XPS, FT-IR, SEM/EDX, TGA, zeta-potential) confirmed the formation of phase-pure hematite with nanoscale crystallites (~19 nm), substantial residual surface carbon (~40 wt%) consistent with Fe–O–C linkages, and a positive surface charge (+15.9 mV). The hierarchical hollow/mesoporous architecture enables fast ion transport and provides extensive interior binding sites, resulting in rapid Pb(II) uptake that reaches 92% removal in ≈15 min at pH 5.0. The adsorption follows a Langmuir isotherm (qmax ≈ 70.6 mg/g) and pseudo-second-order kinetics, indicative of chemisorption coupled to efficient …
Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz
Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz
Theses
This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …
Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern
Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern
Doctoral
From aerospace to agriculture, sensors play a fundamental role in many aspects of modern life. Sensors form an integral part of the complex systems and devices required for the continued functioning and development of services and industries across society. The use of sensors is paramount in areas affecting human health, one such area being the monitoring of indoor air quality, in particular the detection of volatile organic compounds (VOCs). Human contact with VOCs has been associated with many health complications, including skin and eye irritation, cardiovascular damage, and cancers. Optical, electrical, gravimetric, and chemical sensors have been developed for VOC …
Cover Crops Can Reduce Greenhouse Gas Emissions From No-Till Maize In Southern Brazil: Insights From A Long-Term Field Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimélio Bayer
Cover Crops Can Reduce Greenhouse Gas Emissions From No-Till Maize In Southern Brazil: Insights From A Long-Term Field Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimélio Bayer
Adam Liska Papers
Brazil is one of the countries that has the most agricultural area under no-till (NT) management. This research study aims to evaluate life-cycle greenhouse gas (GHG) emissions from maize (M) grain production in agroecosystems that used different cover crops under NT management in southern Brazil. The data for this study were from a long-term 41-year field experiment in southern Brazil. The long-term experiment evaluated the effects of fallow (F) and cover crops (oat (O), vetch (V), cowpea (B), pigeon pea (P), and lablab (L)) on nitrous oxide and methane emissions and soil carbon (C) sequestration in maize agroecosystems. Five cropping …
Deep Reinforcement Learning With Explicit Context Representation, Francisco Munguia-Galeano, Ah-Hwee Tan, Ze Ji
Deep Reinforcement Learning With Explicit Context Representation, Francisco Munguia-Galeano, Ah-Hwee Tan, Ze Ji
Research Collection School Of Computing and Information Systems
Though reinforcement learning (RL) has shown an outstanding capability for solving complex computational problems, most RL algorithms lack an explicit method that would allow learning from contextual information. On the other hand, humans often use context to identify patterns and relations among elements in the environment, along with how to avoid making wrong actions. However, what may seem like an obviously wrong decision from a human perspective could take hundreds of steps for an RL agent to learn to avoid. This article proposes a framework for discrete environments called Iota explicit context representation (IECR). The framework involves representing each state …
Designing An Affordable Motion Capture System For Multi-Robot Research And Education, Hojune Kim , '25
Designing An Affordable Motion Capture System For Multi-Robot Research And Education, Hojune Kim , '25
Senior Theses, Projects, and Awards
In this work, we propose a low-cost motion capture system for real-time tracking of multiple robots’ positions and orientations in indoor environments, specifically tailored for research and educational applications. Precise localization is essential for evaluating robotics algorithms such as decentralized multi-agent control, cooperative path planning, and collision avoidance. [1-3] However, commercial motion capture systems like Vicon and OptiTrack cost between $50,000 and $150,000, making them inaccessible for many smaller institutions, student clubs, and low-resource labs. To address this challenge, we developed an affordable alternative based on three ceiling-mounted 1080p USB cameras and AprilTags. Our system operates at 30 Hz and …
Offline Guessing Games With Two Numbers, Justin Sciullo, Lisa Shen, Sarah Zaske
Offline Guessing Games With Two Numbers, Justin Sciullo, Lisa Shen, Sarah Zaske
Mathematics Undergraduate Research
In an offline guessing game, there is a player called the Questioner and a player called the Responder. The Responder first picks two distinct numbers from the set {1, 2, 3, . . . , n}. The Questioner then creates a set of questions of the form “How many of your numbers are in the set qi ⊆ {1, 2, 3, . . . , n}?” and sends them to the Responder who answers them. The Questioner wins if they can guess the Responder’s numbers no matter which numbers the Responder chose. The Responder wins otherwise. We …
Guessing Games To Determine 1 Of Several Secret Numbers, Kyle Mckee, Julia Osmun, Dori Schlutt
Guessing Games To Determine 1 Of Several Secret Numbers, Kyle Mckee, Julia Osmun, Dori Schlutt
Mathematics Undergraduate Research
A guessing game is a two-player game between a Responder and a Questioner. In a guessing game, the Responder is thinking of x ≥ 1 secret numbers in a set S of size n. The Questioner is tasked with asking questions of the form: “How many numbers are in Q ⊆ S?” until the Questioner knows at least 1 of the Responder’s secret numbers. We find a game-winning strategy for the Questioner with minimal possible questions for games with x = 2. We also find lower-bounds for x = 2 and x = 3.
Investigations Of Conjugate Heat Transfer And Fluid Flow In Partitioned Porous Cavity Using Darcy-Forchheimer Model: Finite Element-Based Computations, Nasir Yasin, Shafee Ahmad, Muhammad Umair, Zahir Shah, Narcisa Vrinceanu, Ghadah Alhawael
Investigations Of Conjugate Heat Transfer And Fluid Flow In Partitioned Porous Cavity Using Darcy-Forchheimer Model: Finite Element-Based Computations, Nasir Yasin, Shafee Ahmad, Muhammad Umair, Zahir Shah, Narcisa Vrinceanu, Ghadah Alhawael
Mathematics & Statistics Faculty Publications
The conjugate heat transfer and fluid flow has vast applications in thermal engineering, particularly for cooling in thermal devices, and automobile engines. This study investigates conjugate heat transfer in 2D enclosures, featuring thin solid fins attached to a porous bottom wall. The porous medium is considered isotropic and homogeneous by the Darcy-Forchheimer model, with fluid phases in local thermal equilibrium. The boundary conditions at the porous fluid interface ensure continuity of the velocities, stresses, temperature, and heat flux. The phenomenon is mathematically modelled by obtaining a set of partial differential equations. The finite element method (FEM) is used to perform …
Cyberattacks On Port Infrastructures: A Decade Of Trends, Incidents, And Mitigation Strategies (2011-2024), Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Gabriel Raicu
Cyberattacks On Port Infrastructures: A Decade Of Trends, Incidents, And Mitigation Strategies (2011-2024), Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Gabriel Raicu
Engineering Management & Systems Engineering Faculty Publications
Port infrastructures are critical to global trade, handling over 80% of the world's cargo by volume. However, their increasing reliance on digital technologies has exposed them to a wide range of cyber threats. This paper provides a comprehensive analysis of cyberattacks targeting port infrastructures from 2011 to the present. We examine the types of attacks, geographical distribution, notable incidents, and underlying vulnerabilities. Additionally, we discuss mitigation strategies and future directions for enhancing cybersecurity in the maritime sector. Our findings highlight the urgent need for robust regulatory frameworks, advanced technological solutions, and collaborative efforts to safeguard critical port operations.
Advancing Root Trait Measurements For A Deeper Understanding Of Soil Biogeochemistry, Brian Rinehart
Advancing Root Trait Measurements For A Deeper Understanding Of Soil Biogeochemistry, Brian Rinehart
Theses and Dissertations--Plant and Soil Sciences
Climate change is disrupting (agro)ecosystems, with the potential for significant losses in crop productivity and ecosystem resilience due to changes in water and biogeochemical cycling. These disruptions can also release more carbon dioxide into the atmosphere through the degradation of soil organic matter. Plant roots have emerged as a potential tool for mitigating these effects, given their roles in plant function and in driving soil biogeochemistry. While this interest is growing, our ability to implement root trait selection is limited due to constraints on characterizing roots and limited clarity on the effects of traits on plant and ecosystem function. My …
Giving Props To Soil Property Predictive Models: Utilizing Mir To Predict Soil Health Properties, Diala M. Abboud
Giving Props To Soil Property Predictive Models: Utilizing Mir To Predict Soil Health Properties, Diala M. Abboud
Theses and Dissertations--Plant and Soil Sciences
Soil health is critical to sustaining life on Earth, influencing plant growth, agricultural productivity, water quality, and overall ecosystem sustainability. In response to climate change and intensifying land use, the need to improve our understanding of soil health has become increasingly urgent. The application of mid-infrared (MIR) spectroscopy coupled with statistical modeling has emerged as a promising, cost-effective approach to predict soil health parameters, offering a quicker alternative to traditional wet chemistry analyses. MIR methods have been successfully applied to predict various soil health properties, such as bulk density (BD), cation exchange capacity (CEC), base saturation (BS), electrical conductivity (EC), …
Maternal Vulnerability Index And Severe Maternal Morbidity, Nansi S. Boghossian, Joshua Radack, Molly Passarella, Ciaran S. Phibbs, Lucy T. Greenberg, Jeffrey S. Buzas, George R. Saade, Jeannette Rogowski, Scott A. Lorch
Maternal Vulnerability Index And Severe Maternal Morbidity, Nansi S. Boghossian, Joshua Radack, Molly Passarella, Ciaran S. Phibbs, Lucy T. Greenberg, Jeffrey S. Buzas, George R. Saade, Jeannette Rogowski, Scott A. Lorch
Faculty Publications
Importance: Few studies have investigated the association of composite measures of neighborhood social determinants of health with severe maternal morbidity (SMM), and no research has examined this association for indices tailored to maternal health. Objective: To examine the association of scores in the Maternal Vulnerability Index (MVI), a tool developed to measure maternal risk of adverse health outcomes, with SMM. Design, Setting, and Participants: This retrospective, population-based cohort study was conducted in 5 states (2008-2020 for Michigan, Oregon, and South Carolina; 2008-2018 for Pennsylvania; and 2008-2012 for California) among individuals delivering a fetal death or a live birth between 22 …
Caregiving Burdens Of Task Time And Task Difficulty Among Paid And Unpaid Caregivers Of Persons Living With Dementia, Matthew Lee Smith, Jodi L. Southerland, Malinee Neelamegam, Gang Han, Shinduk Lee, Chung Lin Kew, Juanita Dawne R. Bacsu, Elyse Couch, Steffi M. Kim, Monique J. Brown Ph.D., Mph, Ayse Malatyali, Lucas Wilson, Zahra Rahemi, Jeremy Holloway, Marcia G. Ory
Caregiving Burdens Of Task Time And Task Difficulty Among Paid And Unpaid Caregivers Of Persons Living With Dementia, Matthew Lee Smith, Jodi L. Southerland, Malinee Neelamegam, Gang Han, Shinduk Lee, Chung Lin Kew, Juanita Dawne R. Bacsu, Elyse Couch, Steffi M. Kim, Monique J. Brown Ph.D., Mph, Ayse Malatyali, Lucas Wilson, Zahra Rahemi, Jeremy Holloway, Marcia G. Ory
Faculty Publications
Background: Demands of caregivers of persons living with dementia (PLWD) are often influenced by the context of their caregiving situation. This study examines common and unique factors associated with caregiving burden in terms of task time and task difficulty among paid and unpaid caregivers of PLWD. Methods: Cross-sectional baseline survey data were analyzed from 107 paid and unpaid caregivers of PLWD participating in a larger NIH-funded study assessing the feasibility of using a novel in-situ sensor system. Oberst Caregiving Burden Scale constructs of task time and task difficulty served as dependent variables. Two least squares regression models were fitted, controlling …
Investing In The Development Of The Next Generation Of Mch Leaders, Karen A. Mcdonnell, Jamal Percy, Lisa Anders, Monique J. Brown Ph.D., Mph, Alice R. Richman, Julianna Deardorff, Monica S. Ruiz, Jihong Liu Sc.D., Kelli Russell, Audrey Snyder, Cassondra Marshall
Investing In The Development Of The Next Generation Of Mch Leaders, Karen A. Mcdonnell, Jamal Percy, Lisa Anders, Monique J. Brown Ph.D., Mph, Alice R. Richman, Julianna Deardorff, Monica S. Ruiz, Jihong Liu Sc.D., Kelli Russell, Audrey Snyder, Cassondra Marshall
Faculty Publications
The public health landscape is constantly evolving to address the strengths and needs of the community. Training for the public health workforce is leading the way, establishing an ecosystem approach that integrates individuals within social, political, and environmental contexts to promote health equity within a framework of social justice. One area of public health that is innovatively preparing the next generation of leaders is maternal and child health (MCH). In the United States, key indicators of health disparities within MCH remain stagnant, highlighting the need for training programs that develop future MCH professionals from diverse backgrounds. These professionals will deliver …
Healthcare Providers’ Perspective On Hiv Testing And Hypothetical Mhealth-Connected Linkage To Care Among Men Who Have Sex With Men (Msm) In South Carolina, Tony Brown, Prince Nii Ossah Addo, Monique J. Brown Ph.D., Mph, Xiaoming Li, Oluwafemi Adeagbo
Healthcare Providers’ Perspective On Hiv Testing And Hypothetical Mhealth-Connected Linkage To Care Among Men Who Have Sex With Men (Msm) In South Carolina, Tony Brown, Prince Nii Ossah Addo, Monique J. Brown Ph.D., Mph, Xiaoming Li, Oluwafemi Adeagbo
Faculty Publications
Background: HIV continues to be an important public health concern in South Carolina (SC). However, an examination of providers’ willingness to use mHealth technologies to address ongoing barriers to HIV care and prevention strategies, particularly among men who have sex with men (MSM) is currently lacking in SC. We therefore explored HIV care providers’ perceptions of HIV testing and treatment uptake among MSM, and providers’ willingness to use mHealth technology to address barriers to HIV testing and treatment in SC. Methods: Between August and December 2021, we conducted semistructured virtual interviews with 10 HIV care providers recruited purposively based on …
Sars-Cov-2 Detection And Persistence In A Remote Amazonian Settlement, Glauco M. Silva, Roberto C. Ilacqua, Franciely G. Gonçalves, Carla M. Santana, Felipe T. Jordão, Paula R. Prist, Melissa S. Nolan Ph.D., Mph, Andreia F. Brilhante, Marcia A. Sperança, Gabriel Z. Laporta
Sars-Cov-2 Detection And Persistence In A Remote Amazonian Settlement, Glauco M. Silva, Roberto C. Ilacqua, Franciely G. Gonçalves, Carla M. Santana, Felipe T. Jordão, Paula R. Prist, Melissa S. Nolan Ph.D., Mph, Andreia F. Brilhante, Marcia A. Sperança, Gabriel Z. Laporta
Faculty Publications
Background: COVID-19 continues to pose a major global health challenge. Despite its geographic distance from Brazil’s major urban centers, Acre state has experienced notable outbreaks. This study assessed the detection and persistence of SARS-CoV-2 in the rural settlement of Santa Luzia, located in the remote municipality of Cruzeiro do Sul, Acre state, Brazil. Methods: In July 2022, a cross-sectional survey was conducted at 40 sites from an ongoing environmental study, selected by deforestation patterns and proximity to health posts. Saliva samples were collected from residents aged 5–90 years, followed by nucleic acid extraction and multiplex RT-qPCR for SARS-CoV-2 detection. Results: …
Socially Shared Regulation Of Learning And Artificial Intelligence: Opportunities To Support Socially Shared Regulation, Jinhee Kim, Rita Detrick, Seongryeong Yu, Yukyeong Song, Linda Bol, Na Li
Socially Shared Regulation Of Learning And Artificial Intelligence: Opportunities To Support Socially Shared Regulation, Jinhee Kim, Rita Detrick, Seongryeong Yu, Yukyeong Song, Linda Bol, Na Li
STEMPS Faculty Publications
Supporting learners in achieving high-level socially shared regulation of learning (SSRL) in the online collaborative learning (OCL) context presents challenges that the utilization of artificial intelligence (AI) technologies may help solve. However, the effective uses of AI to support multifaceted areas (cognition, metacognition, and motivation) and phases (forethought, performance, and reflection) of SSRL remain elusive. Furthermore, research on developing an educational AI and what pedagogical attributes and elements are required for AI to support students' SSRL effectively is limited. This study, therefore, aims to investigate students' perceptions of AI applications in enhancing SSRL and to explore the essential pedagogical elements …
The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis
The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis
STEMPS Faculty Publications
Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …
Designing Ai-Powered Learning: Adult Learners' Expectations For Curriculum And Human-Ai Interaction, Jinhee Kim, Seongryeong Yu, Rita Detrick, Xi Lin, Na Li
Designing Ai-Powered Learning: Adult Learners' Expectations For Curriculum And Human-Ai Interaction, Jinhee Kim, Seongryeong Yu, Rita Detrick, Xi Lin, Na Li
STEMPS Faculty Publications
Despite the potential benefits offered by GenAI technologies to provide innovative solutions to address distinct challenges faced by working adult learners (ALs) in higher education and beyond, there is limited understanding of how best to structure AI-powered learning for this population while ensuring their distinct needs and perspectives are considered. Hence, this study aimed to determine what curriculum and student-AI interaction would be required by situating ALs’ views. Through analyzing 48 e-portfolios and in-depth interviews with 20 ALs from diverse educational and professional backgrounds, the study found that ALs perceived content mastery and developing a lifelong habit of learning as …
Editorial: Ai's Impact On Higher Education: Transforming Research, Teaching, And Learning, Alyse Jordan, Ashley L. Dockens, Natalia Anastasia Pierson, Xinyue Ren
Editorial: Ai's Impact On Higher Education: Transforming Research, Teaching, And Learning, Alyse Jordan, Ashley L. Dockens, Natalia Anastasia Pierson, Xinyue Ren
STEMPS Faculty Publications
[Introduction] This Research Topic provides a comprehensive examination of how artificial intelligence (AI) is transforming higher education. The collected studies reveal several interconnected themes that illuminate both the opportunities and challenges of AI integration in academic settings. This editorial summarizes these themes and articulates their significance for the future of higher education.
Evidence For Crustal Brines And Deep Fluid Infiltration In An Oceanic Transform Fault, Christine Chesley, Katherine Enright
Evidence For Crustal Brines And Deep Fluid Infiltration In An Oceanic Transform Fault, Christine Chesley, Katherine Enright
All Student Scholarship
Although oceanic transform faults (OTFs) are ubiquitous plate boundaries, the geological processes occurring along these systems remain underexplored. The Gofar OTF of the East Pacific Rise has gained attention due to its predictable, yet enigmatic, earthquake cycle. Here, we present results from the first ever controlled-source electromagnetic survey of an OTF, which sampled Gofar. We find that the fault is characterized by a subvertical conductor, which extends into the lower crust and thus implies deep fluid penetration. We also image subhorizontal crustal conductors distributed asymmetrically about the fault. We interpret these subhorizontal anomalies as crustal brines, and we suggest that …
A Method For Empirically Assessing Small Area Estimators Via Bootstrap-Weighted K-Nearest-Neighbor Artificial Populations, With Applications To Forest Inventory, Grayson W. White, Jerzy Wieczorek, Zachariah W. Cody, Emily X. Tan, Jacqueline O. Chistolini, Kelly S. Mcconville, Tracey S. Frescino, Gretchen G. Moisen
A Method For Empirically Assessing Small Area Estimators Via Bootstrap-Weighted K-Nearest-Neighbor Artificial Populations, With Applications To Forest Inventory, Grayson W. White, Jerzy Wieczorek, Zachariah W. Cody, Emily X. Tan, Jacqueline O. Chistolini, Kelly S. Mcconville, Tracey S. Frescino, Gretchen G. Moisen
Faculty Journal Articles
National Forest Inventories monitor forest attributes across a variety of spatial and temporal scales in a given country. Increased interest in reporting and management at smaller scales has driven National Forest Inventories to investigate and adopt small area estimation (SAE) due to the promise of increased precision at these scales. However, comparing and evaluating SAE models for a given application is inherently difficult. Typically, many areas lack enough data to check unit-level modeling assumptions or to assess unit-level predictions empirically; and no ground truth is available for checking area-level estimates. Design-based simulation from artificial populations can help with each of …
Small Area Estimation Of Forest Biomass Via A Two-Stage Model For Continuous Zero-Inflated Data, Grayson W. White, Josh K. Yamamoto, Dinan H. Elsyad, Julian F. Schmitt, Niels H. Korsgaard, Jie Hu, George C. Gaines Iii, Tracey S. Frescino, Kelly S. Mcconville
Small Area Estimation Of Forest Biomass Via A Two-Stage Model For Continuous Zero-Inflated Data, Grayson W. White, Josh K. Yamamoto, Dinan H. Elsyad, Julian F. Schmitt, Niels H. Korsgaard, Jie Hu, George C. Gaines Iii, Tracey S. Frescino, Kelly S. Mcconville
Faculty Journal Articles
Nationwide Forest Inventories (NFIs) collect data on and monitor the trends of forests across the globe. Users of NFI data are increasingly interested in monitoring forest attributes such as biomass at fine geographic and temporal scales, resulting in a need for assessment and development of small area estimation techniques in forest inventory. We implement a small area estimator and parametric bootstrap estimator that account for zero-inflation in biomass data via a two-stage model-based approach and compare the performance to a Horvitz–Thompson estimator, a post-stratified estimator, and to the unit- and area-level empirical best linear unbiased prediction (EBLUP) estimators. We conduct …
Regulation Of Haemodynamic Variables By Laguerre Polynomials Based Model Predictive Control., Sai Sandeep Boda, Hiren Kumar G. Patel, Khyati D. Mistry
Regulation Of Haemodynamic Variables By Laguerre Polynomials Based Model Predictive Control., Sai Sandeep Boda, Hiren Kumar G. Patel, Khyati D. Mistry
ASEAN Journal on Science and Technology for Development
Purpose: Cardiac output (CO) and Mean Arterial Pressure (MAP) are two haemodynamic variables that need regulation in clinical situations, particularly in post-cardiac surgery patients. As it is difficult for clinical personnel to monitor continuously, automatic drug infusion to regulate MAP and CO is recommended and essential in the medical environment. Methods: Two input and two output patient model was used in this work to study the variation of haemodynamic variables in response to the infusion of Dopamine (DP) and Sodium Nitroprusside (SNP) drugs. Model predictive control (MPC) algorithm was exercised here as it was a well-established technique to regulate output …
The Influence Of The Digital Economy On The Ecological Environment And Its Sustainable Development, Xinpan Lyu, Jianhua Dai
The Influence Of The Digital Economy On The Ecological Environment And Its Sustainable Development, Xinpan Lyu, Jianhua Dai
ASEAN Journal on Science and Technology for Development
This study aims to examine the impact of the digital economy on ecological sustainability and its development in China from 2000 to 2022. The study focuses on the role of innovation in the digital sector, where the adoption of big data technologies is considered, with reference to sustainable development, from an environmental perspective. A dynamic threshold model and, in particular, the Iterated Generalized Least Squares (IGLS) technique is used to analyze the given data.The research reveals a significant link between adopting digital technologies and managing environmental sustainability efficiently. To investigate the interconnection between the digital economy and ecological goals, it …
Snake Optimization Algorithm For Fractional Order Controller In Three-Area Load Frequency Regulation, Shubra Goel, Omveer Singh
Snake Optimization Algorithm For Fractional Order Controller In Three-Area Load Frequency Regulation, Shubra Goel, Omveer Singh
ASEAN Journal on Science and Technology for Development
The transition toward renewable energy-dominated power systems have accentuated the intricacies of frequency control, necessitating advanced regulatory mechanisms. This investigation articulates a tri-zonal frequency stabilization approach, employing a hybridized controller that synergizes Fuzzy Fractional-Order PI and Tilt-Integral-Derivative methodologies. The uniqueness of this approach is further amplified by the deployment of the Snake Optimization algorithm for precise parameter tuning. Set within a conventional grid topology integrated with assorted renewable energy sources, the study evaluates the controller’s adaptability and resilience through a series of comprehensive scenario-based analyses.